Mindfulness intervention improves cognitive function in older adults by enhancing the level of miRNA-29c in neuron-derived extracellular vesicles
Bibliographic record
Abstract
Although mindfulness-based stress reduction (MBSR) improves cognitive function, the mechanism is not clear. In this study, people aged 65 years and older were recruited from elderly communities in Chitose City, Japan, and assigned to a non-MBSR group or a MBSR group. Before and after the intervention, the Japanese version of the Montreal Cognitive Assessment (MoCA-J) was administered, and blood samples were collected. Then, neuron-derived extracellular vesicles (NDEVs) were isolated from blood samples, and microRNAs, as well as the target mRNAs, were evaluated in NDEVs. A linear mixed model analysis showed significant effects of the MBSR x time interaction on the MoCA-J scores, the expression of miRNA(miR)-29c, DNA methyltransferase 3 alpha (DNMT3A), and DNMT3B in NDEVs. These results indicate that MBSR can improve cognitive function by increasing the expression of miR-29c and decreasing the expression of DNMT3A, as well as DNMT3B, in neurons. It was also found that intracerebroventricular injection of miR-29c mimic into 5xFAD mice prevented cognitive decline, as well as neuronal loss in the subiculum area, by down-regulating Dnmt3a and Dnmt3b in the hippocampus. The present study suggests that MBSR can prevent neuronal loss and cognitive impairment by increasing the neuronal expression of miR-29c.
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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".