Introduction
1
Chapter 1 - Introduction
Endurance performance is a question of speed and time
The British physiologist, Archibald Vivian (A.V.) Hill (1886-1977), is considered by many to
be a pioneer in the discipline of exercise physiology. During the second semester of the 1926-27
academic year, Hill delivered a series of lectures at Cornell University in New York, giving rise
to the text “Muscular movement in man: the factors governing speed and recovery from fatigue”
(1927). Chapter VI, titled “Speed and energy requirement,” begins with two important
sentences:
“The greatest speed at which animals can move their limbs for a very short interval is
determined, teleologically, by certain simple dynamical considerations, depending
upon the strengths of the structures of which the animal is composed” (pp. 41).
Here, Hill suggests that there is a maximal velocity that each animal can attain, and this is
limited by the strength of its support structures (i.e., cross section of its bones, tendons and
joints); if excessive muscular force is exerted upon these structures, breakage will occur. Hill
goes on to state that ordinary men run with a significant ‘factor of safety,’ whilst fitter
specimens (i.e., athletes) are able to run closer to their ‘limit of safety,’ thereby making them
faster than the majority. These observations may be true for the fastest sprinters; however, many
athletic events take place at a much slower pace and over a prolonged period of time. Hill
addressed such exercise when he said:
“The greatest speed which an animal can maintain for a given time is determined by
considerations of fatigue and the energy expenditure” (pp. 41).
This statement is extremely pertinent as it clearly implies that matching the demand of exercise,
and resisting fatigue, are central to exercise tolerance. Subsequently, Hill plotted the world
record pace for both running and swimming for males and females as the average race pace as a
function of time taken to complete the distance (Hill et al., 1923). Figure 1 shows a
contemporary re-creation of Hill’s calculations for athletic events up until September 2010. This
diagram displays the relationship between running velocity and its tolerable duration. From this
it is clear that a high pace can only be maintained for a short time, but with a reduction in speed,
the duration of exercise increases in a curvilinear fashion.
2
11.0
Average speed (m.s-1)
10.0
9.0
8.0
7.0
6.0
5.0
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Finishing time (s)
Figure 1.1. The relationship between average running speed and finishing time for World record efforts
during track running for the 100, 200, 400, 800, 1500, 5000 and 10000 m, and the half and full marathon,
performed on the road for male (closed circles) and female (open circles) athletes.
Hill’s seminal work culminated in the construction of velocity-time curves for running, cycling,
swimming and rowing (Hill, 1925). This relationship has since been described mathematically
in isolated muscle action (Monod and Scherrer, 1965; Jones et al., 2008), and extended to whole
body exercise such as running (Hughson et al., 1984; Fukuba and Whipp, 1999; Hill et al.,
2011), cycling (Moritani et al., 1981; Pringle and Jones, 2002; Hill, 2004), swimming
(Wakayoshi et al., 1992), and rowing (Hill et al., 2003). Indeed, this relationship has also been
demonstrated with species from across the animal kingdom, as seen in the horse (Lauderdale
and Hinchcliff, 1999), the mouse (Billat et al., 2005), the ghost crab (Full and Herreid, 1983),
and even the lungless salamander (Full, 1986). Understanding the physiological underpinnings
of this relationship has considerable application in both health and disease, as the relationship
between the imposed work-rate and the tolerable duration of exercise appears central to highintensity exercise tolerance in humans.
Energy, oxygen, and muscular work
A first principle in exercise physiology is that energy is required to perform muscular work, and
to maintain a given velocity or work-rate over a prolonged period energy must be supplied at
3
the same rate at which it is utilised. During ‘all-out’ sprint exercise, energy output from the
active muscles may exceed resting values by up to 120 times; while during less intense but
prolonged exercise, such as running a marathon, energy requirement can be ~20 times that at
rest. Hill was aware of such concepts even when exercise physiology was in its infancy, and
provides a useful description of pacing strategy to ensure a ‘best performance,’ and an insightful
understanding of the mechanisms of fatigue that govern the velocity-time relationship (Hill,
1923). In this work, concepts relating to oxygen ‘income’ and oxygen ‘credit’ are introduced.
Hill describes a hypothetical runner who has an energy reserve of 16 litres (i.e., the oxygen
credit) and a maximal oxygen income of 4 litres per minute. For one minute of exercise this
runner can expend an energy equivalent of 20 litres of oxygen, allowing a very fast running
pace, requiring 20 litres of oxygen per minute. 24 litres of oxygen are available for two minutes
of exercise (8 for income, 16 on credit), expended at a lower rate of 12 litres per minute, thereby
reducing running pace. For five minutes of exercise, a slower pace, which utilises 7.2 litres of
oxygen (36 litres in total: 20 of income, 16 of credit), must be maintained to allow the runner to
complete the given duration of exercise. Within this schema, exhaustion would coincide with
the complete depletion of the oxygen credit reserve, if the exercise is performed in excess of the
rate of oxygen income. This simple example clearly shows the importance of energy
expenditure on performance across a range of exercise intensities and durations, and
unmistakeably describes the ‘aerobic’ (oxygen income) and ‘anaerobic’ (oxygen credit) systems
(Hill, 1923).
Adenosine triphosphate (ATP) is the sole fuel available to the contractile machinery of human
skeletal muscle. ATP is the only form of chemical energy that can be converted within living
cells to produce movement, releasing energy as heat. During intense muscular work, the small
intramuscular ATP store (~5 mMkg-1 wet weight) can supply energy to support just a few
seconds of work. As intramuscular ATP stores decline, the hydrolysis of phosphocreatine (PCr)
and the anaerobic breakdown of glucose and glycogen provide an additional, rapidly available,
energy supply. Each of these ‘substrate-level’ phosphorylation routes of energy supply are finite
(oxygen credit; Hill, 1923); therefore, to maintain the energy balance of the cell (i.e., to prevent
a fall in intra-cellular [ATP]; square brackets denote concentration), ATP must be resynthesized
from adenosine di-phosphate (ADP) and inorganic phosphate (Pi) at a rate proportional to its
hydrolysis. During the early stages of exercise, oxidative phosphorylation in the mitochondria
increases to meet the energy demand (as a result of increases in [ADP] and [Pi]); however, for
sustained activity, ATP concentration must be maintained by some other external route which
can provide a sustainable supply of energy. The utilisation of atmospheric oxygen (O2), and the
potential energy from exogenous macronutrients – chiefly, free fatty acids, glucose, and
glycogen – provide such an energy source, with the only by-products being water (H2O) and
4
carbon dioxide (CO2). Healthy humans have the capacity to precisely regulate and adjust their
cardiovascular system to maintain a sufficient supply of atmospheric O2 to the mitochondria
(oxygen income; Hill, 1923), and ventilatory system to expel the associated increase in
metabolic CO2 brought about by increased cellular respiration seen during exercise.
Oxidative metabolism is the principal means by which humans can generate energy to perform
muscular work lasting more than a few minutes. Hence, understanding the dynamic oxygen
uptake ( VO2 ) response to a bout of exercise is essential to appreciate the mechanistic basis of
exercise tolerance in humans, and indeed, in all air-breathing animals. The study of VO2
kinetics involves an investigation into the physiological mechanisms that are responsible for the
increase in VO2 at exercise onset, its regulation during, and recovery following, exercise (Jones
and Poole, 2005). The measurement of pulmonary oxygen uptake ( pVO2 ; abbreviated to VO2
from this point onwards) is relatively straightforward within the laboratory, and conveniently
has been shown to provide an accurate (10%) non-invasive estimate of muscular oxygen
uptake ( mVO2 ; Barstow et al., 1990; Grassi et al., 1996; see Pulmonary vs. muscle oxygen
uptake). Such measurements allow calculation of the O2 deficit and the rate of substrate-level
phosphorylation at exercise onset (Krough and Lindhard, 1913; Whipp et al., 1982). Indeed, it
appears that the VO2 kinetics interact with the traditional parameters of aerobic function (see
Determinants of endurance performance – a contemporary viewpoint) to set the mix of
substrate utilization, the change in acid-base status, and the degree of metabolite accumulation
during exercise (Burnley and Jones, 2007). Such data provides a rich source of information
about an individual’s capacity to perform exercise. Therefore, investigating the link between
these physiological mechanisms and the mathematical power-duration relationship would
further our understanding of whole body bioenergetics and the determinants of high-intensity
exercise tolerance in humans.
5
Review of Literature
6
Chapter 2 - Review of Literature
2.1 - Parameters of the physiological response to exercise
The imposition of exercise presents an instantaneous energy demand upon the body that must be
matched from either substrate level phosphorylation, or through the supply of exogenous
oxygen (O2) to the working muscle. The measurement of oxygen uptake at the mouth provides
an indirect window into energetic events occurring within the muscle. Furthermore, it facilitates
an estimation of the rate of O2 supply to, and its utilization within, the mitochondria, and by
inference the amount of energy derived from ‘anaerobic’ processes. A number of ‘aerobic’
parameters can be derived from such data, including the maximal oxygen uptake ( VO2max ), the
gas exchange threshold (GET) and the O2 cost of sub-maximal exercise (i.e. exercise economy).
Jones and Carter (2000) review evidence to support the notion that each of these ‘traditional
aerobic parameters’ is strongly correlated with exercise tolerance, and each is briefly outlined,
along with that anaerobic capacity.
Maximal oxygen uptake
The maximum oxygen uptake ( VO2max ) is classically defined as highest VO2 value seen during
whole body exercise performed at sea level (Mitchell et al., 1958; Sutton, 1992; Bassett and
Howley, 2000). The measurement of VO2max can provide important information about the
integrated capacity of the pulmonary, cardiovascular and neuromuscular systems to perform
exercise both in health and disease (Jones and Poole, 2005). Within this thesis VO2max is
operationally defined as the maximum VO2 achieved during incremental exercise, typically, but
not always, characterised by a failure of VO2 to increase despite further increases in work-rate
(Davis et al., 1982; Day et al., 2003). Day et al. (2003) recently investigated the issue of ‘peak
vs. maximum’ VO2 during incremental exercise, and demonstrated that a plateau in the VO2
response was not an obligatory consequence of incremental exercise. Indeed, at the limit of
tolerance, peak VO2 at exhaustion ( VO2peak ) was not different from VO2max . Indeed, Astrand and
Saltin (1961) previously demonstrated that exhaustive constant work-rate of relatively short
duration (1-8 minutes) would lead to the same end-point VO2 , despite the difference in the
tolerable duration of exercise. Therefore, within this work no distinction is made between
VO2peak and VO2max during either incremental or constant load exercise. The term ‘ VO2max ’ will
be used to indicate the highest VO2 attained during either a incremental test - regardless of
whether a plateau was observed or not - or during constant work-rate exercise performed to
exhaustion.
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The precise mechanism that limits VO2max has caused considerable debate (e.g., Hill and
Lupton, 1923; Saltin and Strange, 1992; Noakes, 1997, Noakes, 1998; Bassett and Howley,
2000; Richardson; 2000; Gonzales-Alonso and Calbet, 2003). However, during exercise
performed at sea level that employs over one-third of total muscle mass, it is generally accepted
that VO2max is limited principally by the cardiorespiratory system, and specifically by the
maximum cardiac output ( Q ; the product of heart rate and stroke volume; Sutton, 1992; Bassett
and Howley, 2000; Wagner, 2000). This view is taken due to that fact that mammalian skeletal
muscle appears to be able to utilise far more O2 than can be delivered (Saltin and Strange,
1992), suggesting that VO2max is limited through a combination of convective and diffusive O2
delivery, peripheral O2 extraction, and the O2 diffusing capacity of the active muscle (Wagner,
1996; Wagner 2000; Richardson, 2000; Gonzales-Alonso and Calbet, 2003). In addition, factors
such as exercise modality (i.e. small vs. large muscle mass or upright vs. supine exercise), the
environment (i.e. altitude) and participant characteristics (e.g., age, and training or disease
status) alter either O2 availability, or its delivery to the muscle, which in turn influence VO2max
(Bassett and Howley, 2000; Wagner, 2000).
Lactate threshold / gas exchange threshold
There are numerous instances within the literature when different terms are used to identify and
define the same physiological landmark. For example, ‘lactate threshold’ (LT; e.g., Carter et al.,
2000) or ‘lactic acidosis threshold’ (e.g., Wasserman et al., 1990; Bearden and Moffatt, 2001)
when the measurement involves blood sampling, and the ‘gas exchange threshold’ (e.g.,
Stringer et al., 1994) or ‘ventilatory threshold’ (e.g., MacDonald et al., 1997) when expired air
samples are collected. Throughout this thesis the terms gas exchange threshold (GET) will be
used when describing pVO2 response, and LT when the discussion turns to the acid-base status
of an individual. The LT is the lowest metabolic rate at which blood [lactate] (with square
brackets denoting concentration) begins to increase above baseline levels (Wasserman et al.,
1973; Whipp, 1994). Therefore, the LT represents the highest work-rate that can be maintained
without sustained metabolic acidosis, above which, as the work-rate continues to increase, so
does the blood [lactate]. The LT is associated with identifiable thresholds in blood bicarbonate
[HCO3-], venous partial pressure of carbon dioxide (PCO2), pulmonary CO2 output ( VCO2 ) and
minute ventilation ( VE ) (Wasserman, 1994). Indeed, it does not necessarily signify an increase
in anaerobic energy supply rather; it indicates alterations in cellular redox and phosphorylation
potentials that drive mitochondrial respiration (Connett et al., 1990). An alteration in the acidbase status of the tissues - often referred to as ‘lactacidosis’ - is not a result of the lactate
8
accumulation per se; it is the accumulation of free hydrogen ions (H+) that causes the metabolic
acidosis observed during exercise. Lactic acid formed as a result of glycogenolysis and
glycolysis, is a relatively unstable compound that readily dissociates into lactate (L-) and
hydrogen (H+) ions. Bicarbonate buffering of the lactic acidosis results in the production of nonmetabolic CO2 and an increase in both VCO2 and VE measured at the mouth. Hence, it is
possible to non-invasively estimate the LT via the pulmonary gas exchange response, as the
GET can be identified from changes in ventilation (from the V-slope; Beaver et al., 1986; see
General Methods). There is a large degree of variability in the relative intensity associated with
both the LT (~50-60% VO2max ), whilst the GET that typically occurs at 45-60% VO2max . Indeed,
the GET can be as low as ~35% in patient populations and as high as ~80% in highly trained
athletes, and therefore is considered (along with the LT) a strong predictor of endurance
performance (c.f. Jones and Carter, 2000). This intra-person variability should be considered
when ‘normalising’ exercise intensity for constant work-rate exercise, since exercise at 50% of
VO2max may be above the GET in one participant but below it in another, resulting in marked
differences in the metabolic and gas exchange responses to exercise. To overcome this issue for
high-intensity exercise the ‘% Δ’ concept has been utilised. This process involves the
calculation of exercise intensity relative to an individuals GET and VO2max , such that 50% Δ for
example, refers to the work-rate which requires a VO2 equivalent to 50% of the difference
between the VO2 at the GET and VO2max . This method of determining individual work-rates for
each participant is useful to ensure that participants are exercising within the desired exercise
intensity ‘domain’ (Özyener et al., 2001; Lansely et al., 2011).
Exercise economy / efficiency
In contrast to the blood [lactate] response to increasing exercise intensity, providing the increase
in work-rate is rapid enough (>20 watts per minute (W∙min-1), Davis et al., 1982), VO2
typically displays a linear relationship to external work-rate, from rest up to the point maximal
values are attained (i.e., VO2max ; Coats et al, 2003). During cycle exercise ‘delta’ (∆) efficiency
is ~25-30% (Whipp and Wasserman, 1969; Poole and Richardson, 1997). This is the inverse of
exercise economy, which is the increase in VO2 per unit increase in work-rate, typically being
~10 mL of O2 consumed per minute of exercise per watt (W) of external work (i.e. a
DVO2 / DWR of ~10 mL∙min-1∙W-1), with a range of ~9-11 mL∙min-1∙W-1 (Whipp and
Wasserman, 1969; Gaesser and Poole, 1996). The precise slope of this relationship may be
related to muscle fibre type composition (Barstow et al., 2000): with a higher slow twitch fibre
composition tended to have the steepest VO2 -WR slopes of ~11 mL∙min-1∙W-1, compared to
9
individuals with a greater proportion of fast twitch fibres (~9 mL∙min-1∙W-1; Perez et al., 2003);
although others have observed no difference in efficiency between fibre types (Mallory et al.,
2002). In terms of performance, an individual with a greater mechanical efficiency would be
able to sustain a given work-rate for a lower VO2 when compared to an individual with a lower
mechanical efficiency, or alternatively be able to maintain a higher work-rate for the same
absolute VO2 ; both situations would infer an enhanced exercise tolerance. The VO2 -WR
relationship therefore reflects the fact that the pulmonary VO2 response is primarily determined
by the imposed work-rate and the work efficiency (Poole and Richardson, 1997). In addition to
exercise economy/efficiency (Conley and Krahenbuhl, 1980), the fractional utilization of
VO2max (i.e. the ability to maintain a high percentage of VO2max during prolonged exercise)
plays an important role in overall exercise performance (Costill et al., 1973).
Anaerobic capacity
At rest intramuscular phosphocreatine (PCr) stores are in the order of ~120g in a 70 kg human
with a concentration of ~25 mM∙kg-1 that falls to as low as 2 mM∙kg-1 following exhaustive
high-intensity exercise (Eggleton and Eggleton, 1927). The active muscle mass of an endurance
athlete may see a depletion of ~20 mM∙kg-1 on the PCr pool, resulting in around 200 mM of
high-energy phosphates being contributed to the energy pool. The P:O2 is roughly 6:1, therefore
the phosphate bond energy equates to ~33 mM of O2. Then as each mM of O2 is equivalent to
22.4 mL, then the O2 equivalent of the total high energy phosphate pool of ~750 mL. Therefore,
intramuscular PCr stores constitute the major portion of the ‘anaerobic’ capacity. Stores of O2
within the blood and tissues provide another alactic source of energy that contributes to the
anaerobic capacity, as this O2 is available without the support of additional O2 from atmospheric
air. In mammalian blood the amount of physically dissolved oxygen is approximately 0.2 mL
per 100 mL of blood, and as the average human has a venous blood volume of around 3 litres,
this would equate to just 6 mL of O2.
A trained endurance athlete may have maximal rate of O2 delivery and utilisation (i.e., VO2max )
within the muscle of ~5 L∙min-1; such a high rate of O2 turnover cannot be met by dissolved O2
alone. A far greater O2 transporter molecule (haemoglobin, Hb) is contained within the blood,
with an O2 carrying capacity of ~20 mL per 100 mL of blood. The reversible binding of O2 to
haemoglobin is of great importance to oxygen transport in the blood: at high O2 concentrations as in the lung - O2 binds to Hb to form oxyhaemoglobin (HbO2), and at low O2 concentrations as in the exercising muscle - O2 is passed to the respiratory apparatus within the muscle. An
adult with a venous blood volume of 3 litres, and a resting mixed venous O2 content of 150
10
mL∙L-1, performing high intensity exercise may deplete blood O2 stores to ~50 mL∙L-1, therefore
provide roughly 300 mL of O2 to the working muscles. Another O2 carrier/store of similar form
to haemoglobin is found within the muscle known as myoglobin. Myoglobin acts as a relatively
small (~25 mg∙g-1 dry weight in 10 kg of muscle) short term O2 store within the muscle fibres.
However, the P50 of myoglobin occurs at ~3.0 mmHg at physiological temperature (e.g.,
Schenkman et al., 1997) and so would only contribute appreciably (~80 mL of O2 equivalent) to
the energy pool at higher intensities. Additionally, as the P50 of haemoglobin is ~25 mmHg, then
the majority of O2 unloading occurs from the latter proteins. Consequently, the combined
‘anaerobic’ energy store in a healthy adult would be in the region of ~1 L. Once this energy
store has been depleted, the continuation of exercise requires the oxidation of lactate produced
or the supply of atmospheric O2 to the muscle.
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2.2 - Oxygen uptake response to exercise
Within the laboratory, scientific investigations tend to be performed under ‘steady-state’
conditions, either at rest, or during moderate (<GET) or high (>GET) intensity exercise. Such
data has significant value however, human life rarely proceeds in such a manner - undertaking
daily tasks, along with the performance of exercise, cause a continuous flux between metabolic
rates. To match the increased energy demand, an individual requires an efficient coordination of
the pulmonary, cardiovascular and muscular systems to supply atmospheric O2 to the
mitochondria, thereby facilitating aerobic ATP production to support continued activity.
Investigations into the physiological processes that govern energy supply during the transition
from one work-rate to another (i.e., the study of VO2 kinetics) provide an insight into metabolic
control and muscle energetics that cannot be derived from steady-state exercise.
Oxygen uptake response at exercise onset - the oxygen deficit
Krogh and Lindhard, (1913) were among the first to examine the behaviour of the pulmonary
VO2 response at the onset of exercise. In this work, six participants performed a bout of either
‘light’ or ‘heavy’ exercise from rest on a cycle ergometer to investigate changes in ventilation
and gas exchange during the first minutes of exercise. An almost immediate and rapid increase
in ventilation was seen at exercise onset, and VO2 increased ‘gradually’ until the attainment of
a steady-state during light exercise. In addition, it was demonstrated that the increase in
ventilation and VO2 was greater during the heavier intensity work. Hill and Lupton, (1923)
further investigated the relationship between exercise intensity and the kinetics of VO2 . These
authors demonstrated that following an initial lag VO2 would increase exponentially in an
attempt to match the instantaneous energy demand; when balanced with energy supply, this
resulted in a steady-state in VO2 being attained. Rather insightfully, Hill and Lupton (1923)
went on to suggest that the VO2 response reflects a process where lactic acid is oxidised both
before and after exercise, with a steady-state only being reached when the amount of lactic acid
produced was balanced with that being oxidised. Despite, Hill and Lupton (1923) identifying
the exponential nature of the VO2 response, and providing an insightful commentary into
metabolic control at the onset of exercise, nearly thirty years passed before the VO2 response
was first mathematically modelled (Henry, 1951), which took the form:
VO2 (t) = Ap  (1 - e-kt)
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Where VO2 (t) is the VO2 at a given time-point, t is the time after exercise onset, Ap is the
asymptotic (steady-state) amplitude of the response, and finally, k is the rate constant. This
modelling approach revolutionised the study of the VO2 response to exercise, and formed the
basis of all subsequent models. More recently, the convention has been to substitute the rate
constant (kt) for a time constant of the form τ = 1/k (Whipp, 1971). Within this schema, the 
represents the time taken to reach 63% of the Ap (e.g., Linnarsson, 1974; Casaburi et al., 1989;
Whipp and Ward, 1990; Whipp 1994) and in healthy adults has a value of ~20-45 s. Thus:
VO2 (t) = Ap  (1 - e-t/τ)
According to this schema, when 1·τ has elapsed, the response has reached 63% of its target;
with the next passing τ, 63% of the remaining 37% would have been reached; and so on, until
that time when 4·τ have passed, at which point 98% of the anticipated steady-state will have
been attained. Whilst exponential modelling techniques provide an accurate description of the
speed of the VO2 response to exercise, sometimes a simpler method of comparison is preferable
to compare like transitions. Hill and Lupton (1923) determined the time point at which 50% of
the change in VO2 from baseline to attainment of the steady-state (i.e., the ‘half-time’ or t1/2)
would be suitable for this purpose (Whipp and Wasserman, 1972; Cerretelli and di Prampero,
1987). Alternatively, with the addition of a time constant and the assumption of an exponential
response, it is possible to yield a mean response time (MRT) for the initial increase in VO2 at
exercise onset. This is calculated as the weighted sum of the time delay and the time constant
for each component (Hughson et al., 1996; McDonald et al., 1997; McDonald et al., 1998;
Perry et al., 2001).
An inherent characteristic of an exponential process is that the instantaneous rate of change (in
this case in VO2 ) is directly proportional in magnitude to how far the response is from its target
(i.e. from the anticipated steady-state; Whipp and Rossiter, 2005). Following a step increase in
work-rate, the exponential increase in VO2 is consistent with an initial ‘error signal’ and
represents the difference between the energy supply from mitochondrial ATP resynthesis (i.e.
represented by the VO2 kinetics) and the energy requirement from within the muscle (Whipp
and Wasserman, 1972). This delay in oxidative energy turnover (the ‘O2 deficit’; Krough and
Lindhard, 1913) represents a ‘volume’ of energy that must be met by ‘other’ sources. Within
human skeletal muscle, these ‘other’ sources are independent of atmospheric O2, and are
typically described as ‘anaerobic’ in nature (Whipp and Rossiter, 2005). During moderate-
13
intensity exercise (<GET), the O2 deficit describes the area between the actual VO2 and the
required VO2 as determined by the imposed work-rate, and calculated according to:
O2 deficit = ∆ Ap  
Therefore, the magnitude of the O2 deficit is determined by the product of the effective primary
VO2  (i.e. the speed of the VO2 response) and by the Ap. Furthermore, it is possible to
calculate the cumulative O2 deficit as the product of the  and the VO2 at a given time point
(Özyener et al., 2003). The deficit in energy supply during this phase is principally met through
phosphocreatine (PCr) hydrolysis, and glycolysis (leading to the production of lactate and the
hydrogen ion), and a small additional contribution arises from the utilization of previously
stored O2 (Moritani et al., 1981; Gaesser and Wilson, 1988; Housh et al., 1989; Heck 2003), that
is functionally represented by a reduction in mixed venous O2 content (Whipp and Ward, 1982).
Physiologically, the faster the VO2 kinetics (i.e., shorter ) the better (as seen in endurance
athletes; Carter et al., 2000; Jones and Carter, 2000), as this situation would signify that the
combined cardio-respiratory systems are able to quickly deliver atmospheric oxygen (O2) to the
working muscle. This in turn, creates a smaller O2 deficit, and minimising the perturbation of
intercellular homeostasis (e.g., [PCr], [H+], [Pi] and pH; Jones et al., 2008). In contrast,
detraining, aging and many disease states (to the cardiovascular, pulmonary or muscular
systems) result in a ‘slowing’ of the VO2 response, thereby creating a far less favourable
intracellular environment, and a likely reduction in exercise capacity (Barstow and
Scheuermann, 2005).
Technological advances and the development of more complex oxygen uptake models
Up until the mid 1960’s, scientists studying VO2 kinetics were constrained by the use of
Douglas bags to collect expired air (Douglas, 1911). Such measurements provided a relatively
accurate description of the ‘overall’ VO2 response (Hill and Lupton, 1923; Whipp and
Wasserman, 1972), and demonstrated that VO2 follows a single exponential curve at the onset
of exercise (e.g., Henry, 1951; Margaria et al., 1965; Cerretelli et al., 1966). The primary
limitation of such experimentation was that the derived VO2 values were attained from
accumulated VO2 averaged over a given time (generally, 30 s to 1 min), which may not be
sensitive enough to capture subtle differences in the VO2 response. However, the introduction
of rapid response automated gas analysers improved the temporal resolution of the VO2
response and clearly demonstrated that the VO2 response was far more complicated than first
14
assumed (Whipp and Wasserman, 1972; Whipp et al., 1982). Indeed, it was shown that rather
than a single increase in VO2 from exercise onset (to the attainment of a steady-state), there are
in fact two phases in the VO2 response during the first minutes of exercise; one of which is
directly related to an increase in VO2 from within the working muscle (Phase II; Barstow et al.,
1990; Grassi et al., 1996), and one which is not (Phase I; Whipp et al., 1982). Further, it was
shown that the time taken to attain a VO2 steady-state was significantly longer at higher
exercise intensities (Jones et al., 2002; Pringle et al., 2003), leading to the suggestion that
during ‘high-intensity’ exercise (i.e., >GET), there was a second delayed (2-3 min after exercise
onset) increase in VO2 (Phase III; Whipp and Wassermann, 1972). With even greater exercise
intensity (i.e., above ‘critical power’; CP; see The power-duration relationship) then a steadystate in VO2 may not be attained, and in this situation, VO2 increases as a function of both the
work-rate and time, and as such projects towards VO2max (Poole e al., 1988; Hill et al., 2002;
Coats et al., 2003). Each of these phases of the VO2 response will be discussed briefly in the
flowing sections.
Phase I - the ‘cardiodynamic’ component
Whipp et al., (1982) demonstrated an initial rapid (lasting ~10-20 s) increase in VO2 at exercise
onset, known as ‘Phase I’ or the ‘cardiodynamic component’. The majority of this increase in
VO2 as the name suggests, is related to right ventricular output and by extension, pulmonary
blood flow (Whipp et al., 1982; Nery et al., 1982; Grassi et al., 1996; Rossiter et al., 1999).
This effect arises as a result of the contracting muscle action, causing the so-called ‘muscle
pump effect’, which increases venous blood pressure (and venous return), leading to an initial
elevation in cardiac output (e.g., Miyamoto et al., 1982; Weissmann et al., 1982; De Cort et al.,
1991; Grassi et al., 1996). An additional, but far smaller contribution arises from changes in
lung gas stores and mixed venous O2 content (equivalent to ~300 mL of O2; Barstow and Molé,
1987; Casaburi et al., 1989). During this phase, blood returning to the lung has not been
subjected to increased O2 extraction as a result of exercise - it left the microvasculature before
capillary PO2 began to fall. Therefore, Phase I is not directly representative of active muscle O2
utilization (Linnarsson, 1974; Whipp et al., 1982; Barstow and Molé, 1987), and a sharp
exponential increase in VO2 signals the onset of the next phase of the VO2 response (Whipp et
al., 1982; Barstow et al., 1990; Grassi et al., 1996).
15
Phase II - the ‘primary’ component
Following phase I, in healthy individuals VO2 increases in a rapid exponential fashion towards
the actual, or anticipated, steady-state VO2 , to match the energy demand of the imposed workrate (Whipp and Wasserman, 1972; Linnarsson, 1974; Whipp et al., 1982; Barstow and Molé,
1991; Paterson and Whipp, 1991; Özyener et al., 2001). This phase of the VO2 response is most
commonly known as ‘Phase II’, or the ‘primary component’; other names such as the
‘fundamental component’ or the ‘fast component’, have also been used within the VO2 kinetics
literature. The latter of the alternative terms aptly describes a second rapid increase in VO2 ,
which signifies the arrival of mixed venous blood drained from the exercising muscle to the
lung (Casaburi et al., 1989; Grassi et al, 1996). However, there is a temporal lag of ~5-15 s i.e., the ‘time delay’ - between events occurring within the muscle and those measured at the
lung which should be accounted for when interpreting such data (Barstow and Molé, 1987;
Barstow et al., 1990; Grassi et al., 1996).
During moderate exercise the primary component of the VO2 response displays first order
kinetics, and obeys the law of superposition; in that the output (i.e., Ap) can be predicted from
the input (i.e., internal work, external work, and efficiency; Fuijhara et al., 1973). Indeed,
during this phase, VO2 increases to a level (i.e., the amplitude) that is principally determined by
the intensity of the imposed work-rate (e.g., Wilkerson et al., 2004), but is also influenced by
muscle activation patterns (e.g., Burnley et al., 2002) and during cycle ergometry, also pedal
cadence (Zoldaz et al., 2000). The ‘speed’ (i.e., the time constant; τ) at which the VO2 response
reaches its ‘target’ appears to be directly related to the endurance training status of the
individual (e.g., Cerretelli et al., 1979), and may be sensitive to changes in O2 delivery to the
working muscle (Hughson, 2005): still others suggest a intracellular control mechanism (i.e.,
metabolic inertia; e.g., Poole et al., 2008), see Cellular respiration at exercise onset for
discussion.
Phase I is not directly representative of active muscle O2 utilization (Whipp et al., 1982), and
the traditional method of fitting a single exponential model beginning at exercise onset (e.g.,
Henry et al., 1951; Mahler et al., 1980) does not represent events occurring within the muscle.
Thus, for moderate-intensity exercise, after the removal of phase I, the time constant and
primary amplitude are attained by fitting a mono-exponential function the phase II of the VO2
response (Whipp et al., 1982; Özyener et al., 2001), of the form:
VO2 (t) = VO2 (b) + Ap  (1 - e-(t-TDp)/τp)
16
Where VO2 (t) represents the absolute VO2 at a given time point (t), VO2 (b) represents the
average VO2 within the final minute of baseline exercise, Ap signifies the phase II amplitude,
TDp is the time delay and τp is the time constant. During moderate-intensity cycle ergometry,
the gain, or amplitude of the response tends to be ~9-11 mL O2min-1W-1 (e.g., Whipp and
Wassermann, 1969; Poole et al., 1992; Barstow et al., 2000). For higher intensity work-rates
(i.e., heavy and severe exercise), the VO2 response is better described by a bi-exponential term,
and there is some evidence that the gain of the primary amplitude falls below 10 mLmin-1W-1,
and the kinetics appear slowed relative those to observed during moderate exercise (Jones et al.,
2002; Pringle et al., 2003; Scheuermann and Barstow, 2003). The presence of slower kinetics
and a reduced gain within the primary VO2 kinetics suggest that either O2 availability becomes
increasingly limiting with increasing exercise intensity (Hughson et al., 2001) or the metabolic
properties of the recruited muscle fibres are altered during these higher work-rates (e.g., Pringle
at al., 2003).
Control of cellular respiration at exercise onset
As discussed previously, VO2 increases with an approximately exponential time course to attain
a steady-state when the energy demand (i.e., the cellular ATPase rate) is met by the aerobic
energy supply (i.e., the mitochondrial ATP resynthesis rate). Given this ‘lag’ in pulmonary VO2
at exercise onset, ‘anaerobic’ energy stores - principally PCr hydrolysis and glycolysis leading
to the formation of lactate - to counter the decline in cellular [ATP] during this phase. The
development of 31-phosphorus magnetic resonance spectroscopy (31P-MRS) techniques over the
past 20-25 years has enabled scientists to non-invasively investigate the putative control of
cellular metabolism, through measurements of ATP PCr, Pi and (through calculations) ADP
(McCully et al., 1999). Such techniques have shown that the mitochondrial O2 utilization rate
appears closely related to the temporal change in PCr during both the onset and recovery from
moderate-intensity cycle exercise (Rossiter et al., 1999). This relationship is important as it
either suggests that the change in high-energy phosphates directly communicate the cellular
ATP demand (the PCr shuttle hypothesis), or that the fall in cellular ATP levels is buffered by
PCr, and therefore other factors (such as the phosphorylation potential, i.e., [ATP]/[ADP]+[Pi])
communicate the cellular ATP demand to the mitochondria (Mahler, 1980; Tschakovsky and
Hughson, 1999). These studies identified that an increase in the products of ATP hydrolysis
(i.e., increases in [ADP] and [Pi]; Lardy and Wellman, 1952; Chance and Williams, 1955;
Chance, 1965) provide the primary signal to stimulate oxidative phosphorylation and trigger an
17
increase in mitochondrial respiration (Whipp and Mahler, 1980; Tschakovsky and Hughson,
1999).
Whilst the maximal oxygen uptake ( VO2max ) appears to be principally limited by the capacity of
the O2 transport system (Bassett and Howley, 2000), the control processes that determine the
rate of change in VO2
(i.e., the VO2 kinetics) are believed to originate from within the
working muscle (Barstow et al., 1990; Grassi et al., 1999). Barstow et al., (1990), and Grassi et
al., (1996) present models of the control of oxidative phosphorylation which (1) support the
classic O2 deficit theory and the exponential nature of the pulmonary VO2 response at exercise
onset, and (2) where O2 delivery is adequate (i.e., healthy humans performing whole-body
upright exercise), these models reflect a ‘metabolic inertia’ (within the oxidative machinery) in
which the ‘O2 deficit’ is directly attributable to changes in cellular energy balance or an intrinsic
inertia of the oxidative enzymes. Indeed, proponents of this model of metabolic control argue
that most studies demonstrate that the kinetics of muscle O2 delivery (derived from muscle
arterial inflow or changes in cardiovascular dynamics) are somewhat faster than muscle VO2
kinetics (Delp, 1999). In addition, it has been observed that it is possible to independently alter
cardiovascular and VO2 kinetics through prior one-legged cycle exercise (Yoshida et al., 1995).
Increasing arterial O2 content (MacDonald et al., 1997) or muscle availability (Grassi et al.,
1998) does not alter the VO2 kinetics of moderate-intensity exercise. Indeed, even during highintensity exercise (i.e. of heavy- or severe-intensity) these may have little to no influence
(Grassi, 2000; Wilkerson et al., 2006). The inhabitation of nitric oxide synthase following LNAME administration speeds the VO2 kinetics during high-intensity exercise, despite a
potential reduction in muscle O2 delivery (Kindig et al., 2002; Jones et al., 2003). Finally, the
apparent symmetry between the VO2 kinetics and PCr degradation support a phosphate related
control of muscle energetics (Rossiter et al, 1999). However, it should be noted that this locus
of control might change with changes in; environmental conditions (e.g., hypoxia; Engelen et
al., 1996; MacDonald et al., 2000), exercise modalities (e.g., upright vs. supine cycling;
Hughson et al., 1993; Koga et al., 1999), muscle recruitment patterns (such as the transition
from prior exercise; Hughson and Morrissey, 1982), following medicinal intervention (e.g., beta
blockade; Hughson et al., 1984), and with processes related to aging and/or disease (Barstow
and Scheuermann, 2005; DeLorey et al., 2005; Poole et al., 2005). In these situations, it is
considered that there is biochemical evidence for O2 adjusting the phosphorylation and redox
potentials needed to drive oxidative respiration (Wilson et al., 1977; Wilson and Rumsey, 1988;
Hogan et al., 1992) and gave rise to an alternative ‘O2 limitation’ hypothesis (Hughson, 2001;
Hughson, 2005). Even the ‘metabolic inertia’ protagonists admit that at some point altering O2
18
delivery will have an impact upon the speed (i.e. the primary time constant; ) of the VO2
kinetics. Indeed, this observation of a ‘tipping point’ in the control of the VO2 response to
exercise appears to ease the arguments between each camp, such that the limitation to the VO2
kinetics for a given individual is determined by their position relative to this tipping point
(Poole et al., 2008).
