Evidence of Metabolic Dysfunction in Amyotrophic Lateral Sclerosis (ALS) Patients and Animal Models
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that affects motor neurons, leading to muscle weakness, paralysis, and eventual death. Research from the past few decades has appreciated that ALS is not only a disease of the motor neurons but also a disease that involves systemic metabolic dysfunction. This review will examine the foundational research of understanding metabolic dysfunction in ALS and provide an overview of past and current studies in ALS patients and animal models, spanning from full systems to various metabolic organs. While ALS-affected muscle tissue exhibits elevated energy demand and a fuel preference switch from glycolysis to fatty acid oxidation, adipose tissue in ALS undergoes increased lipolysis. Dysfunctions in the liver and pancreas contribute to impaired glucose homeostasis and insulin secretion. The central nervous system (CNS) displays abnormal glucose regulation, mitochondrial dysfunction, and increased oxidative stress. Importantly, the hypothalamus, a brain region that controls whole-body metabolism, undergoes atrophy associated with pathological aggregates of TDP-43. This review will also cover past and present treatment options that target metabolic dysfunction in ALS and provide insights into the future of metabolism research in ALS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".