CongressCritters, can you please get the left hand talking to the right hand?

From this Op-Ed.

The Institute of Medicine has recently released a report outlining the ominous public-health threat of chronic hepatitis C, much of which is the result of unwitting infection through medically-necessary blood transfusions, leading to 350,000 deaths worldwide each year and infecting more than three to five times as many people in the United States as HIV.

Narsty isn’t it? We should get right on that, don’t you think? Any decent models for research?

Currently, chimpanzees are the only experimental animal, except for humans themselves, susceptible to infection with hepatitis C. The Great Ape Protection Act would end the use of chimpanzees in biomedical research, grinding promising studies to a halt and unconscionably delaying the release of anti-viral therapies and a vaccine for chronic hepatitis C.

Whoops.

IACUC 101: Satisfying the erroneous inference by eyeball technique

I stumbled back onto something I’ve been meaning to get to. It touches on both the ethical use of animals in research, the oversight process for animal research and the way we think about scientific inference.

 

Now, as has been discussed here and there in the animal use discussions, one of the central tenets of the review process is that scientists attempt to reduce the number of animals wherever possible. Meaning without compromising the scientific outcome, the minimum number of subjects required should be used. No more.

run more subjects..

We accept as more or less a bedrock that if a result meets the appropriate statistical test to the standard p < 0.05. Meaning that sampling the set of numbers that you have sampled 100 times from the same underlying population, fewer than five times will you get the result you did by chance. From which you conclude it is likely that the populations are in fact different.

 

There is an unfortunate tendency in science, however, to believe that if your statistical test returns p < 0.01 that this result is better. Somehow more significant, more reliable or more..real. On the part of the experimenter, on the part of his supervising lab head, on the part of paper reviewers and on the part of readers. Particularly the journal club variety.

False.

Scientific Research 101: Results!

So you’ve just completed your last assays on physioprofitin signaling in the Namnezian complex. Lo and behold it is qaz-mediated, just like you suspected and the beccans are off the freaking chart. woot! PiT/PlS ratios are within relevant physiological ranges and still this work of art, your labor of love, came through with the experimental goods.
With a hope and a prayer you run your stats….and YES! p < 0.01!!!!!!!!!!!!!!!
What is the correct way to report your big Result?

The statistical analysis____________ qaz-mediated upregulation of physioprofitin in the Namnezian complex.polls

doin it right

[ Please welcome our guest blogger, who identifies as robin, just your average everyday neuropharmacologist. -DM ]
One of the most important yet overlooked tasks of the average pharmacologist is dissolving drugs into solution. Those of you who work with things that don’t have to cross the blood-brain barrier probably have a generally easier time dissolving shit than those of us who prefer to study CNS-active compounds. For those of us who play with compounds that are hydrophobic enough to cross the blood-brain barrier, I can testify that those range from fairly easy to major suck to put into an aqueous solution.