Effects of whey-derived lactopeptide β-lactolin on cognitive performance in mild cognitive impairment: a randomized, double-blind, placebo-controlled trial
Bibliographic record
Abstract
Objective This study aimed to investigate the effects of a long-term intervention with β-lactolin, a tetrapeptide (sequence: glycine-threonine-tryptophan-tyrosine) derived from milk, on cognitive performance in individuals with mild cognitive impairment (MCI).Methods A randomized, double-blind, placebo-controlled trial was conducted. We recruited 48 participants aged 50 years or older with the Japanese version of the Mini-Mental State Examination (MMSE-J) score of 24–28 and a Clinical Dementia Rating (CDR) score of 0.5. Participants were administered β-lactolin (1.8 mg daily) or placebo for 24 weeks. The primary outcomes were the MMSE-J and the Japanese version of the Montreal Cognitive Assessment (MoCA-J) scores for cognitive function.Results A total of 422 individuals were screened, 48 of whom were included in this study. The MMSE-J and MoCA-J scores showed no significant differences between the groups. In the intra-group comparison of the MoCA-J delayed recall score, a significant difference was observed in the β-lactolin group after 12 and 24 weeks of intervention (p = 0.0256, p = 0.0175, respectively). Furthermore, the subgroup analysis stratified for females only showed a significant difference in MoCA-J total score in the β-lactolin group after 24 weeks of intervention (p = 0.0253).Conclusion β-lactolin intake does not significantly improve cognitive function in MCI in an inter-group comparison; nevertheless, the MoCA-J delayed recall score was significantly improved in the β-lactolin group. The number of participants was lower than planned, limiting the confirmation of the effectiveness of β-lactolin on MCI. This report demonstrated the effect size of β-lactolin intervention in MCI, contributing insights for future research.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".