Pulmonary vs. muscle oxygen uptake
In order to accurately investigate muscular bioenergetics and metabolic control during exercise,
it is vital to obtain an accurate quantification of rate energy turnover from within the working
muscle. The direct measurement of metabolic events within the muscle – e,g., via biopsy
sampling - would provide the best indicator of muscle energetics (c.f. Meyer and Foley, 1994).
However, this method is technically challenging and provides only a ‘snap-shot’ at a given time
point. More recently, 31P-MRS techniques have been used to capture such events (e.g., Rossiter
et al., 1999; Rossiter et al., 2002), and have shown that changes in phosphocreatine
concentration ([PCr]) provide a mirror image of that of muscle oxygen uptake ( mVO2 ; Grassi et
al., 1996). Such investigations are expensive, however, and due to the limited bore size of such
magnets at present, measurements can only be made in isolated muscle groups (e.g., Rossiter et
al., 1999; Jones et al., 2008). The measurement of pulmonary VO2 kinetics (denoted pVO2 in
this section) provides an alternative to muscle biopsy and 31P-MRS techniques as equipment is
readily available and enables a continuous measurement of VO2 during whole body exercise,
and an estimate of mVO2 (Whipp et al., 1982).
Using a computer modelling process, Barstow et al. (1990) demonstrated that the time constant
() for Phase II of the pVO2 response would likely provide a close approximation of the  of the
mVO2 response. Grassi et al. (1996) confirmed the earlier theoretical hypotheses by
demonstrating that pVO2 is essentially a ‘mirror image’ of the exponential reduction in [PCr]
during the same time period, showing a similar half time for pVO2 (25.5 s) and mVO2 (27.9 s).
Rossiter et al. (1999) provide further supporting evidence by utilising 31P-MRS to demonstrate
simultaneous measurements of not only the pVO2 response, but also PCr degradation during
moderate-intensity knee-extension exercise (Rossiter et al., 1999). This study clearly showed
the transport delay time from events happening within the muscle to those measured at the
mouth (i.e., Phase I; Rossiter et al., 1999; Rossiter et al., 2002) and also the symmetry between
the increase in pVO2 and the decline in [PCr] following the removal of Phase I (Rossiter et al.,
1999). Comparing direct (Grassi et al., 1996; Koga et al., 2005) and indirect (Rossiter et al.,
19
1999; Rossiter et al., 2002) measurements in tandem demonstrate that with careful measurement
and analysis the  of the Phase II pVO2 response appears to closely (within ~10%) reflect that
seen within the muscle (Barstow et al., 1990; Poole et al., 1992; Grassi et al., 1996). Hence, the
apparent link between events which occur within the muscle (i.e., mVO2 ) and those measured at
the mouth (i.e., pVO2 ) highlight the importance of the measurement and interpretation of pVO2
kinetics as a non invasive measurement of muscular energetics.
Phase III - the ‘steady-state’ or the ‘slow component’
During moderate-intensity exercise (i.e., that performed <GET), VO2 rises rapidly to attain a
steady-state (phase III) within around 2 min (Linnarsson, 1974, Casaburi et al., 1987). Precisely
how long this takes is governed by the Fick equation:
VO2 = Q · (CaO2-CvO2)
By definition, oxygen uptake is the product of blood flow ( Q ) and arterial-mixed venous O2
content difference (C(a-v)O2); when both time courses are complete, as steady-state is attained
(i.e. Phase III). For exercise above the GET, attainment of a steady-state in VO2 is delayed (by
up to ~15 min; Whipp and Wasserman, 1972; Barstow and Molé, 1991, Paterson and Whipp,
1991) due to the emergence of a supplementary, slowly developing phase of the VO2 response.
This phase has been aptly termed the ‘ VO2 slow component’ (Barstow and Molé, 1991,
Paterson and Whipp, 1991; Gaesser and Poole, 1996). Thus, for exercise >GET the crucial
feature of the VO2 response is that the ‘slow component’ is an elevation in VO2 above, rather
than toward, that predicted from the extrapolation of the VO2 -WR relationship of moderateintensity exercise (Whipp and Wasserman, 1972; Roston et al., 1987; Poole et al., 1988).
Subsequently, Poole et al. (1991) demonstrated that during ‘light’ submaximal (~50% VO2max )
exercise, a steady-state in VO2 could be attained. However, during more intense exercise
(~90% VO2max ), following the end of phase II (at ~3min) VO2 increased systematically over
time, thereby evidencing a true VO2 ‘slow component’. These observations are important as
they clearly demonstrates that a higher metabolic threshold exists, that defines a physiological
boundary separating work-rates which elicit a delayed, and elevated, steady-state (i.e., heavy
exercise; GET to CP) from those in which the VO2 slow component develops progressively
over time (i.e., severe exercise; >CP). Indeed, during these higher work-rates, if exercise is
20
maintained for a sufficient time period, VO2 will continue to increase until the attainment of
VO2max , or exhaustion, whichever occurs sooner (Coats et al., 2003).
The VO2 to moderate-intensity exercise (<LT/GET) is well described by a mono-exponential
function (Whipp and Wasserman, 1972), but given the behaviour of the VO2 about the GET, the
VO2 response to heavy- and severe-intensity exercise would be better described by a biexponential function (Whipp et al., 1982). This model separates the primary component from
the VO2 steady-state (heavy) or slow component (severe), and includes an amplitude (As), time
delay (TDs), and a time constant (τs) for this additional phase of the response:
VO2 (t) = VO2 (b) + Ap  (1 - e-(t-TDp)/τp) + As (1 - e-(t-TDs)/τs)
For severe-intensity exercise, the VO2 slow component may emerge slightly earlier, and
depending upon the precise duration and intensity of exercise, and may be of greater magnitude
that that seen during heavy exercise (Özyener et al., 2001). Indeed, during exercise performed
just above CP, the VO2 may exceed 1 Lmin-1 and may represent 25% of the total increase in
VO2 above baseline (Poole et al., 1994). During supramaximal exercise the duration of exercise
may be too short to discern an identifiable slow component, as VO2 rises quickly to the point of
exhaustion ((i.e. of ‘extreme’ intensity; Özyener et al., 2001).
Mechanisms for the oxygen uptake slow component
The mechanistic basis of the VO2 slow component seen during high-intensity exercise (i.e.,
>GET) has been the source of much debate, fuelled by the lack of consensus as to whether it is a
linear or exponential process, and due to the disparity in its nature during exercise performed
<CP (i.e. heavy; asymptotic) and >CP (i.e. severe; truncated at VO2max and/or fatigue). Potential
mediators of the VO2 slow component fall into two broad camps; including a range of whole
body factors such as: an increased O2 cost of ventilatory, cardiac or axillary muscular work, and
elevations in core temperature; and those related to intramuscular factors including: an increase
in muscle temperature, acidosis, a reduction in the contractile efficiency of ‘fast twitch’ muscle
fibres and/or a reduction in mitochondrial P/O ratio. The following section will briefly review
these mechanisms, with the interested reader directed to a number of excellent reviews for
further discussion (Poole et al., 1994; Whipp, 1994; Gaesser and Poole, 1996; Poole and
Richardson, 1997; Jones et al., 2011).
21
Many early investigations attempted to establish the O2 cost of a given process (e.g., the
respiratory cost of breathing or elevations in core temperature) and to relate this with the
magnitude of the VO2 slow component (Hagberg et al., 1978). Alternatively, some groups
correlated the temporal change in a process with that of the VO2 slow component during
exercise performed above the GET (Roston et al., 1987; Casaburi et al., 1987; Poole et al.,
1988). These investigations were indirect and fraught with assumptions. For example, based on
previously published data, Hagberg et al., (1978) concluded that increases in core temperature
and the O2 cost of breathing accounted for more than 100% of the VO2 slow component.
As such, the precise causal mechanism for the VO2 slow component remained speculative until
the introduction of Anderson and Saltin’s (1985) constant-infusion thermodilution technique.
For the first time, researchers were able to estimate blood flow to the muscle, while
simultaneously measuring oxygen utilization within the muscle (i.e., mVO2 ) and also gas
exchange at the mouth (i.e., VE and pVO2 ). Poole et al. (1991) utilised this technique to
demonstrate that during moderate exercise, as would be expected, there was a rapid initial
increase in VO2 at exercise onset, and a steady-state was soon attained. In contrast, during
severe exercise pulmonary ventilation ( VE ) was significantly increased (by ~57 Lmin-1).
Further, following Phase II, VO2 increased systematically throughout exercise, thereby clearly
demonstrating the VO2 slow component. Indeed, it was shown that leg blood flow and muscle
O2 extraction accounted for almost all of the increase seen in leg VO2 (~700 mLmin-1), and
that ~86% of VO2 slow component originated from within the leg musculature (Poole et al.,
1991). Further, Poole et al., (1991) made another important observation: during severe-intensity
exercise the development of the VO2 slow component was mirrored by a reduction in
mechanical efficiency from ~30% at exercise onset (similar to moderate exercise) to ~22% at
the end of exercise. At that point, it was unclear what was causing this decline in muscle
efficiency, be it, muscle temperature, metabolic acidosis (and increasing blood [lactate]),
changes in fibre type recruitment, or a reduction in mitochondrial P/O ratio. A little later,
elegant 31P-MRS studies provided further strong evidence to support the notion that the majority
of the VO2 slow component resides within the muscle; as a synchronous fall in [PCr] was
demonstrated alongside a progressive rise in VO2 measured at the mouth (Rossiter et al., 2001;
Rossiter et al., 2002).
22
Muscle temperature, acid-base status and blood [lactate]
Krustrup et al., (2004) demonstrated a VO2 slow component during cycle exercise performed at
80% VO2max , which was not evident at 50% VO2max , while muscle temperature was similar at
both exercise intensities. However, a decline in muscle pH was evident in the presence of the
VO2 slow component. This observation would suggest that muscle temperature may not a
causal factor for the VO2 slow component, but increasing acidosis instead might be implicated
in this process. Indeed, Poole et al., (1988) have also demonstrated an increase in blood [lactate]
and falling pH (i.e. an increase in metabolic acidosis) alongside the VO2 slow component
during high-intensity exercise, and a number of other groups have confirmed this correlation
(Whipp and Wasserman, 1986; Casaburi et al., 1987; Roston et al., 1987). However, it has been
suggested that this association may be coincidental rather than causal (c.f. Gaesser and Poole,
1996). For example, Ryan et al., (1979) demonstrated that the infusion of sodium L-(+)-lactate
causes an elevation in VO2 at rest and also during exercise. Also, neither the direct infusion of
lactate into exercising dog muscle (Poole et al., 1994), nor the administration of epinephrine in
humans, (which significantly increases blood [lactate] and reduces pH; Gaesser et al., 1994),
has a measurable effect on VO2 . It has also been reported that on occasion, an increase in blood
[lactate] has been observed, whilst VO2 remained constant (e.g., Scheen et al., 1981). Similarly,
a significant slow component in VO2 has been demonstrated during treadmill running whilst
blood [lactate] remained at resting levels (Steed et al., 1994). Furthermore, training intervention
elicits an opposing effect, whereby the development of the VO2 slow component is evident
alongside a fall in blood [lactate] at a given exercise intensity (Casaburi et al., 1987; Jones and
Carter, 2000). This evidence would suggest that muscle temperature, and changes in acid-base
status and blood [lactate] accumulation are not causal factors in the development of the VO2
slow component.
Motor unit recruitment and muscle fibre energetics
Since the development of the VO2 slow component occurs in the presence of increasing blood
[lactate] and falling pH, it has been suggested that these changes may be related to changes in
muscle fibre type recruitment, and especially the recruitment of ‘less efficient’ type IIa fibres as
exercise progresses (Poole et al., 1994; Whipp et al., 1994). Coyle et al., (1992) showed that
cycling efficiency varies at different pedal cadences. Their data suggest that efficiency at 80
rpm was significantly correlated with the proportion of type I fibres in the vastus lateralis, and
this pedal rate was close to peak efficiency in type I fibres. A little later, 100 rpm was shown to
23
be optimal in type II fibres (Sargeant et al., 1999). Barstow et al., (1996) used was stimulated
by these observations to investigate the effect of muscle fibre recruitment on the VO2 kinetics.
In this study, participants cycled at an intensity half way between their LT and VO2max (i.e.,
50% ∆) whilst maintaining 45, 60, 75 or 90 rpm. Barstow et al., (1996) reported that a greater
proportional recruitment of type II fibres in the vastus lateralis was associated with a lower
primary gain. In addition, following 8 min of exercise the magnitude of the VO2 slow
component was shown to be negatively correlated with the percentage type I fibres at every
pedal rate. These observations led the authors to conclude that muscle fibre type distribution
likely influenced the VO2 slow component during heavy exercise. However, the same factors
could also be associated with the fitness level of the participant, and so the influence of the
muscle fibre type on the VO2 kinetics could not be conclusively determined. Pringle et al.,
(2003) designed a study to further test this hypothesis during exercise of moderate-, heavy-, and
severe-intensity. Their principal findings were that the percentage of type I fibres was correlated
with both the primary time constant and the gain at all exercise intensities. In addition, these
were only correlated with the slow component during exercise above the GET, i.e., during
heavy and severe exercise only. This latter observation provides strong evidence to support the
notion that additional muscle fibre recruitment is involved in the progressive increase in VO2
during high-intensity exercise. In an interesting recent study, Copp et al., (2010) measured hind
limb blood flow in rats performing exercise above and below critical speed (CS; analogous to
CP). Blood flow was increased by 35%, and almost half of the muscle regions measured
received elevated blood flow above, compared with below, CS. This increased blood flow
would suggest additional muscle fibre recruitment, and that the additional recruited regions
consisted of predominantly type II fibres (Copp et al., 2010). Whether such effects are evident
in the exercising human are currently unknown, however these observations add further weight
to the argument the additional fibre recruitment is implicated in the VO2 slow component.
To date, little is know about the mitochondrial P/O ratio in humans performing dynamic
exercise, however, Jones et al. (2011) have provided a useful commentary on this subject. They
suggest that the mitochondria may have a central role in determining muscular efficiency, and
that the progressive increase in ions (such as Ca2+, H+ and Pi) may cause the P/O ratio to change
over time (Jones et al., 2011). Indirect evidence would support this notion: under ischemic
conditions muscle efficiency is maintained during 90 s of light (30 W) knee extension exercise,
whilst efficiency is progressively reduced under normal (free flowing) conditions (Krustrup et
al., 2003). Krustrup et al., (2008) also demonstrated the reduced efficiency in type II fibres
through the use of a neuromuscular blocking agent (cistatracurium, CUR), which impairs the
action of type I fibres. In this study they showed a reduction in mechanical efficiency of (~4%)
24
and an increase in muscle VO2 (of ~100 mL·min-1) in the CUR condition, which elicited a
greater reliance upon the activation of type II fibres (Krustrup et al., 2008). This reduction in
P/O ratio in type II fibres would be expected to increase the intracellular [Ca 2+] over type I
fibres, and therefore may explain why VO2 was higher in the CUR condition. In vitro studies
support this contention, as the mitochondrial O2 cost to P/O ratio, (i.e., a similar ratio between
ATP resynthesis and O2 molecules consumed) was unaltered during high intensity exercise
(Tonkonogi et al., 1999), such that there is a progressive increase in energy turnover with time
(Bangsbo et al., 2001).
Characteristics of the oxygen uptake response across the exercise intensity spectrum
The distinct metabolic and gas exchange responses to constant work-rate sub-maximal exercise
can be used to define four exercise intensity domains; ‘moderate’, ‘heavy’, ‘severe’ and
‘extreme’ with increasing intensity, respectively (Whipp and Wasserman, 1972; Whipp and
Mahler, 1980; Poole et al., 1988; Whipp, 1994; Gaesser and Poole, 1996; Hill et al., 2002;
Wilkerson et al., 2004; Jones and Poole, 2005). Alternative terminology exists within the
literature substituting the ‘severe’ and ‘extreme’ with ‘very heavy’ and ‘severe’ domains,
respectively (e.g., Özyener et al., 2001; Smith and Jones, 2001; Ferguson et al., 2007). Within
the current thesis ‘sub-maximal exercise’ will be used to describe work-rates below the
incremental-test determined VO2max , and the exercise-intensity domains will be referred to in
ascending order as moderate, heavy, severe and extreme.
Exercise below the lactate/gas exchange threshold
The moderate-intensity domain
Moderate-intensity exercise encompasses all work-rates below the GET, which itself is
considered synonymous with the LT. Physical work within this domain induces little to no
alteration in the acid-base status. However, following the transition to a higher metabolic rate,
an increase in anaerobic glycolysis may cause an initial overshoot in blood [lactate], which
rapidly stabilises at near to resting levels (~1 mM; Jones and Poole 2005). Following Phase I,
VO2 increases with rapid mono-exponential kinetics (i.e., Phase II) to attain a steady-state
within ~2-3 min in healthy individuals (Whipp and Wasserman, 1972; Whipp and Ward, 1992;
Wilkerson et al., 2004). Under steady-state conditions, the O2 cost of exercise can be matched
through supply of atmospheric O2 and the breakdown of glycogen, and therefore gas exchange
measured at the mouth closely reflects events within the muscle ( mVO2 ; Grassi et al., 1996).
Hence, such measurements can be used to quantify the relative contribution from aerobic and
25
anaerobic pathways (Whipp et al., 1986), and to estimate the rate of carbohydrate and fat
utilization during exercise (Peronnet et al 1991). Within this domain, sustained exercise in
excess of four hours is possible by motivated individuals, with fatigue likely to be due substrate
depletion, and/or hyperthermia and/or central fatigue (Hughes et al., 1982; Bigland-Richie,
1984; Gonzalez-Alonso et al., 1997; St Clair Gibson et al., 2001).
Exercise above the lactate/gas exchange threshold - ‘high intensity’ exercise
The heavy-intensity domain
The GET/LT demarcates the lower boundary of the heavy domain and the upper limit is defined
by the maximal steady-state (MSS), which appears to coincide with the power asymptote of the
power-duration relationship (CP). Again, following Phase I, VO2 rises in an exponential
fashion (Phase II) to attain an amplitude that is largely dependent upon the external power
requirement (Paterson and Whipp, 1991; Wilkerson et al., 2004). In contrast to moderate
exercise, a third component of the VO2 response appears, of delayed onset and with a slower
time course. This additional O2 cost of exercise causes VO2 to increase above, rather than
toward the ‘expected’ steady-state. (Whipp and Mahler, 1980). This phase has been aptly
termed the VO2 ‘slow component’ (Phase III), and represents an additional energetic cost of
exercise with an origin that resides predominantly within the working musculature (Poole et al.,
1991; Gaesser and Poole, 1996; Rossiter et al., 2002). Despite an increased metabolic demand,
constant heavy-intensity exercise elicits an elevated but stable blood [lactate] over time, which
is closely related to the increase in VO2 (Roston et al., 1987). The upper boundary of this
domain coincides with the ‘maximal lactate steady-state’, defined as exercise intensities that
elicit a stable blood [lactate] of up to ~4mM (Pringle et al., 2002). As a result of increases in
cardiovascular effort and changes in acid-base status, and higher perceived exertion is generally
reported over that of moderate exercise (Katch et al., 1978). However, within the heavy domain,
a steady-state can be achieved, and so exercise can be maintained for a considerable, but finite,
period of time (less than three to four hours; MacDougall et al., 1974). Fatigue during heavy
exercise is likely mediated due to by limitations in the rate or capacity for substrate (mainly
carbohydrate) utilization and/or hyperthermia (Hughes et al., 1982; Gaesser and Poole, 1996).
The severe-intensity domain
Severe-intensity exercise includes work-rates above CP, and the highest work-rate that will
elicit VO2max (Coats et al., 2003). Within this domain, VO2 increases as a function of both
power and time (i.e. the slow VO2 component), and consequently cannot be defined by a
26
distinct power output (Poole and Richardson, 1997). Exercise performed in the lower regions of
the severe domain - i.e., those that are closest to CP - typically exhibit the largest VO2 slow
components. Whereas, in the upper regions of this domain, where time to exhaustion is very
short, VO2 may increase so rapidly that there is almost no discernable slow component (Roston
et al., 1987). It should be noted that the work-rate does not have to be ‘maximal’ to achieve
VO2max , as prolonged sub-maximal exercise performed >CP will drive VO2 to VO2max , given
enough time (Poole et al., 1988; Poole et al., 1990; Hill and Ferguson; 1999; Coats et al., 2003).
It has been well established that the VO2 slow component is an important factor that contributes
to fatigue, as the more rapidly it projects towards VO2max (i.e., a with a steep trajectory) the
shorter the tolerable duration of exercise (Margaria et al., 1965; Poole et al., 1988; Whipp,
1994; Hill et al., 2002). It has also been observed that as with VO2 , blood [lactate] increases
and pH falls inexorably during severe exercise and task failure is associated with high-energy
phosphate depletion and the associated accumulation of fatigue inducing metabolites (namely P i
and H+; Fitts and Balog, 1996; Chin and Allen, 1998). Furthermore, a reduction in intracellular
K+ during exercise inhibits the release of Ca2+ from the muscle, thereby limiting the excitationcontracting potential of the muscle fibres to such an extent that the task becomes intolerable
(Fitts and Balog, 1996; Chin and Allen, 1998). Thus, the attainment of VO2max defines the point
at which further exercise can only be completed at the expense of the remaining finite anaerobic
capacity, the final depletion of which, or the intolerable accumulation of metabolites or falling
pH, coincides with the cessation of exercise (Poole et al., 1988).
Exercise above the maximal oxygen uptake
The extreme-intensity domain
The upper limit of the severe-intensity domain is defined by the highest work-rate that elicits
VO2max , albeit momentarily, immediately prior to task failure (Coats et al., 2003). Hill et al.,
(2002) exercised participants at 95%, 100%, 110% and 135% of the VO2 attained at the end of
a incremental test to determine the lowest work-rate at which constant work-rate exercise
resulted in exhaustion before the attainment of VO2max . Linear regression analysis between the
time to achieve VO2max and the time taken to reach exhaustion allowed these authors to calculate
that this occurred at 135% of the peak power output during the incremental test, and in most
participants, exhaustion occurred within ~2 min. Hence, it is evident that humans can perform
short duration exercise at intensities well above those seen within the severe domain, and
27
prompted the argument that a further exercise intensity domain should exist to encompass this
‘supra-maximal’ or ‘extreme’ exercise. (Hill et al., 2002).
28
2.3 - The power-duration relationship
A common experience for competitive athletes and the recreational exerciser is that it is
possible to maintain a fast yet relatively comfortable pace for a considerable period of time; but
if the pace is raised by just a small amount, then perceived effort increases considerably, and the
tolerable duration of exercise decreases dramatically. This effect is exacerbated in individuals
suffering from a wide range of disease conditions. For these individuals, such experiences can
occur at very low exercise intensities, hindering not only their capacity for exercise but tasks in
their daily life. The exercise transition point from “comfortable” to “not so comfortable”
appears to correspond with the boundary between ‘heavy’ and ‘severe’ exercise intensity
domains, and as such has strong physiological and mathematical foundations that are enshrined
within the power-duration relationship (Hill et al., 1923; Monod and Scherrer, 1965; Moritani et
al., 1981; Whipp et al., 1982; Morton, 2006; Jones et al., 2010). The following sections review
the theoretical and mathematical basis of the power-duration relationship, and the link between
the parameters derived from such modelling (i.e., CP and W); their physiological origins are
discussed, and finally, the importance of this model is considered in the determination of
severe-intensity exercise tolerance.
Historical perspectives
Hill et al. (1923) demonstrated a strong relationship between the intensity and tolerable duration
of exercise. This observation led to the description of the ‘velocity-time’ relationship for both
running and swimming. Some years later, while working in the Laboratoire de Physiologie du
Travail at the Centre National de la Recherche Scientifique in Paris, Monod and Scherrer (1965)
examined the influence of load, imposed frequency, and circulatory occlusion during both
dynamic and isometric exercise in a synergic muscle group. These researchers demonstrated
that when a range of constant work-rate, but differing intensity, exercise bouts were performed
to the limit of tolerance, a hyperbolic relationship emerged that defines a ‘fatigue threshold’ that
cannot be derived from a single exercise test. Furthermore, linear regression performed on such
data defines two parameters: ‘critical power’ (CP; expressed in W; the asymptote) and W’
(expressed in kJ; the curvature constant). CP was originally suggested to be dependent, at least
in part, on muscle blood flow (and hence O2 delivery), and defines the maximum rate of work
that can be maintained for “a very long time without fatigue”. Thus, it appears that CP
corresponds with the upper threshold at which a steady-state in VO2 and acid-base status can be
attained, and is considered synonymous with the physiological ‘maximal steady-state’ (MSS;
the heavy- to severe-intensity exercise boundary). The precise physiological determinants of W
are less clear. W appears to be related to the breakdown of phosphocreatine (PCr) and
29
glycogen (leading to the production on lactate) during exercise, and may be related to the
accumulation of ADP, H+, Pi, and a fall in pH (Jones et al., 2008). Irrespective of its
physiological determinants, mathematically W represents an amount of work that can be
performed above CP, independent of work-rate (Moritani et al., 1981; Poole et al., 1988).
At a similar time to the investigations of Monod and Scherrer, Douglas R. Wilkie, working
under A.V. Hill’s guidance presented a computer simulation of the ‘force-time’ relationship of
human muscle (Wilkie, 1960). This model demonstrates that summing the ‘anaerobic’ with the
‘aerobic’ power term could allow scientists to predict time to exhaustion for a given exercise
intensity. Within this model, the aerobic component was described to rise exponentially (with a
time constant of 10 s) towards its maximum, independent of duration. The ‘anaerobic’
component was inversely proportional to exercise duration, and therefore of consistent
magnitude. These observations fuelled the question: “At what exercise intensity – relative to the
other principal physiological measures (e.g., GET/LT and VO2max ) – does CP occur?” Wilkie’s
assumption of such a fast increase in the VO2 kinetics at exercise onset has been questioned (cf.
Morton, 2006) on the grounds that such short time constants are very rarely seen even in elite
athletes (Koppo et al., 2004). Indeed, this conjecture may have contributed to the conclusion
that CP would occur close to, or even above, VO2max (Wilkie, 1980). Moritani et al. (1981)
extended this earlier work to whole-body cycle exercise. Their findings led them to suggest that
CP occurs at a much lower intensity than that proposed by Wilkie (1980), at a work-rate similar
to the ‘anaerobic threshold’ (synonymous with the LT or GET). These viewpoints are in stark
contrast, and following further theoretical and experimental work (e.g., Poole et al., 1988; Jones
et al., 2008), and practical application (e.g., Farrell et al., 1979), both were proven to be
incorrect.
The marathon is an excellent example of an event which provides strong evidence that CP
would lie somewhere appreciably above the LT, and also well below VO2max . Assuming an
even-paced effort, many recreational runners can run at a pace in excess of the LT for the
duration of a marathon (Farrell et al., 1979). As such, CP must occur at a higher metabolic rate
(Poole et al., 1988; Poole et al., 1990). In contrast, these same individuals would not be able to
maintain an energy output so high, that given enough time, would elicit VO2max (Joyner and
Coyle, 2008). In practice, such high work-rates can only be maintained for a few minutes (Poole
et al., 1988; Hill et al., 2002). Further experimental investigations that were designed to identify
and define the physical responses above and below the ‘maximal steady-state’ (analogous with
CP) demonstrated that this point occurs at a work-rate considerably higher than the LT, and
somewhat below the incremental test-derived VO2max (Poole et al., 1990). Indeed, despite
30
typical intra-individual variation, in healthy individuals CP appears to occur at ~70-80% VO2max
, or more precisely, at ~40-50% Δ (i.e., GET plus 40-50% of the GET to VO2max interval; Poole
et al., 1988; Poole et al., 1990; Smith and Jones, 2001; Jones et al., 2010).
Mathematical modelling the power-duration relationship
The power-duration relationship is a mathematical construct that is derived from the
relationship between imposed intensity of exercise (or work-rate) and the tolerable duration of
exercise at said intensity (measured in units of time). Partly because this relationship has been
applied to a range of exercise modalities, various terminologies emerged within the literature.
For example, the intensity of exercise is generally referred as the power output for cycle
exercise, but also speed or velocity for other activities, such as running or swimming. Therefore,
analogous terms such as ‘critical power’ (CP) and ‘critical speed (or velocity)’ (CS and CV,
respectively) exist, and can be interchanged in order to interpret research across a range of
exercise types. For cycle ergometry, the amount of work that can be performed above CP is
known as W (expressed in kJ), whilst for running and swimming, this is generally exchanged
for ‘distance,’ or more correctly, ‘critical distance’ (expressed in metres). For the exercise
physiologist, this work simply involves the time taken to perform a given amount of work, and
provides a model with which to investigate human energetics during high-intensity exercise.
Many models can be derived from this relationship, including those with two- and threemathematical parameters (Morton et al., 2006; Jones et al., 2010). The most common of these
models are outlined in the following section, and the two-parameter models are discussed in
detail as these are of most relevance to the current thesis (see Model selection considerations).
In order to define this relationship for a given individual, at least two (and usually three to five;
Housh et al., 1990) independent high-intensity constant work-rate exercise bouts are performed,
which each elicit a time to exhaustion of ~2-15 min (Poole et al., 1988; Hill, 1993). For each
bout of exercise, the power output and time to exhaustion are recorded (with work done; W;
calculated as W = P  t; Moritani et al., 1981), and the power-duration relationship is calculated
using statistical software that fits the curve to the models presented.
Two-parameter models
The seminal work of Monod and Scherrer (1965) demonstrated a linear relationship between the
work done (W) and time taken to complete the work (t), known as the ‘work-time’ model:
[1]
W = CP · t + W
[linear work-time]
31
Mathematically, this is a two-component energetic supply and demand system with critical
power (CP) denoted by the slope; the y-intercept indicates a ‘fixed energetic reserve’, which has
subsequently been termed the W (Poole et al., 1988; Smith and Hill, 1993; Gaesser et al., 1995;
Fukuba et al., 2003). For constant work-rates performed above CP, the aerobic system alone is
not sufficient to meet the energy demand; therefore, the finite W component is depleted at a rate
proportional to the intensity above CP (Roston et al., 1987). By rearranging the model and
substituting into the equation derived estimates for both CP and W it is possible to calculate the
shortest time to complete a set amount of work:
[2]
t = W / (P - CP)
[predict time to exhaustion]
Whipp et al. (1982) described the relationship between the imposed power output (P) and time
to exhaustion (t) using a simple hyperbolic two-parameter model – the ‘power-time’ model:
[3]
(P - CP)  t = W
[hyperbolic power-time]
This model can be further transformed into two linear models:
[4]
P = (W/t) + CP
[linear power-time]
[5]
P = W (1/t) + CP
[linear 1/time]
The final model [5] is known at the ‘inverse-time’ (or 1/time) model where the slope represents
CP and the intercept W. This linear form of the power-time model is complicated by the lack of
a meaningful demarcation on the x-axis; however, despite this limitation it has been shown to
provide an accurate fit to experimental data (e.g., Miura et al., 1999; Miura et al., 2000; Poole et
al., 1988; Pringle and Jones, 2002; Coats et al., 2003).
Key assumptions and considerations of modelling the power-duration relationship
Building on the work of these pioneering researchers, Hill (1993) presented four key
assumptions that are essential in interpreting the power-duration model(s) in relation to human
exercise performance:
1. Two components provide energy to the exercising human, termed ‘aerobic’ and
‘anaerobic’.
2. The aerobic capacity (i.e., CP) is unlimited in capacity, but rate limited.
3. The anaerobic capacity (i.e., W) is capacity, but is not rate limited.
4. For exercise above CP, exhaustion occurs when W has been completely depleted.
32
These assumptions are central to the determination and interpretation of the power-duration
relationship, but a number of others can be derived from these four and are beyond the scope of
this thesis, and reviews elsewhere (Morton, 2006; Jones et al., 2010). In summary, within these
models, both supply components are endogenous in origin, with CP being rate- but not capacitylimited, and W capacity- but not rate-limited. Exercise can continue at any intensity when the
energy supply matches or exceeds the energy demand. The work-time relationship implies that
it is possible to complete a quantity of work in zero or negative time, if the given quantity of
work is less than or equal to the W constant. Mathematically this is acceptable; however, the
limits of human performance, and indeed the laws of physics, do not support such a situation.
Monod and Scherrer (1965) identified this point, stating that the work-time relationship loses
linearity for exercise durations <2min – a fact that has been either overlooked or ignored in
contemporary research (di Prampero, 1999; Heubert et al., 2005; Morton, 2006). The powertime model also presents an unrealistic assumption: if exercise is performed below CP, then the
energy demand from exercise can be matched aerobically, suggesting an ‘infinite’ exercise time
(Moritani et al., 1981; Bishop et al., 1998; Dekerle et al., 2003; Morton, 2006). Of course, given
enough time, fatigue will ensue irrespective of work-rate, due to the multifaceted nature of
muscle fatigue and the transience of psychological drive to perform exercise (e.g., Fitts, 1994;
Allen, 2008; Allen, 2009; Knicker et al., 2011). Indeed, within the laboratory, exercise
undertaken at the CP can typically be sustained for ~20-60 minutes (Housh et al., 1989;
McLellan and Cheung, 1992; Bull et al., 2000; Brickley et al., 2002), and would possibly be
similar to the average work-rate maintained during a competitive, well-paced, one-hour timetrial (Billat et al., 2003). A further limitation of the power-time model is that the maximal power
output approaches infinity as exercise time nears zero. The work-time model provides a
physiological limit to power production such that work done cannot be less than the work
capacity indicated by W. Of course, at high exercise intensities, the accumulation of work
performed above CP (i.e., W) could conceivably be undertaken in a short period of time,
although not likely in less than 30-45 s in most individuals. The only limits of the power-time
model are mathematical, in that time cannot equal zero, and power output can only approach
CP, and physiological, confined by the limits of the severe-intensity domain (i.e., work rates
above the MSS, and those that can elicit VO2max ).
Three-parameter models
In order to address some of the limitations of the two-parameter models, various additional
parameters have been added to the model, including:
33
[6]
t = W / (P - CP) - k
This model is an extension of a two-parameter model, incorporating a third parameter, (k), that is
the temporal asymptote estimated from the data at t = k. Further to this additional parameter, the
key difference between the two- and three-parameter models is that the horizontal asymptote of
the rectangular parabola – where P and t are the independent and dependant variables,
respectively – is not constrained to t = 0. Morton (1996) developed this model to address some
of the assumptions that limit the two-parameter model: for example, limiting the maximum
available power output; the instantaneous maximum power output (Pmax) would be determined
by the remaining W, and would be of a finite magnitude above CP. Hence, a fully rested
individual could elicit Pmax with a maximal effort, whereas an individual with a completely
depleted W would only be able to produce a maximal power output equivalent to CP. This
model takes the form:
[7]
P = CP + (Pmax - CP) e-t/k
However, despite these additions, the model, none of these procedures contain direct
measurements of human physiological function. This problem was addressed by adding a
mathematical term to describe the delayed aerobic response at exercise onset (i.e., adding time
constant (τ) for the primary VO2 kinetics). This also accounted for the assumption that anaerobic
provision was maximal during short duration efforts (Wilkie, 1980; Vandewalle et al., 1989).
These models take the form:
[8]
P = CP + (τ · (Pmax-CP) · Tlim)-1
[hyperbolic form]
[9]
P = CP + (W · (1-e-(Tlim/τ)) · Tlim-1)
[exponential form]
Early three-parameter models such as those displayed above ([8] and [9]) have a number of
mathematical and physiological benefits: time to exhaustion is identified as the dependent
variable; CP estimates tend to be lower and therefore physiologically more sustainable; and
finally, an upper limit for power production is identified (Gaesser et al., 1995; Morton et al.,
2006 Bull et al., 2008). However, despite a reduction in the power output associated with the
estimated CP, it still cannot be performed indefinitely for reasons discussed previously (Fitts,
1994; Allen, 2009; Knicker et al., 2011). Also, it does not take into account the VO2 time delay
at exercise onset; and assumes that W depletion is linear in relation to exercise intensity, and
therefore only depleted entirely when exercise is performed at CP to exhaustion (Vandewalle et
al. 1989; Gaesser et al., 1995; Morton, 2006; Bull et al., 2008; Jones et al., 2010). From the
presented models it appears that adding parameters of the VO2 response to the power-duration
34
model would lead to a more suitable bioenergetic model. However, to date, a more complete
model remains elusive, and has recently received theoretical attention (Burnley and Jones, 2007).
Model selection considerations
As discussed, the relationship between constant work-rate exercise and time to exhaustion can be
described mathematically using a range of models, including those with two- (Monod and
Scherrer, 1965; Moritani et al., 1981; Whipp et al., 1982), and three- (Morton, 1996)
mathematical parameters. It is important to consider that although these equations are
mathematically equivalent, the derived parameters may (e.g., Morton et al., 1997; Bull et al.,
2000; Hill and Smith, 1999; Hill et al., 2002; Hill et al., 2003), or may not (Gaesser et al., 1995;
Hill, 1993), be statistically similar. Differences in the derived parameter estimates usually arises
when data points are beyond the linear range of the work-time model (i.e., Tlim <2 min; Monod
and Scherrer, 1965), or endurance time is at the extremes of intensity with the hyperbolic powertime model (Poole, 1986; Hill, 1993). Therefore, in order to draw valid physiological inferences
from such modelling, or when the purpose of experimentation is to determine the effect of a
given intervention on the resultant parameters, the selection of a suitable model is essential (c.f.
Hill, 1993; Jones et al., 2010; Hill et al., 2011).
