Plasma cytokine and exertional responses in relation to exercise intensity and volume of exercising muscle mass during arm-crank ergometry
Bibliographic record
Abstract
This original study investigated the effect of submaximal exercise intensity and volume of contracting muscle mass on plasma inflammation-mediating cytokine and perceived exertional responses to acute arm-crank ergometry (ACE). Twelve recreationally active but upper limb untrained males performed 30 min of (i) low-intensity (40% peak oxygen uptake) ACE (LOW); (ii) moderate-intensity (60% peak oxygen uptake) ACE (MOD); and (iii) concurrent low-intensity (40% peak oxygen uptake) ACE plus lower limb cycle ergometry to match total power output in MOD (HYB). Plasma concentrations of interleukin (IL)-6, IL-10, IL-1ra, adrenaline, and cortisol were determined at rest, immediately postexercise, and 1 h and 2 h postexercise. Heart rate (HR) and differentiated ratings of perceived exertion (RPE) were also recorded. Plasma IL-6 concentrations were elevated (p < 0.05) immediately postexercise and 1 h postexercise (∼ 2.5-fold) in all trials and 2 h postexercise in MOD (3-fold). Plasma IL-1ra concentrations were elevated (p < 0.05) 2 h postexercise in MOD only (2-fold). No plasma IL-10, cortisol, and adrenaline responses were observed. HR and differentiated RPE were significantly higher during MOD than HYB and LOW. Peripheral RPE were significantly higher than central and overall RPE in each trial. Thirty minutes of moderate intensity ACE initiated a plasma cytokine response associated with the protective effect of regular exercise against cardiovascular and metabolic disease risk. Further work is required to establish an optimal intensity and duration of upper limb exercise to maximise the anti-inflammatory potential whilst managing the risk of over-use injury.
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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".