Resistance training reduces platelet activation in hypertensive women: the role of purinergic signaling
Bibliographic record
Abstract
BACKGROUND AND AIM: Essential arterial hypertension is a risk factor for stroke, myocardial infarction, heart failure, and arterial aneurysm, which are related to the activation of platelets. Purinergic signaling has a central role in platelet aggregation. Although ATP and ADP can act as a proaggregant agent, adenosine inhibits platelet aggregation and reduces vascular injury. Physical exercise exhibits antiaggregant properties and can modulate purinergic system. The aim of this study was to evaluate the effect of 6 months of resistance training on purinergic system components in platelets and on platelet activation, hemodynamic and anthropometric parameters in hypertensive woman. METHOD: A total of 31 hypertensive and 28 normotensive middle-aged sedentary women were submitted to 6 months of resistance training. Purinergic enzymes activities were assessed in platelets; ATP and Tromboxane B2 (TXB2) levels were measured in serum. Blood pressure (BP), BMI, and body fat were also measured. All variables were statistically analyzed, considering P value less than 0.05. RESULTS: Six months of resistance training was able to significantly reduce BP, ATP, and TXB2 levels as well as NTPDase, ecto-5'nucleotidase, and ADA activities in hypertensive group. After 6 months of resistance training, purinergic system components and TXB2 of hypertensive group were similar to normotensive group in platelets, demonstrating that resistance training was able to modulate platelet activation. A positive correlation was found between BP, enzyme activities, and levels of ATP and TXB2. CONCLUSION: Our findings demonstrated the relationship between purinergic signaling and platelet activation in hypertension and suggests that resistance training serve as tool to reduce platelet aggregation in hypertensive woman by modulating purinergic system.
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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".