Topological Latent Manifold Model v7.0: Full ABF Cascade Integration — ABF-Integrated, Mechanism-Aware, and Clinically Actionable Viability Forecasting

TLMM v7.0 (Topological Latent Manifold Model version 7.0) presents a proposed mechanistic framework that integrates the complete Amyloid–Blood Flow (ABF) cascade into a unified latent-space architecture for mechanism-aware viability forecasting. Building upon the partial ABF integration introduced in TLMM v6.9, this version extends the framework through: Full ABF Cascade Architecture (Aβ → Tau → N → ND → VRI) Hierarchical Vascular Modules (L1–L5) Unified Biological Latent Space Thermodynamic Landscape Modeling Mechanistically-Regularized ELBO Counterfactual Simulation Framework Adaptive Viability Steering (Model Predictive Control) Intervention Portfolio Optimization Mechanism-Aware Missing Data Recovery Cohort-Adaptive Bayesian Calibration Clinical Decision Dashboard Revised Mechanistic Falsifiability Battery (C1–C9) Multi-level Validation and Benchmark Strategy Roadmap Beyond TLMM v7.0 Compared with previous versions, TLMM v7.0 extends the application domain from Alzheimer's disease toward broader vascular and cardiometabolic conditions while preserving a mechanistically grounded modeling philosophy. The manuscript introduces a revised mechanistic falsifiability taxonomy, redesigned biological latent variables, multiscale vascular feedback, thermodynamic regularization, and a complete closed-loop control framework intended as a foundation for future mechanism-aware precision medicine. Important Notice This work presents a proposed methodological framework. All figures, numerical values, benchmark results, validation scores, and clinical dashboards are illustrative synthetic examples created solely for methodological demonstration. They do not represent clinical performance estimates, real patient data, or medical recommendations.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-26
DOI
https://doi.org/10.5281/zenodo.20931180
Primary Topic
Functional Brain Connectivity Studies
Type
preprint
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preprint

Topological Latent Manifold Model v7.0: Full ABF Cascade Integration — ABF-Integrated, Mechanism-Aware, and Clinically Actionable Viability Forecasting

Koji Okino
Zenodo (CERN European Organization for Nuclear Research)
Functional Brain Connectivity Studies
preprint

Topological Latent Manifold Model v7.0: Full ABF Cascade Integration — ABF-Integrated, Mechanism-Aware, and Clinically Actionable Viability Forecasting

Koji Okino
preprint en

Abstract

TLMM v7.0 (Topological Latent Manifold Model version 7.0) presents a proposed mechanistic framework that integrates the complete Amyloid–Blood Flow (ABF) cascade into a unified latent-space architecture for mechanism-aware viability forecasting. Building upon the partial ABF integration introduced in TLMM v6.9, this version extends the framework through: Full ABF Cascade Architecture (Aβ → Tau → N → ND → VRI) Hierarchical Vascular Modules (L1–L5) Unified Biological Latent Space Thermodynamic Landscape Modeling Mechanistically-Regularized ELBO Counterfactual Simulation Framework Adaptive Viability Steering (Model Predictive Control) Intervention Portfolio Optimization Mechanism-Aware Missing Data Recovery Cohort-Adaptive Bayesian Calibration Clinical Decision Dashboard Revised Mechanistic Falsifiability Battery (C1–C9) Multi-level Validation and Benchmark Strategy Roadmap Beyond TLMM v7.0 Compared with previous versions, TLMM v7.0 extends the application domain from Alzheimer's disease toward broader vascular and cardiometabolic conditions while preserving a mechanistically grounded modeling philosophy. The manuscript introduces a revised mechanistic falsifiability taxonomy, redesigned biological latent variables, multiscale vascular feedback, thermodynamic regularization, and a complete closed-loop control framework intended as a foundation for future mechanism-aware precision medicine. Important Notice This work presents a proposed methodological framework. All figures, numerical values, benchmark results, validation scores, and clinical dashboards are illustrative synthetic examples created solely for methodological demonstration. They do not represent clinical performance estimates, real patient data, or medical recommendations.

Zenodo (CERN European Organization for Nuclear Research)
United States Department of Labor (US)
Functional Brain Connectivity Studies
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