The two-parameter models are simple to calculate, and provide good physiological inferences
from the derived parameters, but they fail at the extremes of both intensity and duration (di
Prampero, 1999; Heubert et al., 2005; Morton et al., 2006). However, this relationship does
describe and predict exercise tolerance well during exercise performed above CP (lasting
between ~2-15 min) for both cycling (Moritani et al., 1981; Poole et al., 1990; Nebelsick-Guillet
et al., 1988; Jenkins and Quigley et al., 1990; Bulbulian et al., 1996) and running (substituting
‘speed’ for ‘power’; Hughson et al., 1984; Smith and Jones, 2001). Proponents of the hyperbolic
three-parameter model argue that the more complex model correctly: identifies time to
exhaustion as the dependent variable; defines an upper limit of power production; and provides a
lower, and therefore more sustainable, estimate of CP (Gaesser et al., 1995; Bull et al., 2000).
Despite these apparent improvements, CP can still not be sustained indefinitely, and the delayed
aerobic response at exercise onset is not accounted for within this model (Wilkie, 1980;
Vandewalle et al., 1989; Gaesser et al., 1995; Bull et al., 2000; Bull et al., 2008). In order to
provide a suitable fit to the data within the three-parameter models, it was stipulated that at least
one very high intensity trial (lasting <1min) should be used in the modelling process (Morton,
2006). This point is important, as the converse should then be true, for when very short trials are
avoided, the two-parameter models should then be most appropriate to describe the powerduration relationship (Bishop et al., 1998; Hill et al., 2011).
35
By definition, the severe-intensity exercise domain (and therefore the practical realms of the
power-duration relationship) encompasses all work rates above CP, and given enough time, will
allow the attainment of VO2max (Coats et al., 2003). Indeed, for exercise to be performed at a
high enough intensity for exhaustion to occur in less than 1 min, all but exceptional world-class
endurance athletes would not have fast enough VO2 kinetics to reach VO2max in such short a
time period (Jones, 2006). This would suggest that most individuals would be exercising ‘supramaximally,’ and as such, within the ‘extreme-intensity’ domain (Hill et al., 2002); a point
acknowledged by Vandewalle et al. (1989). Hill et al. (2003) evaluated the three-parameter
models to identify which was most appropriate when the duration of exercise duration ranges
from ~3-10 min, and later demonstrated that for both running and cycling lasting such durations,
the two-parameter models were most suitable (Hill, 2004; Hill et al., 2011). Within the current
thesis, the original ‘work-time’ two-parameter model (Monod and Scherrer, 1965) is used to
compare the effects of various interventions on the power-duration relationship. This decision
was made because the two-component model is simple to apply, linear in nature, has been wellused previously, and accurately describes experimental data during cycle ergometry (Moritani et
al., 1981; Nebelsick-Gullet et al., 1988; Poole et al., 1990; Jenkins and Quigley, 1990; Bulbulian
et al., 1996).
Protocol design and implementation considerations
Modelling the power-duration relationship provides a wealth of useful data to the exercise
physiologist, and requires minimal equipment; typically just a cycle ergometer or treadmill and a
stopwatch. This section briefly discusses a number of methodological factors that should be
considered, and the effect that these may have on the reliability and validity of the parameter
estimates.
Determination of time to exhaustion and the influence of practice
A critical factor that governs both the reliability and validity of the parameter estimates is the
determination of the precise time to exhaustion. This measurement is usually made to the nearest
second, and may be influenced by the selected test termination criteria, the subjective application
of these criteria by the experimenter, and requires a well-motivated participant to provide
maximal effort.
Hopkins et al., (2001) demonstrate that the test-retest coefficient of variation in time to
exhaustion during severe-intensity exercise is ~0.9-2.0%, and, this was shown to be another
1.3% higher in non-athletes vs. athletes. Indeed, a little earlier, Poole et al. (1988) investigated
the repeatability of constant work-rate trials performed to exhaustion and demonstrated a small,
36
albeit significant, learning effect in inexperienced participants. Although there was some
variation in performance between each attempt, on average, time to exhaustion was longer on the
second attempt. Furthermore, relatively short trials (lasting ~4 min) saw a modest increase in
performance of 2-4%, whilst longer trials (of ~8 min) were shown to last ~4-6% longer on the
second attempt. Enhanced exercise tolerance at a given work-rate following practice will
influence the mathematical modelling of the relationship and the derived parameter estimates; as
such, participants accustomed to such experimentation should be sought where possible (Bull et
al., 2000). This need for recruiting experienced participants is highlighted from the observations
of a number of studies. For example, Nebelsick-Gullett et al. (1988) showed high test-retest
correlations for both CP and W in a sample of 25 females, and Smith and Hill (1993) observed
an increase in CP in males and females (+5% and +6%, respectively), with no change in W,
following the second of two sets of predicting trials. In contrast, Gaesser and Wilson (1988)
investigated the difference in the power-duration relationship parameters following two sets of
five predicting trials. They showed that the CP parameter was more robust (r 2 = 0.92) than the
W parameter (r2 = 0.62). Hence, best practice would be to recruit experienced participants and
to allow sufficient practice for those unfamiliar with such experimentation.
Duration of trials
Consideration must be given to the intensity, and hence the duration, of exercise trials utilised to
define the power-duration relationship. Poole et al., (1988) comment that it is important to avoid
power outputs so great that they induce time to exhaustion of less than 1 min. This suggestion is
important because during whole body exercise the power-duration concept is inherently related
to exercise intensities that will elicit VO2max (i.e., of severe-intensity; Moritani et al., 1981; Hill
and Ferguson, 1999; Hill and Smith, 1999; Hill et al., 2002); some individuals with very fast
VO2 kinetics may be able to attain VO2max within ~1 min during very high intensity exercise
(Poole, 1986); however, the majority, whom are limited by the speed of their VO2 kinetics,
would become exhausted before the attainment of VO2max , and therefore, by definition, would
be exercising within the extreme-intensity domain (Hill et al., 2002; Wilkerson et al., 2004).
Furthermore, the work-time relationship appears to lose its linearity with short (2-3 min)
exercise durations (Monod and Scherrer, 1965; Vautier et al., 1995), and so the use of multiple
short trials should be avoided when using two-parameter modelling procedures. Bishop et al.
(1998) showed that the use of the three shortest predicting trials resulted in a reduction in the
calculated W parameter (when compared to the three longest trials), and may have also inflated
CP. The use of longer trials may be equally problematic because gaining a true time to
exhaustion is likely influenced by the motivation of the individuals. Conversely, the use of
37
many longer trials appears to result in a lower CP, and higher W estimates, than then using
shorter trials (Bishop et al., 1998; Hill et al., 2003).
In light of such evidence it is clear that the duration of trials used to define the power-duration
relationship is of fundamental importance (Poole et al., 1986); especially as the range that
results in a visible hyperbolic relationship is most evident from exercise lasting between 2 and
12 minutes (Hill, 1993). Therefore, selecting a wide range of work-rates, including shorter trials
(~2 min), and others that span the range up to the longest trial (lasting ~12 min), would be ideal
when utilising the two-parameter models.
Number of trials and recovery time between efforts
It is important to consider the number of trials used for the modelling of the power-duration
relationship, and also the rest/recovery period allowed between efforts. For linear two-parameter
models, a ‘perfect’ fit can be attained through using only 2 trials (Housh, et al., 1990).
However, an under/over performance in one of these trials would have a significant effect on the
derived parameter estimates (Housh et al., 1991; Wakayoshi et al., 1993; Clingeleffer et al.,
1994). By definition, modelling a hyperbolic relationship requires at least 3 predicting trials,
and it is generally that with each additional trial, the goodness of fit, standard error, and
confidence intervals increase in a step-wise fashion (Hill and Smith, 1994; Hill and Smith
1999). Housh et al., (1990) used the linear work-time model in each combination of 2, 3 or 4
trials and reported that the CP estimate derived from 2 trials (differing by over 2.7 min) was
strongly correlated (r2 ≥ 0.96) with the estimate from 4 trials. When the difference in time to
exhaustion was over 5 min this correlation increased (r2 ≥ 0.98) along with the standard error of
the estimate. The work of Housh et al. demonstrated that accurate prediction could be made
from just 2 trials if the duration of exercise was within 1-10 min, and that time to exhaustion
differed by over 5 min. Despite this evidence, increased reliability can also be gained from
using additional trials, with 3-4 trials being most common (e.g., Smith and Jones; 2001;
Brickely et al., 2002; Pringle and Jones; 2002; Dekerele et al., 2005), although others have used
to 7 trials (e.g., Hughson et al., 1984; Poole et al., 1990; Gaesser et al., 1995; Bull et al., 2000).
As each trial requires a maximal effort the rest period between trials must also be considered; a
poorly recovered participant may not provide produce an optimal performance, thereby
compromising the derived parameters. Some groups have allowed just 30 min between efforts
(Housh et al., 1990), others have given 12 hours (Jenkins and Quigley, 1991), but the majority
allow at least 24 hours between tests (e.g., Poole et al., 1990; Carnevale and Gaesser, 1991;
Smith and Hill, 1993).
38
Cadence
Modern electronically braked cycle ergometers are capable of controlling the imposed power
output independent of pedal cadence. However, while the absolute work-rate is controlled, at a
lower pedal cadence the braking force applied to the flywheel would be greater than if a
participant was pedalling at a faster rate. It is estimated that with an ‘optimal’ pedal cadence, the
efficiency of the human body from internal work to measured external power output (i.e., delta
efficiency) is around 25-30% (Mosely and Jeukendrup, 2001). However, if sub-optimal pedal
cadences are maintained, efficiency is reduced, falling to ~22% (Chavarren and Calbet, 1999).
MacIntosh et al., (2000) demonstrated that for a given power output, the optimal cadence would
result in the lowest muscle activation, thereby minimising the O2 cost and maximising its
efficiency. These authors also reported an increasing optimal cadence with increasing exercise
intensity; however, higher than optimal cadences increase the O2 cost of exercise (Coyle et al.,
1991).
Given the marked differences in both efficiency and O2 cost of a given work-rate, it is
conceivable that cadence differences would influence time to exhaustion, and as a result also the
power-duration relationship. Minor variations in cadence – and therefore the calculated power
output – were seen during trials performed on a friction-braked ergometer, and may have caused
a small increase in the mean W estimate (Carnevale and Gaesser, 1991). Later studies utilising
cadence-independent protocols on electronic cycle ergometers appear to demonstrate that W is
generally unaffected by cadence (Hill, 1995; McNaughton and Thomas 1996). In contrast, two
groups have shown an increase in the CP estimate using a cadence of 60 rpm versus 100 rpm
(Carnevale and Gaesser, 1991; Hill, 1995). Carnevele and Gaesser (1991) suggest that
individuals are motivated to ‘self-regulate’ their cadence at close to their optimal rate. This
could be attributed to differences in muscle fibre type between individuals, with each person
having an ideal cadence that is related to their particular percentage of each fibre type. In
addition, training at one particular cadence is likely to improve efficiency in both the aerobic
and anaerobic pathways at that ‘ideal’ cadence (Carnevale and Gaesser, 1991). Therefore, given
the body of research available on the effects of pedal cadence, it appears best to allow
individuals ‘self-select’ their optimum cadence, typically within a range of ~60-100 rpm (Hill et
al., 2003).
The physiological response to exercise above and below critical power
Poole et al., (1988) identified the distinct pulmonary gas exchange and acid-base profiles to
exercise performed at CP and exercise undertaken at a work-rate just 5% above CP. Exercise
performed at CP (i.e., at the very upper end of the heavy domain) elicited a rapid increase in
39
VO2 and blood [lactate] during the first minutes of exercise. After a few minutes of exercise, a
pronounced VO2 slow component was evident, which stabilized (as did blood [lactate] at ~5-6
mM), and remained relatively constant; all participants completed the target of 24 min of
exercise. Contrastingly, for exercise performed just 5% above CP a completely different
metabolic scenario was evident: following the primary VO2 phase, both VO2 and blood
[lactate] increased inexorably throughout exercise until the attainment of VO2max and the point
of exhaustion (typically within ~17 min). These observations demonstrate a clear difference in
the physiological response to exercise relative to CP; and this disparity has a profound effect on
exercise tolerance – exercise just below CP can be tolerated for some time, whilst just above
CP, the metabolic scenario deteriorated progressively until exercise became unbearable.
However, given that a steady-state was attained during exercise performed at CP, a more
contemporary viewpoint would suggest that this exercise was likely performed at a work-rate
below CP – and indeed, at CP is an estimate of a work-rate, rather than a physiological
measurement per se, the original interpretation was not wide of the mark.
More recently, Jones et al., (2008) investigated muscle metabolic responses to exercise both
above and below CP, via 31Phosphorous magnetic resonance spectroscopy (31P-MRS). The aim
of their study was to further examine the aetiology of fatigue in human muscle during 20 min of
single-leg knee-extension exercise performed 10% above, and 10% below, CP.
31
P-MRS
estimates of [PCr], [Pi] and pH were made throughout each exercise bout to create an
intramuscular fatigue profile. Participants completed the 20 min bout of exercise at 10% below
the CP with relative ease. During this bout, following an initial rapid change [PCr] fell to about
75% of baseline levels and remained stable to the end of the exercise bout. Similarly, [P i] rose
initially, but reached a stable level after ~1 min of exercise, and no significant change in Pi was
then seen between this time and the end of exercise. As would be expected, pH fell at exercise
onset, but again stabilised at ~3 min. Furthermore, a slight recovery in pH was recorded after
~6-8 min, such that no significant difference was seen between end exercise pH and that
measured at rest. It could be argued that these observations indicate an intramuscular steadystate that supports the observations of Poole et al., (1988). Exercise performed 10% above CP
elicited a completely different metabolic scenario, with a continued decline in muscle [PCr] and
pH throughout exercise, and a continued rise in [Pi] until the point of exhaustion. [PCr] fell
precipitously throughout exercise, with an average of just 26% of baseline remaining at the end
of exercise. Similarly, pH declined from 7.07 at rest to 6.87 at the point of exhaustion. [P i] was
shown to rise more rapidly above CP (when compared to <CP), however, a non-significant
increase was shown from 3 min to the end of exercise; the authors suggest that the intraindividual variation in this measure prevented the attainment of a statistical difference. Despite
40
this finding, the end exercise [Pi] was significantly different between the two exercise
conditions, with the mean increase in [Pi] being almost twice as great for exercise performed
above CP.
It is apparent that ‘aerobic’ capacity is an important determinant of CP (Moritani et al., 1981;
Poole et al., 1988). Another potential determinant that has received little direct experimental
attention is that of muscle blood flow, and in particular the distribution of this blood flow to
specific muscle fibres during exercise. Copp et al., (2010) utilised microspheres injected into
the aortic arch of an exercising rat to measure hind limb blood flow during exercise performed
just below and just above critical speed (CS). As seen in humans, exercise below CS was
maintained for a considerable period (>45 min), whereas exhaustion occurred within 5-10 min
when exercise was performed above CS. Hind limb blood flow was significantly increased (by
~35%) during the higher intensity exercise bout, and perhaps more importantly, almost half (15
out of 28) of the muscle or muscle regions received elevated blood flow above, compared with
below, CS. These blood flow measurements show an increase in muscle fibre recruitment above
CS, and the additional recruited regions predominantly consisted of ‘glycolytic’ type II fibres.
Thus, exercise above CS required a disproportionate increase in blood flow, predominantly in
the glycolytic muscle fibres, which have a higher recruitment threshold compared to the slower
‘aerobic’ (type I) fibres (Henneman et al., 1965). Of course, caution should be taken when
comparing data from animal preparations to infer changes in humans. As discussed previously,
in an exercising human the highly oxidative (type I) fibres are initially recruited at exercise
onset, causing VO2 to increase exponentially to attain a steady-state when the energy demand is
met (i.e., for exercise <CP). For higher intensity exercise (i.e. >CP), the type I fibres cannot
match the energy demand, causing these fibres to fatigue. This causes a progressive recruitment
of additional, but less efficient type II glycolytic muscle files, and therefore represents a decline
in muscle efficiency and a perturbation of intracellular homeostasis (cf. Jones et al., 2008). The
recruitment of these new fibres create the VO2 ‘slow component,’ and causes VO2 to
progressively develop until the attainment of VO2max and the point of exhaustion (cf. Poole et
al., 1988). The data from these studies provide an understanding of the importance of CP as a
reliable indicator of an intensity of exercise that can, or cannot, be maintained (i.e., < CP or
>CP, respectively).
Physiological determinants of W
The physiological determinants of the curvature constant of the power-duration relationship (i.e.
W) have been the cause of much debate. However, W represents an amount of ‘work’
(expressed in kJ) that can be utilized at a predictable rate until it becomes fully depleted, at
41
which point the exercise task becomes intolerable. Experimentally confirming a direct
relationship between a mathematical construct (i.e. W) and a physiological mechanism is not
possible. Nonetheless, a number of experimental interventions have been utilised to suggest the
likely physiological origin of W.
Historically, W has been suggested to be principally ‘anaerobic’ in nature (Monod and
Scherrer, 1965; Moritani et al., 1981) and so investigators have attempted to manipulate the
major anaerobic energy stores and to identify a change in the W. The suggestion that
intramuscular phosphocreatine (PCr) and glycogen stores are principal determinants of W has
considerable experimental support as the oral ingestion of creatine monohydrate has been shown
to increase intramuscular PCr stores (e.g., Chanutin, 1926; Harris et al., 1992; Hultman et al.,
1996). An increase in [PCr] following creatine supplementation has been shown to increase
performance during maximal knee extension exercise (Greenhaff et al., 1993) and isokinetic
cycling (Birch et al., 1994). Indeed, during severe-intensity exercise, creatine supplementation
increased time to exhaustion during the highest 2 (of 4) work-rates and resulted in a significant
increase in W (Smith et al., 1998). Miura et al., (1999) employed a similar protocol to Smith et
al., (1998) and again reported an increase (of ~26%) in W and concluded that both creatine
and/or PCr appear to be an important determinant of the curvature constant parameter of the
power-duration relationship for cycle ergometry. Indeed, Smith et al., (1999) demonstrated that
creatine supplementation did not alter CP, but the increase in W was augmented by additional
carbohydrate supplementation, thereby confirming the importance of glycogen (and glycolysis)
as a constituent of W. Miura et al., (2000) further investigated the effect of glycogen depletion
on the power-duration relationship parameters. To induce a state of glycogen depletion,
participants exercised for 75 min at 60% VO2max before undertaking repeated 1 min intervals (at
115% VO2max , with 1 min recovery) until task failure on the evening prior to the experimental
trials. Following an overnight fast, participants then performed one of the four high-intensity
exercise bouts, with the other three performed at one-week intervals thereafter. CP remained
unchanged between the control and glycogen depletion conditions, whereas glycogen depletion
reduced W by ~24%. During high intensity exercise which induces fatigue in ~10 min it has
been shown that muscle glycogen stores remain high at the point of fatigue (in the control
condition; Miura et al., 2000), whereas work-rates of ~60-85% VO2max have shown almost
completely depleted glycogen stores at the point of exhaustion (Bergstrom et al., 1967).
Therefore, the reduction in W following glycogen depletion in the work of Miura et al., (2000)
would indicate that the glycogen status (and hence PCr storage) of the participant is another
42
principal determinant of W, and if the intensity of exercise performed derives a significant
proportion of energy turnover from the stores of W (i.e. of exercise is performed above CP).
This evidence has led many investigators to consider W to be synonymous with the anaerobic
work capacity (e.g., Moritani et al., 1981; Hill, 1993; Whipp and Ward 1994) and so a
comparison of the W with other anaerobic indices may provide further insight into the
physiological determinants of W. The 30 s all-out Wingate test is one of the most commonly
used ‘anaerobic’ exercise tests and employs a protocol in which participants perform maximal
sprint efforts against a fixed resistance on a cycle ergometer (Inbar et al., 1976). Subsequently,
two groups have shown the mean power output of a Wingate test to be related to W (NebelsickGullet et al., 1988; Vandewalle et al., 1989). The later of these studies demonstrated that the
total work done during the Wingate test was correlated but significantly greater than W.
Furthermore, it was suggested that it would not be possible to deplete the total ‘anaerobic
capacity’ during a 30 s Wingate test as the power output at the end of the test was significantly
higher than that associated with the incremental test derived VO2max (Vandewalle et al., 1989).
Indeed, performance of repeated high-intensity bouts of exercise can effect with the magnitude
of the W. For example, high intensity exercise without sufficient rest reduces W (e.g. Ferguson
et al., 2010), whilst a period of sprint interval training increases the capacity for high-intensity
exercise, and tends to increase W (Jenkins and Quigley, 1993). The maximal accumulated
oxygen deficit (MAOD) is determined as the difference between the measured VO2 and the
calculated oxygen demand during supramaximal exercise (Medbo et al., 1988). This concept is
widely used as an index of the anaerobic capacity, and may be related to W (Hill and Smith,
1994; Miura et al., 2002; Chatagnon et al., 2005). Chatagnon et al., (2005) utilised 5-6
predicting trials to estimate W and used the VO2 -WR relationship (to convert from ‘litres of
oxygen’ to a value in kJ) to derive a MAOD value that was correlated (r2 = 0.76) but
significantly lower (~14 kJ) that that seen for W (~25 kJ). These data suggest a common
‘anaerobic’ link between the MAOD and W, although these parameters likely describe different
indices.
With this evidence, it appears that the energy related to W is indeed principally derived through
substrate-level phosphorylation, i.e. from the breakdown of phosphocreatine (PCr) and glycogen
(leading to the formation of lactate), and a small contribution from previously stored O2 (bound
to myoglobin and haemoglobin). Indeed, the close relationship between this parameter and other
‘anaerobic’ type exercise tests would further support this contention. However, other evidence
exists that may question whether this parameter is purely an anaerobic energy reserve, and as
such questions the original hypothesis of Moritani et al., (1981). In a recent study, Ferguson et
43
al., (2010) had participants perform an initial bout exhaustive exercise, which was followed by a
further exhaustive bout of exercise performed 2, 6 or 15 min after the initial bout. These
subsequent bouts were used to define the power-duration relationship and to investigate the
recovery of W, VO2 and blood [lactate] following each recovery period, and demonstrated that
W recovered to 37, 65 or 86% with increasing recovery time, whilst CP was unchanged.
Furthermore, the recovery of W was appreciably slower than that of VO2 , and faster than that
of blood lactate. This latter observation is important as it suggests that the reconstitution of W
is not a unique function of intramuscular PCr or arterial blood [lactate]. As such, it is unlikely
that W simply represents a finite energy store that becomes completely depleted at the point of
exhaustion (Ferguson et al., 2010).
In addition, the performance of prior high-intensity (>LT) exercise can, with a suitable recovery
period (Burnley et al., 2006; Bailey et al., 2009) increase exercise tolerance during subsequent
high-intensity exercise (e.g., Jones et al., 2003; Burnley et al., 2005; Bailey et al., 2009). This
effect is a result of a ‘speeding’ of the overall VO2 kinetics (principally as a result of a
reduction in the VO2 slow component; e.g. Burnley et al., 2005), and has been attributed to
additional/alternative muscle fibre recruitment (e.g., Burnley et al., 2002; Krustrup et al., 2004).
Miura et al. (2009) demonstrate an increase in CP following such an intervention, and as may be
expected due to an enhanced ‘aerobic’ response (i.e. the VO2 kinetics). However, in an earlier
study, an increase in exercise tolerance following a priming bout of exercise performed at 50%
 followed by 10 min recovery, was a result of similarly primed VO2 kinetics, but not as a
result of a change in CP, but due to an apparent increase in W. Each of these studies
demonstrated a significant reduction in the VO2 slow component alongside an increase in
exercise tolerance. This observation may be important because the relationship between the
VO2 kinetics and the degradation of intramuscular [PCr] are closely related (Rossiter et al.,
1999; Rossiter et al., 2000). Indeed, It is well known that the rate of depletion of W is directly
related to the intensity of the imposed power output above CP (Roston et al., 1987), and so a
reduction in the VO2 slow component may suggest a reduced utilization of PCr, the likely
primary constituent of W. Indeed, the more rapidly W is expended, the greater the
accumulation of metabolites that are attributed with the fatigue process (e.g., Pi, ADP, H+, and
intracellular K+; Fitts, 1994; Wilson et al., 1988; Westerblad and Allen, 2003; Robergs et al.,
2004; Jones et al., 2008). In a recent study, DiMenna et al., (2010) demonstrate support for this
contention as the amplitudes of both the VO2 and PCr slow components were reduced during
moderate- to heavy-intensity prone-kicking exercise transitions. Therefore, given the apparent
44
close association between the VO2 slow component, W and the accumulation of metabolites –
it could be argued that either the depletion of [PCr] (and the rate of anaerobic glycolysis), or the
accumulation of these metabolites which are implicated with the fatigue process, leads to the
expression of W.
45
2.4 - Mechanisms of fatigue
Historically, muscle fatigue has been defined as the failure to maintain a required or expected
power output, leading to a reduction in exercise performance (Asmussen 1979). By definition,
fatigue is characterized by a loss of muscle power that results from a decline in both force and
velocity of muscular work (Fitts, 1994), and fatigue is distinguishable from muscle weakness or
damage because the reduction in power output is reversible by rest (Fitts, 1994). The causes of
fatigue are complex; this is not a simple process with a single cause; many factors contribute to
fatigue and these differ depending upon the intensity and duration of the exercise bout (Fitts,
1994; Allen et al, 1995). Depending upon the circumstances of exercise, fatigue may result from
disturbances in the central nervous system (Gandevia, 2001; Taylor and Gandevia, 2008) and/or
peripheral factors within the skeletal muscle (Karlsson and Saltin, 1970; Hermansen and Osnes,
1972; Fitts, 1994; Allen et al, 1995; Westerblad et al., 1998; Allen et al., 2008; Fitts, 2008;
Jones et al., 2008). Therefore, understanding the processes that govern the fatigue process, and
which limit exercise tolerance during moderate, and particularly during high-intensity exercise,
has far reaching implications not only for athletic populations, but also throughout the wide
spectrum of health and disease.
Determinants of endurance performance – traditional perspectives
During human locomotion, theoretical best performances are determined by the product of the
energy cost of exercise (i.e., the amount of metabolic energy spent to cover one unit of distance)
and the maximal metabolic power of the individual (i.e., a function of the maximal aerobic
power and the maximal anaerobic capacity; di Prampero 2003). As the ‘anaerobic’ capacity is
finite, the tolerable duration of prolonged high-intensity exercise appears to depend principally
on
‘aerobic’
parameters,
such
as
maximal
oxygen
uptake
( VO2max ),
exercise
economy/efficiency, or those related to ‘anaerobic’ energy provision, including lactate threshold
(Coyle, 1995; Bassett and Howley, 2000; Jones et al., 2010). Within the laboratory, scientists
typically perform correlation or regression analyses on measures of oxidative capacity (e.g.,
VO2max ), exercise/economy (i.e., the VO2 -WR relationship), or the LT, against some measure
of ‘performance’, such as time to exhaustion at a given work-rate or the time taken to complete
a set amount of work (Coyle et al., 1988; Coyle, 1995; Jones and Doust, 1998; Bassett and
Howley, 2000). The outcome of such analyses is often that each of these parameters is strongly
correlated with performance, but each does not explain specifically why they may determine
exercise tolerance.
46
Determinants of endurance performance – a contemporary viewpoint
An alternative hypothesis was presented by Burnley and Jones (2007): none of the
aforementioned traditional parameters determine endurance performance; rather, they establish
the ‘character’ of, and place constraints upon, the VO2 kinetics during exercise. In turn, the
VO2 kinetics set the rate of aerobic and anaerobic energy turnover at any given moment, the
mixture and amount of substrate utilized, and thus, these factors then determine the tolerable
duration of exercise.
For example, the lactate threshold defines the boundary between the moderate- (<LT) and
heavy- (>LT) intensity domains (Whipp and Wasserman, 1972). Moderate exercise displays a
stable VO2 response and little alteration in acid-base status or blood [lactate] (Whipp et al.,
1982). For heavy-intensity exercise, VO2 also stabilises, but is elevated above that predicted
from the sub-LT VO2 -WR relationship. The resultant increase in VO2 increases the rate of
glycogen utilization, and causes an elevated, but stable blood [lactate] during exercise. While
the LT may define the work-rate that separates these exercise intensity domains, it is the change
in the VO2 response (which controls the type and rate of substrate utilization and acid-base
status) that directly impacts an individual’s tolerance to exercise rather than the LT per se
(Burnley and Jones, 2007). Indeed, if the exercise intensity is increased further, a second higher
threshold exists, above which a steady-state in VO2 can no longer be attained (Poole et al.,
1988; Jones et at 2008). This point corresponds with the asymptote of the power-duration
relationship (i.e., CP), and defines the boundary between the heavy- and severe-intensity
domains (Moritani et al., 1981). During severe-intensity exercise, VO2 increases as a function
of work-rate and time (Roston et al., 1987), and VO2 progresses until the attainment of VO2max
(Coats et al., 2003). Indeed, VO2 ‘slow component’ appears central to exercise tolerance as it
represents a progressive reduction in muscle efficiency, and is related to the accumulation of
fatigue-inducing metabolites and falling pH (such as Pi, H+ and intracellular K+; Jones et al.,
2008). Therefore, the ‘speed’ (i.e., the trajectory) of the VO2 slow component appears critical,
as this determines the rate of muscle fatigue, accumulation of metabolites, fall in pH, and time
taken to attain VO2max . The trajectory of the VO2 slow component can be calculated with the
following formula:
Slow component trajectory
=
As
(Tlim - [4 · P])
47
Where As is the amplitude, Tlim is time to exhaustion, and p is the time constant of the primary
VO2 response. As with the LT, CP does not directly determine exercise tolerance; but it does
determine the nature of the VO2 response, which then in turn determines the type and rate of
substrate utilization, acid-base status, and metabolite accumulation during exercise (Burnley and
Jones, 2007).
Interaction between the oxygen uptake kinetics and the power-duration relationship
By definition, severe-intensity exercise is performed under non steady-state conditions. As such,
it is reasonable to suggest that the VO2 kinetics are closely related to the parameters of the
power-duration relationship (Burnley and Jones, 2007). The ability to perform exercise above
CP (i.e., the highest work rate that can attain a steady state in VO2 ) appears to be determined by
the development of the VO2 slow component (and the time taken to reach VO2max ) and the
progressive depletion of W. Measurement of the former can be easily undertaken in many
laboratories, whilst determining the time course of the latter is far more difficult – principally as
the determinants of W are presently unclear. Traditionally, W has been regarded as a fixed
energetic reserve (comprised of the high-energy phosphate pool, anaerobic glycolysis, and
previously stored O2; Moritani et al., 1981; di Prampero et al., 1999). If this were the case, W
would be depleted at a rate proportional to the magnitude of the power demand above CP
(Fukuba et al., 2003). As such, it may be utilized rapidly by work performed at high power
outputs, or eked out over exercise of a longer duration but lower intensity (Fukuba and Whipp,
1999). The notion that W is a fixed energy source is supported by the strong linear relationship
between power output (above CP) and exercise time seen within the literature (Monod and
Scherrer, 1965; Moritani et al., 1981; Hill, 1993; Bull et al., 2000; Jones et al., 2010).
Furthermore, it could be argued that it is the VO2 kinetics that determines the rate of W
depletion during exercise. For example, the VO2 in response to an increase in work-rate is
important, as both the amplitude and time constant (τ) determine the magnitude of the O2 deficit
(Whipp et al., 1982). The energy deficit during this phase (as a result of a delayed VO2
response) is compensated by substrate-level phosphorylation; the very same source of energy
that has been suggested to constitute W (Moritani et al., 1981). Furthermore, the increase in
VO2 during exercise has been shown to be a near mirror image of the decline in intramuscular
[PCr] (Rossiter et al., 2001; Rossiter et al., 2002), thereby directly related to the depletion of
W, and by extension, the progressive accumulation of metabolites associated with the fatigue
process (e.g., ADP, Pi, H+, and intracellular K+; Jones et al., 2008). Thus, it could be argued that
the development of the VO2 slow component is directly related to the depletion of the
48
‘anaerobic’ energy store or the accumulation of fatigue-inducing metabolites, which result in the
expression of W.
Individuals with a high tolerance for exercise tend to have ‘fast’ primary VO2 kinetics (i.e., a
small τ), and CP is situated at a high percentage of a similarly high VO2max (Cerretelli et al.,
1979; Jones, 2006). This scenario minimises the O2 deficit at exercise onset, extends the range
of work-rates at which the VO2 slow component can stabilise, and provides a high ceiling for
its development (i.e., a high VO2max ). In contrast, untrained individuals (Neder et al., 2000;
Koppo et al., 2004), and particularly those suffering from a range of respiratory, cardiovascular,
or muscular disease states (Nery et al., 1982; Sietsema et al., 1986; Neder et al., 2000; Mezzani
et al., 2010), demonstrate far ‘slower’ VO2 kinetics and incur a larger O2 deficit at exercise
onset. This increases the rate of glycogen utilization, and as CP occurs at a far lower absolute
work-rate, the VO2 slow component appears sooner and can only develop to attain a relatively
low VO2max . Murgatroyd et al. (2011) propose that the kinetics of VO2 are directly related to
the parameters of the power-duration relationship and provide correlative data to test the
following hypotheses: (1) the VO2 primary τ would be inversely related to CP; and (2) the VO2
slow component amplitude would be positively related to W. Each participant performed an
initial set of power-duration trials to determine a work-rate that would elicit exhaustion in 6 min
(WR6). Then on average, five transitions to this work rate were performed (to elicit 95% CIs of
the primary τ to 5 s), with the aim being to provide a high confidence in the modelled VO2
kinetics. The VO2 kinetics of each participant was then correlated with previous estimates of
the power-duration relationship. As hypothesised, it was demonstrated that the primary τ was
inversely correlated with CP (r2 = 0.90), thereby supporting the notion that individuals with
faster VO2 kinetics have an appreciably higher CP (enabling a VO2 steady-state to occur at a
higher-work rate) than those with slower VO2 kinetics. Furthermore, the change in VO2 slow
component was positively correlated with W (r2 = 0.76), and for exercise performed above CP,
a ‘fatigue-cascade’ ensues that links the depletion of W with the development of the VO2 slow
component. Collectively, these observations support the earlier hypothesis of Burnley and Jones
(2007), and provide data that experimentally implicates the VO2 kinetics as a key determinant
of severe-intensity exercise tolerance. It is noted, however, that such experimentation is purely
correlational, and does not prove a cause and effect relationship – further research is required to
confirm the link between the VO2 kinetics and the power-duration relationship.
49
2.5 - Interventions to test the link between the oxygen uptake kinetics and the
power-duration relationship
Burnley and Jones (2007) present a compelling hypothesis that highlights the important role of
the VO2 kinetics in determining exercise tolerance across the exercise intensity domains. These
authors also discuss the potential interaction between the kinetics of VO2 and parameters of the
power-duration relationship (i.e., CP and W) during severe-intensity exercise. Recently,
Murgatroyd et al. (2011) provided interesting correlational data that links the speed of the
primary VO2 kinetics with CP, and the VO2 slow component with W. The following section
will briefly review a range of such interventions which manipulate the VO2 kinetics, VO2max , or
the capacity for substrate-level phosphorylation. The physiological effects of such interventions
should elicit predictable effects on exercise tolerance and the power-duration relationship, and
investigating these relationships may further our understanding of high-intensity exercise
tolerance.
Muscle metabolism
High-energy phosphates stores
It was originally proposed that the high-energy phosphate pool (chiefly phosphocreatine; PCr)
was a principal determinant of W (Moritani et al., 1981). Therefore, intervention that increases,
or reduces, intramuscular [PCr] should have a predictable effect on the magnitude of W – if this
initial hypothesis is correct. Oral creatine supplementation has been shown to increase muscle
PCr content (Miura et al., 1999), and this effect is augmented with simultaneous carbohydrate
ingestion (Smith et al., 1999). Furthermore, Smith et al. (1999) demonstrate that an increase in
intramuscular PCr following creatine supplementation led to a significant increase in W. Whilst
glycogen depletion has been shown to reduce the storage of PCr, leading to a reduction in W
(Miura et al., 2000). The combination of these observations provides strong support for PCr as a
major determinant of W. However, the performance of high-intensity exercise (i.e., >LT) serves
to ‘prime’ the VO2 kinetics, mainly due to a reduction in the VO2 slow component (Burnley et
al., 2005). If sufficient recovery is allowed, this priming can elicit an ergogenic effect during
subsequent high-intensity exercise (e.g., Bailey et al., 2009), such that mean power output and/or
time to exhaustion are increased/extended (Jones et al., 2003; Burnley et al., 2005; Miura et al.,
2009). This ‘priming effect’ appears to be the result of an alteration in muscle fibre recruitment
that increases the oxidative contribution to energy turnover (e.g., Burnley et al., 2002). It could
be argued that this effect would enhance the similarly ‘aerobic’ parameter, CP, as demonstrated
50
by Miura et al. (2009). However, a counterargument would be that a reduction in the VO2 slow
component would extend the time take to attain VO2max , which is representative of increased
capacity to perform work above CP – or increase W – as suggested by Jones et al. (2003).
Reconciling these differences will help us to further understand the mechanistic underpinnings
of W – be it a ‘fixed’ anaerobic energy reserve (Moritani et al., 1981), or simply the capacity to
perform work above CP (Monod and Scherrer, 1965). The performance of fatiguing prior
exercise (i.e., performed >CP, with little or no recovery) would likely reduce muscle PCr stores
and also W (Billat et al., 1999; Heubert et al., 2005; Ferguson et al., 2007; Vanhatalo et al.,
2009). Recently, Ferguson et al. (2010) demonstrated a progressive recovery in W following a
fatiguing bout of exercise that was appreciably slower than that of VO2 , but faster than that of
blood [lactate]. Given the close relationship between the kinetics of VO2 and the utilization of
PCr (Rossiter et al., 2001; Rossiter et al., 2002), disparity between the recovery of VO2 and W
provides support for the notion that W may not be (entirely) an ‘anaerobic energy reserve’ as
first thought (Moritani et al., 1981).
