Archive for the 'General Science' Category

Jul 27 2015

Artificially Selected Organisms

Published by under General Science

A new petition to Whitehouse.gov demands mandatory labeling for all “artificially selected organisms.” The petition says:

ASO plants or animals have had their genetic makeup altered to exhibit traits that are not naturally theirs. Artificial selection (or selective breeding) involves the selection of traits that are beneficial to humans, not what helps the organism survive in nature.

And concludes:

80% of Americans support mandatory labels on food containing DNA.

That last bit is true. A survey performed by Oklahoma State University Department of Agricultural Economics found that 80.44% of Americans supported “mandatory labels on foods containing DNA.” That puts into perspective public support for mandatory labels on genetically modified organisms (GMOs).

The petition is obviously satire, and I think it represents the perfect use of satire – putting into sharp relief the illogic of a specific position or claim. This is a fight that happens almost every time a GMO supporter argues with a GMO critic. It goes something like this:

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Jul 06 2015

The New Seralini Study

Published by under General Science

Seralini, author of the infamous study alleging to show increased rates of tumors in rats fed GM food, the one that was retracted by the journal and then later republished in a separate journal, has published another controversial study.

The study, published in PLOSone, looks at the feed that is fed to lab rodents, the kinds used in GM research. They found:

All diets were contaminated with pesticides (1-6 out of 262 measured), heavy metals (2-3 out of 4, mostly lead and cadmium), PCDD/Fs (1-13 out of 17) and PCBs (5-15 out of 18). Out of 22 GMOs tested for, Roundup-tolerant GMOs were the most frequently detected, constituting up to 48% of the diet.

The implication is that all prior research looking at GMO and pesticide toxicity is now called into question because the control rodents would also have been fed a diet that contains some GMO, pesticides, and also heavy metal contaminants. The concept here is valid – control groups need to be proper controls. If you are testing the effects of a pesticide on rats, and the control rats are also getting the pesticide in their food, then the comparison is compromised. This would dilute out the effects of the test substance by increasing the background rate of tumors and other negative outcomes, the “noise” in the study. This would further mean that studies would have to be more powerful (contain more subjects in each group) in order to detect the diluted signal.

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Jun 30 2015

Lessons From GM Wheat Failure

Published by under General Science

So-called “whiffy wheat” was genetically modified to release a pheromone that repels aphids. The obvious purpose of this modification was to reduce pests without the need for insecticides, and thereby reduce insecticide use.

The trait worked well in the lab. The wheat released sufficient amounts of a warning pheromone that aphids release when attacked. The pheromone both warns aphids to stay away, and also attracts predators, such as a parasitic wasp. The pheromone was derived from the peppermint plant.

The laboratory success meant the wheat was ready for field trials where the GM crop is put to the test in close to real world conditions. The results of those field trials were just published, and unfortunately they showed that the new trait essentially didn’t work – the aphids were not significantly decreased compared to controls, nor was yield increased.

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Jun 16 2015

The Debate over Nutrition Research

Can you recall everything you ate yesterday, including those little snacks you snuck, with reasonably accurate estimates of amounts? How about two days ago? Most people, it turns out, have a hard time recalling with good fidelity their recent food intake, or they have a hard time reporting it accurately not only because of the fallibility of memory but because of biases and denial.

Despite this, a great deal of nutrition research is based upon subjects recalling and accurately reporting what they ate. A recent article in Mayo Clinic Proceedings by Edward Archer et al challenges the legitimacy of this research. They write:

The reliance on M-BMs to inform dietary policy continues despite decades of unequivocal evidence that M-BM (memory-based dietary assessment methods ) data bear little relation to actual energy and nutrient consumption.

This is pretty damming. They charge that the current dietary guidelines are based upon fatally flawed data. They specifically state that such data is based upon fallible memory, uses data collecting techniques known to promote false recall, cannot be independently verified, and often does not contain objective data on physical activity. They go as far as to call such research an, “unscientific and major misuse of research resources.”

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Jun 08 2015

More Quantum Weirdness

Published by under General Science

Science news outlets are reporting:

“It proves that measurement is everything. At the quantum level, reality does not exist if you are not looking at it,” lead researcher and physicist Andrew Truscott said in a press release.

What scientific understanding gets distilled down to the public consciousness is important, and that is one of the primary missions of good science news reporting. What is the bottom line, “take-home” message that the average person should walk away with regarding any particular experiment or scientific question. This often requires translating complex technical science into accessible every-day concepts without sacrificing accuracy. Obviously technical detail must be watered down, and doing this without making the result wrong is part of the skill of good science reporting.

One of the pitfalls of science reporting is distilling down a complex scientific concept to something that is cool, engaging, and sensational, but fundamentally wrong or at least highly misleading. The public then latches onto the sensational myth and forever misunderstands the actual science.

That is, I believe, what has happened with quantum mechanics, which is perhaps the most challenging science to explain to a non-technical audience. It’s hard enough for scientists to wrap their minds around, even with a highly technical understanding of what the experiments are actually showing. It seems to me that Truscott is perpetuating the greatest myth about quantum mechanics with a very poor choice of words to characterize what his recent experiment has shown.

