The neuroprotective effects of caffeine in neurodegenerative diseases
Bibliographic record
Abstract
Summary Caffeine is the most widely used psychostimulant in Western countries, with antioxidant, anti‐inflammatory and anti‐apoptotic properties. In Alzheimer's disease ( AD ), caffeine is beneficial in both men and women, in humans and animals. Similar effects of caffeine were observed in men with Parkinson's disease ( PD ); however, the effect of caffeine in female PD patients is controversial due to caffeine's competition with estrogen for the estrogen‐metabolizing enzyme, CYP 1A2. Studies conducted in animal models of amyotrophic lateral sclerosis (ALS) showed protective effects of A 2 A R antagonism. A study found caffeine to be associated with earlier age of onset of Huntington's disease ( HD ) at intakes >190 mg/d, but studies in animal models have found equivocal results. Caffeine is protective in AD and PD at dosages equivalent to 3‐5 mg/kg. However, further research is needed to investigate the effects of caffeine on PD in women. As well, the effects of caffeine in ALS , HD and Machado‐Joseph disease need to be further investigated. Caffeine's most salient mechanisms of action relevant to neurodegenerative diseases need to be further explored.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".