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May 21, 20260 citationsOpen Access

ITU Tier 1+ #6: Biological Aging (Kₐging)

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MTMunehiro Terada

Key Points

  • This study aims to define biological aging through an operator-algebraic framework and explore its implications for longevity.
  • Utilized operator-algebraic biological-aging theory combining telomere, epigenetic, and proteostasis factors.
  • Calculated K_aging as a modular Hamiltonian incorporating stem and senescence aspects.
  • Generated numerical results alongside falsifiable predictions related to aging interventions.
  • Identified ten predictions related to aging interventions, with an average probability of 0.66 for validation.
  • Highlighted significant factors influencing biological aging, including Hayflick limit and Horvath clock.
  • Discussed potential lifespan extension of 5 years by 2050 through emerging therapies.

Abstract

Tier 1+ Pass-1. 5 paper 6 of 45. Operator-algebraic biological-aging theory on telomere + epigenetic + proteostasis + stem + senescence. Defines Kₐging = -log ρₐging as the operator-algebraic modular Hamiltonian on Hₜelomere ⊗ Hₑpigenetic ⊗ Hₚroteostasis ⊗ Hₛtem ⊗ Hₛenescence. Kₐging inherits from KQG via the CLPW 2023 type II crossed-product specialised to this scale. Numerical results. Hayflick limit 1961, Horvath clock 2013, senolytics Kirkland 2015, Loyal LOY-002 FDA 2024. 11. 26 first lifespan drug. Topics covered. Hallmarks of aging Lopez-Otin 2013/2023, Horvath methylation clock 2013, senolytics dasatinib+quercetin, NMN/NAD+, Yamanaka partial reprogramming Sinclair 2020. 45-vertex polytope #6 top couplings: #5 Kcancer (0. 95), #27 Microbiome (0. 92), #28 Neuro (0. 85), #31 Kqbio (0. 92). Ten falsifiable predictions: Pₐvg=0. 66: arXiv 2026 (0. 90 S), Yamanaka rejuvenation human trial 2028 (0. 55 M), Lifespan +5 yr by 2050 (0. 60 M). Pass-2 roadmap: ~1. 7M: Aging analytics (600K) + Lean Mathlib (200K) + Longevity partnerships (900K). Copyright © 2026 Munehiro Terada / Roboken. Licensed under CC-BY-4. 0.

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Cite This Study

Munehiro Terada (2026) studied this question.

synapsesocial.com/papers/6a0ea0f7be05d6e3efb5f51ahttps://doi.org/10.5281/zenodo.20270954
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