β-alanine Supplementation Improves Fractional Anisotropy Scores In The Hippocampus And Amygdala In Older Adults.
Bibliographic record
Abstract
PURPOSE: Recently, β-alanine (BA) supplementation was shown to improve cognitive function in adults with decreased cognitive function. However, the mechanisms underlying 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. METHODS: Twenty adult men and women between the age of 60-80 years were randomized into a BA (2.4 g·d-1) or placebo (PL) group. At each testing session, participants provided a resting blood sample and completed the Montreal cognitive assessment (MoCA) test and magnetic resonance imaging (MRI), which included diffusion tensor imaging (DTI) 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. RESULTS: No difference (p = 0.331) was observed in the MoCA Δ score between BA (2.7 ± 2.1) and PL (0.8 ± 2.6). In addition, no differences (p’s > 0.05) in Δ scores were noted in any blood marker (BDNF, CRP, TNFα and GFAP). MRI analysis included total volume and volume of both white and gray matter. Changes in the total volume of the right hippocampus (0.026 ± 0.257 ml and -0.493 ± 0.044 ml), and both right (-0.005 ± 0.034 ml and -0.056 ± 0.018 ml) and left amygdala (0.045 ± 0.067 ml and -0.043 ± 0.043 ml) trended towards significance (p = 0.063 for all regions) between BA and PL, respectively. These results suggested that the change of total brain volume for BA tended to be greater than PL. However, no changes were noted in volume of either gray or white matter. Analysis of DTI data resulted in changes in fractional anisotropy (FA) scores that were significantly greater for BA (0.002 ± 0.012 and 0.017 ± 0.02) than PL (-0.023 ± 0.016 and -0.031 ± 0.042) in the right hippocampus (p = 0.033) and the left amygdala (p = 0.05), respectively. No other differences were noted in any other DTI indices measured by MRI. CONCLUSIONS: Results provided a potential mechanism of how BA supplementation may improve cognitive function as reflected by improved tissue integrity within the hippocampus and amygdala. This research was funded by Natural Alternative Inc. (Carlsbad, CA, USA).
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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".