How slimy can scientists be? Read it and weep.

from photonics.com: 02/28/2010
http://www.photonics.com/Article.aspx?AID=41268

The struggle to keep research real

Hank Hogan, Contributing Editor,

Beneath a scientist’s lab coat beats a human heart. So it should be no
surprise that researchers sometimes fudge – or outright fake – their
data.

Often, this manipulation takes the form of a doctored image. Michael
Kalichman, director of the research ethics program at the University
of California, San Diego, recalls reading neuropathology papers as
part of the peer review process prior to publication. Sometimes he’d
find the same image appearing twice in the same submission. The second
time it might be rotated or at a different magnification. In the
paper, though, it would be presented as completely different from the
first image.

“At the very least, somebody was sloppy in their record keeping,”
Kalichman said. “At the very most, somebody was trying to mislead
about what they had actually done.”

While the fraud may appear minimal, the National Institutes of Health
(NIH) in Bethesda, Md., and universities and other organizations take
the problem seriously. To combat it, they give tutorials to
researchers and put systems in place. There also are enforcement arms
that actively investigate allegations.

Fraud figures

The amount of scientific misconduct that goes on is hard to pin down,
Kalichman said. There are well-known examples where a researcher has
been shown to have committed fraud, such as the fake cloning claims of
South Korean scientist Hwang Woo-suk. Based on the number of cases
like this that have been publicly discovered and adjudicated, the rate
of serious research misconduct could be one in 100,000 scientists.

However, the amount of misconduct could be much higher than this low
figure indicates. An analysis of data from several surveys that
appeared in PLoS One in May 2009 found that 1.97 percent of scientists
admitted to serious misconduct, and more than 14 percent had witnessed
it in others.

The paper’s author, Daniele Fanelli, is a research fellow at the
University of Edinburgh in the UK. He noted that the first figure is
probably an underestimate, since not all researchers will report their
own misconduct.

There are good reasons to believe the second figure is an
overestimate, he said. “Most surveys did not control for the
possibility that several respondents are thinking of the same
colleague.”

In one survey, however, only one researcher per department was asked
about misconduct in that department. In that case, the figure was 5.25
percent, Fanelli said.

It must be remembered, however, that what is thought by others to be
lab fraud or misconduct may not, in fact, be so. The Office of
Research Integrity (ORI), which is part of the US Department of Health
and Human Services, oversees and directs research integrity activities
for the US government public health services.

In 2007, the ORI closed 28 cases, with 10 resulting in research
misconduct findings, administrative actions or both. That ratio was in
line with the historical average and shows that most of the
allegations were not true or could not be proved.

Using technology

By some estimates, up to 20 percent of all images submitted for
publication have been improperly manipulated. This figure is open to
debate, in part because the definition of what kind of manipulation is
allowable varies from journal to journal.

In general, it’s considered appropriate to make an adjustment if it’s
done to all pixels and is disclosed. An example might be the use of
false color to make the differences in a gray-scale image more easily
visible.

There are limits to this general principle, however. Adjusting the
brightness and contrast of a gel blot image, for example, would treat
all pixels equally. However, it could result in the gray background
and faint blots disappearing. Paper reviewers and journal editors must
guard against this, which can be hard to detect and which can arise
from innocent intentions.

The original gel blot image on the right had some data removed when
submitted for publication, as can be seen by comparing the two panels
in the area highlighted by the circle. Such manipulation can be
innocent, but it could also be a deliberate attempt to deceive.
Attempts to deceive, on the other hand, often involve adding or
subtracting pixels. That selective treatment makes it possible to
catch the alterations automatically.

“The algorithms that you can develop are ones that target specific
forms of manipulation,” explained Hany Farid, a professor of computer
science at Dartmouth College in Hanover, N.H., and an expert on
digital image forensics.

Farid demonstrated some years ago that image segmentation techniques
based on intensity can be employed to detect deletion, duplication and
removal of small blemishes. A tampered image that is processed through
these segmentation algorithms will yield an output with visible
indicators, such as solid boxes where data has been duplicated or
removed. Software can then look for and find these regions.

Farid noted that the tools to automate the process do not yet exist,
but he foresees a time when they will. He also noted that the
algorithms will never be able to catch all possible fraudulent image
manipulation.

Employing other tools

For that reason, policies must be put in place to guard against fraud.
Farid, for example, advocates having researchers submit the original
images along with those that will appear in a paper.

Another example of a policy solution can be found in the ethics
training done at NIH. This has been regularly held for all of the
agency’s own researchers for the past 10 years, said Joan P. Schwartz,
the agency’s intramural research integrity officer and assistant
director of the office of intramural research.

One part of this training is the use of hypothetical cases, which
change from year to year. The theme for this past year was dual-use
research – work that could be used to help as well as harm. A few
years ago, the training involved image manipulation, which offers the
potential to be both good and bad.

In all instances, the goal of these scenarios is to get everyone in a
department talking, Schwartz said. “We purposely make the cases a
little bit gray so that they generate discussion. They don’t
necessarily have a right or wrong answer.”

In addition to the hypothetical cases, she noted that the agency has
an online course that’s intended to get new employees up to speed with
NIH research guidelines. It has been adopted by many universities and
research organizations around the world.

Despite these efforts, Schwartz noted that the rate of misconduct
appears to be holding steady. Thus, training alone is not the complete
answer.

Another knob to turn

The solution may involve a change in the structure of science, said
Raymond De Vries, a professor of bioethics at the University of
Michigan Medical School in Ann Arbor. Together with colleagues Brian
Martinson and Melissa Anderson, he has surveyed researchers to see how
many self-report minor and major scientific misconduct. The second
category includes such breaches as falsification, fabrication and
plagiarism. The group also has collected scientists’ opinions about
the fairness of the science system and about researchers’ experience
with competitive pressure.

The team’s results show that minor and major misconduct are linked.
Those admitting to the former are far more likely to report committing
the latter. More competitive, rather than cooperative, views on
research also led to more admissions of misconduct.

Another factor is the amount of perceived organizational injustice.
The rewards of science are promotions, tenure, grant money, prestige
and so on. These may not be distributed fairly, and scientists who
report injustice in their workplace also report higher levels of
misconduct. Thus, improving organizational justice – or at least how
it’s perceived – may increase research integrity and decrease lab
fraud.

Summing up the findings, De Vries said of scientists, “If they feel
like they’re being treated fairly, they actually report less
misconduct.”