Cytokine Responses to Acute Intermittent Aerobic Exercise in Children with Prader-Willi Syndrome and Nonsyndromic Obesity
Bibliographic record
Abstract
Prader-Willi Syndrome (PWS), the best characterized form of syndromic obesity, presents with abnormally high fat mass. In children, obesity presents with low-grade systemic inflammation. This study evaluated if PWS and/or nonsyndromic obesity affected cytokine responses to intermittent aerobic exercise in children. Eleven children with PWS (11 ± 2 y, 45.4 ± 9.5% body fat), 12 children with obesity (OB) (9 ± 1 y, 39.9 ± 6.8% body fat), and 12 lean (LN) children (9 ± 1 y, 17.5 ± 4.6% body fat) participated. Children completed 10 2-min cycling bouts of vigorous intensity, separated by 1-min rest. Blood samples were collected preexercise (PRE), immediately postexercise (IP), and 15, 30, and 60 min into recovery to analyze possible changes in cytokines. In all groups, IL-6 and IL-8 concentrations were greater during recovery compared with PRE. PWS and OB exhibited higher IL-6 area under the curve (AUC) than LN (p < .01 for both). PWS demonstrated higher IL-8 AUC than LN (p < .04). IL-10, TNF-α, and IFN-γ did not change with exercise (p > .05 for all). Results indicate that children with PWS respond with increased Il-6 and IL-8 concentrations to acute exercise similarly to controls. Excess adiposity and epigenetic modifications may explain the greater integrated IL-6 and IL-8 responses in PWS compared with controls.
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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".