Metabolite accumulation
Poole et al. (1988) suggest that exercise tolerance above CP may be related to the rate of decline
of some intramuscular factors, such as PCr or pH, to some consistent and low limiting value. In
support of this notion, Jones et al. (2008) demonstrated that both inorganic phosphate (Pi) and
pH fall precipitously over the first 3-6 min of single-leg knee-extension exercise performed
above CP, whilst a progressive reduction in [PCr] was observed until the point of exercise
intolerance (~15 min). Whilst a metabolic steady-state was rapidly attained, and maintained,
throughout the duration of a 20 min bout of exercise performed below CP (Jones et al., 2008).
Furthermore, the higher the work-rate above CP, the faster intramuscular stores of PCr are
depleted (alongside an increase glycolytic rate), and the quicker the bi-products of these
reactions accumulate in the muscle and/or blood (i.e., ADP, Pi, H+, lactate, and intracellular K+;
Monod and Scherrer, 1965; Moritani et al., 1981; Poole et al., 1988; Jones et al., 2008). The
accumulation of these metabolites, and falling pH, are implicitly involved within the
intramuscular fatigue process (Fitts, 1994; Allen et al., 2008; Amann and Calbet, 2008; Allen,
2009). The rate of accumulation of these metabolites appears to be directly related to the
development of the VO2 slow component (Rossiter et al., 2001; Rossiter et al., 2002).
Therefore, during severe-intensity exercise it is reasonable to suggest that as VO2 develops to
attain VO2max (Coats et al., 2003), intramuscular PCr (and pH) will decline, and these fatiguerelated metabolites will accumulate at a similar rate. Recent data would support that contention;
51
irrespective of the inspired O2 fraction, and despite similarly low values of PCr and pH, and
high levels of Pi at exhaustion, hyperoxic breathing attenuated the VO2 slow component and
enhanced exercise tolerance (Vanhatalo et al., 2010). Indeed, Vanhatalo et al. showed an
increase in CP and a small reduction in W with hyperoxia. This finding suggested that the
increase in muscle O2 availability reduced the development of the VO2 slow component and
delayed the perturbation of intracellular homeostasis. Further, the combination of these factors
likely led to the improvement in performance, as the final muscle metabolic state was similar in
normoxia and hyperoxia. Investigating the link between the VO2 slow component and depletion
of the ‘energetic reserve’ – or the rate of ‘metabolite accumulation’ that is expressed as W would be an important next step in understanding the complex nature of high-intensity exercise
tolerance.
Acid-base status
Sustained energy production through the hydrolysis of PCr and anaerobic glycolysis results in
an inevitable formation of lactate and the production of hydrogen ions (H +). These conditions
cause the internal environment of the cell to become more acidic, alongside the accumulation of
metabolites discussed previously (Jones et al., 2008). An important question to consider: what
role does the fall in pH play during severe-intensity exercise? It has been shown that when pH
falls to critical levels, contractile function of the muscle fibres is reduced (Fuchs et al., 1970;
Mainwood and Cechetto, 1980), pH sensitive enzymes, such as phosphofructokinase (PFK;
Trivedi and Danforth, 1966; Kemp and Foe, 1983) are inhibited, limiting energy production
through glycolytic pathways (Sutton et al., 1981). It is possible to offset the fall in pH through
artificially induced alkalosis in the blood through the supplementation of sodium bicarbonate
(NaHCO3) or other similar compounds. Such supplementation enhances buffering capacity
through changes in pH and [HCO3-]), thereby attenuating the rate of H+ accumulation and the
associated fall in pH (Requena et al., 2005; McNaughton et al., 2008). Raymer et al. (2004)
utilised both 31P-MRS and venous blood sampling to determine changes in muscle metabolism
and blood acid-base balance during incremental forearm exercise both with and without
alkalosis. These authors noted an increase in performance with alkalosis (of ~12%), which was
associated with a delayed onset of intracellular acidosis and a delayed but rapid decline in [PCr]
(i.e., a delayed onset of the PCr slow component). No differences were seen in [H +], [Pi] or
blood [lactate]. Two important observations can be made from this data: (1) sodium bicarbonate
increased resting blood pH, thereby enabling a greater blood lactate and H+ efflux throughout
exercise to attain similar values at exhaustion; (2) the delay in the PCr slow component would
52
suggest that alkalosis may have a similar effect on the kinetics of VO2 , and therefore suggests
that an increase in exercise tolerance may be expected during whole-body exercise.
The primary VO2 amplitude is consistently unchanged with alkalosis, whilst the primary time
constant has been reported as faster, slower, and unchanged following alkalosis (Berger et al.,
2006; Kolkhorst et al., 2004; Zoldaz et al., 2005). The amplitude of the VO2 slow component is
typically reduced, or emerges later (Kolkhorst et al., 2004; Berger et al., 2006), suggesting that
attenuation of the phosphocreatine (PCr) slow component may be associated with a similar
reduction in muscle VO2 (Raymer et al., 2004; Forbes et al., 2005). These effects in isolation,
or indeed in combination, would suggest an ergogenic effect. However evidence to support such
an effect remains equivocal at best (Matsun and Tran, 1993; Requena et al., 2005; McNaughton
et al., 2008). In addition, theoretically, alkalosis appears to maintain the function of
phosphofructokinase (PFK) by reducing the inhibitory effect of falling pH, and significant
increases in both muscle and blood [lactate] would support this contention (Osnes and
Hermansen, 1972; Sahlin et al., 1978). Indeed, these observations suggest that alkalosis
preserves, or may even increase, the glycolytic contribution to total energy turnover during
exercise in which these functions are generally perturbed by acidosis (Jones et al., 1977; Sutton
et al., 1981; Bishop et al., 2004; Requena et al., 2005). Again, theoretically, if anaerobic
glycolysis is a major constituent of W, and induced alkalosis enhances such energy turnover,
then an increase in W would likely been seen following sodium bicarbonate ingestion.
However, in a recent study, Vanhatalo et al. (2010) demonstrated that during the ‘3 min all-out
CP test’ both peak and mean power output were unchanged following the ingestion of NaHCO3;
both CP and W were also unaltered. It is clear that there is a complex interplay between the
VO2 kinetics and muscle metabolism during exercise, however, precisely how these factors
interact to influence exercise tolerance is still unclear. Therefore, further investigating the effect
of manipulations in acid-base status on the VO2 kinetics could prove fruitful to our
understanding of exercise tolerance.
Muscle oxygen availability
The O2 transport system – that is, convective and diffusive O2 delivery, peripheral O2 extraction,
and the O2 diffusing capacity of the active muscle – plays an important role in setting the
‘speed’ (i.e., the VO2 kinetics), sustainability (i.e., CP), and maximal rates of oxidative energy
production (i.e., VO2max ; Poole et al., 1988; Wagner, 1996; Bassett and Howley, 2000; Wagner
2000; Richardson, 2000; Gonzales-Alonso and Calbet, 2003). The limitation and control of
these ‘aerobic parameters’ are likely influenced by a number of factors which manipulate
53
muscle O2 availability or utilization, including: the environment (e.g., the inspired O2 fraction;
MacDonald et al., 2000; Calbet, 2003); participant characteristics (e.g., age and training or
disease status; Cerretelli et al., 1979; DeLorey et al., 2004); and the type of exercise performed
(including its modality, body position, muscle mass recruited, and the intensity of the exercise;
e.g., Koga et al., 1999; Tschakovsky and Hughson, 1999; Jones and Poole, 2005). How some of
these factors influence the kinetics of VO2 , exercise tolerance, and the parameters of the powerduration relationship are considered in the following sections.
Inspired oxygen fraction
Alterations in the inspired O2 fraction have been used by a number of research groups to
investigate the effect of muscle O2 availability on VO2 kinetics, VO2max , and exercise tolerance.
Hypoxia reduces the O2 content of the air (compared to normoxia) and ‘slows’ the primary VO2
kinetics (as demonstrated by a reduced primary time constant; ; Engelen et al., 1996; Cleuziou
et al., 2005). In addition, the amplitude of the VO2 slow component is generally reduced in
hypoxia (Cleuziou et al., 2005), presumably limited in scope by a reduction in VO2max , which in
turn reduces exercise tolerance (Calbet et al., 2003). Hyperoxia appears to have little effect on
the primary VO2 time course () during exercise performed in the heavy- or severe-intensity
domains (Wilkerson et al., 2006). Furthermore, the development of the VO2 slow component is
reduced with hyperoxia (MacDonald et al., 1997; Wilkerson et al., 2006), thereby delaying the
time taken to attain VO2max and extending time to exhaustion (Wilkerson et al., 2006). This
research was recently supported by Vanhatalo et al. (2010), who demonstrated an attenuation of
the PCr slow component with hyperoxia alongside an increase in exercise tolerance. Vanhatalo
et al. (2010) also showed for the first time that an increase in muscle O2 availability increased
CP and slightly reduced W. If, as traditionally suggested, substrate-level phosphorylation
accounts for the vast majority of W, then why an increase in O2 availability altered this
parameter is puzzling, although it has been reported that glycogenolysis may be reduced during
high-intensity exercise performed in hypoxia (Stellingwerff et al., 2006). Further investigations
into the effect of the inspired O2 fraction on the power duration relationship are required, using
traditional methods, and specifically to determine the effect of hypoxia, and to confirm [or
disconfirm] the effects noted by Vanhatalo et al. (2010).
Oxygen transport in the blood
An effective method to manipulate O2 delivery to the working muscle is through changes in
blood haematology: through changes in red blood cell count (RBC), haemoglobin concentration
54
([Hb]), haematocrit (Hct), or through manipulations in blood volume which change the ratio of
red cells to plasma. Such changes can be achieved through the removal (donation) of whole
blood (e.g., Balke et al., 1954; Burnley et al., 2006), its subsequent (re)infusion (e.g., Ekblom et
al., 1972; Ekblom et al., 1976; Spriet et al., 1986), the administration of human recombinant
erythropoietin (RhEPO; e.g., Ekblom and Berglund, 1991; Wilkerson et al., 2005), or through
acute plasma volume expansion (APVE; Berger et al., 2006). Karpovich and Millman (1942)
presented the first evidence that performance during endurance events was affected to a greater
extent than short duration events with a reduced [Hb] seen following blood donation, with
similar findings being reported during subsequent work (e.g., Balke et al., 1954; Ekblom et al.,
1972; Ekblom et al., 1976). The subsequent reinfusion of packed red blood cells returned [Hb]
and performance back to (or slightly above) pre donation levels (e.g., Ekblom et al., 1972;
Ekblom et al., 1976; Spriet et al., 1986). Similarly, the administration of RhEPO has been
shown to increase [Hb] and subsequent exercise tolerance (e.g., Russell et al., 2002; Wilkerson
et al., 2005). The findings of these studies consistently demonstrate the importance of [Hb]
which, when reduced following blood donation, results in a reduction in performance (of ~14%;
Burnley et al., 2005); further, exercise tolerance increases following the (re)infusion of
erythrocytes (of 23%; Ekblom et al., 1972) and RhEPO administration (of ~22%; Wilkerson et
al., 2005). Kanstrup and Ekblom, (1984) imposed APVE in the period after blood donation, and
before reinfusion, and showed that the increase in blood volume returned performance to control
levels. Berger et al. (2006) further investigated the effect of APVE, and as would be expected,
an increase in plasma volume served to reduced the relative [Hb] and increased time to
exhaustion by 16%, with no change in the absolute red blood cell count (RBC). This increase in
performance following APVE could be attributed to an increase in total blood volume,
indicating a larger stroke volume, and therefore presumably cardiac output (Bassett and
Howley, 2000).
Connes et al. (2003) administered RhEPO to participants over a four-week period and
demonstrated a significant speeding (in terms of a reduced time constant; τ) of the primary VO2
kinetics in endurance athletes. This work posed some issues of concern, however, due to single
step transitions and unclear identification of the intensity domain for the criterion exercise bout.
Wilkerson et al., (2005) administered an identical RhEPO treatment to that of Connes et al., but
performed repeat transitions to either 80% GET (moderate), 70% of the difference between
GET and VO2max (i.e., 70% ∆; heavy), or 105% VO2max (severe) exercise. No difference was
seen in the VO2 kinetics across the exercise intensity spectrum, but VO2max was increased
during severe-intensity exercise (Wilkerson et al., 2005). Similarly, APVE has been shown to
not alter the VO2 kinetics during severe-intensity cycle exercise (Berger et al., 2006). Burnley
55
et al. (2006) demonstrated no change in the primary VO2 kinetics, but a reduction in the
amplitude of the VO2 slow component during severe-intensity exercise following blood
donation. Indeed, the trajectory of the slow component was unchanged between conditions, and
so it is likely that the reduction in amplitude was due to the reduction seen in VO2max (Burnley
et al., 2006). Gordon et al. (2010) report no change in primary VO2 kinetics, and similar VO2
steady-state values, during both moderate- and heavy-intensity exercise. It appears that the
changes in [Hb] associated with each of these interventions principally alters VO2max , and this
change appears to determine exercise tolerance. For example, the reinfusion of erythrocytes
(e.g., Ekblom et al., 1972; Ekblom et al., 1976; Spriet et al., 1986) and the administration of
RhEPO (e.g., Russell et al., 2002; Wilkerson et al., 2005) increased VO2max and exercise
tolerance. In contrast, blood donation reduces VO2max and also reduces exercise tolerance (e.g.,
Balke et al., 1954; Burnley et al., 2006). The exception to this rule appears to be APVE, which
artificially reduces [Hb] due to an increase in plasma volume. However, APVE increases total
blood volume and cardiac output – the principal determinant of VO2max (although limitations
can occur at any stage of the O2 conductance/diffusion pathway; Wagner, 1996; Wagner, 2000),
and also exercise tolerance (e.g., Kanstrup and Ekblom, 1984; Berger et al., 2006). These
studies suggest that severe-intensity exercise performance is not entirely determined by [Hb].
The small reductions in O2 carrying capacity seen with these interventions appears to have no
effect on the VO2 time course, suggesting that bulk O2 delivery was in excess of the muscular
metabolic requirement. The effect of a reduction in [Hb] on the parameters of the powerduration relationship is currently unknown, and worthy of further investigation.
Perfusion pressure
Despite an increase in cardiac output during supine exercise, and indeed any other activity
where the active musculature is at or above the level of the heart (Hughson et al., 1991; Leyk et
al., 1994), increased muscle blood flow as a result of gravity is absent and O2 delivery to the
working muscle is lower than that of upright exercise (Convertino et al., 1984; Hughson et al.,
1996; MacDonald et al., 1998; Koga et al., 1999). This reduction in muscle O2 availability in
the supine position slows the ‘overall’ VO2 response (e.g., Cerretelli et al., 1977; Convertino et
al., 1984), due to a longer (i.e., slower) primary time constant (τ) and/or a reduction in the
primary amplitude (Hughson et al., 1991; Hughson et al., 1993; Koga et al., 1999; Denis and
Perrey, 2006; Jones et al., 2006). Furthermore, an increase in the amplitude of the VO2 slow
component is typically evident (Hughson et al., 1993; MacDonald et al., 1998; Denis and
Perrey, 2006; Jones et al., 2006), and also leads to a significant reduction in VO2max in the
56
supine position (Astrand and Saltin, 1961; Hughson et al., 1991; Koga et al., 1999; Jones et al.,
2006; Egaña et al., 2007). Indeed, it is well-established that cycling performance is greater in
upright compared to supine body position; during incremental exercise, both peak power output
and time to exhaustion are significantly reduced in the supine position (Astrand and Saltin,
1961, Hughson et al., 1991; Koga et al., 1999; Terkelsen et al., 1999; Jones at al, 2006;
DiMenna et al., 2010); and during constant work-rate exercise, time to exhaustion and
performance during a ‘fatigue test’ are also reduced in the supine position (Egaña et al., 2006;
Egaña et al., 2007; Egaña et al., 2010a; Egaña et al., 2010b). The effect of supine exercise on
the parameters of the power-duration relationship is presently unclear, but may be principally
dependent upon the effect on CP. A reduction in VO2max coupled with no change in CP would
result in a reduction in W, as the capacity to perform work above CP would be reduced.
However, it could be argued that because supine exercise likely slows the VO2 kinetics (and
reduces VO2max ) it may also reduce the maximal sustainable rate of oxidative metabolism (i.e.,
CP). Indeed, if W is principally determined by the capacity for substrate-level phosphorylation,
then a reduction in O2 delivery should have no effect on this parameter.
Conclusions
It is clear from the past discussion that it is possible to manipulate the VO2 kinetics, VO2max ,
and the capacity for substrate-level phosphorylation in order to elicit a predictable effect on
high-intensity exercise tolerance. Currently, the bulk of previous research has tended to utilize
methodology that either compares the difference in physiological response between two
conditions and whether these influence performance during a time to exhaustion test, or some
other form of time trial effort. Although these studies have considerable benefit, investigating
the effect of a given intervention across a range of work-rates to enable the characterisation of
the power-duration relationship provides a further dimension to the collected data. Such
methodology can provide an important insight into the interaction between the VO2 response
and the combined ‘aerobic’ (i.e., CP) and presumably ‘anaerobic’ (i.e., W, or technically, the
work capacity above CP) metabolic pathways, and how this interaction determines severeintensity exercise tolerance.
57
Aims and hypotheses
The principal aim of this thesis is to investigate the interaction between the VO2 kinetics and
the power-duration relationship in order to gain a better insight into the determinants of severeintensity exercise tolerance. During such exercise, tolerable duration of exercise may be
determined by the attainment of VO2max , the capacity for substrate-level phosphorylation,
changes in acid-base status, or the accumulation of metabolites related to the fatigue process.
Manipulating each of these ‘mechanisms’ should have a predictable effect on exercise tolerance
– and therefore should also alter the power-duration relationship. Therefore, the purpose of the
experimental chapters is to determine how these factors interact with the power-duration
relationship. The specific hypotheses of the experimental chapters are as follows:
1. Prior heavy-intensity exercise will ‘prime’ the VO2 kinetics and enhance exercise
tolerance. This effect will increase W.
2. Prior severe-intensity exercise will also ‘prime’ the VO2 kinetics, however, following
10 min recovery; no change will be seen in time to exhaustion or the power-duration
relationship.
3. Sodium bicarbonate ingestion will extend time to exhaustion due to an enhanced
buffering capacity, and will increase W.
4. Blood donation will reduce [Hb] leading to a reduction in VO2max . This effect will
reduce exercise tolerance as a result of a reduction in CP.
5. Supine exercise will reduce VO2max , leading to a reduction in time to exhaustion, as a
result of a reduction in CP.
58
General Methods
59
Chapter 3 - General methods
3.1 - Health and safety
Full ethical approval of the experimental design and procedures was obtained from the ethics
committee of Aberystwyth University prior to the commencement of each experimental study,
and all procedures were performed in accordance with the declaration of Helsinki (1964).
Throughout all experimental testing, care was taken to ensure that the laboratories and
equipment were appropriately clean and safe for the assessment of human participants. All
experimental equipment, such as cycle ergometers, trolleys and benches were cleaned (pre and
post experimentation) using Disifin disinfectant (RMP, GmbH and Co, Ammerbauch,
Germany), which was prepared, stored and replaced as per the manufacturer’s guidelines.
Respiratory apparatus, including mouthpieces, turbines and nose clips were submerged in
Disifin for at least 20 min, and then left to dry naturally in the air before being reused. During
blood analysis, nitrile gloves (Touch N Tuff, Ansell healthcare, Brussels, Belgium) were worn
by the experimenter at all times, and appropriate care was taken to prevent cross contamination.
All contaminated equipment such as sharps, used capillary tubes, vacutainers, and other
biohazard materials were disposed of into appropriate containers for incineration. Following
each experimental session all blood waste bottles were emptied into a container to be
autoclaved, and waste bottles were cleaned with Disifin disinfectant prior be being reused.
All experimentation contained within this thesis was undertaken in the laboratories of the
Department of Sport and Exercise Science of Aberystwyth University. Each exercise test was
undertaken at a comfortable ambient temperature of 20 ± 5°C, at the same time of day ± 3
hours, with each test separated by a minimum of 24 hours (except Blood donation) and within a
4 week period. Participants were permitted the use of an electric fan (Clarke Air, CAM5002,
Clarke International, UK; at a wind speed of 4.0, 5.3 or 6.2 m∙s-1) for cooling during trials, and
if used, this was consistent between each trial. Additionally, participants were allowed to drink
plain water in the laboratory during exercise trials, although this was confined to pre and post
exercise as during the experimental phase the measurement of pulmonary gas exchange would
prevent such fluid intake.
3.2 - Participant recruitment, preparation and care
A convenience sample of participants took part in each of the experimental studies, with the
sample including local athletes, undergraduate and postgraduate students, and staff of
Aberystwyth University. All participants engaged in regular physical activity, familiar with the
60
equipment and procedures for exhaustive exercise testing, and also accustomed to high-intensity
exercise. Prior to any experimental procedures participants were given a full verbal and written
explanation of the procedures, risks and benefits associated with participation and the
commitment required for each study. Following a medical questionnaire, participants provided
written informed consent to participate (see Appendix B). It was stressed to all participants that
they could withdraw their consent at any time, without having to give a reason for their
withdrawal to terminate experimentation, and that all data would be coded and treated in the
strictest confidence. Participants were instructed to arrive for testing rested (no strenuous
exercise in the preceding 24 hours), well hydrated, to refrain from consuming alcohol for 24
hours, and having consumed no food or caffeine in the 3 hours before each test. Adherence to
these instructions was verbally verified prior to each exercise test.
Familiarisation, feedback and test termination procedures
The majority of participants recruited for the studies contained in this thesis were familiar with
laboratory based experimental exercise testing and its associated procedures. However, due to
the unfamiliar nature of a number of the protocols, and the requirement for maximal exhaustive
effort on each visit to the laboratory, participants were offered the opportunity to practice an
example of the exercise test that was to be performed. This was to ensure that each participant
was comfortable with the surroundings and equipment used, and to reduce the learning effect
associated with repeated high-intensity exercise trials.
Participants were given regular feedback on the work-rate during the incremental exercise tests
in order to maintain motivation and to encourage a maximal effort during this test. During all
power-duration relationship predicting trials strong verbal encouragement was given throughout
to ensure a maximal effort from each participant. The point of exhaustion was defined as the
point at which the participant could not maintain the desired cadence, with the test being
terminated when the cadence dropped by >10 rpm and could not be increased to the
predetermined level within 5 s, despite strong verbal encouragement. Feedback on work-rate,
time to exhaustion and performance during all power-duration trials was withheld until all
experimentation was completed, upon which participants had unrestricted access to all their data
and debriefed where required.
61
3.3 - Measurement procedures
Descriptive data
Descriptive data and anthropometric measurements were taken prior to each experimental study,
including the age, height, mass and a verbal description of their typical activity level and
preferred exercise modality for each participant. Height was measured in the Frankfort plane
using a Harpenden Stadiometer (Holtain Ltd, Crymych, UK), measured to the nearest 0.1 cm.
Body mass was measured to an accuracy of 0.1 kg using regularly calibrated laboratory scales
(Seca 645, Seca gmbh & co, Hamburg, Germany). Both height and weight were recorded with
the participant unshod but wearing the attire with which they were to perform the
experimentation.
Cycle ergometers
All experimental testing was performed in the seated position (except Study 4) on an
electronically braked cycle ergometer (Lode Excalibur sport, Groningen, The Netherlands) that
controlled external power output independent of pedal cadence (hyperbolic mode), and was
calibrated regularly by a qualified technician to the manufacturer’s guidelines. The ergometer
was individually adjusted for the comfort of each participant (e.g., saddle and handlebar
position), including the fitting of own pedals if preferred. All adjustments and settings were
recorded and replicated for subsequent tests. During the early stages of each incremental test
participants were encouraged to self selected their preferred cadence of between 70-100 rpm.
This cadence was then recorded and maintained throughout all subsequent tests. Participants
were then simply instructed to maintain their self-selected cadence (± 5 rpm) throughout each
subsequent trials with the test being terminated as previously described.
Pulmonary gas exchange
Pulmonary gas exchange was measured breath-by-breath during all experimental tests using an
on-line rapid response gas analyser (Oxycon Pro, Jaeger, Hoechberg, Germany). Participants
wore a nose clip and breathed through a low dead space (90 mL), low resistance (0.75 mmHg·L1
·s-1 at 15 L·s-1) mouthpiece and impeller turbine transducer assembly (Jaeger Triple V, Jaeger,
Hoechberg, Germany). The inspired and expired gas volume and concentration signals were
continuously sampled at 100 Hz, the latter using paramagnetic (O2) and infrared (CO2) analysers
(Oxycon Pro, Jaeger, Hoechberg, Germany) via a capillary line connected to the mouthpiece.
These analysers were calibrated prior to each test using gases of known concentration (16% O 2,
5% CO2; Viasys, Hoechberg, Germany), and the turbine volume transducer was calibrated using
62
a 3 L syringe (Hans Rudolph, KS). The volume and concentration signals were time aligned by
accounting for the delay in capillary gas transit and analyser rise time relative to the volume
signal. Oxygen uptake ( VO2 ), carbon dioxide output ( VCO2 ) and minute ventilation ( VE ) were
calculated using standard formulae (Beaver et al., 1973) and displayed breath-by-breath.
Incremental test to determine the gas exchange threshold and the maximal oxygen uptake
In all studies, the first (and second, see Study 4,) visit to the laboratory was used to complete an
incremental test to exhaustion. This protocol consisted of 3 min of ‘unloaded’ pedalling (i.e.
pedalling against zero resistance), following which, the work-rate was increased by 30 W∙min-1
until volitional exhaustion, which typically was within 12-15 min. Pulmonary gas exchange (
VO2 ) was measured breath-by-breath basis throughout this test. VO2max was determined as the
highest 5 s average VO2 over a 30 s period, typically seen during the final 60 s of each
exhaustive exercise trial. Breath-by-breath VO2 data was reduced to 5 s averages for the
estimation of the GET using the V-slope method (Beaver et al., 1986). This method requires the
plotting of VE / VO2 and VE / VCO2 against time assessed visually to identify the breakpoint
where VE / VO2 begins to increase while VE / VCO2 remains constant or decreases slightly (see
figure 3.1). The regression equations for both VO2 and VCO2 on both sides of the breakpoint
were then both mathematically and graphically assessed to identify a common VO2 coordinate,
indicating the GET. To account for the time delay in the increase in VO2 to the increase in the
external work-rate during incremental exercise, the work-rate corresponding to GET was
reduced by 2/3 of the ramp rate (i.e. 20W, Whipp et al., 1987).
63
38
36
36
34
34
32
32
30
30
28
28
26
26
24
24
VE/VO2
22
VE/VCO2 (arbitary units)
VE/VO2 (arbitary units)
GET
38
22
VE/VCO2
20
20
0
2
4
6
8
10
12
14
16
Time (min-1)
Figure 3.1: Determination of the gas exchange threshold (GET) estimated by the disproportionate
increase in VE / VCO2 vs. VE / VO2 and denoted by the vertical dashed line.
Pulmonary gas exchange during square-wave exercise
Throughout this thesis the VO2 on-kinetics were estimated through the use of exponential curve
fitting. The general process is outlined below; however, further specific details are supplied
within the methods section of each experimental chapter.
During each power-duration trial, breath-by-breath pulmonary gas exchange data was collected
and analysed using Microsoft Excel 2007 (Microsoft Inc, USA) and Statistical Package for
Social Sciences (SPSS, V17, an IBM company, USA). The data were initially manually filtered
to exclude occasional errant breaths (± 500 mL of a 5 s rolling average of the VO2 data) which
are not considered to be of the normal kinetic profile as a result of coughs, sighs or swallows
etcetera (Lamarra et al., 1987). In spite of these criteria for data filtering care was taken not to
remove breaths that were clearly part of the kinetic trend (i.e. phase I and II of the VO2
response). Subsequently, the data were time aligned to exercise onset (time zero) and linearly
interpolated to provide second-by-second data. Once averaging and interpolation was complete
the data files were imported into a purpose written modelling programme, which described the
VO2 response using non-linear regression algorithms. This involved an iterative process to
minimise the sum of squared error between the fitted function and the observed data.
64
The primary VO2 response was then characterised by the removal the first 20 s of data (to
eliminate phase I) and then fitting from 20 s to 2 min a mono-exponential function of the form:
VO2 (t) = VO2 (b) + A' · (1 - e-(t-TD)/)
Where VO2 (t) is the VO2 at time t; VO2 (b) is the baseline VO2 measured in the 60 s
preceding the transition in work-rate; and A', TD and  are the amplitude, time delay and the
time constant of the primary (Phase II) response, respectively (Rossiter et al., 2001; Burnley et
al. 2006). Initial parameter estimates entered into the model were TD: 15 s, τ: 30 s, A': 3000
mL. These values were chosen based upon the literature (Barstow and Molé, 1991; Barstow et
al., 1996; Engelen et al., 1996). The iterative process was continued until no further reduction in
the residual sum of squares was found.
The primary VCO2 kinetics where modelled using the same exponential function, where VCO2
(t) is the VCO2 at time t; VCO2 (b) is the baseline VCO2 measured in the 60 s preceding the
transition in work rate; and AP, TDP and P are the amplitude, time delay and the time constant
of the primary (Phase II) response, respectively. In addition, the amount of CO 2 produced in 2
min ( VCO2 2 min) and total CO2 production ( VCO2 total) were calculated from this data, and
VCO2max was determined as the highest 30 s average VCO2 during the exercise bout.
The amplitude of the slow component was determined by subtracting the primary amplitude
form VO2max measured during the test, and the rate of increase in VO2 during this phase (i.e.,
the slow component trajectory; L.min-2) was estimated using the following equation:
Slow component trajectory
=
As
(Tlim – [4 · P])
Finally, a 30 s rolling average was applied to the interpolated VO2 data. VO2max was then
determined as the highest mean 30 s VO2 value, typically seen during the last 60 s of each test.
The comparison of the VO2max values from each test and the incremental test calculated VO2max
value allowed verification (or not) of the attainment of VO2max in each participant.
Determination of the power-duration relationship
The linear regression of time to exhaustion against power output during at least three four
constant load exercise tests is used to determine the power-duration relationship. Two
65
considerations must be made when prescribing work-rates for this purpose; they must each be
performed above CP, and, time to exhaustion should be between 2 and 12 min (Moritani et al.,
1981; Poole, 1988). In healthy individuals, CP typically occurs at ~70-80% VO2max , or more
precisely, at ~40-50% Δ (i.e. GET plus 40-50% of the GET to VO2max interval; Poole et al.,
1988; Poole et al., 1990; Smith and Jones, 2001; Jones et al., 2010). Therefore, work-rates
equivalent to 60, 70 and 80% ∆ and 100% WRpeak attained in, or calculated from, an incremental
test was used for each of the power-duration trials in order to satisfy these requirements. Each
trial was preceded by 3 min of unloaded ‘baseline’ pedalling, once completed the work-rate was
increased in a ‘square-wave’ fashion to the desired work-rate. Participants were instructed to
maintain their desired cadence for as long as possible with the test being terminated when the
cadence fell by >10 rpm and could not be increased despite strong verbal encouragement, with
time to exhaustion being recorded to the nearest second. Blood [lactate] was measured both at
rest prior to each test and immediately upon exhaustion.
In order to estimate the parameters of the power-duration relationship (i.e. CP and W), the
external work-rate (W) employed in each power-duration trial was plotted against time to
exhaustion (Tlim). Linear was then used to provide parameter estimates for both CP and W,
using the work-time model (Monod and Scherrer, 1965; Moritani et al., 1981):
W = CP  Tlim + W
Heart rate
Heart rate was measured and recorded at 5 s intervals throughout all experimental tests using
short-range radio telemetry (Polar, S610i, Kempele, Finland). This data was used to monitor
each participant during each test and was subsequently downloaded for analysis of the
physiological response to exercise using computerised software (Polar, Precision Performance,
Kempele, Finland).
Haematology
General preparation
All venous blood samples were taken by researchers trained in the phlebotomy technique and all
samples were taken in accordance with the standard NHS guidelines (CHS132). Upon arrival to
the laboratory and prior to exercise, each participant was seated for 10 min prior to a resting
blood sample being taken. This period was standardised to allow for the restoration of resting
plasma volume levels (Hagan et al., 1978). The antecubital vein of the each forearm was then
66
gently palpated towards the end of the 10 min period to identify a suitable puncture site. The
area around the selected site was then was cleaned using an alcohol swab (70% isopropyl
alcohol; Sterets, Seton healthcare group PLC, Oldham, UK) and allowed to dry naturally in
room air to avoid contamination. A tourniquet was applied, and loosely tightened around the
upper arm if required. The antecubital vein was then secured using the thumb and index finger
before the needle was introduced to the skin at a shallow angle, and entering the vein for the
collection of the sample. The tourniquet was loosened when a free flowing blood sample was
achieved. Samples were collected in either a vacutainer or syringe as required (see later
sections). Once filled, the needle and vacutainer/syringe assembly was withdrawn from the vein,
the puncture site was then immediately covered with a small lint free tissue (Kimcare medical
wipes, Kimberley-Clark Limited, Surrey, UK) and pressure applied until the cessation of
bleeding and to minimise bruising.
Determination of whole blood haematology
Prior to each sample being taken, each participant was seated for 10 min and the puncture site
was prepared as described previously. A 21 gauge needle (BD vacutainer precision glide needle,
BD Diagnostics, Plymouth, UK) puncturing the skin at a shallow angle to enter the vein. A 4.5
mL sample was collected into a vacutainer containing 0.054 mL of ethylenediaminetetraacetate
(BD EDTA vacutainer, BD Diagnostics, Plymouth, UK). All samples were immediately
analysed in an automated haematology analyser (Horiba ABX Pentra 60C+, Horiba medical,
Montpellier, France). Regular calibration and quality control checks were undertaken in
accordance with the manufacturer’s guidelines.
Determination of acid-base status
Prior to each sample being taken, the participant and the puncture site was prepared as described
previously. A 20 gauge needle (BD microlance 3, Becton Dickinson, S.A. Fraga, Spain) was
attached to a blood-gas syringe containing 80IU of dry electrolyte balanced lithium-sodium
heparin (Pico 50, Radiometer Medical ApS, Bronshoj, Denmark) prior to puncturing the skin at
a shallow angle and entering the vein. A 2 mL sample was slowly drawn (at ~0.25 mL·s-1) into
the syringe. Each sample was immediately analysed in triplicate in a commercially available
blood-gas analyser (ABL80 Flex, Radiometer Medical ApS, Bronshoj, Denmark) for the
determination of blood pH and base excess. Additionally, bicarbonate concentration ([HCO3-])
was computed using the Henderson-Hasselbalch equation. A manual calibration cycle was
undertaken prior to each sample being analysed, according to the manufacturer’s guidelines.
67
Determination of blood [lactate]
Blood [lactate] was determined through the fingertip sampling of capillary whole blood. The
fingertip was cleaned using an alcohol swab (70% isopropyl alcohol; Sterets, Seton healthcare
group PLC, Oldham, UK) and allowed to dry naturally in room air to avoid contamination. The
skin was then punctured to a depth of approximately 3 mm on either a finger or thumb tip using
an automatic lancet (Soft clix pro, Accu-check, Roche Diagnostics GmbH, Mannheim,
Germany). The first drop of blood was wiped away using a small lint free tissue (Kimcare
medical wipes, Kimberley-Clark Limited, Surrey, UK) before a free-flowing sample (~20-25
µL) of blood was collected in heparinised tubes (Microvette, Sarstedt, Numrecht, Germany).
Each sample was analysed immediately for blood lactate and glucose concentration using an
automated glucose and lactate analyser (YSI 2300 stat plus, YSI, Yellow Springs, OH, USA).
The analyser was automatically calibrated hourly using manufacturers standard (YSI 2747), and
daily checks of the analyser function included samples of 0 mM and 30 mM lactate standard
(YSI 1531 and YSI 1530) and clinical controls of known concentrations; level 2 (Randox
HN1530) and level 3 (Randox HE1532) prior to each testing session. On each testing occasion
the above samples returned results within 2% of there given criterion value. The purpose of the
blood sampling was to determine the change in blood [lactate] during exercise, blood was
collected during the last 60 s of a period of ‘unloaded’ cycling, and as soon as possible
following exhaustion, typically within 30 s.
3.4 - Statistical analysis
The Statistical Package for Social Sciences (SPSS, V17, an IBM company, USA) was used for
all statistical analysis with specific procedures detailed in each experimental chapter. The many
physiological and performance variables measured within this thesis were analysed using oneor two-way (intensity × condition) ANOVAs with repeated measures, as appropriate. Where
differences were observed between conditions, 95% paired-samples confidence intervals were
used to determine at which specific intensities (60%, 70%, 80%  or 100% peak work-rate) the
differences occurred. Significance was accepted at P < 0.05, and when 95% paired-samples
confidence intervals did not include zero. Results are reported as mean ± SD.
68
Experimental Chapters
69
Chapter 4 – Study 1
The effect of priming exercise on the power-duration relationship
4.1 - Introduction
It has recently been proposed that the pulmonary oxygen uptake ( VO2 ) kinetics is a crucial
determinant of severe-intensity exercise tolerance (i.e., exercise performed above the critical
power, CP; Burnley and Jones, 2007). It is contested that the VO2 kinetics interact with the
finite capacity for substrate-level phosphorylation (derived from phosphocreatine (PCr)
hydrolysis and glycolysis, leading to the formation of lactate) and the prevailing maximum
oxygen uptake ( VO2max ) to determine the tolerable duration of exercise performed above CP.
