Effects of Cognitive Intervention and Rehabilitation Training on the Expression of miR-134-5p in Elderly Patients with Diabetes Mellitus and Cognitive Impairment
Bibliographic record
Abstract
OBJECTIVE: This study aimed to analyze the effect and potential mechanism of cognitive intervention and rehabilitation training in elderly patients with diabetes mellitus complicated with mild cognitive impairment. METHODS: In this study, 128 elderly patients with diabetes mellitus complicated with mild cognitive impairment were randomly divided into the control group and the training group. The effects of the two groups were compared before and after the cognitive intervention. The expression of miR-134-5p was assessed by qRT-PCR. The relationships between miR-134-5p and Mini-Mental State Examination Scale and Montreal Cognitive Assessment Scale were evaluated. RESULTS: After 3-month management, the Mini-Mental State Examination Scale, Montreal Cognitive Assessment Scale, the Chinese version of the diabetes self-efficacy rating scale, and WHO quality of life brief were improved in both control group and training group, and the training group showed better improvement. Cognitive intervention and rehabilitation training restricted the expression of miR-134-5p. The levels of miR-134-5p were pertinent to cognitive function. CONCLUSION: Cognitive intervention and rehabilitation training might prevent the development of diabetes mellitus complicated with mild cognitive impairment by inhibiting miR-134-5p.
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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".