Reproducibility Archive: A Conditional Bioheat-Transport and Amyloid-Kinetics Framework for Testing Interactions Between Metabolic Compensation and Vascular Dysfunction

This reproducibility archive contains the complete, self-contained Python 3.11 simulation scripts, publication-grade vector figures, and machine-readable verification and uncertainty-quantification datasets supporting the manuscript "A Conditional Bioheat–Transport and Amyloid-Kinetics Framework for Testing Interactions Between Metabolic Compensation and Vascular Dysfunction." Methodological Framework:The provided computational pipeline establishes a conditional multiscale model that couples a three-dimensional (3D) Cartesian node-centered finite-difference Pennes bioheat and advection-diffusion solver (ILU-BiCGStab) to a high-barrier curvature-corrected Kramers nucleation framework. It systematically evaluates how modeled inner-membrane proton-leak uncoupling and vascular thermal/clearance impedance jointly govern deep-parenchymal temperature elevation and secondary-nucleation lag time. Archive Contents: 4 Executable Python Scripts (.py): Fully self-contained generators for the 3D finite-difference slab verification, multiscale heat-transfer scaling, canonical 2D/3D regime mapping, and global sensitivity screening. 11 Machine-Readable Datasets (.csv): Includes precise outputs for the 3D ILU-BiCGStab solver convergence logs, matched-nocturnal factorial branches (Compensatory vs. Isometabolic Null), high-barrier quartic potential fields (u_0 = 180), and full 41x41 subsampled mid-plane arrays. Global Sensitivity Screening: Outputs of the $N = 10,000$ Latin Hypercube Sampling (LHS) ensemble and dynamic 4D Gauss-Legendre tensor quadrature (331,776 nodes), demonstrating exact variance-based Sobol decomposition and epistatic interaction amplification. 4 Vector Figures (.pdf): High-resolution compiled figures matching the manuscript submission. Usage & Interpretation:The code and outputs herein represent a theoretical and computational research framework designed to evaluate how assumed metabolic compensation and perfusion changes affect amyloid-related kinetic observables under explicitly defined physical boundary conditions. The calculations do not establish that microprotein variation directly causes thermal trapping or initiates Alzheimer's disease. Mechanistic interpretation requires consistent experimental calibration and prospective validation. Keywords Alzheimer's Disease; Pennes Bioheat Transfer; Kramers Escape Rate; Uncertainty Quantification; Latin Hypercube Sampling; Sobol Indices; Perivascular Clearance; Computational Biophysics License & Access Access Right: Open Access License: Creative Commons Attribution 4.0 International (CC-BY 4.0) or MIT License (for software) Related/Alternate Identifiers Is supplemented by (this is the generic 1D Kramers math dataset): 10.5281/zenodo.23841572