Above CP, the VO2 slow component does not stabilize, and its trajectory steepens with
increasing power output (Roston et al., 1987). As a result, VO2max is attained more rapidly at
higher work-rates in the severe-intensity domain, with exhaustion occurring soon thereafter. By
extension, the VO2 kinetics interact with VO2max and may determine the curvature of the powerduration relationship (the W parameter, with CP being the asymptote). These proposals suggest
that altering the VO2 kinetics, VO2max and/or the capacity for substrate-level phosphorylation
would predictably alter the time to exhaustion and hence one or both of the parameters of the
power-duration relationship (cf. Burnley and Jones, 2007).
When repeated bouts of heavy- or severe-intensity exercise are performed (the former
representing work-rates performed between the gas exchange threshold (GET) and CP,
respectively) the kinetics of VO2 in response to the second bout of exercise is substantially
altered (Jones et al., 2003). The “priming” effect was first described as a ‘speeding’ of the
overall VO2 kinetics (Pendergast et al., 1983; Gerbino et al., 1996; MacDonald et al., 1997).
Later studies demonstrated that this overall speeding could be attributed to a reduction in the
amplitude of the VO2 slow component, with the time constant of the primary component being
unaffected (Bearden and Moffatt, 1973; Burnley et al., 2000; Burnley et al., 2002; Scheuermann
et al., 2001; Koppo and Bouckaert, 2002; Burnley et al., 2006). When recovery duration is
sufficient to restore baseline VO2 , it has been consistently demonstrated that the amplitude of
the primary component is increased following priming (i.e. priming increases the anticipated
‘steady-state’ VO2 ; Burnley et al., 2002; Fukuba et al., 2002; Perrey et al., 2003; Burnley et al.,
2006). However, other studies have demonstrated faster primary kinetics in the primed state
70
(Rossiter et al., 2001; Tordi et al., 2003; Faisal et al., 2009). Thus, primed VO2 kinetics is
characterized by an increase in the primary VO2 amplitude, a reduction in the VO2 slow
component and, on occasion, a speeding of the primary kinetics (Jones et al., 2003).
In the primed state, the increase in the aerobic contribution early in exercise, coupled with a
delay in the attainment of VO2max consequent to a reduced VO2 slow component (should the
primary VO2 amplitude project to a submaximal value), can influence exercise performance.
Priming exercise in the heavy- and/or severe-intensity domain followed by sufficient recovery
(>9-10 min) has been shown to increase time to exhaustion by 10-60% (Jones et al., 2003;
Carter et al., 2005; Bailey et al., 2009) and increase mean power output during short-term highintensity performance by 2-5% (Burnley et al., 2005; Palmer et al., 2009). Jones et al., (2003)
showed that this enhancement of exercise tolerance was associated with a tendency for W to be
increased, whereas more recently Miura et al., (2009) reported that priming increased the CP. In
contrast, severe-intensity priming followed by a brief recovery period (Ferguson et al., 2007;
Ferguson et al., 2010) or prior sprint exercise (Wilkerson et al., 2004; Heubert et al., 2005) has
been shown to reduce subsequent exercise tolerance, reflected in a reduction in the W
parameter with no change in the CP (Heubert et al., 2005; Ferguson et al., 2007; Ferguson et al.,
2010). More prolonged recovery reduces (Ferguson et al., 2010) or even eliminates (Vanhatalo
et al., 2009) these negative effects on exercise tolerance and the parameters of the powerduration relationship.
In spite of intensive study in recent years, the influence of priming exercise intensity on the
kinetics of VO2 and the parameters of the power-duration relationship remains equivocal. This
may be due to most investigators using a power output equal to GET plus 50% of the difference
() between VO2 and GET to induce a priming effect (Burnley et al., 2000; Jones et al., 2003;
Miura et al., 2009). Though this work-rate typically produces a priming effect, it has the
unfortunate characteristic of being in close proximity to CP, which typically occurs at ~40-60%
Δ (Poole et al., 1988; Smith and Jones, 2001; Pringle and Jones, 2002). Hence, participants
within these studies may not be exercising exclusively in the heavy- or severe-intensity domain.
Furthermore, there appears to be little agreement between those studies in which the priming
was performed above or below 50% : Bailey et al., (2009) observed no priming effects and no
effect on time to exhaustion following exercise at 40% , whereas severe-intensity priming (at
70% ) increased time to exhaustion for recovery durations >9 min. In contrast, Ferguson et
al., (2010) observed a reduction in performance, and W, 15 min following severe-intensity
priming. The present study was therefore designed to investigate the effects of priming intensity
71
with specific reference to the critical power on the kinetics of VO2 , the time to exhaustion, and
the parameters of the power-duration relationship.
Aims and hypothesis
The aim of the present study was to test two hypotheses: first, that priming exercise performed
exclusively in the heavy-intensity domain (<CP) followed by 10 min of recovery would increase
the primary VO2 amplitude, reduce the amplitude and trajectory of the VO2 slow component
and increase time to exhaustion during subsequent bouts of severe-intensity exercise. This, in
turn, would alter the power-duration relationship by increasing the W parameter. Secondly,
priming exercise performed exclusively in the severe-intensity domain (>CP) followed by 10
min of recovery would increase the primary VO2 amplitude, reduce the amplitude and
trajectory of the VO2 slow component, but would have no effect on the time to exhaustion. As a
result, prior severe-intensity exercise would have no effect on the power-duration relationship.
Ten minutes of recovery was chosen due to previous work showing consistent priming and
performance effects using this recovery period (Jones et al., 2003; Burnley et al., 2005).
4.2 Methods
Experimental design and protocols
Ten healthy trained male cyclists (age 31 ± 8 years, height 181 ± 6 cm; weight 77.2 ± 11.3 kg)
volunteered to participate in this study and provided written informed consent. Each participant
reported to the laboratory on thirteen occasions over a four-week period. The first visit was used
to collect all demographic and anthropometric data, and to perform an incremental test to
determine the GET and VO2max . These data was then used to calculate a range of work-rates for
all subsequent exhaustive tests. An initial ‘control’ condition series of four exhaustive tests were
performed on separate days (visits 2-5) to define the power-duration relationship and to identify
work-rates for the prior heavy- and severe-intensity exercise bouts (visits 6-13). Prior heavy
exercise was calculated as GET plus 50% of the difference between GET and CP, whereas the
prior severe exercise work-rate was derived by linear regression as a power output which could
be maintained for 8 minutes (P = (W/480) + CP; Ferguson et al., 2007). Both the prior heavy
and prior severe priming bouts were maintained for 6 min. At 6 min, participants were allowed
to ‘spin down’ against zero resistance for 1 min, and then rested passively for 6 min before
remounting the ergometer and performing 3 min of unloaded pedalling. After this 3 min period,
one of the four severe-intensity work-rates was immediately imposed and the participants again
exercised to exhaustion as described above. 1 min before and immediately after each exercise
72
bout, a fingertip capillary blood sample was taken to determine blood [lactate]. Participants
repeated this process on separate days and in a randomized order until all experimental trials
were completed.
Please refer to the General Methods for further details of the participant instruction prior to
exercise and for a description of the methods employed during the incremental test, for the
determination of the power-duration relationship, and details of the measurement of pulmonary
gas exchange and test termination criteria.
4.3 - Results
Incremental exercise and the ‘control’ condition power-duration relationship
During the incremental exercise test participants achieved a peak power output at the limit of
tolerance of 411± 48 W, and a VO2max of 4.36 ± 0.41 L.min-1 (57 ± 8 mL.kg-1.min-1). The GET
occurred at 2.38 ± 0.63 L.min-1 and was achieved at 163 ± 56 W. The work-rates calculated for
the heavy- and severe-intensity priming bouts were 225 ± 52 W (25 ± 1% ∆) and 319 ± 46 W
(63 ± 2% ∆), respectively. The work-rates for the exhaustive exercise tests were: 60% ∆, 311 ±
50 W, 70% ∆, 336 ± 49 W, 80% ∆, 361 ± 49 W and 100% WRpeak, 411 ± 48 W.
The blood [lactate] measured at baseline was similar between work-rates within conditions but
significantly different between conditions. The blood [lactate] prior to the control trials was 0.9
± 0.3 mM. Blood lactate was significantly elevated at all work-rates following prior heavy
exercise (to 1.8 ± 0.5 mM) and to a considerably greater extent following prior severe exercise
(to 6.4 ± 1.4 mM; F = 141.65, P < 0.001). There was no significant difference in the blood
[lactate] at the end of exhaustive exercise in each experimental condition (9.6 ± 1.4 mM after
the control trials, 9.4 ± 1.3 mM after prior heavy priming and 10.0 ±1.4 mM after prior severe
priming).
Heavy priming
Table 4.1 presents the VO2 responses to the various trials to exhaustion after heavy priming.
Compared to the control condition, heavy priming had no effect on the baseline VO2 (Table 1),
nor the time constant of the primary response for any of the subsequent bouts (F = 1.06, P =
0.37). However, the primary amplitude was significantly increased during the 70%  and 100%
WRpeak trials (F = 15.27, P < 0.001; 95% CI, 70% , 0.06, 0.43 L.min-1; 100% WRpeak, 0.05,
0.40 L.min-1), and when the amplitude was expressed in absolute terms (baseline VO2 + AP), the
73
amplitude was significantly increased at 60% and 70% 
peak
(F = 42.31, P <
0.001, Table 4.1). The 95% confidence intervals associated with the parameter estimates of the
primary time constant were 5.2  0.7 s across all conditions, and for the primary amplitude were
0.08  0.01 L.min-1 across all conditions. Following heavy priming exercise, the VO2 slow
component was reduced (F = 15.13, P < 0.001), with this difference being significant at 60% 
only (95% CI, –0.35, –0.04 L.min-1). The trajectory of the VO2 slow component was also
significantly reduced at 60% and 70%  following priming exercise (F = 10.01, P = 0.002,
Table 1). The VO2max was significantly increased after priming at 70%  (F = 10.76, P = 0.001;
95% CI, 0.03, 0.22 L.min-1), 80%  (95% CI, 0.05, 0.42 L.min-1) and 100% WRpeak (95% CI,
0.15, 0.42 L.min-1, Table 1). An example of these VO2 responses is presented in Figure 4.1
(Panels A and B).
There was a significant main effect of heavy priming on time to exhaustion (F = 7.29, P =
0.005), and post-hoc analysis revealed that exercise tolerance was significantly increased at 70%
 (95% CI, 3, 108 s) and 100% WRpeak (95% CI, 5, 36 s). As shown in Table 4.2, there was no
effect of heavy priming on the critical power (control vs. heavy priming, 284  47 W vs. 283 
44 W; 95% CI, –7, 5 W), whereas the W was significantly increased (16.0  4.8 kJ vs. 18.7 
4.8 kJ, 95% CI, 0.3, 5.2 kJ). An example of the power-duration relationship in a subject
demonstrating improved exercise tolerance following heavy priming is shown in Figure 4.1
(Panel C).
Severe priming
The VO2 responses to severe-intensity exercise following severe priming exercise are presented
in Table 4.1. Severe-intensity priming significantly increased the baseline VO2 at 70%  and
100% WRpeak (F = 4.95, P = 0.02). The primary time constant was not altered following severeintensity priming, but the primary amplitude was significantly increased at 60%, 70% and 80%
 (F = 15.27, P < 0.001). The absolute primary amplitude was significantly increased at all
work-rates after severe-intensity priming exercise (Table 4.1). The VO2 slow component was
significantly reduced by severe-intensity priming exercise at 60% (95% CI, –0.43, –0.14 L.min) and 70%  (95% CI, –0.42, –0.16 L.min-1; Table 4.1) and this was also reflected in a
1
reduction in the slow component trajectory at these work-rates (95% CIs: 60% , –0.03, –0.01
L.min-2; 70%  –0.14, –0.07 L.min-2; Figure 1D and E). Finally, the VO2max at 70% and 80% ,
and 100% WRpeak was significantly increased by prior severe-intensity exercise (95% CIs: 70%
, 0.12, 0.41 L.min-1; 80% , 0.03, 0.27 L.min-1; 100% WRpeak, 0.18, 0.44 L.min-1).
74
The time to exhaustion during severe-intensity exercise was not significantly affected by severeintensity priming exercise (Table 4.1). The parameters of the power-duration relationship were
unaffected by severe-intensity priming exercise (CP: 284  47 W vs. 275  45 W: 95% CI, –19,
2 W; W, 16.0  4.8 kJ vs. 16.7  4.7 kJ, 95% CI, –1.4, 3.9 kJ, Table 4.2). The confidence
intervals associated with the parameter estimates of the power-duration relationship were 30 
19 W for the critical power and 10.5  10.0 kJ for the W across all conditions.
Table 4.1: Power-duration relationship following priming exercise
Control
Heavy
Severe
Participant
CP (W)
W' (kJ)
CP (W)
W' (kJ)
CP (W)
W' (kJ)
1
302
16.6
290
20.8
298
13.3
2
310
15.4
312
14.6
267
14.7
3
334
11.9
340
12.8
340
10.9
4
283
17.4
288
14.8
280
13.8
5
347
16.4
342
24.1
341
20.6
6
307
6.8
298
13.5
292
12.6
7
247
14.5
244
20.1
241
15.2
8
287
24.3
281
24.4
262
25.4
9
224
14.8
223
18.5
225
17.2
10
201
21.5
215
23.4
205
22.5
Mean ± SD
284 ± 47
16.0 ± 4.8
283 ± 44
18.7 ± 4.8*
275 ± 45
16.7 ± 4.7
95% CIs
.-7,5.
.0.3, 5.2.
.-19, 2.
.-1.4, 3.9.
Values and mean ± SD. 95% CIs: paired samples 95% confidence intervals associated with each
parameter in comparison with control. *Significantly different from control (P < 0.05).
75
Table 4.2: Oxygen uptake kinetics and exercise tolerance following priming exercise
Control
Heavy
Severe
Baseline VO2 (L.min-1)
1.21
±
0.25
1.31
±
0.16
1.37
±
0.16
1.26
±
0.11
1.25
±
0.22
1.16
±
0.14*
1.31
±
0.11
1.25
±
0.18
1.35
±
0.17
1.25
±
0.08
1.3
±
0.19
1.39
±
0.14*
25.8
±
8.5
25.7
±
6.7
25.2
±
5.5
26.9
±
6.4
25.7
±
5.1
31.6
±
12.3
27.4
±
12.4
29.3
±
8.1
26.4
±
7.1
18.5
±
7.9
24.8
±
8.9
18.2
±
9.9
2.47
±
0.56
2.53
±
0.47
2.53
±
0.46*
2.53
±
0.46
2.77
±
0.52*
2.87
±
0.44*
2.59
±
0.39
2.82
±
0.44
2.93
±
0.36*
2.68
±
0.31
2.92
±
0.32*
2.88
±
0.39*
3.68
±
0.46
3.84
±
0.51*
3.91
±
0.50*
3.79
±
0.50
4.02
±
0.46*
4.22
±
0.50*
3.89
±
0.40
4.07
±
0.49
4.29
±
0.38*
3.94
±
0.35
4.22
±
0.40*
4.27
±
0.38*
0.74
±
0.14
0.55
±
0.22*
0.45
±
0.18*
0.56
±
0.23
0.45
±
0.21
0.28
±
0.19*
0.35
±
0.21
0.41
±
0.27
0.25
±
0.14*
0.10
±
0.03
0.07
±
0.04*
0.08
±
0.04*
0.16
±
0.04
0.10
±
0.04*
0.05
±
0.03*
0.20
±
0.08
0.18
±
0.10
0.17
±
0.12
4.42
±
0.46
4.39
±
0.35
4.36
±
0.38
4.35
±
0.35
4.48
±
0.35*
4.50
±
0.34*
4.25
±
0.50
4.48
±
0.40*
4.51
±
0.33*
4.02
±
0.36
4.30
±
0.36*
4.32
±
0.34*
572
±
140
671
±
271
533
±
122
315
±
91
370
±
112*
306
±
70
220
±
47
255
±
48
207
±
42
Primary τ (s)
AP (L.min-1)
Absolute AP (L.min-1)
-1
AS (L.min )
-2
AS trajectory (L.min )
VO2max (L.min-1)
Time to exhaustion (s)
116 ± 24
137 ± 28*
118 ± 30
Values are mean ± SD. *Significantly different from control (P < 0.05). AP, primary amplitude; Absolute
AP, Baseline VO2 + Ap; AS, slow component amplitude.
76
Figure 4.1 - Oxygen uptake and power-duration relationships following priming exercise
4.5
4.5
D
4.0
3.0
-1
2.5
2.0
.
.
2.0
1.5
1.0
1.0
0.5
0.5
0.0
0.0
4.5
4.5
E
4.0
4.0
3.5
3.5
3.0
3.0
-1
2.5
2.0
.
2.5
2.0
1.5
1.5
1.0
1.0
0.5
0.5
0.0
500
0.0
500
F
C
450
450
400
400
Power output (W)
Power output (W)
2.5
1.5
-1
VO2 (L.min )
B
VO2 (L.min )
3.5
3.0
VO2 (L.min )
.
4.0
3.5
-1
VO2 (L.min )
A
350
300
350
300
250
250
0
0
0
100
200
300
400
Time (s)
500
600
700
0
100
200
300
400
500
600
700
Time (s)
Figure 4.1: Oxygen uptake responses and power-duration relationships following heavy- and severeintensity priming exercise in subject 8. Panel A shows the VO 2 responses in the control condition, panel
B the VO 2 response after heavy priming exercise and panel C the power duration relationships for each
condition. The dashed horizontal lines in panels A and B represent the VO2max , whilst the vertical dotted
lines are intended to allow comparison of the time to exhaustion between conditions. Note the consistent
and considerable increase in time to exhaustion following heavy priming exercise in this subject, and the
primed VO 2 responses in panel B (particularly evident at 60%  [black circles] and 100% WRpeak [white
triangles]). The responses to exercise at 70%  and 80%  are represented by white circles and black
triangles, respectively. These responses were associated with no change in the CP but an increase in W
(panel C; control, white circles; primed, black triangles). Panels D-F show the VO 2 responses and
power-duration relationships after severe-intensity priming. Severe-intensity priming had little effect on
time to exhaustion during subsequent severe-intensity exercise, in spite of primed VO 2 kinetics (as
shown by the enhanced primary amplitude and, when evident, the reduced trajectory of the slow
77
component). As a consequence, there was no notable difference in the power-duration relationship
between control condition (white circles, panel F) and following severe-intensity priming exercise (black
triangles, panel F). See text for further details.
4.4 - Discussion
Heavy priming
Prior heavy-intensity exercise resulted in primed VO2 kinetics during subsequent severeintensity exercise: the primary VO2 amplitude was increased with no change in the primary
time constant, and the slow component amplitude and trajectory was reduced (Table 4.1). These
responses have been demonstrated repeatedly in the past (MacDonald et al., 1997; Bearden and
Moffatt, 2001; Burnley et al., 2000; Koppo and Bouckaert, 2001; Scheuermann et al., 2001;
Burnley et al., 2002; Fukuba et al., 2002; Perrey et al., 2003; Burnley et al., 2005; Burnley et
al., 2006;), with other reports suggesting that the primary time constant is reduced after priming
exercise (Rossiter et al., 2001; Tordi et al., 2003; Faisel et al., 2009). The increased VO2
response in the first 2-3 min of exercise has been demonstrated to enhance exercise performance
(Jones et al., 2003; Burnley et al., 2005; Carter et al., 2005; Bailey et al., 2009; Miura et al.,
2009; Palmer et al., 2009). In the present study time to exhaustion was increased by ~19%
following heavy-intensity priming exercise, which was statistically significant at 70%  and
100% WRpeak (Table 4.1). The increased time to exhaustion was associated with an increase in
the W of ~2.7 kJ or ~17%, supporting the previous work of Jones et al., (2003), who observed
that W tended to increase following priming at 50%  and the same 10 min recovery duration
as used in the present experiments. Heavy-intensity priming exercise did not alter the CP, which
is consistent with previous evidence (Jones et al., 2003) but not with the more recent study of
Miura et al. (2009), who observed an increase in CP of ~8 W following priming exercise at 50%
. Thus, although several reports have shown improved exercise tolerance following heavy
priming exercise, and that this could be due to either an increase in the CP or the W, the present
results provide the first evidence that priming performed exclusively in the heavy-intensity
domain can significantly increase the W without altering the CP.
The physiological determinants of the W, and, by extension, the determinants of time to
exhaustion during severe-intensity exercise are unclear (Jones et al., 2010). It has recently been
suggested that the tolerable duration of severe-intensity exercise may depend upon three
interrelated factors, namely, the amount of energy available from substrate-level
phosphorylation, the VO2 kinetics, and the VO2max (Burnley et al., 2007). Severe-intensity
exercise requires an obligatory energetic contribution from substrate-level phosphorylation that
78
is itself limited by the depletion of its constituents (chiefly PCr) and/or the accumulation of
metabolites such as H+ and inorganic phosphate (Jones et al., 2008; Vanhatalo et al., 2010). The
kinetics of VO2 dictates the rate of energy supply from substrate-level phosphorylation during
both the primary phase and as the VO2 slow component develops (evidenced by the existence
of a PCr slow component; Rossiter et al., 2001; Jones et al., 2008), whilst the VO2max limits the
development of the VO2 kinetics (Burnley et al., 2007). In this context, the results of the
present study could be interpreted in the following way: heavy-intensity priming exercise
increased the aerobic contribution to early exercise and reduces the amplitude and trajectory of
the VO2 slow component. In addition, heavy-intensity priming exercise increased the VO2max ,
providing a greater scope for the VO2 response. Because prior heavy exercise does not lead to
progressive PCr depletion or metabolite accumulation (Jones et al., 2008), the capacity for
substrate-level phosphorylation should be completely intact 10 min after heavy-intensity
priming exercise. Thus, the primed VO2 kinetics may have served to reduce the rate of
substrate-level phosphorylation and delay the attainment of VO2max , which may have resulted in
the increase in time to exhaustion and therefore the W.
Severe priming
Severe-intensity priming exercise resulted in a substantial baseline blood [lactate] elevation (to
~6-7 mM), an increase in the primary VO2 amplitude at 60, 70 and 80%  (of ~270 mL.min-1),
and a reduced VO2 slow component amplitude and trajectory at 60 and 70%  (Table 4.1). In
spite of these priming effects, and in stark contrast to heavy-intensity priming exercise, these
responses were associated with no change in time to exhaustion or the parameters of the powerduration relationship. Previous studies have demonstrated that prior exercise resulting in
substantial baseline blood [lactate] elevation (typically >5 mM) is associated with either no
significant change in exercise performance (Koppo and Bouckaert, 2002; Burnley et al., 2005)
or a significant decrease in time to exhaustion (Wilkerson et al., 2004; Ferguson et al., 2007;
Bailey et al., 2009; Ferguson et al., 2010). In this study, severe-intensity priming tended to
reduce the CP with no change in the W (Table 4.2), although this tendency for CP to fall can be
attributed to substantial reductions in CP in two participants, with the remainder showing little
change. Previous studies investigating severe-intensity prior exercise have suggested that the CP
is unaffected, but that the W is reduced (Ferguson et al., 2007; Ferguson et al., 2010). The latter
effect was not observed in the present study, despite the fact that the same work-rate has been
shown to substantially deplete W when measured following 2 min of recovery (Ferguson et al.,
2007). It is possible that the capacity for substrate-level phosphorylation was reduced after the
79
severe-intensity priming and the 10 min recovery period; however, this reduction was balanced
by the priming effects on the VO2 kinetics. Although speculative, this might explain why no
measurable changes in performance or the parameters of the power-duration relationship were
observed after severe-intensity priming exercise in the present study.
Recovery duration
The design of the present experiments (priming exercise followed by 10 min of recovery)
followed from earlier work showing robust effects on the VO2 response and of substantial
enhancements in exercise performance after 10 min of recovery (Burnley et al., 2002; Jones et
al., 2003). However, priming effects have been observed following at least 30-45 min of
recovery (Burnley et al., 2006), whereas the recovery of the muscle high-energy phosphates and
pH typically requires less than 20 min (e.g., Baker et al., 1993). Furthermore, Bailey et al.
(2009) have recently reported that the greatest positive priming effect (measured as time to
exhaustion at 80% Δ) occurred 20 min after 6 min of priming at 70% Δ. These investigators also
showed that the VO2 response and performance were unaffected by priming exercise at 40% Δ
followed by 3, 9, or 20 min recovery, in contrast with the present study. For comparison, the
priming intensities for the current study were ~25% Δ and ~63% Δ, for the heavy- and severework-rates, respectively. Although an essential feature of experimental design was the strict
assignment of heavy- and severe-intensity priming, the choice of these priming work-rates and
10 min recovery duration was unlikely to optimize the performance effects. The heavy-intensity
priming bouts produced relatively modest priming effects on the VO2 response that led to a
significant increase in time to exhaustion at 70%  and 100% WRpeak only, whereas the 10 min
recovery may have been too short to allow the priming effects to outweigh the fatiguing effects
of severe-intensity priming. The relationship between the priming effects on the VO2 kinetics
and exercise tolerance therefore appears to rest on something of a ‘knife edge’ when
intermediate recovery durations (6-15 min) are utilized, with increased (Burnley et al., 2000;
Jones et al., 2003; Carter et al., 2005; Bailey et al., 2009; Miura et al., 2009), decreased
(Wilkerson et al., 2004; Ferguson et al., 2007; Ferguson et al., 2010) and unaltered performance
(Burnley et al., 2000; Koppo and Bouckaert; present study) all having been observed. More
prolonged recovery intervals (≥20 min) may produce more consistent performance effects,
although only if the priming is of severe-intensity (Bailey et al., 2009).
The oxygen uptake slow component and exercise tolerance
One intriguing feature of the present results was that the improvement in time to exhaustion at
70%  following heavy priming exercise was not associated with a significant reduction in the
80
amplitude of the VO2 slow component, but was instead occasioned by a reduced VO2 slow
component trajectory. This suggests that a reduced VO2 slow component amplitude, per se, is
not a prerequisite for enhanced exercise performance after priming exercise. Also, a reduced
VO2 slow component following priming exercise is not necessarily associated with
performance enhancement either (Koppo and Bouckaert, 2002; Carter et al., 2005; Burnley et
al., 2009; present study). That said, it is important to note that the interpretation of the VO2
slow component amplitude during exhaustive severe-intensity exercise is not straightforward,
since its amplitude depends upon the primary amplitude and the VO2max . If the primary
amplitude is increased and the VO2max does not change, the VO2 slow component amplitude
must decrease, even if this is of no mechanistic significance. This is effectively illustrated by
the data presented in Table 4.1 and Figure 4.1: the amplitude of the VO2 slow component
systematically decreases with increasing power output, whereas the trajectory increases. For
severe-intensity work-rates, the trajectory of the VO2 slow component is probably the more
meaningful parameter as it does not depend upon the value of the primary amplitude or the
VO2max (Burnley et al., 2007). However, quantifying the VO2 slow component using its
trajectory during severe-intensity exercise carries with it the implicit assumption that the
increase in VO2 during this phase is linear. Although the VO2 slow component can, on
occasion, be described as a linear function of time (e.g., Casaburi et al., 1989), the consensus
appears to favor some form of non-linear increase as exercise progresses (e.g., Whipp et al.,
2005). Consequently, the trajectory data reported herein should be considered an index, only, of
the rate at which the VO2 slow component develops throughout the duration of exhaustive
exercise.
Limitations
Due to the nature of the present experiments, the methods contain a number of limitations.
Firstly, the control power-duration relationship had to be established before the priming bouts
were conducted. This was necessary to partition the priming work-rates into the heavy- and
severe-intensity domains, although this may have resulted in an order effect for time to
exhaustion in the control vs. primed conditions. However, the order of the primed bouts (heavy
and severe) was randomized and the performance effects were distinct (see above). Secondly,
we were unable to repeat each trial in order to enhance the signal-to-noise ratio of the VO2
responses. As a result, the confidence in the parameter estimates was lower than is typically the
case for studies of VO2 kinetics. However, the confidence intervals associated with the primary
amplitude was smaller than the increase reported, therefore there is confidence that this effect is
81
real. Thirdly, due to the number of exhaustive trials involved in these experiments (13 per
subject) we were unable to perform additional trials if the confidence intervals associated with
the parameters of the power-duration relationship were large. As a result the confidence in the
parameter estimates was typically poor, representing ~11% of the critical power and ~66% of
the W, limiting the possibility of detecting meaningful changes in these parameters.
Conclusion
In summary, prior heavy exercise increased the primary VO2 amplitude and increased the
tolerable duration of severe-intensity exercise performed after 10 min of recovery. This was
associated with a significant increase in the W. Prior severe exercise also primed the VO2
response but had no significant effect on exercise tolerance, the CP or the W. Thus, despite
similar priming effects on the VO2 kinetics following prior heavy- and severe-intensity
exercise, the effect on exercise performance was positive following prior heavy-intensity
priming and neutral following prior severe-intensity priming and a recovery period of 10 min.
The present results are consistent with the concept that when the VO2 kinetics is primed in the
absence of muscle fatigue, the amount of work that can be performed above the CP is increased.
82
Chapter 5 – Study 2
The effect of sodium bicarbonate ingestion on the power-duration relationship
5.1 - Introduction
During intense exercise, energy transfer from anaerobic glycolysis results in the inevitable
formation and accumulation of lactate, which dissociates almost immediately to form a lactate
anion (La-) and a proton (i.e., a hydrogen ion; H+; Brooks, 1985; Gladen, 1989). A progressive
increase in hydrogen ion concentration ([H+]) leads to a concomitant fall in muscle and blood
pH (Fletcher and Hopkins, 1907; Sahlin et al., 1978). This change in acid-base status has been
shown to inhibit both the release of calcium (Ca2+) from the sarcoplasmic reticulum (Donaldson
et al., 1978; Stephenson et al., 1998; Allen, 2009) and the binding of actin and myosin within
the muscle (Fabiato and Fabiato, 1978; Byrant-Chase and Kushmerick, 1988). Each of these
effects directly reduces the contractile function of the muscle fibres (Fuchs et al., 1970;
Mainwood and Cechetto, 1980). Furthermore, falling pH can also inhibit pH sensitive enzymes,
such as phosphofructokinase (PFK; Trivedi and Danforth, 1966; Kemp and Foe, 1983), which
in turn may limit energy production through glycolytic pathways (Sutton et al., 1981). Hence, to
preserve muscle function and glycolytic energy supply, buffers within the intracellular space
(such as bicarbonate; HCO3-) attempt to ‘mop up’ free H+ (Fitts, 1994), and favour the
movement of ions from the muscle to the extracellular fluid (Stewart, 1983). Despite these
regulatory mechanisms, prolonged energy transfer from anaerobic pathways (i.e., PCr
degradation and anaerobic glycolysis) increases [H+] in muscle and blood, thereby reducing pH,
and with increasing acidosis, may overcome the buffering capacity of the cell (McNaughton et
al., 2008). The ingestion of sodium bicarbonate (NaHCO3) or other similar compounds (such as
sodium citrate or sodium lactate) appears to maintain the efflux of H+ from the muscle
(Mainwood and Worsley-Brown, 1975), thereby attenuating the fall in pH (e.g., McNaughton,
1999; Hollidge-Horvatt et al., 2000; Stephens et al., 2002), and potentially delaying the onset of
muscle fatigue.
Maintenance of energy supply to the muscle is critical for exercise of more than a few seconds,
and so it is important to understand the interaction between acid-base status and metabolic
pathways. Theoretically, alkalosis appears to maintain the function of PFK by reducing the
inhibitory effect of falling pH, and a significant increase in both muscle and blood [lactate]
during exercise would support this contention (Osnes and Hermansen, 1972; Sahlin et al.,
1978). Indeed, this may suggest that alkalosis preserves, or may even increase, the glycolytic
contribution to total energy turnover during exercise in which these functions are generally
perturbed by acidosis (Jones et al., 1977; Sutton et al., 1981; Bishop et al., 2004; Requena et al.,
83
2005). A number of research groups have investigated the effect of alkalosis on the VO2
kinetics (Kolkhorst et al., 2004; Zoldaz et al., 2005; Berger et al., 2006); the primary VO2
amplitude is consistently shown to be unaltered (Berger et al., 2006; Kolkhorst et al., 2004;
Zoldaz et al., 2005), whilst the time constant has been longer (indicating slower kinetics;
Kolkhorst et al., 2004), shorter, (suggesting faster kinetics; Zoldaz et al., 2005), and also
unchanged by alkalosis (Berger et al., 2006). During high-intensity (>CP) exercise lasting more
than a few minutes, following alkalosis the amplitude of the VO2 slow component is typically
reduced, or it emerges later (Kolkhorst et al., 2004; Berger et al., 2006). Indeed, support for this
notion is provided by the attenuation of the phosphocreatine (PCr) slow component, indicating a
reduction in muscle VO2 (Forbes et al., 2005). The effect of alkalosis on VO2max does not
appear to have been measured during either prolonged or intermittent exercise; however,
mechanistically it should remain unaltered, as seen during all-out exercise (Vanhatalo et al.,
2010).
To date, the interaction between induced alkalosis and the power-duration relationship has not
been studied using traditional methods (e.g., Moritani et al., 1981; Hill et al., 2002). Using a
novel ‘3-min all out CP test,’ Vanhatalo et al. (2010) demonstrated that neither performance nor
the CP or W estimates are altered following alkalosis. However, since alkalosis appears to
facilitate an increase in glycolytic energy turnover (Bishop et al., 2004; Requena et al., 2005),
and as anaerobic glycolysis has been suggested to contribute to W (Moritani et al., 1981;
Gaesser et al., 1995), an increase in W may have been expected. This possibility was not seen
in the Vanhatalo et al. (2010) study. Along with the VO2 kinetics, VO2max and CP, W appears
to be a key determinant of high-intensity exercise tolerance (Burnley and Jones, 2007).
Therefore, gaining a better appreciation of the metabolic determinants of W’ would improve our
overall understanding of whole body bioenergetics and exercise tolerance in both health and
disease.
Aims and hypothesis
The principal aim of the current study was to investigate the effect of NaHCO 3 ingestion on
blood acid-base status (i.e., pH and [HCO3-]) and the kinetics of VO2 and VCO2 , in order to
identify changes in buffering capacity and substrate metabolism during exercise. In addition, the
effect of NaHCO3 on exercise tolerance (i.e., time to exhaustion), and its interaction with the
power-duration relationship (i.e. CP and W), was examined to determine the complex interplay
between these physiological, mathematical and performance parameters. It was hypothesised
that ingestion of NaHCO3 would: (1) increase blood pH and bicarbonate concentration ([HCO3-
84
]) prior to exercise; (2) have no effect on the primary VO2 kinetics but would elicit a reduction
in the amplitude of the VO2 slow component, to attain a similar VO2max to the placebo
condition; (3) these effects would be ergogenic, thereby increasing time to exhaustion; (4) this
would alter the power-duration relationship, with no change in CP and a significant increase in
W.
5.2 Methods
Experimental design and protocols
Eight healthy males (age 31 ± 10 years; height 182.8 ± 6.7 cm; weight 82.6 ± 11.4 kg)
volunteered to participate in this study, and reported to the laboratory on nine occasions over a
three-week period. During the first visit all demographic and anthropometric data was collected,
following which an incremental test was performed to estimate GET and determine VO2max .
From these data a range of work rates were calculated for the four subsequent power-duration
trials. Power-duration trials were performed twice: once having ingested a drink containing 0.30
g·kg-1 NaHCO3 (Na), and once following a metabolically inert placebo (Pl) drink. The NaHCO3
drink consisted of 0.30 g·kg-1 NaHCO3, 0.04 g·kg-1 of microcrystalline cellulose (C6H10O5), and
0.02 g·kg-1 sodium chloride (NaCl). The placebo drink consisted of 0.15 g·kg-1 C6H10O5 and
0.05 g·kg-1 of NaCl. Each supplement was mixed in a 330 mL bottle and drunk by each
participant; the bottle was then refilled with tap water, swilled and consumed again to ensure
that all the contents were ingested. During pilot work with three participants who were not
involved in the final study these drinks were verified as indistinguishable in terms of appearance
and volume of powder; and again for taste, texture, smell and colour when dissolved in plain tap
water. All drinks were administered in a double blind, randomised order within a 15 min period,
and exercise commenced 1 hour thereafter. Participants provided two venous blood samples on
two visits to the laboratory. One sample was taken at rest, and another/a second sample was
taken one hour after the ingestion of either the NaHCO3 or placebo drink in order to determine
the effect of the drinks on the acid-base balance of the blood
Please refer to the General Methods for further details of the participant instruction prior to
exercise and for a description of the methods employed during the incremental test, for the
determination of the power-duration relationship, and details of the measurement of pulmonary
gas exchange, blood sampling, and test termination criteria.
85
5.3 Results
Incremental exercise
Following the initial kinetic phase, VO2 increased as a linear function of work rate to attain
VO2max at 4.90 ± 0.59 L∙min-1 (or 60 ± 8 mL∙kg∙min-1) and a peak work rate (WRpeak) of 445 ±
63 W. GET occurred at 2.50 ± 0.43 L∙min-1 (or 135 ± 34 W), which was equivalent to 51 or
30% of VO2max and WRpeak, respectively. From these data, work rates were calculated for each
participant, equivalent to 327 ± 60, 352 ± 51, 383 ± 55 and 445 ± 63 W for the 60, 70, 80% Δ
and 100% WRpeak conditions, respectively.
