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ZENODO
Preprint . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
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Bioelectrical and Biological Pattern Failure Before Cell Death: A Recursive Diagnostic Terrain Model for Chronic Fatigue, Autonomic, and Immune Collapse in POTS, MCAS, ME/CFS, Autism, ADHD and Chronic Illness

Authors: Graham, Jessina;

Bioelectrical and Biological Pattern Failure Before Cell Death: A Recursive Diagnostic Terrain Model for Chronic Fatigue, Autonomic, and Immune Collapse in POTS, MCAS, ME/CFS, Autism, ADHD and Chronic Illness

Abstract

Title: Bioelectrical and Biological Pattern Failure Before Cell Death: A Recursive Diagnostic Terrain Model for Chronic Fatigue, Autonomic, and Immune Collapse in POTS, MCAS, ME/CFS, Autism, ADHD and Chronic Illness Patient and Provider Handouts with Clinical Walkthrough: https://grahammedical.substack.com/p/bioelectric-and-redox-terrain-failure Description:This work presents the second layer in a recursive diagnostic terrain framework that redefines redox imbalance, methylation collapse, and purinergic amplification as early, actionable checkpoints in complex chronic illness. It builds upon the foundational terrain architecture introduced in: Graham, J. (2025). Intracellular Iron Deficiency and Mitochondrial Iron Miscompartmentalization as a Convergent Mechanism... https://doi.org/10.5281/zenodo.15693226 Here, ferroptotic bias is recast not as a terminal event but as a nutrient- and redox-sensitive terrain checkpoint that precedes immune, vascular, and autonomic collapse. This system stratifies collapse trajectories across PEM, ME/CFS, POTS, MCAS, Autism, ADHD and related disorders. This links biochemical and bioelectrical signals (e.g. P2X7/NLRP3 activation, glutathione depletion, D-dimer/VEGF elevation) to terrain-based diagnostics that are clinically actionable. The model integrates evolutionary physiology, redox and mitochondrial biology, and methylation dynamics to detect pre-symptomatic failure and define therapeutic inflection points. It incorporates Michael Levin’s bioelectrical patterning model to explain morphogenetic disarray and immune bifurcation as pattern memory loss. Clinical Use & Licensing:Released under Creative Commons Attribution 4.0 International (CC BY 4.0) to support open access. A Scope and Clinical Use Declaration is embedded to define ethical and medico-legal parameters. While openly accessible, any clinical, translational, or derivative use requires full scope fidelity. Fragmented or decontextualized use risks iatrogenic harm, diagnostic misclassification, and therapeutic misdirection. This model is clinically actionable, recursive, non-theoretical, and diagnostically inseparable. It is a harm reduction tool. Author Context:Developed by a credentialed clinician with a background in zoology, former bedside nurse, and disabled patient. This work unites layered clinical insight, evolutionary modeling, and lived experience into a single recursive diagnostic lens. It is unapologetically patient-first and epistemically non-fragmentable. Ethics Statement: “Nothing about us, without us.” Those who do not recognize patient agency have no agency in this discussion.

Keywords

Fatigue Syndrome, Chronic, Mast Cell Activation Syndrome, Bioelectric Energy Sources, Autism Spectrum Disorder, neurodegeneration, Intracellular Space/metabolism, Iron Deficiencies, Ferroptosis/physiology, Autoimmune Diseases, myalgic encephalomyelitis, Postural Orthostatic Tachycardia Syndrome, Attention Deficit Disorder with Hyperactivity, Necroptosis/physiology, Pyroptosis/physiology, Dysautonomia, Familial/etiology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green