A Bounded Multiscale Stochastic Framework for Cellular and Tissue Aging: Structural Uncertainty, Repair–Damage Control, Intervention Timing, and Falsifiable Predictions

Abstract

Aging is a multiscale dynamical process in which mitochondrial dysfunction, oxidative burden, genomic instability, transposable-element activity, epigenetic drift, cellular senescence, and chronic inflammation interact through feedback. We develop an auditable stochastic differential-equation framework that represents six coupled latent states while explicitly separating implementation verification, numerical robustness, structural robustness, and biological validation. The model uses a dimensionless oxidative-burden index and bounded production terms to prevent mathematically induced divergence from being mistaken for biological acceleration. We evaluate the model as a family of mechanistic hypotheses using transition-age sweeps, continuous versus biphasic transition structures, endpoint-specific repair–damage sensitivity decomposition, intervention-onset sweeps, finite-duration treatment and withdrawal, alternative bounded saturation functions, leave-one-coupling-out stress tests, and a spatial reaction–diffusion extension.Under the nominal stochastic parameterization, age-100 combination perturbation changes mitochondrial function by approximately +83.7%, genomic instability by −43.2%, epigenetic drift by −21.1%, senescence by −38.2%, and inflammaging by −29.0% relative to baseline; these are model outputs and not clinical effect sizes. Total-order sensitivity indicates repair-control dominance for genomic instability and epigenetic drift, but not for senescence or inflammaging. Intervention-onset benefit decreases across the tested range of 30–70 years, so the present equations do not generate an interior rejuvenation window. Importantly, after standardizing the scale of alternative bounded saturation functions, the structural alternatives produce similar mitochondrial and senescence outputs but materially different genomic-instability values, demonstrating that functional form remains a non-negligible uncertainty dimension without producing the artificial orders-of-magnitude collapse that can arise from dimensionally inconsistent saturation functions. A finite 10-year intervention produces transient path dependence with incomplete convergence after withdrawal, but this does not establish biological hysteresis. Deterministic time-step refinement, Monte-Carlo precision audits, boundary-drift checks, non-additivity contrasts, and independent sensitivity-rank repetitions were added to distinguish numerical reliability from biological uncertainty. A spatial extension predicts lower spatial autocorrelation under a fragmented treatment-associated geometry, yielding a directly testable tissue-level hypothesis.The principal contribution is not a clinical prediction or a claim of validated anti-aging efficacy. It is an executable, bounded, falsifiable model family in which quantitative conclusions are explicitly classified according to parameter uncertainty, structural assumptions, intervention timing, and network composition. The framework is therefore hypothesis-generating and designed to support subsequent empirical calibration and held-out validation.