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🌿 K Mackintosh FMRC

The Fungal–mTOR Regenerative Circuit

Where biology, computation, and consciousness converge.
Open research in quantum biology, regenerative systems, and neuromorphic intelligence.

Website Substack Repo License


🧬 Overview

The FMRC explores how life maintains its harmonic equilibrium — the delicate balance between growth, repair, and intelligence — through the interaction of fungal metabolites, cellular signaling, and quantum computation principles.

This repository hosts the code, models, and publications supporting the discovery of the Fungal–mTOR Regenerative Circuit (FMRC) — a systems-biology framework revealing how nature’s oldest intelligences (Basidiomycetes, elephants, and cellular ecosystems) regulate longevity, repair, and consciousness through biophysical resonance.

“Fungi taught the planet how to recycle energy before DNA learned to evolve.”


🔬 Core Research Modules

Module Focus Key Output
src/fmr_circuit/models.py mTOR/AMPK/SIRT1–TP53–Autophagy simulation ODE-based cellular feedback model
src/fmr_circuit/ecology.py Ecological metabolite-to-cellular transfer PK bridge from environment to intracellular levels
notebooks/02_generate_figures.ipynb Reproducible figures and data visualization Publication-ready images and tables
notebooks/03_insert_figures_with_captions.ipynb Auto-figure injection pipeline Markdown-ready papers with embedded figures
docs/paper_draft_auto.md Generated manuscript Version-controlled paper with embedded visuals

🧫 Biological Hypothesis

The FMRC proposes that:

  1. Basidiomycete fungi produce ergothioneine, β-glucans, and triterpenes that fine-tune cellular mTOR/AMPK balance.
  2. These metabolites signal autophagic repair, pluripotency maintenance, and TP53 activation, preventing degenerative collapse.
  3. In elephants and other long-lived species, redundant TP53 copies and ecological diet synergy sustain telomere integrity and mitochondrial resilience.
  4. The same pathway can be simulated, measured, and reintroduced into human physiology through targeted dietary, mycological, and quantum-biological approaches.

🧠 Computational Framework

Built with a hybrid model of Systems Biology + Neuromorphic Logic:

  • Mathematical core: coupled differential equations representing mTOR ↔ AMPK ↔ TP53 dynamics.
  • Data layer: ecological → biochemical → cellular transfer models.
  • Simulation engine: solve_ivp() with configurable metabolite intakes and environmental conditions.
  • Visualization layer: automatic heatmaps, 3D surfaces, and multi-panel figures.
  • Publication layer: executable notebooks that compile a full paper (with figures and captions) into docs/paper_draft_auto.md.

🧩 Installation

git clone https://github.com/mackKaliOs/fungal-mtor-regenerative-circuit/tree/main
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

📚 Citation

If you use this research, please cite:

Mackintosh, K. (2025). The Fungal–mTOR Regenerative Circuit: An Ecological and Computational Model for Cellular Longevity. The Mackintosh Code (v1.0). https://kayleighymackintosh.substack.com

🌿 License

This project is licensed under the MIT License. © 2025 Kayleighy Mackintosh — Open Science for Regeneration and Truth.

🤝 Funding & Collaboration

The Fungal–mTOR Regenerative Circuit (FMRC) is open for collaborative research, experimental validation, and multi-disciplinary partnerships.

🌱 Focus Areas Quantum Biology • Neuroenergetics • Mitochondrial Longevity Mycology • Ergothioneine Synthesis • Metabolite Pathways Neuromorphic Computation • Regenerative Medicine • Oncology

If you are an institution, researcher, or foundation interested in supporting this work, please connect:

📧 research@mackintoshenterprises.com • 🌐 mackintoshenterprises.com • 🧬 Substack: The Mackintosh Code

“Open collaboration accelerates evolution — from biology to code, from cell to cosmos.”

About

Open-source research on the ecological and biochemical mechanisms of regeneration. Models the interaction between Basidiomycete metabolites, mTOR/AMPK/SIRT1 signaling, and TP53/autophagy balance — bridging ecology, computation, and cellular longevity.

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