Acid-base status
Similar resting values were seen for pH (Pl: 7.41 ± 0.01 vs. Na: 7.41 ± 0.01; 95% CI, -0.01,
0.00) and [HCO3-] (Pl: 22.0 ± 1.8 vs. Na: 21.5 ± 0.4 mM·L-1; 95% CI, -0.4, 1.3 mM·L-1) prior to
the ingestion of the placebo or NaHCO3 drinks. The ingestion of 0.3 g·kg-1 NaHCO3 had no
effect on these variables within either the placebo (pH; pre: 7.41 ± 0.01 vs. post 7.41 ± 0.01;
95% CI, -0.01, 0.00) and ([HCO3-]; pre: 22.0 ± 1.8 vs. post: 21.7 ± 0.5; 95% CI, -0.6, 1.2 mM·L1
) and NaHCO3 (pH; pre: 7.41 ± 0.01 vs. post 7.41 ± 0.01; 95% CI, -0.01, 0.01) and ([HCO3-];
pre: 22.0 ± 1.8 vs. post: 21.8 ± 0.7; 95% CI, -0.7, 0.01 mM·L-1) conditions. Similarly, no
difference was also seen between conditions post ingestion for pH (Pl: 7.41 ± 0.01 vs. Na: 7.41
± 0.01; 95% CI, -0.01, 0.00) and [HCO3-] (Pl: 21.7 ± 0.5 vs. Na: 21.8 ± 0.7 mM·L-1; 95% CI, 0.5, 0.2 mM·L-1).
Oxygen uptake kinetics
NaHCO3 ingestion had no effect on the VO2 kinetics of subsequent severe-intensity exercise.
Baseline VO2 (Pl: 1.26 ± 0.90 vs. Na: 1.32 ± 0.76 L·min-1; F = 4.476; P = 0.07), the primary
time constant (Pl: 28.9 ± 3.0 vs. Na: 25.6 ± 2.2 s; F = 1.448; P = 0.268), the primary amplitude
(Pl: 2.96 ± 0.97 vs. Na: 2.86 ± 1.08 L·min-1; F = 3.777; P = 0.093), and the absolute primary
amplitude (Pl: 4.22 ± 1.63 vs. Na: 4.17 ± 1.55 L·min-1; F = 0.515; P = 0.496) were unaltered.
Similarly, the VO2 slow component amplitude (Pl: 0.76 ± 0.07 vs. Na: 0.77 ± 0.05 L·min-1; F =
0.082; P = 0.782), its trajectory (Pl: 169 ± 16 vs. Na: 183 ± 012 mL·min-1; F = 0.555; P =
0.481), and VO2max (Pl: 4.81 ± 0.17 vs. Na: 4.80 ± 0.18 L·min-1; F = 0.164; P = 0.698), were
also unchanged following NaHCO3 ingestion.
86
Table 5.1: Oxygen uptake kinetics following sodium bicarbonate ingestion
Placebo
NaHCO3
Baseline VO2 (L∙min-1)
60% Δ
1.25
±
0.25
1.33
±
0.25
70% Δ
1.32
±
0.28
1.32
±
0.21
80% Δ
1.22
±
0.26
1.30
±
0.28
100% WRpeak
1.26
±
0.28
1.32
±
0.26
60% Δ
32.0
±
9.3
25.6
±
6.1
70% Δ
30.7
±
5.8
29.2
±
9.1
80% Δ
29.3
±
9.4
26.2
±
7.6
23.9
±
15.4
21.3
±
11.6
60% Δ
2.79
±
0.36
2.71
±
0.40
70% Δ
2.88
±
0.37
2.77
±
0.33
80% Δ
3.08
±
0.36
2.91
±
0.31
3.09
±
0.37
3.03
±
0.36
60% Δ
4.04
±
0.54
4.04
±
0.42
70% Δ
4.19
±
0.53
4.08
±
0.48
80% Δ
4.30
±
0.52
4.21
±
0.55
4.35
±
0.44
4.35
±
0.46
60% Δ
0.89
±
0.19
0.83
±
0.17
70% Δ
0.78
±
0.27
0.83
±
0.16
0.60
±
0.30
0.65
±
0.29
60% Δ
83
±
36
82
±
25
70% Δ
157
±
47
186
±
27
80% Δ
263
±
90
283
±
99
60% Δ
4.92
±
0.49
4.87
±
0.50
70% Δ
4.97
±
0.52
4.92
±
0.46
80% Δ
4.90
±
0.53
4.86
±
0.61
100% WRpeak
4.46
±
0.52
4.54
±
0.60
Primary τ (s)
100% WRpeak
-1
Ap (L∙min )
100% WRpeak
-1
Absolute Ap (L∙min )
100% WRpeak
-2
As (L∙min )
80% Δ
-2
As trajectory (mL.min )
VO2max (L∙min-1)
Values are mean ± SD; No significant differences were seen between the placebo and NaHCO 3 conditions
(P < 0.05). Note: Time to exhaustion was so short (<120 s) at the 100% WRpeak that there was no
discernable VO 2 slow component; therefore data for both its amplitude and trajectory are not presented.
Carbon dioxide kinetics
NaHCO3 ingestion did not alter VCO2 baseline (Pl: 1.31 ± 0.18 vs. Na: 1.50 ± 0.18; F = 1.788;
P = 0.223), its primary time constant (Pl: 52.8 ± 4.1 vs. Na: 54.6 ± 2.4 s; F = 0.528; P = 0.500),
87
or amplitude (Pl: 4.53 ± 0.11 vs. Na: 4.67 ± 0.30 L·min-1; F = 0.556; P = 0.489). However, a
significant increase in VCO2max was observed between conditions (Pl: 5.38 ± 0.20 vs. Na: 5.60 ±
0.19 L·min-1; F = 14.083; P = 0.007). Furthermore, alkalosis significantly increased total
amount of CO2 produced over the first 2 min of exercise (Pl: 6.8 ± 0.3 vs. Na: 7.1 ± 0.4 L·min -1;
F = 7.077; P = 0.032), but had no effect on the total CO2 produced between conditions (Pl: 31.5
± 2.9 vs. Na: 29.4 ± 2.8 L·min-1; F = 1.188; P = 0.312).
Table 5.2: Carbon dioxide kinetics following sodium bicarbonate ingestion
Placebo
NaHCO3
Baseline VCO2 (L∙min-1)
60% Δ
1.15
±
0.27
1.26
±
0.33
70% Δ
1.23
±
0.29
1.18
±
0.21
80% Δ
1.13
±
0.25
1.20
±
0.31
100% WRpeak
1.17
±
0.35
1.27
±
0.39
60% Δ
63.1
±
18.4
53.6
±
9.3
70% Δ
56.4
±
17.0
62.8
±
14.2
80% Δ
62.0
±
21.4
61.9
±
15.6
46.9
±
15.0
46.4
±
9.3
60% Δ
3.87
±
0.52
3.86
±
0.61
70% Δ
4.17
±
0.56
4.68
±
0.53
80% Δ
4.87
±
0.46
4.84
±
0.46
100% WRpeak
4.99
±
0.23
5.33
±
0.77
60% Δ
6.14
±
1.00
6.50
±
0.84
70% Δ
6.64
±
0.99
7.18
±
1.01*
80% Δ
7.00
±
1.09
7.16
±
1.10
100% WRpeak
6.61
±
0.97
7.69
±
1.61*
60% Δ
65.67
±
19.88
53.19
±
19.17
70% Δ
30.73
±
7.26
33.08
±
5.53
80% Δ
19.88
±
7.18
21.16
±
8.91
11.09
±
6.27
10.42
±
4.27
60% Δ
4.97
±
0.55
5.11
±
0.47
70% Δ
5.33
±
0.54
5.63
±
0.55
80% Δ
5.63
±
0.70
5.66
±
0.63
100% WRpeak
5.60
±
0.55
5.99
±
0.69
Primary τ (s)
100% WRpeak
-1
Ap (L∙min )
VCO2 2 min (L)
VCO2 Total (L)
100% WRpeak
VCO2max (L∙min )
-1
Values are mean ± SD; No significant differences were seen between the placebo and NaHCO 3 conditions
(P < 0.05).
88
5.5
5.0
4.5
4.0
VO2 (L.min-1)
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
-60
0
60
120
180
240
300
360
Time to exhaustion (s)
6.5
6.0
5.5
5.0
VCO2 (L.min-1)
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
-60
0
60
120
180
240
300
360
Time to exhaustion (s)
Figure 5.1: Pulmonary gas exchange response for VO 2 (upper panel) and VCO2 (lower panel) in the
placebo (solid circles/long dashed line) and NaHCO3 (open circles/short dashed line) condition in a
representative participant for the 70% Δ work rate. Note the similar time to exhaustion (Pl: 313 vs. Na:
322 s) between conditions and the contrast in the VO 2 and VCO2 responses between conditions.
89
Blood [lactate] and heart rate
Following the ingestion of the NaHCO3 drink, a significant increase in blood [lactate] was seen
both pre (Pl: 0.67 ± 0.06 vs. Na: 0.77 ± 0.06 mM; F = 16.124; P = 0.005) and post exercise (Pl:
8.62 ± 0.347 vs. Na: 10.05 ± 0.64 mM; F = 5.629; P = 0.049). No significant difference in
baseline heart rate was seen between conditions (Pl: 96 ± 4 vs. Na: 99 ± 5 b·min -1; F = 4.726; P
= 0.066). However, following NaHCO3 ingestion heart rate was significantly higher at 2 min
(Pl: 156 ± 3 vs. Na: 160 ± 4 b·min-1; F = 23.333; P = 0.002) and at exhaustion (i.e., HRmax; Pl:
173 ± 4 vs. Na: 175 ± 4 b·min-1; F = 8.484; P = 0.023).
Table 5.3: Blood [lactate], heart rate and time to exhaustion following NaHCO3 ingestion
Placebo
NaHCO3
Blood [lactate] 'Pre' (mM)
60% Δ
0.72
±
0.20
0.87
±
0.27*
70% Δ
0.62
±
0.16
0.73
±
0.20
80% Δ
0.67
±
0.20
0.75
±
0.11
0.66
±
0.27
0.74
±
0.27
60% Δ
8.14
±
1.64
9.42
±
2.16
70% Δ
8.93
±
0.76
10.28
±
2.02*
80% Δ
9.29
±
1.01
10.51
±
2.03
100% WRpeak
8.13
±
1.06
10.01
±
2.02*
60% Δ
96
±
13
100
±
16
70% Δ
100% WRpeak
Blood [lactate] 'Post' (mM)
-1
HR baseline (b·min )
95
±
13
98
±
80% Δ
97
±
12
98
±
12
18
100% WRpeak
95
±
13
99
±
13
60% Δ
152
±
8
158
±
9*
70% Δ
159
±
9
160
±
8
80% Δ
160
±
10
160
±
10
155
±
15
163
±
15*
60% Δ
178
±
12
179
±
11
70% Δ
174
±
11
178
±
11
80% Δ
172
±
13
173
±
13
100% WRpeak
165
±
11
170
±
12*
60% Δ
850
±
273
781
±
247
70% Δ
419
±
70
392
±
57
80% Δ
263
±
77
276
±
83
-1
HR 2 min (b·min )
100% WRpeak
-1
HRmax (b·min )
Time to exhaustion (s)
100% WRpeak
127
±
62
136 ± 39
Values are mean ± SD; * indicates a significant difference between the Placebo and NaHCO 3 conditions
(P < 0.05).
90
Exercise tolerance and the power-duration relationship
NaHCO3 ingestion had no ‘overall’ effect on time to exhaustion (Pl: 415 ± 35 vs. Na: 396 ± 26
s; F = 0.499; P = 0.503). A non-significant trend for a reduction in time to exhaustion (of 7-9%)
was seen at 60%  (Pl: 850 ± 273 vs. Na: 781 ± 247 s; 95% CI, -155, 293 s) and 70% Δ (Pl: 419
± 70 vs. Na: 392 ± 57 s; 95% CI, -27, 80 s), whilst the opposite was seen at 80% Δ (Pl: 263 ± 77
vs. Na: 276 ± 83 s; 95% CI, -50, 24 s) and 100% WRpeak (Pl: 127 ± 62 vs. Na: 136 ± 39 s; 95%
CI, -33, 15 s) – where time to exhaustion appears slightly enhanced (by ~5-7%). NaHCO3
ingestion significantly reduced CP (Pl: 303 ± 48 vs. Na: 296 ± 53 W; 95% CI, 0,14 W), and
increased W (Pl: 19.5 ± 8.6 vs. Na: 22.4 ± 9.2 kJ; 95% CI, -5.2, -0.7 kJ), when compared to
ingestion of the placebo drink.
600
550
Power output (W)
500
450
400
350
300
0
0
200
400
600
800
1000
Time to exhaustion (s)
Figure 5.2: Non-linear power-duration relationship for a representative participant in the placebo (open
triangles) and NaHCO3 (closed triangles) conditions. Note the altered power-duration relationship with a
reduced CP (Pl: 280 vs. Pl: 300 W), denoted by the narrow and large dashed lines, respectively. Also,
note the altered curvature, as result of an increase in W (Pl: 20.8 vs. Na: 27.5 kJ) following alkalosis.
91
5.4 - Discussion
The principal findings of this study are that NaHCO3 ingestion did not induce a state of
metabolic alkalosis measurable within the venous blood one hour after ingestion. Measurements
of blood pH, bicarbonate concentration, and base excess were not significantly different
between conditions. This intervention had no effect on either the VO2 response or VO2max
during subsequent exercise. NaHCO3 ingestion did not alter the primary VCO2 kinetics but did
result in an increase in VCO2max . Furthermore, although an increase in total CO2 production was
seen at 2 min, an overall increase in CO2 was not observed at exhaustion. Presumably related to
the increase in CO2 production, a significantly higher blood [lactate] was seen at the end of
exercise in the NaHCO3 condition. Despite these changes, no difference in time to exhaustion
was seen between conditions. However, there was an apparent shift in the power-duration
relationship, with CP being significantly reduced, and W being significantly increased
following alkalosis.
Acid-base status
Venous blood samples taken one hour after the ingestion of a typical optimal loading dose (0.3
g·kg-1 body mass; e.g., McNaughton et al., 1992) of NaHCO3 showed no measurable change in
pH or [HCO3-] when compared to the control (placebo) or the resting (pre ingestion) samples.
These findings stand in contrast to many recent studies that have shown measurable and
consistent changes in these parameters (Matson and Tran, 1993; Requena et al., 2005;
McNaughton et al., 2008). Matson and Tran (1993) performed a meta-analysis on twenty nine
studies to show the effect of alkalosis on the acid-base status of the blood (signified by changes
in pH and [HCO3-]). Various loading doses (0.01-0.04 g·kg-1 body mass) were administered in a
variety of forms (solutions, capsules and intravenous injections), consumed (or injected)
immediately or over a 3 h period, with sampling (and subsequent exercise) being undertaken 1-2
hours post administration within this analysis. The largest increase in performance was
associated with higher doses (0.24 ± 0.70 g·kg-1) of NaHCO3, demonstrating that a 0.3 g·kg-1
body mass dose (increases venous plasma pH by ~0.03-0.06 units and [HCO3-] by ~4-5 mM·L-1)
appears effective in inducing an alkaline extracellular environment (McNaughton, 1992; Matson
and Tran, 1993; Siegler et al., 2010). In light of the present data, it should be noted that even the
study that demonstrated only a modest alteration in pH following supplementation, (0.03;
McCartney et al., 1983), was larger than the greatest change in pH (0.02) in one participant in
the present study. It could be speculated that a sample consisting of many non-responders was
inadvertently selected for the present work, although this is unlikely given the number of studies
that have shown an increase in both pH and [HCO3-] previously; and the fact that a theoretically
92
optimal dose and administration protocol was selected (Matson and Tran, 1993; Requena et al.,
2005; McNaughton et al., 2008).
Whilst no difference was seen in blood acid-base status, other measures (such as the VCO2
kinetics, VCO2max and blood [lactate]) may suggest that NaHCO3 altered both the buffering
capacity and the type of energy turnover between conditions. First, total CO2 production was
significantly higher during exercise with alkalosis, and led to an increase in VCO2max . However,
despite this observation, total CO2 production was not significantly different between
conditions, suggesting that more CO2 was produced early in exercise, and this likely tailed off
over the length of the bout. Second, this increase in CO2 production would indicate an increase
in lactate production and the buffering of free H+ ions during exercise. Despite blood [lactate]
not being measured during exercise, a significant increase in this measure was seen at
exhaustion following NaHCO3 ingestion. It could be suggested that increased buffering may
have taken place during the early stages of exercise – in line with the increase in CO2 measured
at 2 min – and may have been facilitated by changes in pH and [HCO3-]; although, as discussed
previously, this was not seen in blood measures. The combination of a consistent change in
blood pH and [HCO3-] seen within previous research studies, and the related changes seen in
both CO2 and lactate production following NaHCO3 ingestion, would suggest that pre-exercise
alkalosis may have been evident in this work. Therefore, the lack of change in blood acid-base
balance seen in the current study appears to be the exception rather than the rule. Hence,
coupled with typical changes in both CO2 production and increases in blood [lactate] seen with
alkalosis, the current discussion will assume that the typical effects of alkalosis were present.
Oxygen uptake kinetics
NaHCO3 ingestion did not alter either the time constant or the amplitude of the primary VO2
kinetics. These observations are in agreement with a recent study that employed similar
methodology (Berger et al., 2006), but in contrast to others (Zoldaz et al., 2005; Kolkhorst et
al., 2004). For example, Zoldaz et al. (2005) demonstrated a speeding of the time constant at
87% VO2max , and propose that as alkalosis would increase resting pH (Nielsen et al., 2002;
Raymer at al., 2004; Stephens et al., 2002), this would in turn increase ADP concentration and
stimulate an increase in mitochondrial respiration (Mahler, 1985). They also suggest that the
VO2 kinetics may be speeded following NaHCO3 ingestion due to the inhibitory effect of H+
ions on ATP supply through anaerobic glycolysis (Korzeniewski and Zoldaz, 2004). Kolkhorst
et al. (2004) argue that because induced acidosis speeds the VO2 kinetics due to enhanced
muscle perfusion and a rightward shift in the oxyhaemoglobin dissociation curve (e.g. Gerbino
93
et al., 1996; MacDonald et al., 2001), alkalosis would likely have an opposing effect – it would
slow the VO2 kinetics. This contention appears plausible, however, acceleration seen in the
VO2 kinetics in these early priming studies was due to an increase in the primary amplitude,
rather than a change in the time constant per se (Burnley et al., 2000). Furthermore, this effect
appears to be related to changes in muscle recruitment patterns (Burnley et al., 2002), and
therefore casts some doubt over the mechanistic basis for the observations of Kolkhorst et al.
(2004). Alternatively, the cause of this disparity could, in part, be due to the fact that pulmonary
gas exchange measured on a breath-by-breath basis is inherently noisy and may lead to
potentially spurious conclusions. Berger et al. (2006) discuss this point to support the findings
of their study, showing that averaging the VO2 response of a number of repeat transitions
enhances the signal to noise ratio, thereby improving confidence in the parameter estimates
(Lamarra et al., 1987). A key strength of the present study is that the VO2 response was
measured across a range of work rates within the severe-intensity domain, and as such provides
an insight into the effects of NaHCO3 across this exercise intensity domain.
Alkalosis had no effect on the trajectory and the amplitude of the VO2 slow component, or
VO2max . These findings are in agreement with a number of previous studies (Heck et al., 1998;
Zoldaz et al., 1997; Santalla et al., 2003). Many early studies showed no change in the slow
component amplitude, but these studies generally did not model the VO2 kinetics; rather, they
estimated the effects by comparing the measured response between different time points (e.g., 3
to 6 min; Zoldaz et al., 1997) or during trials of 6 min duration (e.g., Zoldaz et al., 2004), rather
than modelling the VO2 response into its distinct phases (Whipp et al., 1982). Subsequent higher
order mathematical modelling work by a number of research groups investigated the effect on
the slow component and showed a significant reduction (of 39%; Kolkhorst et al. 2004), or a
non-significant trend (of ~19%) towards a reduction in the VO2 slow component amplitude
(Berger et al., 2006). Furthermore, a 32% reduction in the phosphocreatine (PCr) slow
component amplitude shown by
31
P magnetic resonance spectroscopy (31P-MRS) methods
indicates a likely reduction in mVO2 slow component amplitude (Forbes et al., 2005). Hence,
the apparent disparity between the current work and these previous studies is hard to explain,
especially as all three studies cited above modelled the VO2 kinetics from either a single
exercise transition (Kolkhorst et al., 2004), repeated transitions at the same work rate (Berger et
al., 2006), or following a range of severe-intensity exercise intensities as in the present study.
Berger et al. (2006) suggest two potential mechanisms for this reduction in the slow component
amplitude. First, there is strong evidence that the pVO2 slow component is in some way related
to the recruitment of type II muscle fibres, and associated with (but not necessarily the cause of)
94
an elevation in blood lactate concentration during exercise. Their data support this view, as the
increased accumulation of blood lactate towards the end of exercise was related to a decrease in
the VO2 slow component. Alternatively, Berger et al. suggest that the accumulation of fatiguing
metabolites (e.g., Pi, ADP H+, intracellular K+) within the muscle may increase the ATP (and
therefore O2) cost of exercise by an increase in Ca2+ and Na+-K+ pump activity. Comparable
levels of alkalosis and a similarly greater accumulation in blood lactate was seen in the current
work, therefore it is surprising that a similar reduction in the VO2 slow component was not
evident. This is particularly the case as both scenarios would enhance H+ efflux from the cell,
thereby increasing in intracellular pH (Forbes et al., 2005; Nielsen et al., 2002; Raymer et al.,
2004) and hypothetically reducing muscle fatigue (Bangsbo and Juel, 2006; Lamb and
Stephenson, 2006).
Exercise tolerance
The ingestion of NaHCO3 had no overall effect on time to exhaustion between conditions in this
study. However, on average, time to exhaustion tended to be reduced at 60 and 70% Δ, and
increased at 80% Δ and 100% WRpeak following alkalosis. In effect, these changes in
performance may have cancelled each other out and led to no overall change in performance.
Furthermore, there were considerable idiosyncratic intra-individual performance effects
following alkalosis, with some participants demonstrating improvements, decrements, and no
change in time to exhaustion between conditions, and within exercise intensities. The
combination of these observations may have obscured any real effect from being statistically
evident in the present study, at both an individual work rate level, and also as an overall effect
on time to exhaustion. It has been suggested that the greatest improvement in performance
following alkalosis may occur in those individuals with the lowest work capacities, as they tend
to have a lower capillary density and as such a higher dependence on lactate and proton
transporters than more highly trained participants (Messionnier et al., 2007; Price and Simons,
2010). Therefore, as many of the participants in the present study could be described as ‘well
trained’, it could be argued that the potential ergogenic effect of alkalosis may have been limited
in these individuals.
It has been shown previously that alkalosis appears to be most effective at enhancing
performance during intense exercise lasting ~1-7 min (Wilkes et al., 1983; Costill et al., 1984;
McKenzie et al., 1986; McNaughton et al., 1992; Bird et al., 1995). In the present work, time to
exhaustion ranged from ~2-14 min in both conditions. It would have been possible to select a
range of work rates that would have elicited exhaustion within the optimal (1-7 min) range in
order to potentially maximise the effect of the sodium bicarbonate ingestion. However, a
95
principal aim of this study was to define the power-duration relationship in each condition and
so the traditional experimental design was adhered to within this work (i.e., selecting exercise
intensities to elicit exhaustion in 2-15 min, Hill, 1993). Therefore, for some participants,
exercise performed at 60 and 70% Δ was undertaken well outside the ‘optimal’ effective
duration of exercise. Indeed, although not significantly different, time to exhaustion at these
work rates were lower in the NaHCO3 condition (by ~30-70 s, or ~14-30%) when compared to
the placebo group.
In order to understand the mechanisms that may underpin the ergogenic effect of alkalosis,
research groups have utilised muscle biopsy measurements (Hollidge-Horvatt et al., 2000;
Stephans et al., 2002) and more recently, non-invasive 31P-MRS to determine changes in muscle
metabolism and acid-base balance (Raymer et al., 2004). These studies show that generally,
alkalosis leads to an enhanced rate of glycolytic ATP production, and studies that show an
increase blood [lactate] are consistent with this view (Spriet et al., 1986; McNaughton et al.,
1992). Within the current study alkalosis tended to reduce performance during exercise lasting
~10-15 min, and is in contrast to the observations of Hollidge-Horvatt et al. (2000). Other
groups have shown that alkalosis appears to improve exercise tolerance during more prolonged
exercise (lasting 30-60 min), which likely draws the majority of its energy from oxidative
pathways (George et al., 1988; Potteiger et al., 1996; McNaughton et al., 1999). During such
exercise, wherein lactate accumulation or glycogen depletion play an important role in the
fatigue process, an increase in anaerobic energy turnover would more likely hinder, rather than
enhance, exercise tolerance. Although these studies show changes in performance beyond the
scope of the present work, they provide evidence to support the notion that changes in acid-base
balance may enhance performance during more prolonged exercise.
Whereas more prolonged exercise appears to be inhibited by alkalosis, there was a tendency for
performance to be enhanced at both 80% Δ and 100% WRpeak. At these work rates, time to
exhaustion ranged from ~1.5-7 min in the alkalosis condition, and therefore strongly supports
the notion that alkalosis improves performance during short duration high-intensity exercise
(Wilkes et al., 1983; Costill et al., 1984; McKenzie et al., 1986; McNaughton et al., 1992; Bird
et al., 1995; Requena et al., 2004; Lindh et al., 2007; McNaughton et al., 2008). Taking a wider
view, many studies that have showed enhanced performance following alkalosis were preceded
by either several short high-intensity efforts (Costill et al., 1984; McKenzie et al., 1986; Bishop
et al., 2004; Bishop et al., 2005), or prolonged sub-maximal exercise (Jones et al., 1977; Sutton
et al., 1981). It could be argued that these preceding bouts of exercise induced a ‘priming effect’
on the VO2 kinetics (although not measured in these studies) that may have contributed to the
increase in performance (e.g., Burnley et al., 2005). Indeed, increases in blood [lactate]
96
following repeated high-intensity exercise bouts (Costill et al., 1984; McKenzie et al., 1986),
and during 20 min period performed at 66% VO2max (Jones et al., 1977; Sutton et al., 1981),
would suggest that the VO2 kinetics may have been primed, and this may have contributed to
enhanced performance. Whether or not the ‘prior exercise’ effect would have produced a greater
ergogenic effect than that seen with an increase in buffering capacity and anaerobic energy
production following alkalosis has not been empirically examined.
Power-duration relationship
This is the first known study to examine the effect of NaHCO3 ingestion on parameters of the
power-duration relationship using the traditional method of separate prediction trials. Whilst
time to exhaustion was not altered, a significant alteration in the power-duration relationship
was observed, with CP being reduced, and W increased, following alkalosis. Recently, the ‘allout critical power test’ was used to determine the effect of alkalosis on the power-duration
relationship, and showed no change in either parameter (Vanhatalo et al., 2010). Vanhatalo and
colleagues discuss the sensitivity of detecting changes in performance during a single all-out
test. They concluded that, as this model identifies increases in CP as a result of training
(Vanhatalo et al., 2008) and a reduction in W following prior sprint exercise (Vanhatalo et al.,
2009), then it is also likely to detect changes following alkalosis, and so argue that their recent
results were valid (Vanhatalo et al., 2010). Similarly, the power-duration relationship has also
been shown to be well defined using traditional methods (e.g., Morton, 2006), and so the
differing effect on the power-duration relationship between these two studies is unclear.
In physiological terms, strong evidence exists to support the notion that CP is aerobic in origin,
such that it represents a metabolic steady-state in terms of VO2 , acid-base status, and muscle
metabolism (Poole et al., 1988; Hill et al., 2002; Jones et al., 2008). In previous work, alkalosis
has had no effect on a range of measures of ‘aerobic’ function, such as the ventilatory and
lactate thresholds (Kowalchuck et al., 1984) and VO2max (Vanhatalo et al., 2010). Also, the
neuromuscular fatigue threshold that identifies the maximal steady-state threshold (i.e., CP)
using iEMG techniques has also been shown to be unaltered following NaHCO 3 ingestion
(Housh et al., 1991). Korzeniewski and Zoldaz (2001) present computer models of oxidative
phosphorylation to suggest that additional ATP supply from anaerobic glycolysis (leading to an
increase in W, as seen in the current study) would likely slow the VO2 kinetics (which was not
seen in the current study), thereby increasing ADP concentration and in turn, limiting the
activation of oxidative phosphorylation (Korzeniewski and Liguzinski, 2004). Indeed, the data
of Hollidge-Horrvat et al. (2000) provide support for this notion, as they demonstrate enhanced
97
intracellular acidosis and a likely inhibitory effect of H+ on ATP supply through aerobic
glycolysis. This remains speculative however, as the evidence for a reduced rate of oxidative
phosphorylation is gleaned from theoretical rather than experimental studies; i.e., this effect
may have led to the reduction in CP seen in the current study. If this were the case, then the shift
to anaerobic glycolysis – leading to the observed increase in W - would appear to be a plausible
explanation for the change in the power-duration relationship, despite no change in overall time
to exhaustion.
The determinants of W are less clear. Classically it has been considered to be largely
‘anaerobic’ in nature, with the precise magnitude being dependent upon the depletion of the
intramuscular high-energy phosphate pool – a source related to anaerobic glycolysis (Miura et
al., 2000; Moritani et al., 1981). Also, it is considered that the accumulation of Pi and H+ ions,
which impair muscle contractibility, may also limit W (Fitts, 1994; Jones et al., 2008).
Although not directly measured in the current study, it could be suggested that evidence exists
for a shift in the relative contribution of aerobic and anaerobic glycolysis following alkalosis.
Figure 5.1 shows the VO2 and VCO2 responses to exercise of one participant performing a bout
of exercise at the same intensity in each condition. In this example it appears that from 40 s
onwards in the NaHCO3 condition VO2 appears to be slightly lower throughout exercise, and
also at VO2max . Furthermore, from 50 s onwards the opposite effect is evident for the VCO2
response, which itself appears higher from this point, throughout exercise, and at VCO2max .
Indeed, total CO2 production over the first 2 min of exercise was shown to be significantly
greater following alkalosis. It should also be noted that total CO2 production was not different
between conditions. Indeed, others have reported higher VCO2 values and an increased
respiratory exchange ratio at the end of exercise (Cox and Jenkins 1994; Stephens et al., 2002;
Vanhatalo et al., 2010). This is likely due to increased bicarbonate buffering in blood, resulting
in increased CO2 release via carbonic acid that in turn increased CO2 production during the
exercise transient and at VCO2max . Hollidge-Horrvat et al. (2000) showed an increase in
glycogen utilization during exercise performed following alkalosis, supporting the view that a
greater efflux of H+ from the active muscle attenuates the fall in intracellular pH, thereby
facilitating a greater glycolytic contribution to energy turnover (Bishop et al., 2004; Jones et al.,
1977; Requena et al., 2005 Sutton et al., 1981). With this evidence it is possible that alkalosis
increased the rate of anaerobic glycolysis in the current study, and therefore may go some way
to explain the increase in W. Indeed, as the inability to maintain exercise above CP appears to
be associated to a low muscle pH (Jones et al., 2008), and as induced alkalosis attenuates the
fall in pH, by definition, this should increase in W (Poole et al., 1988). These observations
98
provide strong support for the increase in W seen following pre-exercise alkalosis in the current
study. The alternative, that induced alkalosis has no effect on the relative contribution of aerobic
and anaerobic pathways to total ATP turnover despite a significant reduction in blood pH
(Bangsbo et al., 1996), provides the basis for further discussion. It may be that NaHCO3
ingestion is effective in lowering plasma pH, but potentially ineffective in altering intramuscular
pH (Bishop et al., 2004; Costill et al., 1984; Hood et al., 1988), although others show a
contrasting effect (Nielsen et al., 2002; Stephens et al., 2002). Therefore, if an increase in
glycolytic turnover is dependent upon a reduction in intramuscular pH, the variability in this
measurement may go some way to explain the differences seen in exercise tolerance and W.
Conclusion
Induced alkalosis had no effect on the VO2 kinetics or VO2max attained during subsequent
exercise. As shown previously, variable effects on time to exhaustion were seen within this
study that gave rise to no significant differences in overall performance between conditions.
These observations provide further support for the notion that the interaction between the VO2
kinetics and VO2max are a key determinant of exercise tolerance during severe-intensity exercise.
This is the first study to show a shift in the power-duration relationship following NaHCO3
ingestion: CP was significantly reduced, and W significantly increased. These observations
provide support for a proportional increase in anaerobic glycolysis to overall energy turnover.
99
Chapter 6 – Study 3
The effect of blood donation on the power-duration relationship
6.1 - Introduction
Over the last half-century, many research groups have investigated the effect of reducing O2
delivery to the working muscle through the removal of one unit (~450 mL) of whole blood (e.g.,
Balke et al., 1954; Woodson et al., 1978; Schaffartzik et al., 1993; Panebianco et al., 1995;
Duda et al., 2003; Burnley et al., 2006; Gordon et al., 2010). These authors note a significant
(~5-10%) reduction in the blood haemoglobin concentration ([Hb]) following this procedure,
which in turn leads to a similar reduction in VO2max (e.g., Ekblom et al., 1972; Ekblom et al.,
1976; Kanstrup et al., 1984; Duda et al., 2003; Burnley et al., 2006). In contrast, both the
amplitude and time constant (τ) of the primary VO2 kinetics have been shown to be unaltered
across the exercise intensity spectrum following blood donation (Burnley et al., 2006; Gordon et
al., 2010). These observations suggest that despite a reduction in [Hb], O2 delivery is still likely
to be in excess of the metabolic demand. This contention is further supported by the observation
of similar steady-state VO2 values during both moderate- and heavy-intensity exercise
following blood donation (Gordon et al., 2010). During non steady-state exercise (i.e., of severe
intensity), the reduction in VO2max appears to limit the scope for development of the VO2 slow
component (which is reported as being reduced), whilst its trajectory remains similar between
conditions (Burnley et al., 2006). Hence, a reduction in [Hb] appears to have little effect upon
the VO2 kinetics, but it consistently reduces VO2max , leading to a significant reduction in
exercise tolerance (Ekblom et al., 1972; Ekblom et al., 1976; Kanstrup et al., 1984; Burnley et
al., 2006). How these effects influence the power-duration relationship is currently unknown.
However, as the submaximal O2 cost of exercise (Gordon et al., 2010) and the kinetics of VO2
at exercise onset (Burnley et al., 2006; Gordon et al., 2010) are similar between conditions, it
can be postulated that CP would be also be unaltered. Indeed, similar CP and a concurrent
reduction in VO2max (e.g., Burnley et al., 2006) would suggest a limitation in the capacity to
perform work above CP, thereby reducing W. Experimentally testing this hypothesis would
further strengthen our understanding of the determinants of exercise tolerance (Burnley and
Jones, 2007).
100
Aims and Hypothesis
The aim of this study was to investigate the effect of blood donation on the VO2 kinetics and
VO2max , and the subsequent effect on exercise tolerance and the power-duration relationship. It
was hypothesised that blood donation will elicit a significant reduction in [Hb]. During severeintensity exercise, this reduction in [Hb] will have no effect on the primary VO2 kinetics.
Furthermore, the trajectory of the VO2 slow component will be unchanged, whilst its amplitude
will be limited – and as such, reduced – by a significant reduction in VO2max . These effects will
serve to reduce exercise tolerance across the severe-intensity domain. The reduction in VO2max
will reduce the capacity to perform exercise above CP, and as such W will be reduced, with no
change in CP following blood donation.
6.2 - Methods
Experimental design and protocols
Seven healthy males (age 30 ± 5 years, height 179.9 ± 8.0 cm; weight 76.2 ± 9.6 kg)
volunteered to participate in this study and provided written informed consent. Each Participant
reported to the laboratory on five occasions over a two-week period. All demographic and
anthropometric data were collected during each participant’s first visit to the laboratory,
following which an incremental test was performed to exhaustion to estimate their GET and
VO2max . From these data a range of work-rates were determined for all subsequent powerduration trials. These trials were randomised, and performed on two consecutive days with two
trials per day; each trial was separated by at least 3 hours. Participants then voluntarily donated
~450 mL of whole blood from the antecubital vein of the arm to the Welsh Blood service. A
period of at least 24 hours was then allowed between blood donation and subsequent exercise
testing. Following this period, an identical set of power-duration trials were performed on the
next 2 days (i.e., at 24 and 48 hours post blood donation), except that the order was again
randomised.
Please refer to the General Methods for further details of the participant instruction prior to
exercise and for a description of the methods employed during the incremental test, for the
determination of the power-duration relationship, and details of the measurement of pulmonary
gas exchange, blood sampling, and test termination criteria.
101
6.3 - Results
Incremental exercise
Following the initial kinetic phase, VO2 increased as a linear function of work-rate to attain
VO2max at 4.26 ± 0.47 L∙min-1 (or 56 ± 4 mL∙kg-1∙min-1) and a peak work-rate (WRpeak) of 394 ±
64 W. GET occurred at 2.00 ± 0.50 L∙min-1 (or 123 ± 54 W), which was equivalent to 47 or
30% of VO2max and WRpeak, respectively. From these data, work-rates were calculated for each
participant, equivalent to 286 ± 58, 312 ± 60, 340 ± 61 and 394 ± 64 W for the 60, 70, 80% Δ
and 100% WRpeak conditions used in all subsequent exhaustive trials.
Table 6.1: Haematological parameters following blood donation
Control
6
3
24 h post donation
48 h post donation
RBC (10 ∙mm )
4.92
±
0.23
4.64
±
0.28*
4.55
±
0.29*†
[Hb] (g∙dl)
14.3
±
0.6
13.4
±
0.6*
13.1
±
0.8*
Hct (%)
42.7
±
1.2
40.4
±
2.5*
39.3
±
2.4*
87
±
3
3
MCV (µm )
87 ± 3
86 ± 3
RDW (%)
12.7 ± 0.9
13.1 ± 1.2
13.0 ± 0.7
Values are mean ± SD; * indicates a significant difference between the control and blood donation
conditions; † indicates a significant difference between the 24 and 48 h post blood donation samples (P <
0.05); RBC indicates red blood cell count; [Hb] indicates the haemoglobin concentration; Hct indicates
that haematocrit concentration; MCV indicates the mean cell volume; and RDW indicates the red cell
distribution width.
