Definition of research misconducts
"Research Misconduct" means fabrication, falsification,
plagiarism, or other practices that seriously deviate from
those that are commonly accepted within the scholarly
community for proposing, conducting, publishing or
otherwise reporting research. It does not include honest
error or honest differences in interpretations or judgments
of data.
http://www.ncsu.edu/sparcs/policy/references/interim.html
The most prevalent problem
Experiments
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Sloppy experimentation
and misrepresentation of
data
Data acquisition (data
selection or questionable
statistics)
Improperly handling
image data
Data acquisition
Data analysis
Data presentation
Guidelines for image manipulation (J. Cell Biol.)

No specific feature within an image may be enhanced, obscured,
moved, removed, or introduced.
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Adjustments of brightness, contrast, or color balance are acceptable
if they are applied to the whole image and as long as they do not
obscure or eliminate any information present in the original.
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Nonlinear adjustments (e.g., changes to gamma settings) must be
disclosed.
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The grouping of images from different parts of the same gel, or from
different gels, fields, or exposures must be made explicit by the
arrangement of the figure (e.g., using dividing lines) and in the text
of the figure legend.
(http://www.jcb.org/misc/ifora.shtml#digim)
Not
recommended
(pixel number
changed)
Do not use
nonlinear adjustments
Make sure the "Resample Image" box in "Image Size" dialog window is not
checked and the "Width", "Height", and "Resolution" boxes should be linked by the
graphic chain. (JCB)
linked
Do not check this box
Resampling refers to changing the “pixel dimensions” (and
therefore display size) of an image. When you downsample
(decrease the number of pixels), information is deleted from
the image. When you resample up (increase the number of
pixels), new pixels are added.
Downsampled (decrease the number of pixels)
Original
Resampled up (increase the number of
pixels)
Pitfalls in image acquisition from microscope
• Sample preparation
fixation, permeabilization
mountant, sealant
• Objectives (NA, reflective index of immersion medium)
• Fluorochromes and filters
• Chromatic aberration
• Spherical aberration
• Acquisition settings
• Quantitations
North, A. J. (2006) Seeing is believing? A beginners’ guide to practical
pitfalls in image acquisition. JCB 172: 9-18.
Guidelines for digital images (Nat. Cell
Biol.)

Authors should list all image acquisition tools and image software
packages used.

Authors should document key image-gathering settings and
processing manipulations in the Supplementary information.

Images gathered at different times or from different locations should
not be combined into a single image, unless it is stated that the
resultant image is a product of time-averaged data or time-lapse
sequence. If juxtaposing images is essential, the borders should be
clearly demarcated in the figure and described in the legend.
Guidelines for digital images (Nat. Cell Biol.)

The use of touch-up tools, such as cloning and healing tools in
Photoshop, or any feature that deliberately obscures manipulation,
is to be avoided.

Processing (such as changing brightness and contrast) is
appropriate only when applied equally across the entire image and
when it is applied equally to controls. Contrast should not be
adjusted so that data disappear.

When submitting revised final figures upon conditional acceptance,
authors may be asked to submit original, unprocessed images.
(http://www.nature.com/ncb/about/ed_policies/index.html#i
mages)
Guidelines for gels and blots (NCB)

Vertically sliced gels that juxtapose lanes that were not contiguous in
the experiment must have a clear separation or a black line delineating
the boundary between the gels.

Cropped gels in the paper must retain important bands.

Cropped blots in the body of the paper should retain at least six band
widths above and below the band.

High-contrast gels and blots are discouraged. Multiple exposures
should be presented in supplementary information if high contrast is
unavoidable. Immunoblots should be surrounded by a black line to
indicate the borders of the blot, if the background is faint.

For quantitative comparison, appropriate reagents, controls and
Guidelines for microscopy images
(NCB)

Cells from multiple fields should not be juxtaposed in a single field;
instead multiple supporting fields of cells should be shown as
supplementary information.

Adjustments should be applied to the entire image. Threshold
manipulation, expansion or contraction of single ranges and the
altering of high signals should be avoided.

Pseudo-coloring and nonlinear adjustment (e.g., gamma changes)
are only allowed if unavoidable and must be disclosed.

