Brain Creatine is associated with cognitive function but dietary supplementation does not affect memory performance in the young Yucatan miniature pig
Bibliographic record
Abstract
Creatine supplementation may enhance memory in humans. We measured creatine in liver and brain and analyzed the effect on memory performance in 3‐mo‐old pigs fed diets unsupplemented (n=7) or supplemented with 200 mg creatine/kg/d (CR; n=8) for 2 wk. In a 5′x5′ pen, pigs explored 2 sets (4As, 4Bs) of objects 50 min apart. Pigs were then tested with both objects (2As+2Bs) with one of each object in the same position as before (A1, B1), and the others moved (Am, Bm); the test was repeated 24 h later with a third object (C). Pigs looked at first (p=0.004) and spent more time with (p<0.001) the moved objects, validating this memory test in pigs. Creatine was higher in CR liver (p=0.002), but lower in CR brain (p<0.03), suggesting dietary creatine did not reach the brain. Memory test outcomes were not different between diet groups. However, pigs that exhibited a better memory of object A had higher levels of the creatine precursor, GAA, in the brain (p=0.01, R 2 =0.41; linear regression). Moreover, 24 h later, creatine and GAA (p<0.05, R 2 =0.29) were associated with recognizing C as novel. Interestingly, memory was also negatively associated with plasma homocysteine (p=0.04, R 2 =0.37). We conclude that creatine is associated with improved memory performance, but dietary supplementation was not effective. A pre‐existing deficiency might need to be present to observe an effect of supplementation, similar to that observed in vegans.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".