The Effect of 12-Week Resistance Exercise on the Levels of Vaspin serum and Blood Pressure in Hypertensive Elderly Women
Bibliographic record
Abstract
Introduction: Adipose tissue as a gland, secreting hormones, including Vaspsin that are associated with metabolic disorders.The aim of of the present study was to investigate the effect of 12 week resistance exercise on plasma levels of vaspin and blood pressure (BP) in hypertensive elderly women. Methods: 30 hypertensive elderly women were randomly divided into two groups: the control and experimental groups. The training program, included resistance exercises, which were conducted increasingly for 12 weeks. Blood samples from all subjects after 12 weeks and were analyzed using t-test. Results: After 12 weeks of resistance exercise, no significant differences in the serum levels of vaspin was seen in the experimental group (p=0.25), but in the control group, significant Increase in the serum levels vaspin was observed (p=0.03); also, significant decreases were seen in both systolic (p=0.04) and diastolic BP (p=0.002 in the experimental group but in the control group, no significant changes were obtained in systolic BP (p=0.24) and diastolic BP (p=0.43), respectively. Conclusion: 12 weeks of resistance exercise can prevent increasing trend of vaspin serum levels and even reduce its levels Considering the reduction in systolic and diastolic BP following 12 weeks of resistance training, it can be indicated that the changes in BP are independent of changes is vaspin levels.
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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".