The effects of type of recovery in resistance exercise on responses of platelet indices and hemodynamic variables
Bibliographic record
Abstract
To examine the effects of two different volume-matched resistance exercise (RE) recovery protocols (passive and active) on platelet indices and hemodynamic variables. Twelve Healthy participants (mean ± SD; 25 ± 3 yrs) completed a traditional resistance exercise (TRE) protocol that included three sets of six repetitions at 80% one repetition maximum (1RM) with two minutes passive recovery between sets, exercises and an interval resistance exercise (IRE) protocol that included three sets of six repetitions at 60%1RM followed by active recovery including six repetitions of the same exercise at 20%1RM. Blood samples for multiple platelet indices were taken before the protocols, immediately-post (IP), and after 1-hour recovery. Hemodynamic variables were measured before, IP, and every five minutes during recovery. Mean platelet volume and platelet large cell ratio P_LCR decreased from baseline to recovery. Heart rate (HR) and rate pressure product (RPP) were augmented at IP following IRE compared to TRE. HR was significantly elevated for 20 minutes after both RE protocols, and RPP recovered by five minutes. Systolic blood pressure was increased at IP compared to baseline and all recovery time points for both RE protocols. Our research demonstrated that both RE protocols, produced transient increases in platelet indices (MPV, and P_LCR) and hemodynamic variables (SBP, HR, and RPP), all of which returned to baseline within an hour. Notably, the IRE protocol elicited a greater increase in HR and RPP compared to the TRE protocol.
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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 | 0.001 |
| 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 | 0.000 | 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".