On Cells and Identity
A Harsh Truth About Science
The average life sciences student faces a peculiar problem throughout his academic life: his first approach to cells is the comparison between (rather simplified and summarized) animal and plant cells, followed years later a mention of the notion of tissue and the existence of many types of animal and plant cells, a brief exposition to bacteria (and the eukaryote/prokaryote division), only to reach a final stage—usually the first years of college—were all these notions will be forcefully washed away to be replaced by new, more exact categorizations. If our hypothetical student continues his education and chooses to specialize in, say, neurology, he will now learn that neurons are only a portion (albeit a big one) of the cells present in the brain and important to its function. He will have to learn about astrocytes (not to mention reactive astrocytes) and about oligodendrocytes, and… Even with neurons alone, he will have to learn about the bazillion types of neurons (or, at the very least, the ones he has research interest in) and when he finally does it and lets out a sight of relief there will be a dozen newly characterized ones.
Puzzles of Puzzles
I could go on with this futile exercise a few dozen paragraphs more, but what I’ve laid down is enough to be illustrative of this problem—or simply characteristic, for some—of classifying cells (and anything, generally): granularity. If you keep looking, you’ll keep finding. In modern terms, granularity is a fancy name for the now very famous f*ck around, find out phenomenon. Curiously enough, this is also a characteristic of knowledge gained through scientific means123 as a whole. If we were to try and see the Truth as a puzzle and managed to discover a piece of it, we would soon realize that the piece we are holding is not only a piece of the Truth but a whole new puzzle. In other words, the Truth is a fractal; a never-ending story.
Back to cells. Granularity has struck again. Pieces of the puzzle turned our to be puzzles themselves when we began analyzing what cells of a given population were transcribing4 , since we found that supposedly homogenous populations had far, far more diversity than what we expected. In simpler terms, we’ve realized that a group we have historically called ‘cells A’ is better described as ‘cells A.1’, ‘cells A.2’, ‘cells A.3’, or, if you have really bad luck, ‘cells A that are remarkably close to cells B’. Eventually, someone will find that even ‘cells A.1’ could actually be classified as ‘cells A.1.1’, ‘cells A.1.2’, and so on… Puzzles of puzzles.
Thankfully, granularity is more of an obstacle than a fundamental problem. If you accept that the level of detail you can theoretically gather is near-infinite and then find a level of detail that is practical for your purposes, you are golden. It is not inaccurate for the poor teacher to tell elementary school kids cells are divided into animal and plant cells, for it is practical. At the same time, it is untrue, but so are any further divisions. Are they all not, after all, merely human abstractions of reality?
Are Neurons, Neurons?
What makes a neuron a neuron? What about an astrocyte? And an adipocyte? Traditionally, morphology (i.e. the shape of the cells) was the fundamental determinator. Later, certain proteins specific to that cell-type served as markers5. Now, transcripts present in the cell.
The truth is that, while these can be extremely specific, they are terrible determinators of what a cell is. They are practical ones and, thus, not exactly inaccurate ones, but they are simply a tool to divide cells for further study: it’s not the truth.
There’s nothing in nature that makes a ‘neuron’ a ‘neuron’. After all, ‘neuron’ is merely a manmade category to describe a cell with certain measurable or observable characteristics. If you were to go back in time and remake all of the scientific corpus of knowledge, the same categories might not even develop, or perhaps completely different characteristics would be used to classify cells.
We can see and measure characteristics or consequences of what things are, but not know what things are by themselves. It is a dilemma akin to Plato’s Cave in which science is doomed to reside. Though it is not a curse, at least if one grants science the place it oughts to hold.
Models and Dogmas
This thing, this terrible thing, I believe is no curse. It is simply a characteristic or, rather, a consequence of what science is and has always been: a tool. This truth, that science is a mere tool, is so often rejected nowadays and replaced with the fantasy of capital-S Science. ‘Trust the Science! Trust the Scientists!’ are an example of recent mottos or maxims (perhaps even secular litanies of some sort) that demonstrate this6.
Science (again, capital-S) has been elevated into a sort of cult with a corpus of beliefs that you either abide fully to (‘Do you trust Science?’) or turn into the modern equivalent of an uncultured medieval peasant. This, as it has been pointed out a gazillion times, is a surprisingly anti-scientific and fallacious way of acting, if one still considers science a tool to discover material truths and not the Truth itself. Scientific theories and hypothesis are nowadays often revered as dogma and the Scientific Method often finds itself inverted: instead of observing, experimenting, and then (and only then) coming to conclusions, many now come to conclusions and then plan experiments to prove them7. One of the greatest tools in the search for Truth has been sequestered, uplifted, and made into an idol. Instead of models that approximate the truth now we pretend we have dogmas, the Truth itself.
When you turn a tool that helps you understand the material world around you by observing it and modeling it into a creed, you reduce the vastness of human experience into one dimension. Now Man is material. Everything about Man is now material. The way we speak about the body? As if it were a machine, moving things here and there pretending it is not bound to cause some effect elsewhere. The climate? As if it were easy to control and to predict. We pretend we are masters of all, that we can rule over the world because we have Science™, but then tiny little things—like single cells—shows us that we now nothing.
The largest sin of biologists was to convince us that we are no more than a bunch of cells. Neurologists and psychologists told us love was no more than molecules crashing around our brains and health officials told us the kind thing was to let grandparents die isolated from the once they loved. Lab-coats have seek to turn the material into the real, observation and logic into peer-reviewed slogs of slang without any true meaning. They publish because they have to, not because they have something worth saying.
But I can’t pretend I’m not a part of it, to a point. After all, I study under those same people I now criticize. I read their papers. Sometimes, when I’m not careful enough, I place Science upon the same meaningless pedestal they do. And for that, I’m sorry.
We’ve killed wonder. Ironic, because it was wonder—the sense of standing before something greater than ourselves—that turned us into scientists in the first place.
The purpose of this rather obnoxious wording is to make it very clear that I consider science to be a tool, not a body of belief one can choose to believe or not.
For a quick example, look at the concept of atom. The original idea is that it is indivisible (hence the name, ἄτομος meaning literally indivisible). But once you look closer… protons, neutrons, electrons… and closer… quarks and weird stuff some folk like to pretend they understand.
Also of measurements. The Coastline Paradox is one of the most famous examples.
Quick, oversimplified summary for folk with little knowledge of molecular biology: your DNA is made up of genes, which are transcribed into strings of RNA (a molecular cousin of sorts of DNA) called Messenger RNA or mRNA, which are later translated into proteins. Reading the fragments of RNA present in a cell (i.e. single-cell RNA-sequencing) shows you what genes are actually being used (i.e. turned into proteins) by a given cell.
For instance, MAP2 for neurons and GFAP for astrocytes.
The Pandemic gave us hundreds of thousands of examples of this kind of thinking.
Such experiments and the interpretation of their results are, as one can imagine, terribly biased.