Oxygen uptake kinetics
Compared to the control (C) condition, blood donation (BD) did not alter baseline VO2 (C: 1.15
± 0.16 vs. BD: 1.16 ± 0.21 L·min-1; F = 3.160, P = 0.119) or the primary time constant (C: 32 ±
13; vs. BD: 30 ± 18 s; F = 0.355, P = 0.573). However, blood donation significantly reduced the
VO2 primary (C: 2.52 ± 0.43; vs. BD: 2.37 ± 0.33 L·min-1; F = 33.541, P = 0.001) and absolute
amplitudes (C: 3.68 ± 0.48; vs. BD: 3.51 ± 0.42 L·min-1; F = 16.882, P = 0.006). This reduction
in amplitude reached significance at 80%  (C: 2.54 ± 0.37; vs. BD: 2.39 ± 0.32 L·min-1; 95%
CI: 0.02, 0.29 L·min-1) and 100% WRpeak (C: 2.83 ± 0.28 vs. BD: 2.52 ± 0.28 L·min-1; 95%
CI: 0.17, 0.44 L·min-1).
Blood donation did not alter the trajectory of the VO2 slow component (C: 171 ± 108; vs. BD:
188 ± 110 mLmin-2; F = 2.368, P = 0.175), but did elicit a reduction in its amplitude (C: 0.48 ±
0.37; vs. BD 0.39 ± 0.29 L·min-1; F = 6.543, P = 0.043). This reduction in amplitude reached
102
significance at 60%  (C: 0.85 ± 0.15; vs. BD: 0.61 ± 0.13 L·min-1; 95% CI: 0.02, 0.44 L·min-1)
and 70%  (C: 0.69 ± 0.21; vs. BD: 0.48 ± 0.34 L·min-1; 95% CI: 0.04, 0.40 L·min-1). VO2max
was also reduced following blood donation (C: 4.16 ± 0.45; BD: 3.91 ± 0.35 L·min -1; F =
15.245, P = 0.008), and again, this only reached significance at 60%  (C: 4.21 ± 0.52; vs. BD:
3.90 ± 0.34 L·min-1; 95% CI: 0.08, 0.54 L·min-1) and 70%  (C: 4.27 ± 0.43; vs. BD: 4.02 ±
0.30 L·min-1; 95% CI: 0.06, 0.44 L·min-1).
Blood [lactate] and heart rate
Blood [lactate] was similar between conditions both pre- (C: 0.94 ± 0.10; vs. BD: 0.87 ± 0.09
mM; F = 3.948, P = 0.09) and post-exercise (C: 9.04 ± 0.71 vs. BD: 9.05 ± 0.67 L·min-1; F =
0.001, P = 0.982). Similarly, heart rate was unchanged pre-exercise (C: 96 ± 4 vs. BD: 98 ± 4
b·min-1; F = 0.207, P = 0.665), at 2 min (C: 159 ± 3 vs. BD: 162 ± 2 b·min-1; F = 2.094, P =
0.198), and post-exercise (C: 175 ± 2 vs. BD: 173 ± 3 b·min-1; F = 0.503, P = 0.505), in both
conditions.
Exercise tolerance and the power-duration relationship
Overall, Blood donation significantly reduced time to exhaustion (C: 355 ± 83; vs. BD: 281 ±
91 s; F = 17.081, P = 0.006), and this was significant at 60% ∆ (C: 695 ± 193 vs. BD: 512 ± 25
s; 95% CI, 88, 277 s) and 70% ∆ (C: 370 ± 72 vs. BD: 294 ± 80 s; 95% CI, 10, 142 s). A nonsignificant trend towards a reduction in time to exhaustion was seen at 80% ∆ (C: 227 ± 40 vs.
BD: 203 ± 42 s; 95% CI, -6, 54 s) and 100% WRpeak (C: 130 ± 25 vs. BD: 117 ± 19 s; 95% CI, 8, 34 s). Estimates for the power-duration relationship were derived from these data. CP was
significantly reduced following blood donation (C: 259 ± 54; vs. BD: 246 ± 42 W; 95% CI: 2,
26 W), and W remained unchanged (C: 18.2 ± 3.7, vs. BD: 18.0 ± 3.1 kJ; 95% CI: -1.2, 1.6 kJ).
103
Table 6.2: Oxygen uptake kinetics following blood donation
Control
Post blood donation
Baseline VO2 (L∙min-1)
60% Δ
1.13
±
0.10
1.14
±
0.20
70% Δ
1.09
±
0.23
1.15
±
0.23
80% Δ
1.24
±
0.15
1.21
±
0.25
1.15
±
0.20
1.14
±
0.21
60% Δ
2.24
±
0.40
2.14
±
0.33
70% Δ
2.48
±
0.51
2.40
±
0.56
80% Δ
2.54
±
0.37
2.39
±
0.32*
2.83
±
0.28
2.52
±
0.28*
60% Δ
3.37
±
0.55
3.29
±
0.38
70% Δ
3.58
±
0.56
3.54
±
0.52
80% Δ
3.78
±
0.50
3.56
±
0.37*
3.98
±
0.32
3.66
±
0.41*
60% Δ
7.89
±
0.61
7.60
±
0.91
70% Δ
7.93
±
0.39
7.72
±
0.56
80% Δ
7.57
±
0.73
7.11
±
0.84
100% WRpeak
7.28
±
1.11
8.50
±
1.09
60% Δ
28
±
7
30
±
24
70% Δ
33
±
14
37
±
18
80% Δ
35
±
14
28
±
10
33
±
15
23
±
16
60% Δ
0.85
±
0.15
0.61
±
0.13*
70% Δ
0.69
±
0.21
0.48
±
0.34*
0.38
±
0.21
0.36
±
0.20
60% Δ
95
±
30
121
±
62
70% Δ
168
±
27
157
±
71
249
±
154
278
±
124
60% Δ
4.21
±
0.52
3.90
±
0.34*
70% Δ
4.27
±
0.43
4.02
±
0.30*
80% Δ
4.17
±
0.45
3.95
±
0.32
100% WRpeak
3.99
±
0.43
3.75
±
0.44
100% WRpeak
-1
Ap (L∙min )
100% WRpeak
-1
Absolute Ap (L∙min )
100% WRpeak
-1
-1
Primary gain (mL∙min ∙W )
Primary τ (s)
100% WRpeak
-1
As (L∙min )
80% Δ
-2
As trajectory (mL∙min )
80% Δ
-1
VO2max (L∙min )
Values are mean ± SD; * indicates a significant difference (P < 0.05) between control and post blood
donation conditions; data is not provided for the slow component trajectory at 100% WR peak because the
time to exhaustion was generally around 120 s and so there was no discernable slow component.
104
600
550
Power output (W)
500
450
400
350
300
250
200
0
0
200
400
600
800
1000
Time (s)
Figure 6.1: Non-linear power-duration relationship for a representative participant in the control (closed
triangles) and blood donation (open triangles) conditions. Note the reduced time to exhaustion following
blood donation at each work-rate and the altered power-duration relationship. No difference was seen in
the W estimate (Pre: 17.9 vs. Post: 17.7 kJ), whereas CP was reduced following blood donation (Pre: 270
vs. Post 247 W), denoted by the large and narrow dashed lines, respectively.
6.4 - Discussion
Blood donation significantly reduced RBC, [Hb] and Hct, and by extension, the O2 carrying
capacity of the blood. For clarity, only the reduction in [Hb] will be discussed from this point,
as all of these measures are related and collectively demonstrate a reduction in O2 transport via
the blood. The primary amplitude was reduced, with no change in its time course. In addition,
the trajectory of the VO2 slow component was unchanged, whilst the amplitude was reduced,
presumably limited by a reduction in VO2max . The combination of these effects served to reduce
time to exhaustion during severe-intensity exercise; this was associated with a significant
reduction in CP, whilst W remained unchanged.
Haematology
As hypothesised, the withdrawal of ~450 mL of whole blood caused a significant reduction (of
~7%) in [Hb], with similar reductions also being seen in red blood cell count and Hct. These
105
observations suggest that the O2 carrying capacity of the blood was likely reduced and is akin to
previous research (e.g., Panebianco et al., 1995; Duda et al., 2005; Burnley et al., 2006; Gordon
et al., 2010). It is likely that a reduction in O2 delivery was evident for at least three days post
donation; blood samples taken at 24 and 48 h post donation showed no difference in [Hb]
between each of these samples, and both were significantly lower than the control condition.
Furthermore, the relative age and distribution of the red blood cells remained unchanged
following donation (indicated by mean cell volume and red cell distribution width,
respectively), suggesting that it is unlikely that significant erythropoiesis had begun during the
experimental period. Indeed, the time course for erythropoiesis, and therefore replenishment of
[Hb], has been shown to take at least seven days (Panebianco et al., 1995; Valeri et al., 2003).
Participants were advised to ingest additional fluids post donation in an attempt to replace blood
volume to pre donation levels, and it is likely that total plasma volume would have been
replaced between 6-8 hours after donation (Ruttmann et al., 2003). Acute plasma volume
expansion often seen following exercise may go some way to explain the significant difference
in the red blood cell count between the two post donation samples (cf. Convertino et al., 1991);
i.e., further plasma entering the systemic blood would reduce the relative amount of red blood
cells and by doing so reduce the concentration of these cells. With this supporting contention it
is likely that in the current study blood donation had the desired effect of reducing the O 2
carrying capacity of the blood. By undertaking all testing within a three day period post
donation, it is possible that total blood volume would have been replaced to a similar level as
pre donation by an increase in plasma volume, without a significant increase in red blood cell
mass.
Oxygen uptake kinetics
Blood donation did not alter the time course of the primary VO2 kinetics, but led to a significant
reduction in the primary amplitude, which reached significance at 80% Δ and 100% WR peak.
Whilst the ‘speed’ of the primary VO2 kinetics (i.e., the ) is similar that that seen in previous
studies, the reduction in the amplitude appears initially to be in contrast to that seen during
moderate-, heavy-, and severe-intensity exercise (Burnley et al., 2006; Gordon et al., 2010).
However, no difference was seen in the primary VO2 amplitude at both the 60 and 70% Δ work
rates in the present study, thus the data partially support the observations of Burnley et al.,
(2006). Indeed, despite a reduction in [Hb] during these work-rates it appears that cardiac output
was able to adjust to maintain adequate O2 availability to the working muscle, such that the
primary VO2 kinetics were unaltered following blood donation. The contrast at the higher work
rates is hard to reconcile, especially as an 80% Δ work rate was performed in each study. It
106
could be argued that in present study, participants were generally ‘fitter’ than those who took
part in the earlier study of Burnley et al.; i.e., current participants attained a higher WRpeak (by
~55 W) and VO2max (by ~10 mLkg-1min-1). Therefore, despite 80% Δ being used in each study,
participants were exercising at an absolute work rate that was ~45 W higher in the present work.
It may also be that at these high work-rates the reduction in bulk muscle O2 availability
following blood donation may have limited the amplitude of the primary VO2 kinetics. It could
also be that muscle O2 availability becomes increasingly important in certain conditions (such as
blood donation) the further exercise is performed above CP, however, it is impossible to
confirm this possibility with the data of Burnley et al. (2006). This view may gain support from
the observation of a similar reduction in VO2max following blood donation in each study (see
later in this discussion). In contrast, a reduction in O2 availability typically manifests in a slower
time constant (such as with hypoxia; Engelen et al., 1996; MacDonald et al., 2000) or beta
blockade (Hughson et al., 1984), rather than reducing the VO2 amplitude. In other situations,
however, such as during supine exercise, a reduction in muscle O2 availability elicits a reduction
in the primary VO2 amplitude, with no change in the time constant (Koga et al., 2005).
Therefore, the present data generally support the ‘metabolic inertia’ hypothesis for the control of
VO2 kinetics (Grassi, 2005) – at least at 60 and 70%  work rates, as the ‘speed’ (i.e. ) of the
primary VO2 kinetics was unaltered following blood donation.
Blood donation significantly reduced VO2max , as seen consistently in previous research (e.g.,
Ekblom et al., 1972; Ekblom et al., 1976; Kanstrup et al., 1984; Duda et al., 2003; Burnley et
al., 2006). This reduction in VO2max would have limited the scope for development of the VO2
slow component, and as such, the amplitude of the latter was significantly reduced in this study
and as seen previously (Burnley et al., 2006). The trajectory of the VO2 slow component was
unaffected by blood donation. This supports the notion that during upright exercise O 2 delivery
is equal to, or in excess of, the metabolic demand (Bangsbo et al., 2000). During ‘submaximal’
(i.e., moderate- and heavy-) exercise, compensatory adjustments in cardiac output and muscle
blood flow can maintain muscle O2 delivery and VO2 to near control levels (MacDonald et al.,
2000). Thus, it would be expected that these adjustments be less able to accommodate changes
in O2 delivery when exercise is performed within the severe domain, with VO2 rising on a
trajectory towards its maximum (Poole et al., 1988; Özyener et al., 2001). However, as VO2max
is reduced, and the trajectory of the slow component is unchanged following blood donation, it
appears that the reduction in [Hb] is matched through alterations in cardiac output and muscle
blood flow which adapt faster than the VO2 kinetics (Tschakovsky and Hughson, 1999).
107
Indeed, in the present study, the trajectory of the VO2 slow component was similar between
conditions, reflecting a similar ‘rate’ of muscle fatigue (e.g., Jones et al., 2008; Allen, 2009),
and hence a similar recruitment of additional motor units over time (e.g., Burnley et al., 2006).
Furthermore, these data indicate that a reduction in muscle O2 delivery as a consequence of
blood donation serves to reduce the maximum rate of O2 consumption (i.e., VO2max ). In light of
the present methodology, this is presumably a consequence of an overall reduction in maximal
O2 delivery that is principally dependent upon [Hb] (Connes et al., 2003; Wilkerson et al., 2005;
Burnley et al., 2006).
Exercise tolerance and the power-duration relationship
As hypothesised, time to exhaustion was reduced following blood donation. This reduction
reached significance at the ‘lower’ end of the severe-intensity domain, with a 36% and 26%
reduction in performance being seen at 60 and 70% ∆, respectively. While not significant, a
small reduction in time to exhaustion (of ~11-12%) was seen at both 80% ∆ and 100% WRpeak.
This reduction in exercise tolerance is consistent with the findings of previous research (e.g.,
Ekblom et al., 1972; Ekblom et al., 1976; Kanstrup et al., 1984; Burnley et al., 2006). As
hypothesised, a reshaping of the power-duration relationship was evident following blood
donation; however, this resulted in a reduction in CP (by ~5%), with no change in W. The
original hypothesis was derived from the notion that: (1) both the VO2 kinetics and the O2 cost
of submaximal exercise are unchanged following blood donation (Gordon et al., 2010), and (2)
a subsequent reduction in O2 delivery (as a consequence of a reduced [Hb]) should have little
effect on CP. Furthermore, as W represents an amount of work that can be performed above CP
(Moritani et al., 1981), an intervention that reduces the capacity to perform work above CP
(such as a reduction in VO2max ) should by definition, reduce W. In hindsight, it could have been
hypothesised that blood donation would not alter one of the likely determinants of W (i.e.,
substrate-level phosphorylation), as these metabolic pathways are independent of atmospheric
O2. The observation that W was unaltered following blood donation provides some support for
the notion that this parameter is indeed primarily ‘anaerobic’ in nature (Moritani et al., 1981;
Poole et al., 1988).
The observation that CP was reduced following blood donation is puzzling, as previously, both
the VO2 kinetics and the O2 cost of submaximal exercise (including intensities up to CP) have
been shown to be unaffected by a small reduction in [Hb] (Gordon et al., 2010). Indeed, at the
lower end of the severe-intensity domain (i.e., at 60 and 70% ), the primary VO2 kinetics were
unaltered, suggesting adequate O2 availability. In contrast, it could be argued that at 80%  and
108
100% WRpeak this may have not been the case, and the reduction in exercise tolerance
manifested itself in a reduced CP rather than W. The precise physiological mechanism
underpinning this effect remains unclear, especially in light of the fact that heart rate kinetics
remained unchanged in the current study. It may be that O2 delivery and utilisation were in
excess of metabolic demand, or that stroke volume increased to match demand following blood
donation. An alternative standpoint would be to re-consider that work-rates for each of the
power-duration trials were calculated using the %∆ concept (i.e., between GET and VO2max )
from data collected prior to blood donation. The main physiological effect of this intervention
was to reduce VO2max (and likely the incremental exercise WRpeak), so if the work-rates for the
power-duration trials were determined after blood donation they would have been somewhat
lower than those used in this study. Hence, as blood donation reduced the work-rate at CP – and
the power-duration trials remained at the same absolute work-rate – then the relative intensity of
each of the power-duration trials would be increased post blood donation. This would, in turn,
increase the relative exercise intensity of each work rate, thereby increasing the rate of depletion
of intramuscular PCr (and presumably W) throughout exercise. Couple this likely increased rate
of substrate-level phosphorylation with the reduction in VO2max and it is no surprise that
exercise tolerance was reduced following blood donation.
Conclusions
This study provides further evidence that the removal of one unit (~450 mL) of whole blood
reduces [Hb], and by extension, the O2 carrying capacity of the blood. In contrast to previous
research, this intervention reduced the amplitude (but not the time course) of the primary VO2
response, and in turn, increased the O2 deficit and the rate of depletion of intramuscular PCr
stores during the transient. The trajectory of the VO2 slow component was similar between
conditions, whilst the magnitude (i.e., the amplitude) of the VO2 slow component was reduced,
presumably as a consequence of a reduction in VO2max . The interaction between the VO2 slow
component and VO2max appears to the critical to performance, as the consistent reduction in
VO2max seen following blood donation limits the scope for the aerobic contribution to energy
turnover and therefore places a greater reliance on the PCr hydrolysis and anaerobic glycolysis;
which are likely major contributors to W. Combine the reduction in maximal oxygen uptake
(i.e., VO2max ) with a significantly reduced maximal sustainable rate of O2 delivery and
utilization (i.e., CP), and an unchanged ‘anaerobic capacity’ (i.e., W), and it is not surprising
that exercise tolerance is reduced following blood donation. Exactly how the removal of a unit
of whole blood reduces CP remains unclear. However, this effect appears to increase the rate of
109
depletion of W throughout exercise; and as the VO2 kinetics develop over time to attain the
reduced VO2max quicker, then exhaustion occurs soon thereafter, presumably with the final
depletion of W.
110
Chapter 7 – Study 4
The effect of supine exercise on the power-duration relationship
7.1 - Introduction
During upright exercise, an additional arterial hydrostatic pressure component increases
perfusion pressure and hence muscle blood flow, but is absent in a supine posture (Folkow et al.
1971; Hughson et al. 1993). Therefore, during supine exercise, and indeed any other activity
where the active musculature is at or above the level of the heart, increased muscle blood flow
as a result of gravity is absent and O2 delivery to the working muscle is lower that that of
upright exercise (Convertino et al., 1984; Hughson et al., 1996; MacDonald et al., 1998; Koga
et al., 1999). As a consequence of lower arterial pressure in the legs in the supine position,
blood flow to the leg muscles is reduced (Eiken, 1988; MacDonald et al., 1998), despite an
increase in cardiac output (Hughson et al., 1991; Leyk et al., 1994). During high-intensity
(>GET) supine exercise, there is a general agreement that the ‘overall’ VO2 response is slower
than that seen during upright cycling (in terms of mean response time; MRT; e.g., Cerretelli et
al., 1977; Convertino et al., 1984; Hughson et al., 1993; Leyk et al., 1994; Koga et al., 1999;
Egaña et al., 2006). More specifically, this change in MRT appears to be a result of a longer
(i.e., slower) primary time constant (τ) and/or a reduction in the primary amplitude (Hughson et
al., 1991; Hughson et al., 1993; Koga et al., 1999; Denis and Perrey, 2006; Egaña et al., 2006;
Jones et al., 2006). In addition, during high-intensity (>CP) supine exercise, an increase in the
amplitude of the VO2 slow component is typically evident (Hughson et al., 1993; MacDonald et
al., 1998; Denis and Perrey, 2006; Jones et al., 2006). As well as slowing of the VO2 response,
this reduction in muscle O2 availability in the supine position also leads to a significant
reduction in VO2max (Astrand and Saltin, 1961; Hughson et al., 1991; Koga et al., 1999; Jones et
al., 2006; Egaña et al., 2007). Given the apparent negative effect that supine exercise appears to
have on both the VO2 kinetics and VO2max , it is not surprising that a reduction in perfusion
pressure has been shown to affect muscle power production (Wright et al., 1999; Hepple, 2002)
and an increased rate of muscle fatigue (Tachi et al., 2004). Indeed, it is well established that
cycling performance is greater in upright compared to supine body position, as during
incremental exercise, both peak power output and time to exhaustion are significantly reduced
in the supine position (Astrand and Saltin, 1961, Hughson et al., 1991; Koga et al., 1999;
Terkelsen et al., 1999; Jones at al, 2006; DiMenna et al., 2010); and during constant work-rate
exercise, time to exhaustion and performance during a ‘fatigue test’ are reduced in the supine
position (Egaña et al., 2006; Egaña et al., 2007; Egaña et al., 2010a; Egaña et al., 2010b).
111
The majority of studies that have investigated the physiological differences between body
positions have prescribed the intensity of a criterion exercise task relative to an upright
incremental test, i.e., exercise performed at the same absolute work-rate in both the upright, and
supine position (e.g., Convertino et al., 1984; Koga et al., 1999). Given that peak power output
attained in an incremental test is reduced in the supine position (Convertino et al., 1984; Koga
et al., 1999), the relative exercise intensity would be higher than that of the equivalent upright
bout, thereby potentially placing an individual into a different exercise intensity domain (Whipp
and Wasserman, 1972; Jones and Poole, 2005). Egaña et al., (2006) demonstrated a significant
reduction in VO2max during supine exercise performed at the same relative exercise intensity
(80% peak power output in a posture-specific incremental test). However, no change was seen
in time to exhaustion between positions, presumably due to the lower absolute work-rate
performed during the supine trials.
It is well established that a reduction in perfusion pressure alters both the VO2 kinetics and
VO2max (Koga et al., 1999) and elicits a reduction in performance during exercise perfumed at
the same absolute intensity (Egaña et al., 2010). The effect of supine exercise on the parameters
of the power-duration relationship is presently unclear, but may be principally dependent upon
the effect on CP. A reduction in VO2max coupled with no change in CP would result in a
reduction in W, as the capacity to perform work above CP would be reduced. However, it could
be argued that as supine exercise likely slows the VO2 kinetics (and reduces VO2max ) then it
may also reduce the maximal sustainable rate of oxidative metabolism (i.e., CP). Indeed, if the
W is principally determined by the capacity for substrate-level phosphorylation, then a
reduction in O2 delivery should have no effect on this parameter.
Aims and Hypothesis
The aim of this study was to normalise exercise intensity relative to a posture specific
incremental test, and to the compare the effect of supine exercise on the VO2 kinetics, VO2max
and the power-duration relationship. It was first hypothesised that time to exhaustion, peak
power output, and VO2max would be significantly reduced during supine incremental exercise.
Second, during severe-intensity exercise, the primary time constant (τ) would be significantly
longer, and the amplitude reduced in the supine position. Furthermore, the VO2 slow
component will commence from a lower VO2 , but would progress at a similar rate (i.e. the
trajectory will be unchanged), such that the amplitude would comparable to the upright
112
condition as VO2max would also be reduced. Finally, time to exhaustion will be similar between
conditions; as a consequence of a reduction in CP, with no change in W.
7.2 - Methods
Experimental design and protocols
Nine healthy trained male cyclists (age 31 ± 8 years; height 178.4 ± 6.4 cm; weight 83.2 ± 14.2
kg) volunteered to participate in this research and provided written informed consent.
Participants reported to the laboratory on ten occasions over a 3-week period. During the first
visit all demographic and anthropometric data was collected. Following these measurements, or
in the second visit, participants performed an upright or a supine incremental test, in random
order, to estimate GET and to determine VO2max . Four work-rates were then calculated (relative
to the posture specific incremental test) for each body position for each of the subsequent
constant work-rate power-duration trials.
All upright trials were performed on an electronically braked cycle ergometer (Lode Excalibur
Sport. Groningen, The Netherlands). A custom built supine rig was used for each supine trial,
which allowed the use of the same cycle ergometer as the upright position. Participants were
orientated in a horizontal position on a secure mat, with the hips approximately 30 cm behind
the ergometer and the head supported on a 10-15 cm mat (height selected for each participants
comfort). Handgrips were provided (located approximately by the hips) to enable participant’s
to produce force on the pedals without sliding backwards on the bed. The ergometer itself was
at the front of the rig with the rear end raised on a support so that the bottom bracket axle was
32 cm above the bed of the rig. This elevation is similar to that used in other supine studies (2045 cm; Koga et al., 1999; Denis and Perrey, 2006; Egana et al, 2007; DiMenna et al., 2009).
Relative to the leg extension distance and the hip and knee angles, the cycling position was
similar in both the upright and supine positions; the exception being that the legs were
positioned above the heart in the supine position.
Please refer to the General Methods for further details of the participant instruction prior to
exercise and for a description of the methods employed during the incremental test, for the
determination of the power-duration relationship, and details of the measurement of pulmonary
gas exchange, blood sampling, and test termination criteria.
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7.3 - Results
Incremental exercise
Following the initial kinetic phase of the VO2 response, VO2 increased as a linear function of
work-rate for the upright (UP) and supine (SUP) conditions, respectively (UP: 9.01 ± 0.06 vs.
SUP: 9.41 ± 0.86 mLminW-1; 95% CI, -1.11, 0.30 mLmin-1W-1). Both VO2max (UP: 4.41 ±
0.35 vs. SUP: 3.90 ± 0.31 L∙min-1; 95% CI, 0.30, 0.72 L∙min-1; or UP: 55 ± 11 vs. SUP: 48 ± 9
mL∙kg∙min-1; 95% CI, 4, 9 mL∙kg∙min-1) and peak work-rate (UP: 403 ± 43 vs. SUP: 334 ± 31
W; 95% CI, 53, 85 W) were significantly reduced in the supine position. Similarly, both the
work-rate (UP: 145 ± 44 vs. SUP: 109 ± 21 W; 95% CI, 17, 56 W) and VO2 (UP: 2.30 ± 0.33
vs. SUP: 1.92 ± 0.27 L∙min-1; 95% CI, 0.14, 0.61 L∙min-1) at the GET were significantly lower
in the supine position.
No difference was seen in baseline heart rate (UP: 97 ± 20 vs. SUP: 88 ± 14 b·min-1; 95% CI, 8, 26), whilst HRpeak was significantly lower in the supine position (UP: 189 ± 12 vs. SUP: 169
± 13 b·min-1; 95% CI, 13, 28). From these data, four work-rates were calculated for each body
position (UP: 298 ± 40, 323 ± 40, 349 ± 41 and 397 ± 44 W and SUP: 244 ± 25, 266 ± 27, 289 ±
28 and 334 ± 31 W).
Oxygen uptake kinetics
A similar baseline VO2 was seen in each condition (UP: 1.26 ± 0.20 vs. SUP: 1.17 ± 0.23
L·min-1; F = 5.258; P = 0.051). For supine exercise, the primary time constant was longer (UP:
28 ± 8 vs. SUP: 35 ± 11 s; F = 14.724; P = 0.005), and reached significance at 60%  (UP: 27 
5 vs. SUP: 33  13 s; 95% CI, -16, -1 s) and 100% WRpeak (UP: 25  11 vs. SUP: 35  10 s;
95% CI, -20, -2 s). In addition, both the primary amplitude (UP: 2.68 ± 0.39 vs. SUP: 2.38 ±
0.39 L·min-1; F = 101.276; P < 0.001) and absolute primary amplitude were reduced in the
supine position (UP: 3.93 ± 0.35 vs. SUP: 3.55 ± 0.34 L·min-1; F = 40.455; P < 0.001). This
reduction in primary amplitude was significant at 60%  (UP: 2.45  0.41 vs. SUP: 2.31  0.30
L·min-1; 95% CI, 0.19, 0.57 L·min-1), 70%  (UP: 2.60  0.30 vs. SUP: 2.25  0.32; 95% CI,
0.09, 0.55) and 80%  (UP: 2.79  0.32 vs. SUP: 2.53  0.30 L·min-1; 95% CI, 0.15, 0.48
L·min-1).
The trajectory of the VO2 slow component was similar between conditions (UP: 154 ± 79 vs.
SUP: 131 ± 70 mL·min-2; F = 2.506; P = 0.264) but the amplitude of the VO2 slow component
was reduced in the supine position (UP: 0.66 ± 0.31 vs. SUP: 0.52 ± 0.27 L·min-1; F = 6.643; P
114
= 0.037). Finally, a significant reduction in VO2max (UP: 4.47 ± 0.39 vs. SUP: 3.93 ± 0.33
L·min-1; F = 43.038; P < 0.001) was seen during supine exercise. This difference was
significant at all work rates; 60%  (UP: 4.48  0.39 vs. SUP 3.90  0.44 L·min-1; 95% CI,
0.40, 0.78 L·min-1), 70%  (UP: 4.62  0.35 vs. SUP: 4.04  0.24 L·min-1; 95% CI, 0.27, 0.88
L·min-1), 80%  (UP: 4.54  0.41 vs. SUP: 3.95 0.25 L·min-1; 95% CI, 0.31  0.88 L·min-1)
and 100% WRpeak (UP: 4.24  0.37 vs. SUP: 3.83  0.36 L·min-1; 95% CI, 0.19, 0.62 L·min-1).
Blood [lactate] and heart rate
Baseline blood [lactate] was similar for each body position (UP: 1.0 ± 0.1 vs. SUP: 1.0 ± 0.5
mM; F = 0.082; P = 0.782), while in the supine position blood [lactate] was significantly lower
at exhaustion (UP: 8.3 ± 0.6 vs. SUP: 7.00 ± 0.4 mM; F = 15.157; P = 0.005). Baseline heart
rate was similar in each body position (UP: 95 ± 3 vs. SUP: 93 ± 3 b·min-1; F = 1.169; P =
0.311). Heart rate at 2 min (UP: 160 ± 3 vs. SUP: 150 ± 3 b·min -1; F = 44.203; P < 0.001) and
HRpeak were lower in the supine position (UP: 175 ± 3 vs. SUP: 163 ± 3 b·min -1; F = 48.990; P
< 0.001). In order to compare the heart rate response to a number of previous studies, the heart
rate at 6 min into the 60% Δ work-rate was calculated for both conditions, and was significantly
lower during supine exercise (UP: 167 ± 12 vs. SUP: 155 ± 15 b·min-1; 95% CI, 5, 20 b·min-1).
115
Table 7.1: Oxygen uptake kinetics during supine exercise
Upright
Baseline
60% Δ
VO2
Supine
(L∙min-1)
1.25
±
0.29
1.21
±
0.28
70% Δ
1.29
±
0.17
1.17
±
0.29
80% Δ
1.27
±
0.14
1.18
±
0.23
100% WRpeak
1.22
±
0.16
1.13
±
0.14
60% Δ
27
±
5
35
±
13*
70% Δ
31
±
7
33
±
11
80% Δ
31
±
5
39
±
11
25
±
11
35
±
10*
60% Δ
2.45
±
0.41
2.11
±
0.30*
70% Δ
2.60
±
0.30
2.25
±
0.32*
80% Δ
2.79
±
0.32
2.53
±
0.32*
100% WRpeak
2.90
±
0.40
2.72
±
0.37
60% Δ
3.70
±
0.28
3.29
±
0.28*
70% Δ
3.89
±
0.27
3.39
±
0.26*
80% Δ
4.06
±
0.25
3.00
±
0.24*
100% WRpeak
4.07
±
0.47
3.82
±
0.30*
60% Δ
8.19
±
0.65
8.48
±
0.60
70% Δ
8.12
±
0.99
8.56
±
1.09
80% Δ
8.00
±
0.41
8.56
±
0.71*
7.30
±
0.72
8.09
±
1.11*
60% Δ
0.78
±
0.14
0.61
±
0.28
70% Δ
0.73
±
0.41
0.65
±
0.19
80% Δ
0.49
±
0.28
0.29
±
0.19
60% Δ
91
±
40
79
±
38
70% Δ
164
±
72
148
±
49
80% Δ
206
±
78
171
±
86
(L∙min-1)
60% Δ
4.48
±
0.39
3.90
±
0.44*
70% Δ
4.62
±
0.35
4.04
±
0.24*
80% Δ
4.54
±
τp (s)
100% WRpeak
-1
Ap (L∙min )
Absolute Ap (L∙min-1)
Ap gain (ml.min.W)
100% WRpeak
As (L∙min-1)
As trajectory (ml.min-1)
VO2max
3.95 ± 0.25*
0.41
100% WRpeak
4.24 ± 0.37
3.83 ± 0.36*
Values are mean ± SD. * indicates a significant difference between the upright and supine positions (P <
0.05).
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Table 7.2: Blood [lactate], heart rate and time to exhaustion during supine exercise
Upright
Supine
Blood [lactate] 'Pre' (mM)
60% Δ
1.1
±
0.8
0.9
±
0.3
70% Δ
1.0
±
1.3
1.1
±
0.2
80% Δ
0.9
±
0.1
1.0
±
0.2
100% WRpeak
0.9
±
0.2
1.0
±
0.2
60% Δ
8.0
±
1.4
6.7
±
1.6*
70% Δ
8.7
±
1.5
6.9
±
1.1*
80% Δ
8.5
±
1.5
6.9
±
1.7*
100% WRpeak
8.2
±
1.6
7.4
±
1.2
60% Δ
92
±
14
94
±
8
70% Δ
96
±
12
94
±
12
80% Δ
96
±
9
96
±
9
100% WRpeak
97
±
12
90
±
8
60% Δ
154
±
11
146
±
13*
70% Δ
160
±
9
150
±
11
80% Δ
161
±
9
151
±
10*
100% WRpeak
164
±
13
153
±
12*
60% Δ
179
±
11
164
±
13*
70% Δ
181
±
11
166
±
8*
80% Δ
174
±
12
164
±
7*
100% WRpeak
169
±
9
160
±
10*
60% Δ
714
±
262
623
±
190
70% Δ
387
±
83
405
±
102
80% Δ
258
±
60
234
±
56
100% WRpeak
129
±
27
Blood [lactate] 'Post' (mM)
HR baseline (b·min-1)
-1
HR 2 min (b·min )
HRpeak (b·min-1)
Time to exhaustion (s)
141 ± 39
Values are mean ± SD. * indicates a significant difference between the upright and supine positions (P <
0.05).
117
Exercise tolerance and the power-duration relationship
Time to exhaustion was inversely correlated with power (r2 values >0.99), linear regression
provided a high goodness of fit of the data in each position, and was similar between conditions
(UP: 372 ± 30 vs. SUP: 351 ± 22 s; F = 1.455; P = 0.262). The linear work-time model was
used to define the power-duration relationship, and it evidenced a significant reduction in CP
during supine exercise (UP: 275 ± 36 vs. SUP: 216 ± 13 W; 95% CI, 40, 78 W), with no change
in W (UP: 17.2 ± 5.1 vs. SUP: 17.1 ± 5.8 kJ; 95% CI, -4.7, 4.9 kJ).
5.5
5.0
4.5
4.0
VO2 (L.min-1)
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
-100
-50
0
50
100
150
200
250
300
350
400
Time to exhaustion (s)
Figure 7.1: Oxygen uptake response for a representative participant exercising at 70% Δ in the upright
(solid circles/long dashed line) and supine (open circles/short dashed line) position. Note: the slowing of
the response, reduction in the VO 2 primary amplitude, similar VO 2 slow component, and a reduction in
VO2max during supine exercise; whilst time to exhaustion remains similar between conditions.
7.4 - Discussion
During supine incremental exercise, peak power output, time to exhaustion and VO2max were
significantly reduced in the supine position. During supine constant work-rate exercise
performed at the same relative intensity, the primary VO2 kinetics were ‘slowed’, with a longer
(i.e., slower) primary VO2 time constant, and a reduction in the primary VO2 amplitude. The
118
VO2 slow component originated from a lower absolute VO2 , but progressed at a similar rate,
whilst the overall amplitude of the VO2 slow component was reduced, presumably limited in its
development by a reduction in VO2max . Time to exhaustion was similar between conditions,
however, due to the imposition of a lower absolute power output in the supine position, a
difference in the power-duration relationship was evident, with CP being reduced, and W
remaining unchanged.
Incremental exercise
Identical incremental test protocols were performed (i.e., 3 min baseline, 30 W·min-1 ramp rate)
in each body position. This protocol facilitated a direct comparison of the VO2 response, and
exercise tolerance between upright and supine exercise. A comparison of the overall
DVO2 / DWR relationship demonstrated that the O2 cost of work (of ~9-9.5 mL·min-1W-1) was
similar between conditions, suggesting that exercise economy was similar between conditions
(Whipp and Wassermann, 1969; Gaesser and Poole, 1996). Both the VO2 , and work-rate at
GET, were reduced during supine exercise, in agreement with the majority of previous research
(Astrand and Saltin, 1961; Hughson et al 1991; Koga et al 1999), but not all (Jones et al., 2006;
DiMenna et al., 2009). The time taken to reach exhaustion, and hence peak power output, was
reduced (by ~20%) in the supine position. This reduction in performance was accompanied with
a ~13% reduction in VO2max , again, in agreement with previous research (e.g., Astrand and
Saltin, 1961; Hughson et al 1991; Koga et al 1999; Terkelsen et al., 1999; Jones at al, 2006;
DiMenna et al., 2009). These observations are consistent with the theoretical interpretation that
a reduced perfusion pressure, and hence muscle O2 availability, leads to a reduction in VO2max
and exercise tolerance (Stenberg et al, 1967; Hughson et al., 1996) .
