ingest: MS myelin glucose signaling article (2026-05-04)

Brain glucose levels regulate OPC fate: high glucose → proliferation,
low glucose → maturation. Acetyl-CoA from glucose drives histone
acetylation for OPC division; ketone bodies substitute for myelin
synthesis. Ketogenic diet rescues myelin in ACLY-deficient mice.

Connects to: N-Dimensional Gene Hypothesis, PIST polymorphic shifter,
topological state machine, FAMM delay lines, waveprobe manifolds
This commit is contained in:
Brandon Schneider 2026-05-06 23:53:20 -05:00
parent bf1c44ce4b
commit 70f9b10127
7 changed files with 183 additions and 0 deletions

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#!/usr/bin/env python3
"""Ingest MS myelin glucose signaling article into Research Stack database."""
import json, time, hashlib
from pathlib import Path
RESEARCH_STACK = Path("/home/allaun/Documents/Research Stack")
ARTICLE = {
"id": "ms-myelin-glucose-2026-05-04",
"source": "https://multiplesclerosisnewstoday.com/news-posts/2026/05/04/brain-sugar-levels-act-signal-myelin-growth-study-finds/",
"title": "Brain sugar levels act as signal for myelin growth, study finds",
"date": "2026-05-04",
"publication": "Multiple Sclerosis News Today",
"summary": "Glucose levels in the brain regulate oligodendrocyte progenitor cell (OPC) fate — high glucose drives OPC proliferation via histone acetylation, low glucose triggers maturation into myelin-producing oligodendrocytes. Acetyl-CoA from glucose is required for OPC division; mature oligodendrocytes can source acetyl-CoA from ketone bodies for myelin synthesis. ACLY enzyme knockout reduces early myelin but ketogenic diet rescues it.",
"key_findings": [
"OPC activity correlates with local brain glucose levels",
"High glucose → acetyl-CoA → histone acetylation → OPC proliferation",
"Low glucose → OPC maturation into myelin-producing oligodendrocytes",
"ACLY enzyme required for glucose-to-acetyl-CoA conversion in OPCs",
"Mature oligodendrocytes use ketone bodies as alternative acetyl-CoA source",
"Ketogenic diet rescues myelin production in ACLY-deficient mice",
"Same cell lineage interprets different metabolic signals at distinct stages"
],
"relevance_to_research_stack": {
"topics": [
"metabolic_epigenetic_switch",
"myelin_repair_mechanism",
"glucose_signaling_pathway",
"oligodendrocyte_differentiation",
"ketogenic_metabolic_intervention",
"histone_acetylation_gene_regulation"
],
"connections": [
"N-Dimensional Gene Hypothesis: glucose gradient as spatial morphogen signal",
"PIST biological polymorphic shifter: metabolic state → cell fate switch",
"Topological state machine: glucose level as continuous state variable",
"FAMM delay lines: metabolic latency in cell fate decisions",
"Waveprobe manifolds: glucose gradient as scalar field on brain manifold"
]
},
"metadata": {
"ingested_at": time.time(),
"content_hash": hashlib.sha256(
"glucose myelin OPC oligodendrocyte acetyl-CoA ACLY ketogenic histone acetylation".encode()
).hexdigest()[:16],
"tags": ["neuroscience", "metabolism", "myelin", "multiple-sclerosis", "epigenetics", "glucose-signaling"]
}
}
def ingest():
# Save to germane research data
germane_dir = RESEARCH_STACK / "shared-data/data/germane/research"
germane_dir.mkdir(parents=True, exist_ok=True)
out_path = germane_dir / "ms_myelin_glucose_signaling_2026-05-04.json"
with open(out_path, 'w') as f:
json.dump(ARTICLE, f, indent=2)
print(f"✓ Ingested: {out_path}")
# Append to research index
index_path = germane_dir / "research_ingestion_index.json"
index = []
if index_path.exists():
with open(index_path) as f:
index = json.load(f)
index.append({
"id": ARTICLE["id"],
"title": ARTICLE["title"],
"date": ARTICLE["date"],
"source": ARTICLE["source"],
"ingested_at": ARTICLE["metadata"]["ingested_at"],
"tags": ARTICLE["metadata"]["tags"],
})
with open(index_path, 'w') as f:
json.dump(index, f, indent=2)
print(f"✓ Index updated: {index_path} ({len(index)} entries)")
# Print connections
print(f"\nResearch Stack connections:")
for conn in ARTICLE["relevance_to_research_stack"]["connections"]:
print(f"{conn}")
if __name__ == "__main__":
ingest()

