Effects of acupuncture on brain metabolism in patients with chronic partial sleep deprivation cognitive dysfunction: A case–control study
Bibliographic record
Abstract
Patients with chronic partial sleep deprivation (SD) may experience cognitive dysfunction. The purpose of this study is to explore the pathways of electroacupuncture (EA) by observing the changes in brain metabolites before and after EA treatment in patients with chronic partial SD cognitive dysfunction. The research subjects included 26 chronic partial SD cognitive dysfunction patients and 27 healthy subjects. Montreal Cognitive Assessment Scale, Pittsburgh Sleep Quality Index Scale (PSQI), Stanford Sleepiness Scale, Wechsler Memory Scale, Hamilton Anxiety Scale, Hamilton Depression Scale, Stroop paradigm, psychomotor vigilance test, 2-back test task, and mood assessment test were used to assess sleep quality, cognitive function, and emotional state of subjects. Magnetic resonance spectroscopy was used to detect the basal ganglia of the brain, and the characteristics of metabolites of the 2 groups were comprehensively analyzed, and the correlation with clinical cognitive function evaluation indicators was analyzed. Compared with the control group, the Montreal Cognitive Assessment Scale and Wechsler Memory Scale scores of the observation group were reduced before treatment, while the Pittsburgh sleep quality index, Hamilton Anxiety Scale, and Hamilton Depression Scale scores were improved. The completion ability of Stroop, 2-back, and psychomotor vigilance test decreased. The GABA/Cr on the left side of the basal ganglia area increased. "Adjusting Zang-fu and Arousing Spirit" EA can improve the sleep quality and cognitive function of chronic partial sleep deprivation cognitive dysfunction patients, which may be related to regulating the levels of NAA, Cho, and GABA in the basal ganglia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".