Peripheral expression of inflammatory markers in overweight female adolescents and eutrophic female adolescents with a high percentage of body fat
Bibliographic record
Abstract
The objective of this study was to evaluate the peripheral expression of inflammatory markers in adolescents with different nutritional status and its correlation with parameters of the metabolic syndrome. Seventy-two female postpubescent adolescents were divided into 3 groups: eutrophic (Co), eutrophic with a high body fat percentage (HBF), and overweight (OW). Data related to the parameters of the metabolic syndrome and the peripheral expression of tumour necrosis factor (TNF)-α, interleukin (IL)-6, and IL-10 were evaluated. Higher values of glycemia and insulin resistance were found in the HBF group than in the Co group. No differences related to the peripheral expression of the cytokines were found among the groups. In the HBF group, a positive correlation was observed between TNF-α and IL-6, IL-10 and the proinflammatory cytokines, and IL-6 and glycemia. In the OW group, a positive correlation was found between IL-6 and triglycerides. Adolescents with normal weight but body fat excess present a metabolic profile and body composition similar to those of overweight adolescents. This suggests that these adolescents have a risk of developing cardiovascular diseases similar to that of overweight adolescents. The positive correlation between IL-10 and TNF-α and IL-6 suggests an attempt to inhibit the production of these cytokines by IL-10.
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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) | 0.001 | 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".