TITLE:
Homeostasis at the Edge of Order: Cancer, Modulated Electro-Hyperthermia, and the Role of 1/f Noise
AUTHORS:
Andras Szasz
KEYWORDS:
Ising Model, Spin Glass, SOC, mEHT, Pink Noise, Edge of Chaos, Nonthermal Processes, Homeostasis, Stochastic Resonance
JOURNAL NAME:
Advances in Bioscience and Biotechnology,
Vol.17 No.8,
August
31,
2026
ABSTRACT: Homeostatic regulation ensures a dynamic equilibrium, maintaining the constancy of an organism’s internal environment despite continuous external fluctuations and internal metabolic demands. Homeostasis reflects a balance between stability and adaptability. This review explores how the biophysics operating near a second-order phase transition may be an evolved property of living systems, enabling maximal sensitivity, dynamic range, and information processing. Growing evidence suggests that biological systems operate near critical points, on the “edge of chaos”. Departure from criticality manifests in pathological states such as cancer, where the breakdown of cooperative cellular order may be interpreted as a transition away from the critical regime. The modulated electro-hyperthermia (mEHT) is a therapeutic intervention whose biophysical action can be understood through the lens of membrane-level dynamics in tumor cells. The homeostatic dynamics exhibit 1/f noise, a hallmark signature of self-organized criticality (SOC) in homeostasis, and it is a practical diagnostic indicator of physiological health versus disease. Together, these threads weave a coherent biophysical narrative: growing theoretical and experimental evidence suggests that many biological systems operate near criticality, and understanding this edge has profound implications for both fundamental biology and clinical medicine. One of the most powerful conceptual frameworks in modern biophysics is statistical mechanics, whose dynamics can be characterized by the Ising model, a useful tool for describing phase transitions at the boundary between order and chaos. Its capacity to capture collective behavior, long-range correlations, and phase transitions near a critical point renders it uniquely suited to modeling phenomena as diverse as neural dynamics, gene expression networks, cellular communication, and tissue organization, making it a suitable modeling tool for studying cancer development and prevention. My objective is to show the behavior of a living system at a phase transition and the corrections that arise when the system deviates from this delicate state, and connect these ideas to cancer and therapeutic intervention.