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Jun 01 2015

Citation Bias – Confirmation Bias for Scientists

Published by under General Science

I’m a big fan of science for many reasons. Not only is the subject matter of science often incredibly interesting, but the process of science seems to work better than any other method humans have developed for knowing about the universe in which we live. Any fair-minded and knowledgeable view of human history cannot avoid this conclusion.

It’s therefore worthwhile thinking about and exploring the science of science itself, what we might call metascience. It is, in fact, a common narrative among skeptics and science communicators that, while science is awesome, it is practiced by biased and flawed humans. The history of science is one of error, bias, and ego that manages to slowly grind toward the truth.

Metascience is as important as metacognition, or thinking about thinking, and I write about both topics often. These are core knowledge-bases for any critical thinking skeptic. Here is a list I compiled of the most important issues with the quality of science. The goal here is not to criticize science, but to improve its practice, make it more efficient, minimize wasted resources, and help the public sift the reliable from the nonsense.

I’m now going to add another important concept to the list – citation bias.

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May 29 2015

A Chocolate Science Sting

John Bohannon is at it again. In 2013 he published the results of a sting operation in which he submitted terrible papers with fake credentials to 304 open access journals. Over half of the journals accepted the paper for publication. He published his results in Science magazine, and it caused a bit of a stir, although arguably not as much as it should have.

Bohannon was asked to repeat this feat, this time to expose the schlocky science of the diet industry. He was asked to do this for a documentary film which will be release shortly, but he has already published his reveal. You can read his full account for details, but here is the quick summary.

He collaborated with others to perform a real (although crappy) scientific study. His researchers recruited 16 people, with one drop out, the remaining 15 were divided into three groups: low carb diet for three weeks, low carb diet plus daily chocolate for three weeks, and no change in diet. The results were not surprising in that the two diet groups lost 5 pounds on average, while the no diet group did not. However, they also found that the chocolate group lost 10% more weight. He explains:
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May 12 2015

In Defense of Prior Probability

This post is a follow up to one from last week about reproducibility in science. An e-mailer had a problem with the following statement:

“I tend to accept claims based upon published rigorous evidence that shows a consistent robust result with reasonable effect sizes with evidence in proportion to the plausibility. “

In response they wrote:

“I think this might open up for arbitrary amounts of discrimination based on gut feelings. As an example, if it really was so that aliens regularly conducted semi-stealthy visits to planet earth (as the proponents seems to suggest), we might actually never realise so, because there could be a double standard demanding arbitrarily high levels of evidence based on gut feelings about prior probability.

Allowing prior conceptions this power could even open up for psychological effects such as post hoc adapting the prior judgement such that it is just low enough to allow to discard the presented evidence.”

This is a common reaction, especially when prior probability is used as part of an argument for rejecting a scientific claim (to be clear, I don’t think the e-mailer is doing this, they just seem to have an honest question). I am a strong proponent of prior probability, used as part of a Bayesian analysis. That is, in fact, at the heart of the difference between science-based medicine (a term I coined to reflect my approach) and evidence-based medicine.

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May 08 2015

A Reproducibility Experiment

Published by under General Science

I have been writing quite a bit here and on Science-Based Medicine about metascience – the study of science itself. When you think about it, science is perhaps the most critical and broadly applicable technology of our modern civilization. It is the one endeavor from which all other technologies derive.

It therefore is very important that we understand how the institutions and processes of science are functioning. If there are any inefficiencies or biases in the system they can cause great harm, a waste of resources and a slowing of progress.

A recent metascience project called, The Reproducibility Project: Psychology, asks a very important question:

Do normative scientific practices and incentive structures produce a biased body of research evidence?

The project focuses on one specific aspect of this question – how reproducible are published psychological studies? They looked at 100 studies published in prominent psychology journals with positive results that have been generally accepted. They then crowdsourced scientists conducting replications of these studies, with 270 authors participating.

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May 05 2015

Open Science

Published by under General Science

There is a movement to open access to scientific information, and with the relatively new resources provided by the internet and social media, we may be heading rapidly in that direction. However, I don’t think this will be an easy transition and we should consider the possible unintended consequences.

A 2012 commentary by Nosek and Bar-Anan outlined the changes that would open science:

We call for six changes: (1) full embrace of digital communication, (2) open access to all published research, (3) disentangling publication from evaluation, (4) breaking the “one article, one journal” model with a grading system for evaluation and diversified dissemination outlets, (5) publishing peer review, and, (6) allowing open, continuous peer review. We address conceptual and practical barriers to change, and provide examples showing how the suggested practices are being used already.

The Center for Open Science outlines a similar mission:

1-Increase prevalence of scientific values – openness, reproducibility – in scientific practice
2-Develop and maintain infrastructure for documentation, archiving, sharing, and registering research materials
3-Join infrastructures to support the entire scientific workflow in a common framework
4-Foster an interdisciplinary community of open source developers, scientists, and organizations
5-Adjust incentives to make “getting it right” more competitive with “getting it published”
6-Make all academic research discoverable and accessible

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