Posted on 08/02/2006 2:16:46 PM PDT by oxcart
For decades, in thousands of laboratories across the country, biomedical researchers have relied on laboratory rats and mice to devise treatments for cancer, heart disease, inflammation and a host of other human afflictions.
But what if, despite all the rigorous procedures to ensure valuable test results, many of those studies have been skewed by the most seemingly mundane of factors: what the animals are routinely fed?
The concern is that researchers have unwittingly administered hormones present in some rodent chow.
A small but growing number of scientists are warning that these hormones are a hidden element in millions of laboratory experiments – potentially affecting researchers' conclusions on countless aspects of disease.
"Many people don't give a second thought to it," said Leslie Leinwand, a molecular biologist at the University of Colorado in Boulder. "You just buy this stuff in big bags and feed it to mice and rats, and very few people are aware what is in there."
The most commonly used laboratory rodent chows contain soy as a key source of protein. The problem, research has shown, is that soy naturally contains chemicals known as phytoestrogens. These substances can wriggle their way into the lab animals' natural estrogen system, altering their physiology, whether they are male or female.
(Excerpt) Read more at dallasnews.com ...
I remember that. Wasn't it the case that some people might have been wrongly diagnosed as having breast cancer and treated for it when they really didn't because of the contamination? I'll have to look into it.
ping
Oey vey.
SOY vey!
time for a weston a price ping?
I work in biochemistry research. The rodent diet is very closely watched. Also, there are several controls in any experiment that would render this meaningless. This article implying that the majority of medical research is tainted by diet is irresponsible at best.
I don't personally work with rodents. I work with tissue culture. But my neighboring labs work with rodents.
I think the only thing this means is that Dr. Leinwand will be applying for grant money from the NIH to study her findings further.
Pass the saccharine please
"I think the only thing this means is that Dr. Leinwand will be applying for grant money from the NIH to study her findings further."
Her application would generate a lot of laughs on the NIH study section. Like I said, this is basically a non-issue and it only makes her look like a goofball who isn't paying enough attention to her experimental animals.
don't forget the alar.
No, salt raises your blood pressure.
Although I am, at times, amazed by some of the research the NIH chooses to fund, I have to think that her claim that switching lab rats from a diet of soy protein to milk protein miraculously improved the health of the male rats will be treated with a great deal of skepticism by her peers.
Heisenberg Principle.
Margins of error are not based upon stray factors that may affect results, but are rather designed to take into account sampling variation.
Suppose you have a large tank which is filled with black and white beads and you want to determine what percentage of the beads in the tank are white. Both types of beads have similar physical characteristics, and the contents of the tank are well mixed.
Suppose you take out ten beads. Three are white and seven are black. What can you say about the concentration of white beads in the pool? It seems likely to be about 30%, but it would hardly be surprising if it were 22% or 38%. Indeed, it shouldn't really be surprising to find it was really 15% or 45%. It probably isn't below 10%, and probably isn't above 50%, but drawing only ten beads can't really tell you much with certainty. Even if 90% of the beads were black, drawing ten beads at random would yield three white ones about 5% of the time.
Now suppose that instead of taking out ten beads, you take out twenty and find six of them white. It becomes possible to refine ones estimates much more. If I did the math right, slightly less than 1% of twenty-bead draws from a 90%-black pool would yield exactly six white ones. Thus, one can pretty well say the pool isn't 90% black, but one still can't nail down the concentration precisely.
If one takes out a hundred beads instead of twenty, the likelihood that the draw is a major statistical anomoly will go down. And if one takes out a thousand beads, it will go down even further. Note, btw, that it doesn't matter at all how many beads there are in the pool. A thousand-bead sample will be just as good for estimating the concentration in a pool holding a million beads as for one holding a billion, if the beads in the pool are well and uniformly mixed.
If the beads in the pool are not well-mixed, there may be a sampling bias which cannot be eliminated by an increased sample size. Stated error margins are meaningless when sampling bias exists. Indeed, the presence of sampling bias often makes it difficult or impossible to obtain really meaningful results, though it doesn't stop people from putting forth their results whether meaningful or not.
I see this type of thing happen all the time in pharmaceutical research. I always wondered why some PhDs don't fire on all cylinders. I think it's because in many universities our scientific educations are so specialized and spoon-fed, there's no time for independent thinking and growth.
You're neglecting synergistic effects.
But salt is bad for your blood pressure!
"You're neglecting synergistic effects."
The point is that competent scientists know what their lab animals are being fed and don't take the word of the animal caretakers. This scientist got lazy and screwed up and is trying to deflect criticism from herself to a supposition that all scientists are just as ignorant and negligent as she is.
"No, salt raises your blood pressure."
Actually, studies are inconclusive on this. Generally it is a very good idea to avoid excessive NaCl and to err on the side of caution if you have high BP, but some well-designed studies show that BP is unaffected by salt intake. In other words, maybe yes, but not proven.
Controlled experiment bump.
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