Aging as Cybernetic Attractor Decay: Beyond the Stochastic-Programmed Dichotomy

preprint OA: closed CC-BY-4.0
AI-generated summary by claude@2026-07, 2026-07-17

Aging results from the decay of cybernetic attractors in biological information-processing networks, not stochastic damage or programmed senescence, and this decay is reversible through restoring regulatory configurations.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

AI-generated deep summary by claude@2026-07, 2026-07-17 · read from full text

The provided text does not include any substantive description of the paper’s objectives, methods, study population, results, or limitations, aside from generic publication/license placeholders. Because no scientific content is available to extract, a meaningful biomedical summary cannot be produced without the full paper text. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

The debate between stochastic deterioration (Meyer et al., 2025) and programmed senescence perpetuates a false dichotomy dating back to Weismann. The precision of molecular aging clocks and aging reversibility demands a different explanation: aging is neither stochastic wear-and-tear nor genetic programming, but rather cybernetic decay, predictable trajectories emerging as developmental regulatory architectures lose information-processing fidelity. I define biological systems as hierarchical information-processing networks where aging represents computational drift from developmental attractors. Three observations support this framework: (1) site-specific equilibrium states inconsistent with pure stochasticity, (2) developmental network dominance in aging signatures, and (3) rejuvenation restoring regulatory configurations rather than repairing molecular damage. This framework reconciles why aging follows predictable population trajectories despite individual variability (conserved computational architectures), why epigenetic clocks work (measuring attractor drift), and why reprogramming reverses aging (restoring computational precision). It predicts that regulatory network entropy outperforms mutation burden in age prediction, and that interventions restoring information coherence reverse aging clocks more effectively than targeted molecular repair. Under this framework, biological entities function as computers, and aging emerges as a fundamentally reversible and controllable process across both short-term development and long-term evolution.
Full text 621 characters · extracted from oa-doi-fallback · click to expand
There is a newer version available for this {{ publicationType }}. View latest version {{ publication.field_name }} {{ publication.subfield_name }} Copyright: © {{ publicationYear }} {{ publication.presentation_authors[0].full_name + (publication.presentation_authors.length > 1 ? ' et al' : '') }}. This is an open access publication distributed under the terms of the CC BY 4.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Check the {{ publicationType | capitalize }} Source for copyright and license information. Listen on

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2026) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
unpaywall
last seen: 2026-05-24T02:00:01.246996+00:00
License: CC-BY-4.0