User:Anthony.Sebastian/Homeostasis/Sebastian Notes/Archive 1

Referring to animal systems, pioneering physiologist Walter Cannon,   who coined the word homeostasis in 1926, defined it as follows:

The coordinated physiological reactions which maintain most of the steady states in the body are so complex, and are so peculiar to the living organism, that it has been suggested (Cannon, 1929) that a specific designation for these states be employed--homeostasis.

Note that Cannon applied the term 'homeostasis' to the "steady states in the body", not specifically to the physiological mechanisms maintaining them.

Cannon recognized that “living being[s]” function as ‘open’ systems (see Life), having many “relations” with their surroundings — for example through airways, gastrointestinal tract and skin. He noted that the surroundings could perturb the system, dislocating its key internal components or subsystems to states of activity outside of their relatively stable and optimal ranges — the “steady states” in his definition. A change in outside temperature, for example, might perturb the stability of admittedly dynamical internal biochemical processes to the detriment of the organism. The organism reacts to such potentially adverse effects of its surroundings with physiological adjustments that tend to maintain steady-state, i.e., to maintain 'homeostasis'.

This article will explore the concept of homeostasis in an early 21st century biological setting, exemplify ‘homeostatic’ (homeostasis-maintaining) mechanisms, and relate homeostasis (dynamic stability) to physiology, cybernetics, and the concepts of cellular and organismic adaptability and adaptation, growth, development and reproduction.

Terminology and examples of usage

In common usage, ‘homeostasis’ refers not only to a living system’s internal stability, but also to its ability to, or tendency to, maintain that stability. Because living systems can adjust their physiological processes in response to destabilizing perturbations, we can attribute to them the property or behavior of ‘homeostasis’, by which property or behavior it maintains ‘homeostasis’. Such characterizes the vagaries, or flexibility, of language.

Use of the adjectival form, homeostatic, adds a modicum of coherence. Typically biologists speak of ‘homeostatic mechanisms’, namely mechanisms that achieve, or tend to achieve, internal stability. They do not typically speak of homeostatic mechanisms as mechanisms that yield an organism’s ‘ability’ to make the physiological adjustments required for stability. To explain that requires investigation of principles that underpin the activity of living itself, including evolutionary forces enabling self-organization and autonomy (see Life).

In its narrow sense applied to living systems, homeostatic mechanisms operate as built-in autonomous physiological processes, goal-directed to maintain, within an optimal range or steady-state, the properties, functions or behaviors of the system’s key components or subsystems when perturbed to move outside that ‘set-point’ range, or ‘set-range’.

For a cell, homeostatic mechanisms operate, for example, to maintain its internal concentration of hydrogen ion near its optimal value (set-point), the failure of which would have widespread effects on the naturally-selected catalytic activity of enzymes necessary for cell organization and survival. For a multicellular organism, homeostatic mechanisms operate, for example, to maintain near optimal supplies of oxygen to an organ, the failure of which could lead to organ dysfunction and cascading deleterious effects on other organs.

In its broader sense applied to living systems, homeostatic mechanisms operate as the totality of those physiological adjustive processes that ensure the near steady-state functioning required to sustain the activity of living. Because living systems grow in time, behave differently in different environments, and manufacture living things like themselves, set-point optimality does not remain fixed. Homeostatic mechanisms can accommodate the changes, indicating their complexity.

Homeostasis and longevity

Cell homeostasis, tissue homeostasis, and organ homeostasis determine organismic homeostasis . Therefore the 'efficiency' with which cells, tissues and organs in maintain homeostasis would likely influence the longevity of the emergent organism.

To quantify the homeostasis efficiency of a complex system, even one low in hierarchy, like a eukaryotic cell, one might try valuating the degree/promptness of homeostasis of its major subsystems in response to a perturbation spectrum. But that could only quantify efficiency under the environmental conditions of the studies. Each different environmental condition might affect efficiency differently, and variably differently, in the various subsystems. Because an enormous number of environmental conditions test homeostasis-maintaining ability of the organism during a lifespan, one would need to obtain and integrate too much detail of human subsystems’ properties for any valuation of efficiency of homeostasis to have practical value in controlling human lifespan.

The property of 'lifespan' in the human system emerges only when organismic homeostasis fails completely and death results. A model that could predict lifespan long in advance of death, even one that age-modified the prediction, might lend itself to teaching how to treat the system to improve the efficiency of homeostasis of its subsystems.

What form would such a model take? For personal benefit — a major goal of aging research — the model would seem to require itself to extensively interrogate the individual human system before running its lifespan-predicting algorithm. And do such interrogation time after time as time goes by. One would want the model’s systems readout, however implemented and interpreted in relation to previous readouts, followed by a prediction of lifespan as well as a prescription of steps to take to reverse damage and improve homeostasis-maintaining ability. A massive-load-capable information-gathering-and-processing method, abstract, computational: a cyber-smart doctor, distributed geographically or miniaturized.

But that ideal model allows control of lifespan for extreme longevity, as opposed to merely extending it substantially beyond present norms. Yet, learning to extend lifespan substantially may crucially underpin any model that permits control of lifespan for extreme longevity. Minimized energy consumption in the form of food extends lifespan in diverse genera. That would seem to have potential for obese humans, but not necessarily for non-obese humans. We do not know whether calorie minimization, ceteris paribus, extends lifespans in non-obese humans. If it did, we might want to revise our quantitative criteria for obesity to retain its connotation of poor health. We have no firm idea what body mass indexes, or percent body fat, however adjusted for other anthropomorphic variables, associate with human lifespans substantially greater than current norms.

Depending on how extreme the possible longevity, achieving it may require the complex task of controlling the entire human environment, the biosphere at minimum. Hopefully, but likely, all humans will require a large core-biosphere-set of common conditions, however geo-regional, for super-efficient organismic homeostasis. In recognizing that, the motivation of individuals for youthful longevity may impel them to interact in ways to achieve that common set of conditions. Sacrifices might involve opposing nature’s algorithmic drive to reproduce. Doing that would step us closer to the question of optimal sustainable population size, and if one can be determined satisfactory, how to achieve that ethically.

The property of lifespan has interest because the desirer of longevity wants a long healthy mental life, a long-lived kingdom of the mind. Why? Because as one’s knowledge increases so do the number of paths for curiosity to pursue — and a healthy youthful mind dictates the exercise of curiosity. Often one has ambitions and goals that require many prolonged stages. Those who do not believe in ‘afterlife’ feel they should get the greatest possible satisfaction from living before dying. Living longer increases the chances of participating in breakthroughs to extreme longevity.

Though some suggest the possibility that someday supercomputers, perhaps quantum computers, will have the ability to simulate the processes that generate conscious and self-conscious experience in simulated humans living in a simulated biosphere . For all we know, we live as a simulation in a simulated world, as an experiment, perhaps an iterative run of a model program developed by model-building systems scientists beyond our ken.