Brain Vitalization Gymnastics Improved Cognitive Function Marked by Increased BDNF, Decreased Serum Interleukin-6 and Decreased S-100β Expression among Elderly in West Denpasar Primary Health Clinic
Bibliographic record
Abstract
BACKGROUND: Brain vitalisation gymnastics (BVG) is a form of physical exercise which attempts to synchronise bodily movements with cognition within the same time frame. AIM: This study aims to prove BVG can improve cognitive function among the elderly. METHODS: The impact of BVG was evaluated as opposed to elderly gymnastics (regarded as a control group) for a 4-week study period. Outcomes measured were improvements of cognitive function assessed by MoCA-Ina questionnaire, as well as the difference in serum levels of BDNF, IL-6, and S100β. An experimental pretest-posttest control design was applied to evaluate BDNF and IL-6 levels, while the post-test only designed to evaluate S100β levels. Parametric data were tested for normality before being proceeded into either parametric (independent student' t) or non-parametric (Mann Whitney) test. RESULTS: BVG significantly improved cognitive function better than elderly gymnastics with MoCA-Ina score of 1.53 ± 1.58 dan 0.11 ± 2.54, respectively (p ≤ 0.047). BVG group also had increased BDNF levels when compared with control (-6020.58 ± 7857.22 dan 0.11 ± 2.54; p = 0.027). Whereas BVG had lower IL-6 levels as opposed to the control group (median pre-test IL-6: 2212, median post-test IL-6: 3197.50; p = 0.004). Meanwhile, S100β levels were found lower among BVG when compared with the control group, although statistically insignificant (p = 0.40). CONCLUSION: BVG programme for 4 weeks improved: (1) brain plasticity as shown by increased serum BDNF and S100β levels (although the latter was statistically not-significant), as well as marked decrease of IL-6 levels, (2) cognitive function as proven by an increase of MoCA-Ina score when compared with elderly gymnastics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".