So, in med school we've been studying the gastrointestinal tract for the past two weeks. As it turns out, that path ultimately leads to one thing: poop. Here are some fun facts about feces:
- Poo is brown because it contains stercobilin, a breakdown product of bilirubin, which is itself a breakdown product of hemoglobin. Hemoglobin is the substance that makes blood red, and bilirubin is the substance that makes people with jaundice turn yellow. The chemical structures of all these molecules contain series of alternating double bonded carbons called conjugated systems, which absorb specific light wavelengths well and thus cause pigmentation. Bilirubin enters the digestive tract through bile, but if the bile duct is obstructed, poo will be white or gray.
- Poo smells bad because of compounds containing sulfur. These are created by bacterial breakdown of proteins containing cysteine and methionine. This is also the reason farts smell bad. The gaseous volume of farts is mostly nitrogen, carbon dioxide, and hydrogen -- nitrogen from swallowed air, and carbon dioxide and hydrogen from bacterial breakdown of carbohydrates. Gut bacteria will only digest carbohydrates that you can't digest yourself, so foods that contain lots of protein and indigestible carbohydrates, e.g. beans, will cause smelly flatulence. The sound of gas moving through your digestive tract, a.k.a. stomach growling, is medically called "borborygmus". High altitude climbers experience copious flatulence, as gas occupies more volume in a low pressure atmosphere.
- The urge to poo comes from distension of the rectum wall. This causes a reflex relaxation of the internal anal sphincter, a muscle you can not consciously control. You keep poo in by flexing your external anal sphincter. If you don't act on the urge to poo, the rectum will eventually contract and push the feces back into the colon.
- The cholera bacteria is deadly because it produces cholera toxin. This toxin begins a reaction cascade that ultimately opens a channel on the surface of intestinal cells, which allows chloride ions and water to flow into the digestive tract. This causes massive amounts of watery diarrhea, which dehydrates the unfortunate host. This channel is mutated in cystic fibrosis, and it is hypothesized that people who are heterozygous for this mutation have some resistance to cholera toxin, explaining the high frequency of this mutation.
Well, that's it. Medicine is alternately the science of the mundane and the disgusting, but I suppose that's why I'm all the more amazed when I find fascination in the humblest things. Back to the books.
Thursday, January 14, 2010
Thursday, January 7, 2010
Science Culture
Before I started working in science, I was a bit naïve. In my imagination, science took place in a beautiful, purified paradise. Researchers didn't worry about money. They precisely executed carefully designed experiments, obtained clear and distinct data, and most of all, only started building theories post hoc.
In reality, science is done by people, in the real world. We want personal advancement. We are under financial and deadline pressure. Labs are messy and experimental set-ups are usually haphazard. Data are often ambiguous. Research is tedious and time-consuming. In the face of all this, it's nice to take some uncertainty out of the picture. So, more often than not, we choose experiments where we know the outcome ahead of time. Most work is just applying a well-known phenomenon to a new situation -- while it is technically "new research," the results are very much expected.
Except when they come out "wrong." A great article from WIRED mentions something I've seen several times, working in different labs. We take our results expectation too far, and begin committing bad science -- pushing statistics, denying results, dropping projects. Shouldn't theories be designed to fit data, not the other way around? While I thought that maybe this would be a problem, I was shocked by how common it was to ignore "bad data," even as a instructional point. If it's repeatable, and nothing is wrong with our methods, then what can we do?
In reality, science is done by people, in the real world. We want personal advancement. We are under financial and deadline pressure. Labs are messy and experimental set-ups are usually haphazard. Data are often ambiguous. Research is tedious and time-consuming. In the face of all this, it's nice to take some uncertainty out of the picture. So, more often than not, we choose experiments where we know the outcome ahead of time. Most work is just applying a well-known phenomenon to a new situation -- while it is technically "new research," the results are very much expected.
Except when they come out "wrong." A great article from WIRED mentions something I've seen several times, working in different labs. We take our results expectation too far, and begin committing bad science -- pushing statistics, denying results, dropping projects. Shouldn't theories be designed to fit data, not the other way around? While I thought that maybe this would be a problem, I was shocked by how common it was to ignore "bad data," even as a instructional point. If it's repeatable, and nothing is wrong with our methods, then what can we do?
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