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June 4, 20260 citationsOpen Access

Public Data Validation of the Neutralization Destiny Equation

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MYMenggang Yu

Key Points

  • This research aims to unify the causal interrelationships of aging hallmarks by exploring the residual capacity of the repair system.
  • Analyzed five publicly available datasets including NHANES, UK Biobank cognitive and imaging data, Horvath epigenetic clock, and canine breed data.
  • Conducted independent statistical tests on six core corollaries of the Neutralization Destiny Equation.
  • Utilized standard statistical methods for analysis, ensuring reproducibility.
  • All six statistical tests confirmed the predicted directions of the Neutralization Destiny Equation and its corollaries.
  • The results included clear effect sizes and robust confidence intervals, supporting the findings as statistically significant.
  • Findings are based on publicly available data, allowing for independent verification.

Abstract

Current aging research has identified twelve independent hallmarks, yet their causal interrelationships remain without a unified explanation. This paper proposes that the origin of this fragmentation lies in a long-overlooked variable—the residual capacity of the repair system itself, denoted E(t). Using five publicly available datasets (NHANES n=13,974; UK Biobank cognitive data n=427,053; UK Biobank multi-organ imaging data n=386,417; Horvath epigenetic clock 24 age groups; canine breed data 46 breeds) and four published meta-analyses, this paper conducts independent statistical tests on six core corollaries of the Neutralization Destiny Equation E(T)+M(T)=1. All six tests yielded results supporting the predicted directions of the equation and its corollaries, with clear effect sizes and robust confidence intervals. All tests in this paper use publicly available data and standard statistical methods and can be independently reproduced by any researcher. This paper does not presuppose any biological theory; it only conducts statistical tests on public data.

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Cite This Study

Menggang Yu (2026) studied this question.

synapsesocial.com/papers/6a21171dd499ed480b17007dhttps://doi.org/10.5281/zenodo.20506649
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