Adjustments of individual color channels are sometimes necessary
on “merged” images, but this should be noted in the figure legend.
Note: Any manipulation that violates these
guidelines is a misrepresentation of the original
data and is a form of misconduct (JCB 166: 1115, 2004).
Tips from “Digital Imaging: Ethics”
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Digital images that will be compared should be acquired under identical
conditions.
Intensity measurements of digital images should be performed on raw
data and the data should be calibrated to a known standard.
Manipulation of digital image should always be done with a copy of the
raw image data.
Sample adjustment to the entire image or cropping an image is usually
acceptable.
Manipulations that are specific to one area of an image and are not
performed on other areas are questionable.
Use of software “filters’ to improve image quality is usually not
recommended
Cloning objects into an image, or from other parts of an image, is very
questionable.
Avoid the use of lousy compression (JPEG file: may lead to change
resolution of image and intensity value of any given pixel.)
Tips from “Digital Imaging: Ethics”
(cont)

Be careful when changing the size (in pixels) of a digital image.
Decreasing the image size can cause the XY resolution in an image
to be reduced. If the size reduction is not by a power of two, the
software program has to be creative in determining the intensity
values of each pixel (guessing). Increasing image size causes the
software to interpolate (guessing) to create pixels in between the
existing pixels, which does not increase resolution. In fact, it may
make it more difficult to resolve features because of aliasing
artifacts.
http://micro.magnet.fsu.edu/primer/java/digitalimaging/processing/jpegcom
pression/
Examples of improper image manipulations
(JCB: 166 11-15, 2004)
(JCB 166: 11-15, 2004)
Adjustment the intensity of
a single band.
O
X
Improper adjustment of
contrast
(JCB 166: 11-15, 2004)
(JCB 166: 11-15, 2004)
Manipulated images (left)- cut individual band and paste
it to a new image -revealed by contrast adjustment
(right)
NCB 5: 320-329, 2003/Corrigendum in NCB 6: 373, 2004
(JCB 166: 11-15, 2004)
Enhancing a specific feature – the immunogold particles.
Acceptable ways to highlight a feature such as immunogold particle:
1. Add arrows
2. Pseudocoloring particles without altering the brightness of individual
pixels (e.g., colorize function of Photoshop) : should be disclosed in the
figure legend.
Misrepresentation of a microscope field-combine images from
separate microscope fields into a single field.
(JCB 166: 11-15, 2004)
JCB 176: 131-132, 2007
Detecting image manipulation in the Hwang et al. stem cell paper.
The image in the top row purports to show negative staining for a
particular cell surface marker in four different cell lines.
Adjustment of tonal range in Photoshop clearly shows that the two
middle images are identical (lower panel).
Cell 123: 833-847, 2005/Erratum in Cell 124: 645, 2006
Image checking system:
Used by JCB, JEM, JGP (Rockefeller University Press)
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All digital images in manuscript accepted for publication will be
scrutinized by our production department for any indication of
improper manipulation.
Questions raised by the production department will be referred to
the editors, who will request the original data from the authors for
comparison to the prepared figures. If the original data cannot be
produced, the acceptance of the manuscript may be revolved.
Cases of deliberate misrepresentation of data will result in
revocation of acceptance, and will be reported to the corresponding
author’s home institution or funding agency.
(http://www.jcb.org/misc/ifora.shtml#digim)
Data acquisition
Garbage in = Garbage out
Sample selection
Unbiased, representative (patients, cells from a population)
Define the question. => What information are needed?
• Human tissue samples (well defined clinical manifestation; pathology; pedigree)
• Tumor vs. surrounding (normal) tissues
Question => required information => collection of relevant data
Data selection
It is easy to see the results you expect, and ignore the rest.
Don’t fool yourself ! The unexpected, unfit data may be meaningful.
孫老師的血壓 ＝> 決定是否可以吃大餐？
Mendel’s peas?
300/150, 145/103, 138/97, 125/85, 60/60
Which data point do you choose?
Selecting or discarding certain data should have explicit rationale.
Best to describe the rationale clearly.
Double-blind test
Presenting ALL information could be meaningful !
Inverse PCR from an Olfactory Receptor (OR) gene,
to look for association with an H enhancer element
Expected result
2.3kb (expected size)
DNA sequence => M71-H
Unexpected results.
1 kb (localized to chr. 13)
Not associated with any other OR
OR regulated by another trans element?
Lomvardas et al.
(2006) Cell 126:
403-13.
Not specific to olfactory tissue.
Common to nose and spleen?
Ubiquitous regulation? Chrosomsomal association?
Describe and discuss the criteria for data acquisition
and analysis
Colocalization of the H Enhancer with OR Promoters
(identified by Anti-M50)
Define colocalization as 25% overlap of
pixels from the H and OR signals on
sections from a Z series
DNA FISH
M50/M71/OMP: DIG; FITC-conjugated anti-DIG
antibody (green).
H: biotin; rhodamine-conjugated neutravidin (red)
Anti-M50/M71 (blue)
The inability to detect colocalization of H
with OR genes in all cells is likely due to
our inability to retain these
interchromosomal interactions
stoichiometrically throughout the fixation
and denaturation procedures.
Lomvardas et al. (2006) Cell 126: 403-13.
Are these images representative (typical)?
Describe the phenotypic
range and distribution
Yao & Sun (2005) EMBO J. 24: 260212.
Sample size
Keep clear lab notes
•
•
•
•
•
Organize your thoughts
Historical records
Helps you to remember
Allows other people to replicate your experiment
Defense against fraud
Belongs to the lab.
Content:
• Date (bound note book, not loose leaf; numbered pages)
• Title of the experiment
• Brief statement of purpose
• Description of the experiment
• Summary (interpretation) of the results
Record everything as soon as you can.
Ref: At the Bench: A Laboratory Navigator. Chapter 5, Laboratory Notebooks.
CSHL Press
Always preserve raw data
Microscopy Society of America on ethical digital image processing (as published in
Microscopy Today Nov/Dec 2003, p61):
Ethical digital imaging requires that the original uncompressed image file be stored
on archival media (e.g., CD-R) without any image manipulation or processing
operation. All parameters of the production and acquisition of this file, as well as any
subsequent processing steps, must be documented and reported to ensure
reproducibility.
Generally, acceptable (non-reportable) imaging operations include gamma
correction, histogram stretching, and brightness and contrast adjustments. All other
operations (such as Unsharp-masking, Gaussian blur, etc.) must be directly
identified by the author as part of the experimental methodology. However, for
diffraction data or any other image data that is used for subsequent quantification, all
imaging operations must be reported.
Reproducibility
A reliable result should be reproducible (by you and by others).
Single case:
A single event (patient, comet), but multiple observations.
A single observation: not reliable.
Extraordinary claims demand extraordinary proof.
Responsibility of the scientist
You may be pushed to obtain certain results. In many cases of fraud,
the perpetrator has blamed the PI, saying that the PI expected a
particular result, and the researcher felt compelled to produce it. It is
true that a PI may want a result. But your data are your responsibility,
and it is up to you to be sure the data are recorded honestly and
accurately.
Ref: At the Bench: A Laboratory Navigator. Chapter 5, Laboratory Notebooks.
CSHL Press
Responsibility of PI
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Check all primary data? (may be difficult)

