Skip to main content

The Fallibility of the Scientist


Let me begin this blog as a whole with an awful truth about the scientist in general and the chemist in particular. This is a flaw that I disdain, but have to admit is present if I am going to stay honest to myself and to you, my readers. This flaw is that of not going full out on meticulous detail when publishing findings to a scientific journal. Now this may mean not going in full detail in a lab notebook causing the experiment to be irreproducible, or this may mean presenting visuals that represent “impossible science”, or this may mean getting to a certain conclusion through shady means, among other things. All of these things happen in all fields of science, and especially in chemistry. And when these flaws are apparent, the scientists involved in not going full out on detail on a report get called out by the scientific community, in the same way when a murder is committed, the murderer is called out by the community (s)he murdered in. And like murderers, those scientists who perform these flaws of vague report and questionable lab practices are far outnumbered by the honest scientist.
Here, I will look at two of these cases.

----------------------------------

The first report comes from the periodical Science Magazine. In the 16JAN2004 issue, a report by Zhiwen Zhang was run about how β-N-acetylglucosamine-serine can be used to biochemically render e. coli ineffective at harming humans. In general, this is a cyclic ether bound to the nitrogen of an amine, which has a plethora of biological consequences. If Zhang's report is correct, this would make e. coli poisoning far easier and cheaper to treat.
In the 27NOV2009 edition, the editors of Science Magazine formally retracted this report. The reason for this? The lab report of the original experiments for this reports are no longer available, thusly making the reproduction of the experiments impossible.
Okay... so what? Fake it until you make it again, right? Wrong. There is the problem with funding. Who is going to fund searching for finding the precise procedures for rendering e. coli useless? Who will run the research again? Zhiwen Zhang? Not after the blunder he made. Next week, I will write in full detail about why the “fake it until you make it” mentality should be avoided.
----------------------------------

The second report also comes from Science Magazine. In the 09OCT2009 issue, there was a paper entitled “Reactome Array: Forging a Link Between Metabolome and Genome” by , which has since been formally retracted. The reason can be found in the article “Paper About Reactome Array Stirs Controversy” by Ana Beloqui, María-Eugenia Guazzaroni, Florencio Pazos, José M. Vieites, Marta Godoy, Olga V. Golyshina Tatyana N. Chernikova, Agnes Waliczek, Rafael Silva-Rocha, Yamal Al-ramahi, Violetta La Cono, Carmen Mendez, José A. Salas, Roberto Solano, Michail M. Yakimov, Kenneth N. Timmis, Peter N. Golyshin, and Manuel Ferrer (Ana Beloqui et. al.) in the 11JAN2010 edition of Science Magazine.
The Reactome Array is a potential means for performing biochemical analysis on hundreds of metabolites at a time. The specific purpose of the experiment is to determine enzyme activity by utilizing a Cy3 dye label as an indicator. After the reaction is finished, proteins can be plucked from the mix and run through many spectral analysis.
The trouble with this paper began when it was found that there were gaps in the on-line supplemental material to the paper. Ana Beloqui et. al. advertised all of the graphs procured in the labs would be produced on-line at the time of publication of the paper. Well, they were. Most of them anyways. Not all of them, though. The troubles would have stopped there if it weren't for an incorrect graph. In one graph, it showed a biochemical reaction that could not physically happen; or so the biochemists argued. Ana Beloqui et. al. argued that this was a false statement.
The mistake here, as far as I can tell, is that the biochemists that made the claims of impossible chemistry never did actually reproduce the experiment. They kept on clinging to the statement “impossible chemistry” while the terms “unknown group” and “so many proteins produced” came out the corners of their mouths. But the reproduction of the experiment as far as I can tell has never been done.
So the hierarchy of science took precedence over the actual scientific process, and the article was retracted. The argument of “theoretical impossibility” from more well established scientists came against “observed fact” coming from lesser-known scientists, and the prior won. Who is actually right? In theory, the prior. In actuality, I don't know. I don't have the equipment to reproduce the experiment. Though, if I get the right funding...
----------------------------------

These are just two of the numerous cases where scientists prove their humanity. Humans are, in fact, fallible, science be damned. So the next time you hear an expert say anything, ask yourself if that expert is so blinded by their own God-Complex to see the truth. Only after you've determined that the answer to that question is no can you start to believe what they say to be true. If any scientist tells you something to be true, ask that scientist to produce the lab notes so that you can reproduce the experiment in question so that you can see for yourself.
Because that's how science works. If you don't believe it, you do it yourself so that you can see. If you don't see it, you continue not believing. But if you do see it, you change your belief. After all, science deals with the numbers. Under the guise of science, you cannot take something on faith to be true. The numbers have to add up.

Take that as you will.
-Alan Eister, Δαβ

Comments

Popular posts from this blog

Basic Statistics Lecture #3: Normal, Binomial, and Poisson Distributions

As I have mentioned last time , the uniform continuous distribution is not the only form of continuous distribution in statistics.  As promised, here are the three most common continuous distribution types.  As a side note, all sampling distributions are relative to the algebraic mean. Normal Distribution: I think most people are familiar with the concept of a normal distribution.  If you've ever seen a bell curve, you've seen the normal distribution.  If you've begun from the first lecture of this lecture series, you've also seen the normal distribution. This type of distribution is where the data points follow a continuous curve, is non-uniform, has a mean (algebraic average) equal to the median (the exact middle value), falls from highest probability at the mean to (for all practical purposes) zero as the x-values approach $\pm \infty$, and therefor has equal number of data points to the left and to the right of the mean, and has the domain of $(\pm \i

Confidence Interval: Basic Statistics Lecture Series Lecture #11

You'll remember last time , I covered hypothesis testing of proportions and the time before that , hypothesis testing of a sample with a mean and standard deviation.  This time, I'll cover the concept of confidence intervals. Confidence intervals are of the form μ 1-α ∈ (a, b) 1-α , where a and b are two numbers such that a<b, α is the significance level as covered in hypothesis testing, and μ is the actual population mean (not the sample mean). This is a the statement of there being a [(1-α)*100]% probability that the true population mean will be somewhere between a and b.  The obvious question is "How do we find a and b?".  Here, I will describe the process. Step 1. Find the Fundamental Statistics The first thing we need to find the fundamental statistics , the mean, standard deviation, and the sample size.  The sample mean is typically referred to as the point estimate by most statistics text books.  This is because the point estimate of the populati

The Connections Between the Sciences

I apologize for taking so long with this entry of my blog. I have been abnormally busy lately with my academics and poetry. Today, I am writing on how all of the sciences are related to one another, in the hopes that you will come to realize that the sciences are not as separate as popular culture and news has us believe. This blog will be geared to those individuals – weather you're the average person or a student of science, or a full blown scientist – who have the opinion that the different fields of science are completely isolated from one another. This sentiment is not true, and I hope to show the false-hood of this concept here. In physics, we have the concept of “The Right-Hand-Rule”. This pretty much determines whether the a force perpendicular to two vectors is “positive” or “negative”. Torque is a good example of this. The amount of torque placed on, say, a bolt by a crescent wrench is perpendicular to the position vector and the fo