Posted on behalf of Retread
Endocrinology was pretty simple in med school back in the 60s. All the target endocrine glands (ovary, adrenal, thyroid, etc.) were controlled by the pituitary; a gland about the size of a marble sitting an inch or so directly behind the bridge of your nose. The pituitary released a variety of hormones into the blood (one or more for each target gland) telling the target glands to secrete, and secrete they did. The master gland ruled.
Things became a bit more complicated when it was found that a small (4 grams or so out of 1500) part of the brain called the hypothalamus sitting just above the pituitary was really in control, telling the pituitary what and when to secrete. Subsequently it was found that the hormones secreted by the target glands (ovary, etc.) were getting into the hypothalamus and altering its effects on the pituitary. Estrogen is one example. Any notion of simple control vanished into an ambiguous miasma of setpoints, influences and equilibria. Goodbye linearity and simple notions of causation.
As soon as feedback (or simultaneous influence) enters the picture it becomes like the three body problem in physics, where 3 objects influence each other’s motion at the same time by the gravitational force. As John Gribbin (former science writer at Nature and now prolific author) said in his book ‘Deep Simplicity’, “It’s important to appreciate, though, that the lack of solutions to the three-body problem is not caused by our human deficiencies as mathematicians; it is built into the laws of mathematics.” The physics problem is actually much easier than endocrinology, because we know the exact strength and form of the gravitational force.
Organic chemists dearly love linearity. Nothing is more linear and causal than a multistep synthesis. We always search for conditions producing just what we want in high yield with as few unwanted products as possible, thank you. Le Chatelier’s principle is used again and again to force reactions to go just the way we want. It is a type of thinking that will not help us understand what is going on within our cells.
At one time it was thought that we had about 100,000 genes coding for proteins. The best current estimates are around 20,000. These genes code for structural proteins (like those of muscle and bone) and enzymes which do things like metabolize sugar or build the components of structural proteins (amino acids) or of DNA and RNA (nucleotides). We are gradually finding out that a lot of our genes function as controlling elements.
For instance, we have 478 genes for enzymes called kinases which form phosphate esters on the hydroxyls of threonine, serine and tyrosine of proteins, radically altering their function usually (the phosphate group adds a lot of negative charge). We have 107 genes for enzymes (called phosphatases) just for removing the phosphate from tyrosine (never mind serine and threonine). Another 600 or so genes code for enzymes which add (or remove) a small protein called ubiquitin from other proteins. Again feedback, control and nonlinearity.
Where this leaves the notion of causality in the cell, and worse, our ability to comprehend it — we do think linearly after all — will be the subject of the next post.
Retread
Equilibrium thermodynamics enforces the linear view. Efficient refrigerators and gigawatt power plants are useful. Excluding conceptually and computationally incovenient analytical classes is criminal (not subject to grant funding of the sure thing, the PERT chart, and the least publishable bit).
Belousov-Zhabotinsky reaction, chemical oscillators overall. Life is Ilya Prigogine’s non-equilibrium thermodyanmics, feedback, chaos, fractal form and function. We know that summed deterministic treatments interpolate well and extrapolate poorly – economics, psychology, climatology, controlled hot fusion, biology.
The soft scientist says, “WE MUST DO SOMETHING!”
The hard scientist says, “We must de something useful.”
Excluding what you can’t think about isn’t all bad. Look what math did with continuous functions, which are a vanishingly small subset of all functions. They also did pretty well algebraic numbers even though they are also a vanishingly small subset of all numbers which include the infinitely more numerous transcendentals — even though proving that a number as simple as pi was transcendental took a lot of work. It still isn’t easy — see “Making Transcendence Transparent” by Ed Burger and Bob Tubbs.
“We know that summed deterministic treatments interpolate well and extrapolate poorly – economics, psychology, climatology, controlled hot fusion, biology.”
That’s what makes them fun to think about and study.