Cytokine response to resistance exercise in children with excess adiposity and Prader‐Willi syndrome
Bibliographic record
Abstract
Interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and irisin (cytokines) are affected by excess body fat (obesity), skeletal muscle, and resistance exercise (RE). The purpose of this study is to determine whether Prader-Willi Syndrome (PWS), a genetic cause for obesity (OB), or non-syndromic OB influences these cytokine responses to RE. Nine children with PWS (11.4 ± 3.3 years, 45.6 ± 5.2% BF), 11 children without OB (9.2 ± 1.4 years, 18.6 ± 5.0% BF), and 12 children with OB (9.6 ± 1.3 years, 40.4 ± 5.4% BF) participated. Children stepped onto an elevated platform wearing a weighted vest for 6 sets of 10 repetitions per leg separated by 1 min of rest. Blood samples were obtained before exercise (pre), immediately post (IP), and during recovery (+15 and +60 min). There were no group-by-time interactions for any cytokine; and neither time nor group effects for TNF-α or irisin (p ≥ 0.378). For IL-6, 60+ was higher than pre, IP, and +15 (p < 0.001). Children with PWS and OB had increased IL-6 than children without OB (p ≤ 0.038). Neither PWS nor OB affected IL-6, TNF-α or irisin responses to RE. However, excess body fat was associated with higher IL-6 concentrations.
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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) | 0.001 | 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".