Pay attention to details. Do not look only at final assembled figures.

Establish lab culture, attitude for proper ethics
Responsibility of the coauthors

Authorship should be justified

Each coauthor should write down his/her specific contribution.
Plagiarism

The action to pass off someone else’s work as your own

Self-plagiarism: ranging from duplicate publication to “salamislicing”, where authors add small amounts of new data to a previous
paper (e.g., The previous paper analyzed 15 patient samples and
the new one adds 15 more).
General rules to avoid plagiarism

The article cannot contain a large chunk of material (e.g., a whole
paragraph) that has been published previously by others–
including Introduction, Materials and Methods... etc.

If reuse of substantial part of your own work is necessary, clear
citation of the previous publication is required.
Warning: a number of publishers are planning to set up
“plagiarism detection software” to tackle this problem. (Nature
435: 258-259, 2005)
Dealing with fraud

Prevention is better than treatment.
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Catch it within the lab.
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Whistle-blowing.
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Do not treat it lightly. A single case may destroy your career.

Credibility is key in science.
Investigation; internal and external
http://www.ncsu.edu/sparcs/policy/references/interim.html
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Damage control.
 Admission
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to wrong-doing.
Honesty is the best principle.
(http://www.indiana.edu/~poynter/)
Additional Info Sources:
Responsible Conducts in Research
UC, San Diego
http://ethics.ucsd.edu/resources/resources-topics.html
Online Research Ethics Course
http://ori.hhs.gov/education/products/montana_round1/research_ethics.html
Office of Research Integrity
http://ori.dhhs.gov/
Progress of science is built on trust.
Jean Shepherd, “In God We Trust, All Others Bring Data.”