β-Alanine supplementation improves fractional anisotropy scores in the hippocampus and amygdala in 60–80-year-old men and women
Bibliographic record
Abstract
Recently, β-alanine (BA) supplementation was shown to improve cognitive function in older adults with decreased cognitive function. Mechanisms supporting these improvements have not been well defined. This study examined the effects of 10-weeks of BA supplementation on changes in circulating brain inflammatory markers, brain derived neurotrophic factor (BDNF), and brain morphology. Twenty participants were initially randomized into BA (2.4 g·d−1) or placebo (PL) groups. At each testing session, participants provided a resting blood sample and completed the Montreal cognitive assessment (MoCA) test and magnetic resonance imaging, which included diffusion tensor imaging to assess brain tissue integrity. Only participants that scored at or below normal for the MoCA assessment were analyzed (6 BA and 4 PL). The Mann-Whitney U test was used to examine Δ (POST–PRE) differences between the groups. No differences in Δ scores were noted in any blood marker (BDNF, CRP, TNF-α and GFAP). Changes in fractional anisotropy scores were significantly greater for BA than PL in the right hippocampus (p = 0.033) and the left amygdala (p = 0.05). No other differences were noted. The results provide a potential mechanism of how BA supplementation may improve cognitive function as reflected by improved tissue integrity within the hippocampus and amygdala.
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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".