Myokine Response to Blood-Flow Restricted Resistance Exercise in Younger and Older Males in an Untrained and Resistance-Trained State: A Pilot Study
Bibliographic record
Abstract
Abstract Purpose The purpose of this study was to examine the response of myokines to blood-flow restricted resistance-exercise (BFR-RE) in younger and older males before and after completing a 12-week resistance-training program. Methods There were 8 younger (24.8 ± 3.9 yrs) and 7 older (68.3 ± 5.0 yrs) untrained male participants completed this study. Anthropometric and maximal strength (1RM) measurements were collected before and after a 12-week, supervised, progressive full-body resistance-training program. As well, an acute bout of full-body BFR-RE was performed with venipuncture blood samples collected before and immediately following the BFR-RE, followed by sampling at 3, 6, 24 and 48 h. Results The 12-week training program stimulated a 32.2% increase in average strength and 30% increase in strength per kg of fat free mass. The response of particular myokines to the acute bout of BFR-RE was influenced training status (IL-4, untrained = 78.1 ± 133.2 pg/mL vs. trained = 59.8 ± 121.6 pg/mL, P = 0.019; IL-7, untrained = 3.46 ± 1.8 pg/mL vs. trained = 2.66 ± 1.3 pg/mL, P = 0.047) or both training and age (irisin, P = 0.04; leukemia inhibitory factor, P < 0.001). As well, changes in strength per kg of fat free mass were correlated with area under the curve for IL-4 (r = 0.537; P = 0.039), IL-6 (r = 0. 525; P = 0.044) and LIF (r = − 0.548; P = 0.035) in the untrained condition. Conclusion This study identified that both age and training status influence the myokine response to an acute bout of BFR-RE with the release of IL-4, IL-6 and LIF in the untrained state being associated with changes in strength per kg of fat free mass.
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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) | 0.002 | 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".