Homeostasiset

Homeostasiset is a term used in theoretical biology and systems engineering to describe a framework for understanding how living and artificial systems maintain internal stability through a network of regulatory processes. It extends the classic concept of homeostasis by incorporating dynamic setpoints and multi-scale feedback.

The concept envisions organisms as coupled networks of subsystems—organs, tissues, cells, and even symbiotic communities—that continuously adjust to internal needs and external demands. Setpoints are not fixed; they shift with context, experience, and prior exposure, a notion related to allostasis but organized within an integrated regulatory architecture.

Mechanisms include negative feedback, feedforward signaling, circadian modulation, hormonal and metabolic sensing, and adaptive gain control. Cross-system coupling allows changes in one subsystem to trigger compensatory responses elsewhere, stabilizing variables such as temperature, pH, energy balance, and hydration despite perturbations.

In practice, Homeostasiset provides a lens for studying disease states, designing resilient artificial control systems, and guiding bioengineering approaches that require robust stability in changing environments. It emphasizes distributed control, redundancy, and context-aware regulation, highlighting how regulation can be learned, adapted, and reorganized in response to stressors and aging.

As a developing concept, it lacks formal measurement criteria and remains widely theoretical. It is mainly used as an integrative description rather than a single testable theory, serving to unify diverse observations about dynamic stability across biological and engineered systems.