Potential for creatine and other therapies targeting cellular energy dysfunction in neurological disorders
Bibliographic record
Abstract
Substantial evidence indicates that bioenergetic dysfunction plays either a primary or secondary role in the pathophysiology of cell death in neurodegenerative and neuromuscular disorders, and even in normal aging. Agents that ameliorate bioenergetic defects may therefore be useful in therapy. Creatine, which increases muscle and brain phosphocreatine concentrations, and may inhibit the activation of the mitochondrial permeability transition, protects against neuronal degeneration in transgenic murine models of amyotrophic lateral sclerosis and Huntington's disease and in chemically mediated neurotoxicity. Initial studies of creatine use in humans appear promising; however, further long-term, well-designed trials are needed. Coenzyme Q10, Gingko biloba, nicotinamide, riboflavin, carnitine, lipoic acid, and dichloroacetate are other agents which may have beneficial effects on energy metabolism, but the preclinical and clinical evidence for efficacy in neurological diseases remains limited. These compounds are widely used as dietary supplements; however, they must be subjected to rigorous evaluation through randomized, double-blinded trials to establish efficacy, cost-effectiveness and safety in neurological disorders.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".