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@ -29,3 +29,6 @@ counts, decompressor cost, and comparison baselines.
* [[Hutter Prize Compression]]
* [[Hutter Tensor Field Analysis DAG]]
* [[Mass Number Sidecar Rule]]
* [[Pathological Manifold Torus]]
* [[Pathological Menger-Horn Composite]]
* [[Pathological PIST Shells]]

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@ -16,6 +16,9 @@ work.
* [[PIST Shifters]]
* [[Soliton N-Space Path]]
* [[Compression and Soliton Mining]]
* [[Pathological Manifold Torus]]
* [[Pathological Menger-Horn Composite]]
* [[Pathological PIST Shells]]
!! Durable Sources

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@ -15,6 +15,9 @@ variants.
* [[Hutter Prize Compression]]
* [[Soliton N-Space Path]]
* [[Compression and Soliton Mining]]
* [[Pathological PIST Shells]]
* [[Pathological Manifold Torus]]
* [[Pathological Menger-Horn Composite]]
!! Durable Source

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created: 20260506230000000
modified: 20260506230000000
tags: ResearchStack Compression Hutter CAD Geometry Torus
title: Pathological Manifold Torus
type: text/vnd.tiddlywiki
! Pathological Manifold Torus
3D slice of a hypertorus used as a PIST pathological manifold for Hutter Prize
compression geometry. A 3D projection of the 4D structure, with points sampled
via irrational φ-rotations (Φ, Φ², Φ³) and the psi angle encoded as color.
The torus provides periodic boundary conditions for routing across the
compression manifold — no endpoints, no zero-mass singularities.
!! Links
* [[Hutter Prize Compression]]
* [[Pathological Menger-Horn Composite]]
* [[Pathological PIST Shells]]
!! Durable Source
`../../3-Mathematical-Models/cad_models/hypertorus_slice.scad`

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created: 20260506230000000
modified: 20260506230000000
tags: ResearchStack Compression Hutter CAD Geometry MengerSponge GabrielHorn
title: Pathological Menger-Horn Composite
type: text/vnd.tiddlywiki
! Pathological Menger-Horn Composite
Composite manifold: Menger sponge nodes mounted as structural attachment points
along Gabriel's horn backbone (x-axis curve y = 1/x). PIST shell coordinates are
nested inside each sponge node.
The horn provides infinite surface area with finite volume — the byte container
surface. The Menger sponge provides fractal addressing (Hausdorff dimension
~2.7268) for routing between shells. Together they form one of three pathological
manifolds for Hutter Prize compression-geometry folding.
Composite structure is Torus-Menger-Horn, as referenced in
[[04_Hutter_Prize_Equation.md|Hutter Prize Equation §Torus-Menger-Horn folding]].
!! Links
* [[Hutter Prize Compression]]
* [[Pathological Manifold Torus]]
* [[Pathological PIST Shells]]
!! Durable Source
`../../3-Mathematical-Models/cad_models/composite_manifold.scad`

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created: 20260506230000000
modified: 20260506230000000
tags: ResearchStack Compression Hutter CAD Geometry PIST Shells
title: Pathological PIST Shells
type: text/vnd.tiddlywiki
! Pathological PIST Shells
Concentric polygonal rings representing PIST shell encoding. Each shell k is
drawn as a regular (2k+1)-gon with radius proportional to k. Mirror involution
axes are marked at the t = k symmetry points (red markers).
Inner shells are dense with low curvature; outer shells are sparse with high
curvature — this is the tension gradient used in compression. The mirror
involution (k, t) → (k, 2k+1-t) preserves mass and is self-inverse, providing
the geometric basis for resonance jumps and shell-preserving RG flow.
One of three pathological manifold structures (Torus-Menger-Horn) for Hutter
Prize compression folding.
!! Links
* [[PIST Shifters]]
* [[Hutter Prize Compression]]
* [[Pathological Manifold Torus]]
* [[Pathological Menger-Horn Composite]]
!! Durable Source
`../../3-Mathematical-Models/cad_models/pist_shells.scad`