Justification for using relative exercise intensities
Clear differences in performance were evident during incremental exercise, but a direct
comparison (of time to exhaustion) could not be made during subsequent power-duration trials
as these were performed at the same relative (not absolute) work-rate. This study was not
performed to directly compare exercise tolerance between each body position; that has already
been established (e.g., Hughson et al., 1991; Egaña et al., 2006). Instead, the principal aim was
to identify differences in the VO2 kinetics, and to examine how a change in body position
influences the power-duration relationship. Two key requirements must be met for such an
investigation: first; a range of (two or more) constant work-rate trials must be performed; and
second; time to exhaustion must be within ~2-12 min (Moritani et al., 1981; Poole, 1988). In
119
order to satisfy the latter, the decision was taken to standardise the exercise intensity (relative)
to a posture-specific incremental test, thereby lowering the imposed work-rate for each supine
trial. Indeed, data from one research group provides strong support for this contention; for
example, exercise performed at 80% peak power output in an upright incremental test (i.e., at
the same absolute intensity) led to a reduction in time to exhaustion in the supine position (of
~56-70%; Egaña et al., 2006; Egaña et al., 2007; Egaña et al., 2010). However, when the same
relative intensity exercise was compared, a small, but not-significant, reduction in exercise
tolerance was reported (Egaña et al., 2006). Therefore, in order to meet the principal aims of the
current study, utilising exercise at the same relative intensity was clearly justified. Furthermore,
these data provide an insight into effect of a reduction in muscle O2 availability on VO2
kinetics, and a unique perspective into the interaction between the power-duration relationship
and whole body bioenergetics.
Oxygen uptake kinetics
This was the first study to examine differences in the VO2 response between supine and upright
exercise performed at the same relative exercise intensity. The principal findings are that
exercise in the supine position altered the primary VO2 kinetics, with a longer (i.e. slower)
primary time constant, and a reduction in the primary amplitude. Following this phase, whilst
the trajectory of the VO2 slow component was similar between conditions, the amplitude was
reduced, presumably as a result of a reduction in VO2max .
In the supine position, the primary VO2 kinetics were significantly ‘slowed’ when compared to
upright exercise. Specifically, the primary amplitude was reduced, as would be expected given
that the absolute work-rate was lower in each supine trial (Wilkerson et al., 2004). In addition,
the primary time constant was longer (by ~20%), presumably as a result of the likely reduction
in muscle O2 availability. This latter observation is comparable to other forms of exercise where
perfusion pressure is reduced (Hughson et al., 1991; Hughson et al., 1996), or following
interventions that restrict muscle O2 supply (e.g., ischemia, hypoxia, β-blockade; Hughson,
1984; Engelen et al., 1996). Increasing bulk O2 availability through lower body negative
pressure (Hughson et al., 1993), or following a bout of high-intensity priming exercise (Jones et
al., 2006; DiMenna et al., 2009), appears to reverse this effect, thereby ‘speeding’ the VO2
kinetics back towards control values. In order to compensate for the gravitational assist to leg
blood flow, increased strain was likely placed upon the cardiovascular system in the supine
position. A direct comparison of the heart rate kinetics between the present data and other
published research is problematic, due to differing work-rates (relative vs. absolute),
120
measurement time points, and the length of each exercise trial (e.g., of a fixed duration, or to
exhaustion). However, at rest, heart rate was similar in each condition, consistent with a number
of previous studies (Koga et al., 1999; Jones et al., 2006; DiMenna et al., 2009), whilst others
report a lower resting heart rate (Denis and Perrey, 2006; Egaña et al., 2010). This lower heart
rate was evident at 2 min (by ~10 b·min-1; indicative of a slower ‘primary phase’ of
cardiovascular response), and also at exhaustion (i.e. at HRpeak; by ~12 b·min-1). Other groups
have reported a reduction in heart rate at various time points during exercise lasting from 30 s to
~10 min (Hughson et al., 1993; Koga et al., 1999; DiMenna et al., 2009; Egaña et al., 2006a;
Egaña et al., 2006b; Egaña et al., 2010). Elstad et al., (2009) demonstrate a reduction in stroke
volume in the supine position, and so couple this effect with a reduction in HR (as seen in this
study) then it is not surprising that cardiac output kinetics are also generally slower in the supine
position (Leyk et al., 1992). It is clear from this evidence that the cardiovascular system is
unable to adjust to meet the increased demand for O2 from within the muscle. However, an
increase in mean arterial pressure has been shown (Elstad et al., 2009), thereby increasing
muscle blood flow in a further attempt to maintain the supply of O2 to the working muscle
(McDonald et al., 1998). However, the kinetics of muscle blood flow are almost always faster
than that of muscle VO2 kinetics ( mVO2 ; Grassi et al., 1996; Bangsbo et al., 2000), and
because leg blood flow is similar (McDonald et al., 1998), unless there were substantial
differences in regional blood flow within the muscle itself in the supine position, changes in leg
blood flow should not limit mVO2 (Poole et al., 2008).
Due to the reduction in the primary amplitude in the supine position, the VO2 slow component
commenced from a lower absolute VO2 , and from that point, developed at a similar rate until
the attainment of VO2max (i.e. the trajectory was unchanged). Koga et al., (1999) demonstrated
an increase in the amplitude of the VO2 slow component in the supine position. This was not
the case in the present study, as a reduction in VO2max appears to have limited its development.
The VO2 slow component appears to be closely related to an additional and progressive
recruitment of type II muscle fibres (Krustrup et al., 2004). These fibres display a slower time
constant and a greater O2 cost of contraction than type I fibres (Barstow and Molé, 1991), and
lead to an increase in blood lactate production (Roston et al., 1987). Indeed, Egaña et al., (2010)
demonstrate an increase in muscle activation that began sooner and progressed more quickly in
the supine position. Furthermore, an increase in blood [lactate] has been seen in the supine
position (Leyk et al., 1994; Egaña et al., 2007); hence both of these observations support our
understanding of the VO2 slow component, and support previous observations during supine
exercise (Koga et al., 1999). However, during exercise that was performed at the same relative
121
intensity, the trajectory of the VO2 slow component was unchanged between conditions, and
blood [lactate] was lower at exhaustion. Therefore, it could be postulated that both muscle
activation and the rate of muscle fatigue were similar in each condition in the present study. The
final observation, that the overall magnitude of the VO2 slow component was significantly
reduced in the supine position, is interesting, as interventions that elicit such an effect –
including priming exercise (e.g., Jones et al., 2003; Burnley et al., 2005; Study 1), hyperoxia
(e.g., Wilkerson et al., 2006) or endurance training (e.g., Jones and Carter, 2000) – are
considered to be ergogenic. In contrast with this view, time to exhaustion in the present study
was similar between conditions despite a reduction in the VO2 slow component amplitude;
which by definition, is the change in VO2 from the end of the primary phase, until either a
steady-state is attained (<CP) or, until VO2max and/or the point of exhaustion (>CP). Therefore,
this measure is sensitive to changes in the amplitude of the primary VO2 response, and also
VO2max . Indeed, other interventions that reduce muscle O2 availability - such as hypoxia and
blood donation - reduce VO2max , which may in turn reduce the VO2 slow component amplitude
(e.g., Calbet et al., 2003; Burnley et al., 2006; Study 3). These observations add weight to the
argument that it is the trajectory (not the amplitude) of the VO2 slow component (and its
interaction with VO2max ) that plays the most important role in determining severe-intensity
exercise tolerance.
Power-duration relationship
The current study has provided the first known demonstration of the hyperbolic power-duration
relationship during supine cycling. Given the reduction in absolute work-rate in the supine
position, and that time to exhaustion was similar between conditions, a change was seen in the
power-duration relationship, specifically, CP was reduced, whilst W remained unchanged. CP
represents an important threshold of aerobic function, which corresponds with the upper limit of
steady-state exercise (Poole et al., 1988; Jones et al., 2008). The CP therefore represents a key
parameter of exercise tolerance (Burnley and Jones, 2007). During supine exercise, the
gravitational assist to leg blood flow is absent, reducing the supply of atmospheric O2 to the
working muscle, slowing the VO2 response and lowering VO2max (e.g. Koga et al., 1999), and
now for the first time – reducing CP. These observations support the overwhelming consensus
of the aerobic nature of CP. The present data suggest that W was similar between conditions.
This observation provides support for the notion that W is likely comprised of an energy source
related to substrate-level phosphorylation as it was not influenced by a reduction in O2
availability (Moritani et al., 1981). This observation could also be interpreted as the supine
122
exercise lowered the total work performed (i.e., lower work-rates performed for the same
duration), however this reduction came from the ‘aerobic compartment (i.e., work performed
below CP) rather than from a change in W.
Conclusion
This is the first known study to examine the effect of supine exercise on the VO2 kinetics,
VO2max , and the power-duration relationship during exercise performed at the same relative
exercise intensity. Supine exercise significantly ‘slowed’ the primary VO2 kinetics, with a
longer primary VO2 time constant, and the primary VO2 amplitude was reduced. As exercise
progressed, the development of the VO2 slow component (i.e., the trajectory) was similar
between conditions, suggesting a similar rate of muscle fatigue. The overall magnitude of the
slow component was reduced in the supine position, with a reduction in VO2max limiting the
scope for its development. These findings build on previous research by establishing differences
in the power-duration relationship between upright and the supine cycling. Despite a similar
time to exhaustion, the reduction in absolute power output led to a significant reduction in CP,
with no change in W during supine exercise. This study provides further evidence to support
the link between the VO2 kinetics and the power-duration relationship: both the primary VO2
time constant and CP were negatively effected in the supine position, suggesting that these
parameters may be mechanistically related. Similarly, the trajectory of the VO2 slow
component, rather than its magnitude, appears to be inherently linked to the rate of depletion of
W Indeed, in the supine position at least, exhaustion appears to coincide with the complete
depletion of W, which likely occurs shortly after the attainment of VO2max .
123
General discussion
124
Chapter 8 – General Discussion
Summary of the main themes investigated within this thesis
Burnley and Jones, (2007) hypothesised that the ‘traditional’ parameters of physiological
function – the lactate or gas exchange threshold (LT or GET, respectively), the maximal steadystate or critical power (MSS or CP, respectively), the maximal oxygen uptake ( VO2max ), and the
economy/efficiency of exercise – do not directly determine exercise tolerance (Burnley and
Jones, 2007). Rather, these parameters determine the character of, and place constraints upon,
the oxygen uptake ( VO2 ) kinetics during exercise. The VO2 kinetics then regulate rate and type
of substrate utilization, and interact with these physiological ‘thresholds (the LT or GET and the
MSS or CP) to determine the degree of metabolite accumulation, acid-base status, whether a
steady-state can be achieved in VO2 , and if not, the time taken to attain VO2max . Therefore, it
was proposed that the nature of the VO2 response plays the pivotal role in determining the
tolerable duration of exercise across the exercise intensity domains.
The present thesis has focused on exercise performed within the ‘severe-intensity domain’,
which encompasses all work-rates above CP that if performed to exhaustion, will elicit VO2max
(Monod and Scherrer, 1965; Moritani et al., 1981; Coats et al., 2003). As the hyperbolic powerduration relationship describes and also predicts the tolerable duration of severe-intensity
exercise, and as the kinetics of VO2 – and their interaction with the O2 deficit and VO2max –
appear to play a crucial physiological role in exercise tolerance, then investigating the
physiological link between these concepts has provided a more complete physiological model
(Burnley and Jones, 2007; Murgatroyd et al., 2011). A range of acute interventions were
selected to manipulate either the VO2 kinetics (Priming exercise, Blood donation, Supine
exercise), VO2max (Blood donation, Supine exercise), intramuscular [PCr] (Severe priming
exercise), or acid-base status (Sodium bicarbonate) to determine the subsequent effect on time
to exhaustion, and the parameters of the power duration relationship.
The following sections will provide a brief summary of the VO2 kinetics and the characteristics
of the power-duration relationship during severe-intensity exercise. Next, the limitations of the
methodology utilised in this thesis will be discussed, before reviewing the principal
experimental findings in light of the theoretical model of Burnley and Jones (2007).
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Summary of the oxygen uptake response to severe-intensity exercise
At the onset of high-intensity exercise (>LT), the pulmonary VO2 response increases on an
exponential time course in an attempt to match the energy demand from within the working
muscle (Whipp et al., 1982). The delay in the VO2 response during this phase (the ‘O2 deficit’;
Krough and Lindhard, 1913) is compensated for by substrate-level phosphorylation, i.e., PCr
breakdown and glycolysis, until a steady-state in VO2 is achieved (Poole et al., 1988; Jones et
al., 2008). During such exercise, the primary VO2 kinetics are supplemented by an additional
VO2 ‘slow component.’ This represents an increase O2 cost of exercise that predominantly
resides within the working muscles (Poole et al., 1991). The increased O2 cost also delays the
attainment of a steady-state during heavy exercise (<CP), and during severe exercise (>CP) sets
VO2 on a trajectory towards its maximum (i.e., VO2max ; Whipp and Wasserman, 1972; Poole et
al., 1988; Hill et al., 2002). The VO2 slow component appears to be related to the recruitment
of additional, less efficient, motor units (e.g., Poole et al., 1994; Barstow et al., 1996; Endo et
al., 2007; Vanhatalo et al., 2010), and this progressive reduction in muscle efficiency
exacerbates the production and accumulation of fatiguing metabolites that further impair muscle
function (Coats et al., 2003). Therefore, development of the VO2 slow component appears to be
central to the processes we associate with muscle fatigue during high-intensity exercise (Fitts
1994; Allen 2008; Cannon et al., 2011); once VO2max is attained, exhaustion soon occurs (Poole
et al., 1988; Coats et al., 2003). During high-intensity exercise, minimising the magnitude of the
O2 deficit and/or attenuating the development of the VO2 slow component will preserve the
finite capacity for substrate-level phosphorylation, delay the attainment of VO2max , and likely
enhance exercise tolerance (Whipp and Ward, 1992; Burnley and Jones, 2007).
Summary of the power-duration relationship
Time to exhaustion during high-intensity (>CP) exercise is accurately described as a hyperbolic
function of the external power requirement, with an asymptote ‘critical power’ (CP). The
curvature constant of this hyperbola (W) is mathematically equivalent to the amount of work
that can be performed above CP, i.e., the product of power requirement and time to exhaustion
(e.g., Monod and Scherrer, 1965; Moritani et al., 1981; Whipp et al., 1982; Jones et al., 2010).
The physiological processes that determine these parameters are, by extension, the same as
those that determine the tolerable duration of high-intensity exercise. Therefore, first
understanding the determinants of CP and W, and second, how these interact, is critical in order
to understand the principal determinants of high-intensity exercise tolerance.
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It is generally accepted that CP represents the highest work-rate at which a sustainable steadystate can be achieved in VO2 , intramuscular PCr and Pi, and arterial acid-base status (blood
[lactate] and H+). As such, CP defines the heavy- to severe-intensity domain boundary (i.e., the
MSS; Poole et al., 1988; Jones et al., 2008). These observations would suggest that CP
represents an important parameter of ‘aerobic’ function (i.e., in addition to the GET and VO2max
), and represents the highest work-rate that can be maintained without a progressively
developing ‘anaerobic’ contribution (Coats et al., 2003; Barker et al., 2006).
The physiological determinants of W are less clear; although W does appear to be related to
intramuscular high-energy phosphates, anaerobic glycolysis, and a source related to previously
stored O2 (Moritani et al., 1981; Fukuba and Whipp, 1999; Miura, 1999, Miura, 2000). This
would appear to be in agreement that the notion that W is synonymous with maximum O2
deficit (Hill and Smith, 1993) and anaerobic work capacity (Moritani et al., 1981; Hill, 1993).
Alternatively, it has been proposed that W is inherently related to the intramuscular
accumulation of ADP, Pi, H+, and the build up of K+ in the intracellular/extracellular space to
the point of exercise intolerance (Poole et al., 1988; Coats et al., 2003; Fukuba et al., 2003;
Jones et al., 2008). In contrast, it has been demonstrated that the recovery of W is somewhat
slower than that of VO2 kinetics, but faster than blood lactate, suggesting that W is consistent
with metabolite accumulation rather than the depletion of a fixed energetic store (Ferguson et
al., 2010). Either way, in power-duration parlance, W is defined through the relationship
between the imposed work-rate (>CP) and the tolerable duration of exercise, and therefore
reflects a mathematical value (expressed in kJ or a unit of distance) that, along with CP,
determines time to exhaustion during high-intensity exercise (Jones et al., 2010).
Finally, an important feature of the power-duration relationship is that its parameters (CP and
W) are derived from performance itself, rather than correlating a physiological measurement
with time to exhaustion at a given work-rate, or the time taken to complete a set amount of
work. This is pertinent as a single physiological parameter is unlikely to entirely account for CP
or W, but these parameters are reliant upon the combined bioenergetics pathways and
mechanisms of fatigue that determine exercise tolerance during high-intensity exercise.
Limitations of this thesis – methodological considerations
One of the principal aims of the current thesis was to simultaneously investigate the effect of a
range of acute interventions on the VO2 kinetics of severe-intensity exercise and determine
effects stemming from a change in exercise tolerance on the power-duration relationship. In
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order to achieve such an aim, participants involved in this research undertook between 9 and 13
separate exhaustive exercise tests in a given study. Such experimentation requires a highly
motivated individual to undertake each exercise test in the mind-set to give a maximal
performance and to obtain an accurate measure of their physiological response during each trial.
This methodology allowed for the investigation of the effect of these interventions at a range of
work-rates within the severe-intensity domain – an obvious strength of the thesis, but it was
only possible to undertake a single transition to each work-rate in each experimental condition
due to the high number of trials performed as part of each study. Given the inherent variability
of breath-by-breath gas exchange data, it is recommended that researchers average together
several like transitions before analysis in order to reduce noise and to increase statistical
confidence in the parameter estimates derived from the exponential modelling process (Lamarra
et al., 1987; Whipp and Rossiter, 2005). Therefore, it is possible that confidence in the VO2
parameter estimates may not be as strong as if repeat transitions had been performed. Indeed,
this may have accounted for the sometimes-surprising changes seen at one work-rate but not at
others; for example, the increase in the primary VO2 time constant () seen at 60%  and 100%
WRpeak, but not at 70 and 80% , in the Supine study.
Due to the number of exhaustive trials involved in these experiments it was not possible to
perform additional trials if the confidence intervals associated with the parameters of the powerduration relationship were large. As a result, confidence in the parameter estimates was
typically poor; for example, in the Priming study, parameter estimates represented ~11% of CP
and ~66% of W, thereby limiting the possibility of detecting meaningful changes in them.
Indeed, although using just two trials provides a perfect fit to the data, it cannot describe the
hyperbolic relationship between exercise time and intensity. In order to achieve this aim
additional trials must be performed, and in general, increasing the number of trials increases the
fit of the data (Housh et al., 1990; Smith and Jones, 1999; Pringle and Jones 2002; Dekerle et
al., 2006). One alternative would have been to use the ‘3-min all-out CP test’ to assess
differences in the power-duration relationship following each of these interventions (Burnley et
al., 2006; Vanhatalo et al., 2007). This methodology involves recording the decline in power
output over time during an all-out effort, thereby providing 180 data points and a potentially
more accurate fit to the data. Indeed, this test has been previously used to demonstrate changes
in the power-duration relationship following: a training intervention (Vanhatalo et al., 2008),
prior exercise (Vanhatalo et al., 2008), and induced alkalosis (Vanhatalo et al., 2010). However,
because an aim of the current studies was to also detect changes in VO2 kinetics a compromise
had to be reached, and this was to undertake four trials in each condition using the traditional
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experimental and modelling methods (Monod and Scherrer, 1965; Moritani et al., 1981; Hill,
1993; Jones et al., 2010).
On 3 occasions (out of 312 trials), a participant was able to exercise for longer at a higher power
output than they managed at a lower work rate (in the same experimental condition). This rare
scenario would have influenced the fit of the power-duration relationship data (i.e., lowering r2
values), and would likely have had an influence on the derived parameter estimates (Hill et al.,
2011). In hindsight, it may have been prudent to omit such exercise bouts, or to retest the
individual. However due to complex methodology (Blood donation), and the requirement to
compare physiological responses at each work-rate, such solutions were not undertaken. Indeed,
each exercise test was taken on face value and included in all analyses, so the physiological
responses and performance measures reported within this thesis are representative of the
complete sample group.
Summary of the main experimental observations
The following section will briefly review the main findings of each experimental chapter and
how these findings and observations fit with similar previous research. Following this, these
data will be discussed in light of the theoretical discussion of Burnley and Jones (2007).
Study 1 – Priming exercise and the power-duration relationship
Both prior heavy- and severe-intensity exercise ‘primed’ the VO2 kinetics during subsequent
high-intensity exercise. Specifically, the primary VO2 amplitude was increased (with no change
in its time course; ), and both the trajectory and amplitude of the VO2 slow component were
reduced following each priming protocol. These effects are consistent with those seen
previously (e.g., Jones et al., 2003; Burnley et al., 2005; Carter et al., 2005; Bailey et al., 2009;
Miura et al., 2009).
Priming exercise performed exclusively within the heavy-intensity domain significantly
increased time to exhaustion and the amount of work that can be performed above CP.
Therefore, for the first time, the improvement in performance following heavy priming was
shown to be a consequence of an increase in W, supporting the trend observed by Jones et al.
(2003). These observations are important as they demonstrate that the VO2 kinetics and W are
both sensitive to an increase in oxidative energy turnover as a result of increased muscle fibre
recruitment following priming exercise (Burnley et al. 2005).
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Prior severe exercise followed by 10 min recovery had no effect on exercise tolerance or the
parameters of the power-duration relationship, despite evidence of primed VO2 kinetics.
Previously, Ferguson et al. (2007) used the same severe priming bout but with 2 min recovery
and demonstrated a reduction in W. Allowing a longer recovery period in the present study
appears to have allowed sufficient time for the recovery of muscle homeostasis (i.e., PCr
content and H+), such that exercise tolerance and the power-duration relationship were
unaltered. It has been shown previously that prior severe-intensity exercise (at 70% ) with an
extended recovery (20 min) facilitated a 30% increase in time to exhaustion during subsequent
exercise performed at 80%  (Bailey et al., 2009). These observations suggest that if the
recovery duration had been longer in the present study an improvement in exercise tolerance
would have been likely – and an alteration in the power-duration may have been observed. It
could be speculated that this may have increased W, as seen with heavy priming.
Study 2 – Sodium bicarbonate ingestion and the power-duration relationship
Sodium bicarbonate ingestion 1 h before exercise did not alter the VO2 kinetics or VO2max
during subsequent high-intensity exercise. This is in contrast to the reduction in the VO2 slow
component seen previously (Kolkhorst et al., 2004; Berger et al., 2006). Alkalosis did not alter
the VCO2 kinetics, but an increase in CO2 production at 2 min, and VCO2max and blood [lactate]
at exhaustion, was observed. No overall difference in exercise tolerance was seen between
conditions. However, a small increase in performance was seen at the highest work-rates, and a
small decrease in time to exhaustion at the lower work-rates; therefore, alkalosis ‘reshaped’ the
power-duration relationship, with CP being reduced and W increased following sodium
bicarbonate ingestion. This change in the power-duration relationship suggests a possible shift
in the substrate utilization ‘mix’: these data support the notion that capacity for glycolysis was
increased with alkalosis, as this energy source contributes to W (Moritani et al., 1981; Gaesser
et al., 1995). These observations are in contrast with some recent work that demonstrated no
change in exercise tolerance or the power-duration relationship following alkalosis during the
‘3-min all-out’ CP test (Vanhatalo et al., 2010).
Study 3 – Blood donation and the power-duration relationship
Blood donation significantly reduced [Hb] and by extension, the O2 carrying capacity of the
blood (Balke et al., 1954; Panebianco et al., 1995). This reduction in [Hb] had no effect on the
primary VO2 time course (i.e., the ), but did reduce the amplitude of the response. In addition,
the trajectory of the VO2 slow component was similar between conditions, whilst the amplitude
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was reduced. The reduction in amplitude was presumably limited in its development by a
significant reduction in VO2max , with the latter likely causing a reduction in exercise tolerance
following blood donation (Ekblom et al., 1972; Ekblom et al., 1976; Krustrup et al., 1984;
Burnley et al., 2006). For the first known time, a reduction in CP was observed following blood
donation. This demonstrates that both CP and VO2max are influenced by a reduction in muscle
O2 availability, and further confirms the ‘aerobic’ nature of these parameters. Indeed, the
reduction in VO2max and exercise tolerance are the polar opposite of that seen following the
reinfusion of erythrocytes (Ekblom et al., 1972; Ekblom et al., 1976; Spriet et al., 1986), or
following RhEPO administration (Connes et al., 2003; Wilkerson et al., 2005), and therefore
demonstrate the important role of [Hb] on the kinetics of VO2 and exercise tolerance.
Study 4 – Supine exercise and the power-duration relationship
During supine exercise performed at the same relative (to a posture specific incremental test)
exercise intensity, the gravitational assist to leg blood flow was absent. This led to a reduction
in the primary VO2 amplitude and reduced its time constant (). The former observation is
likely a result of the reduction in absolute work rate (e.g., Wilkerson et al., 2004), while the
latter is possibly a result of the reduction in muscle O2 availability as a result of the change in
body position (Hughson et al., 1991; Koga et al., 1999). Despite the reduction in O2 available to
the mitochondria, the trajectory of the VO2 slow component was similar between conditions;
however, the amplitude was reduced, and limited in its development by a reduction in VO2max .
This reduction in VO2max is seen consistently, irrespective of whether relative or absolute
intensity work-rates are used, and typically causes a reduction in exercise tolerance (Astrand
and Saltin, 1961; Koga et al., 1999; Egaña et al., 2007; Egaña et al., 2010). Due to the reduction
in absolute work-rate in the supine position – despite no difference in time to exhaustion
between conditions – the amount of work performed in the supine position was less than in the
upright position. This change in work capacity altered the power-duration relationship, with CP
being reduced, and W” unaffected. Again, as with blood donation, both CP and VO2max are
sensitive to changes in O2 availability to the working muscle.
Main research findings
Within the current thesis a vast amount of experimental data has been collected – from breathby-breath VO2 measurements, to a host of blood parameters, heart rate kinetics, and on to
measures of exercise tolerance. The experimental findings of each study have been highlighted
131
individually, and the following section(s) will provide a more broad discussion of the integration
of the determinants of severe-intensity exercise tolerance.
The ‘typical’ VO2 kinetic profile was observed in each participant during each trial. Similarly,
the hyperbolic power-duration relationship remained evident, regardless of experimental
condition. This demonstrates the robustness of these models and their collective importance in
describing the physiological response to high-intensity exercise. While direct measures of W
were not possible in this work, the observation that the VO2 slow component developed to attain
VO2max at exhaustion would also suggest that W was either depleted or accumulated (Jones et
al., 2008) at the point of exhaustion. These collective observations provide strong support for the
theoretical discussion of Burnley and Jones (2007).
Determinants of the capacity to perform exercise above CP
A.V. Hill first described the relationship between the intensity of exercise and its tolerable
duration during running and swimming events almost a century ago (Hill, 1923). In the last halfcentury, scientists have developed a range of mathematical models to describe the ‘powerduration’ relationship (Monod and Scherrer, 1965; Moritani et al., 1981). The beauty of these
model is that they uses performance itself to define two parameters that have physiological
significance, and each appears central to determining the capacity to perform high-intensity
exercise (Whipp et al., 1982; Poole et al., 1988; Jones et al., 2008). The highest work-rate at
which an individual can attain a steady-state in VO2 , intramuscular high-energy phosphates, and
acid-base status is defined by the ‘aerobic’ parameter, critical power (CP). The capacity to
perform exercise above CP is determined by the curvature constant, that is, W (Whipp et al.,
1982; Fukuba et al., 1999). Traditionally, W has been described as a fixed ‘anaerobic energy
reserve’ (expressed a unit of work; kJ) that primarily consists of intramuscular PCr stores,
anaerobic glycolysis (leading to the production of lactate and H+), and previously stored O2
(Moritani et al., 1981). Recently, however, this view has been challenged and has fuelled the
question: what is the W?
For exercise performed above CP, the VO2 slow component develops over time until the
attainment of VO2max , and therefore represents a continually increasing metabolic rate and/or a
progressive decline in muscle efficiency (Poole et al., 1988; Özyener et al., 2001). Given the
close symmetry between the VO2 response and the decline in muscle PCr stores at exercise
onset, and progressively during non-steady state exercise (i.e., >CP; Rossiter et al., 2001;
Rossiter et al., 2002), the evidence suggests that these two physiological processes are
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inherently linked. Therefore, the VO2 slow component appears to set the rate of PCr utilization,
and by extension, determines the concomitant accumulation of metabolites (i.e., ADP, P i and
H+) and decline in pH seen during severe-intensity exercise (Jones et al., 2008). Indeed, during
exhaustive constant work-rate exercise, given enough time, VO2 will attain VO2max , PCr and pH
will decline to some low limiting value, and the accumulation of metabolites associated with the
fatigue process will become unbearable (Poole et al. 1988; Jones et al., 2008).
Burnley and Jones, (2007) used these observations to suggest that manipulating VO2 kinetics,
VO2max , or the capacity for substrate-level phosphorylation would have a predictable effect on
severe-intensity exercise tolerance, and that this would be demonstrated in a change in the
power-duration relationship. The current thesis was designed to test this hypothesis; its
experiments have demonstrated that manipulating the primary VO2 kinetics (increased
amplitude; Priming exercise and longer ; Supine exercise) predictably altered the magnitude of
the O2 deficit at exercise onset. Also, they have shown that both CP and VO2max are sensitive to a
reduction in muscle O2 availability (Blood donation and Supine exercise).
The next point to consider is the role of the VO2 slow component that is set on a ‘trajectory’
towards VO2max . The absolute amplitude of the VO2 slow component is calculated as the
difference between primary VO2 amplitude and VO2max (Whipp and Rossiter, 2005). Given that
the amplitude of the slow component is determined by the imposed work-rate (above CP) and
VO2max , interventions that reduce VO2max also reduce the amplitude (such as Blood donation and
Supine exercise). The reduction in amplitude seen following these interventions suggests an
ergogenic effect – such as after heavy-intensity priming exercise (e.g., Jones et al., 2003; Burley
et al., 2005; Priming exercise), following hyperoxia (Vanhatalo et al., 2010), or training
interventions (e.g., Carter et al., 2000; Jones and Carter, 2000) – however this is not the case.
Therefore, it could be argued that it is the trajectory, rather than the amplitude, of the VO2 slow
component that best demonstrates the progression of muscle fatigue, and may be most strongly
correlated with W (Murgatroyd et al., 2011).
Whichever mechanism, or combination of mechanisms, is ultimately responsible for the
cessation of exercise is unclear. Therefore, trying to attribute W to one particular mechanism
may be incorrect, and in fact, the principal determinants of W may differ in response to the
prevailing metabolic scenario. Indeed, the development of each of these ‘fatigue mechanisms’ to
the point of exhaustion could be expressed as W – mathematically, it simply represents the
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capacity to perform work above CP – irrespective of the limiting mechanism (Moritani et al.,
1981).
Future directions
Prior to the current thesis there was a plethora of research evidence reporting differences in the
VO2 response between a control or placebo condition against some ‘intervention.’ There was
also a fair amount describing a change in the power-duration in response to a range of
experimental conditions. However, there was little evidence describing the interaction of the
VO2 kinetics and the power-duration relationship. This was surprising, as each of these
‘models’ can be used independently to describe, and even predict, the tolerable duration of highintensity exercise. Through reviewing the vast body of literature it became clear that the VO2
kinetics appear to play a pivotal role in exercise tolerance above CP; the development of the
VO2 slow component determines the rate of depletion/accumulation of W - or ‘the capacity to
perform work above CP’ – and this theoretical relationship was first described by Burnley and
Jones, (2007).
The current thesis has provided experimental data in support of these observations and has
demonstrated that predictable effects on the power-duration relationship are caused by
manipulating the VO2 kinetics, VO2max , the capacity for substrate-level phosphorylation, or the
ability a tolerate a change in acid-base status. This work, and that of others, has furthered our
understanding of this complex relationship, but there is still much work to be done. The
physiological origin of CP is well known, and this thesis has shown that limiting muscle O 2
availability (through blood donation and supine exercise) reduces CP. For completeness,
confirming whether similar effects occur with hypoxia (and also whether the opposite is true
with hyperoxia), or with the reinfusion of whole blood or the administration RhEPO, would be
useful.
The principal aim of subsequent research in this area should be to attempt to separate the likely
principal mechanisms of fatigue, those being: the developing VO2 slow component and its
interaction with VO2max ; depletion of high-energy phosphates and metabolite accumulation; and
changes in the acid-base status. It has been demonstrated within this work that induced alkalosis
(through sodium bicarbonate ingestion) can enhance performance at the highest work-rates
within the severe-intensity domain (i.e., close to VO2max ), but hinders performance during
exercise performed just above CP. Further manipulation of the acid-base, such as artificially
inducing acidosis (through the infusion of lactate/adrenaline), may help to separate the role of
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the acid-base status from the fall in PCr and the development of VO2 . Investigating the role of
substrate-level phosphorylation, through glycogen depletion and creatine supplementation
studies, or using iodoacetic acid to block PCr resynthesis, may also help to confirm the
metabolic origins of W. In terms of methodology, using traditional power-duration modelling
procedures would make most sense as it enables characterisation of the VO2 kinetics, and if this
was undertaken alongside 31P-MRS measurements, we may gain an important insight into the
complex determinants of severe-intensity exercise tolerance.
Conclusions
The tolerable duration of high-intensity exercise is directly related to the intensity of the
imposed exercise task. When the work rate is high, exercise time is short, and with a reduction
in exercise intensity an increase in time to exhaustion is observed. These observations are
grounded in the mathematical ‘power-duration relationship’ that both describes and predicts
exercise tolerance in the humans, irrespective of exercise modality, and also right across the
animal kingdom. Given the importance of this relationship it is no surprise that scientists have
tried to understand its physiological origin for well over a centaury (e.g., Hill, 1923; Monod and
Scherrer, 1965; Moritani et al., 1981; Poole et al., 1988; Jones et al., 2010). Two parameters
can be derived from modelling this relationship, firstly, the critical power (CP; i.e., the
boundary between the heavy- and severe-exercise intensity domains), is the highest work rate at
which a metabolic steady-state can be attained. Secondly, the curvature constant (W) represents
an amount of energy (expressed in kJ) to perform work above CP, and is likely is related to the
capacity for substrate-level phosphorylation and/or the accumulation of fatigue related
metabolites (Jones et al., 2008).
Burnley and Jones (2007) hypothesised that during exercise performed above CP, the kinetics of
VO2 interact with VO2max and W to determine the tolerable duration of severe-intensity
exercise. This thesis was designed to experimentally test these hypotheses through the
manipulation of the VO2 kinetics, VO2max or W. Study 1 showed clearly that it is possible to
manipulate the VO2 kinetics (increasing the primary amplitude, and reducing the trajectory of
the slow component) through the implementation to high-intensity ‘priming exercise’. When the
priming bout was performed in the ‘heavy’ domain, an increase in exercise tolerance was
observed, as a result of an increase in W. Whilst following 10 min of recovery, ‘severe’
priming did not alter performance despite primed VO2 kinetics and the parameters of the
power-duration relationship remained unchanged. It could be argued that in this condition, W
would have been depleted to some extent by the priming bout and was not fully replenished
135
within 10 min, if the recovery period was extended, then an increase in exercise tolerance may
be likely. Study 2 investigated the importance of the acid-base status during exhaustive exercise,
and demonstrated that despite a likely state of induced alkalosis, exercise tolerance was
unchanged, as were the VO2 kinetics and VO2max , but a shift in the power-duration relationship
was observed. Specifically, CP was reduced and W was increased – suggesting a change in the
energy production pathways. Studies 3 and 4 were designed to investigate the effect of
reduction in muscle O2 availability, through supine exercise and blood donation, respectively.
Supine exercise reduced exercise capacity through a slowing of the time constant and reducing
the amplitude of the primary, a reduction in the amplitude (but not trajectory) of the slow
component due to a similar reduction in VO2max . Similarly, blood donation reduced the
amplitude of the primary and slow components (but not the trajectory of the latter), VO2max , and
exercise tolerance. A consistent feature of both these studies is that CP was reduced and no
change was seen in W - which was likely a result of the similar reduction in the primary
amplitude and VO2max .
In agreement with Burnley and Jones (2007), it is apparent that the work rate associated with CP
and the magnitude of the VO2max are critical to exercise tolerance. CP determines the point at
which the slow component begins to develop as a function of both the imposed power output
and time, i.e., it projects towards VO2max , despite exercise being performed at a constant work
rate. Then, VO2max is important as it sets the limit for the development of the slow component,
which once attained, signals the point of imminent exhaustion. A reduction in the amplitude of
the slow component has often been considered to represent an ergogenic effect, with the
opposite being true when a large slow component is observed. However, an important
consideration is that a given intervention may alter the amplitude of the slow component, but
this does not prove a cause and effect relationship, as the position of CP and VO2max determine
the start and end point for the development of the slow component. This these provides some
compelling evidence that in fact it is the trajectory of the slow component that best indicates a
change in muscle metabolism and an ergogenic/ergolytic effect of a given intervention. Indeed,
the observation that time to exhaustion is less the greater the imposed power output, and that the
slow component projects more steeply towards VO2max with increasing work rates supports this
view. Indeed, it is likely that the development (i.e., the trajectory, not the amplitude) of the slow
component is the key factor that determines the rate of depletion/accumulation of W over time and with the attainment of VO2max , exercise intolerance occurs soon thereafter.
136
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