The role of dietary supplements that modulate one-carbon metabolism on stroke outcome
Bibliographic record
Abstract
PURPOSE OF REVIEW: Ischemic stroke results in disability and mortality worldwide. Nutrition is a modifiable risk factor for stroke. For example, deficiencies in one-carbon metabolism have been linked to increased risk of stroke through elevated levels of homocysteine. Some countries world-wide fortify their diets with folates to prevent neural tube defects, but deficiencies in other one-carbon metabolites, such as vitamin B12 and choline are still present in many populations. The aim of this review is to understand the current evidence on how dietary supplementation by nutrients which modulate one-carbon metabolism impact stroke outcome. RECENT FINDINGS: The results from clinical studies evaluating lowering homocysteine through B-vitamin supplementation on stroke risk remain unclear. Other clinical and preclinical studies have shown increasing dietary intake of one-carbon metabolism has some benefit on stroke outcome. Preclinical studies have shown that increased levels of nutrients which modulate one-carbon metabolism help facilitate recovery in damage models of the central nervous system. One the mechanisms driving these changes is neuroplasticity. SUMMARY: The data suggest that increasing dietary nutrients that modulate one-carbon metabolites in patients that are at a higher risk for and suffer from central nervous system diseases, such as stroke, could benefit in addition to other therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".