Exercise Induced Adipokine Changes and the Metabolic Syndrome
Bibliographic record
Abstract
The lack of adequate physical activity and obesity created a worldwide pandemic. Obesity is characterized by the deposition of adipose tissue in various parts of the body; it is now evident that adipose tissue also acts as an endocrine organ capable of secreting many cytokines that are though to be involved in the pathophysiology of obesity, insulin resistance, and metabolic syndrome. Adipokines, or adipose tissue-derived proteins, play a pivotal role in this scenario. Increased secretion of proinflammatory adipokines leads to a chronic inflammatory state that is accompanied by insulin resistance and glucose intolerance. Lifestyle change in terms of increased physical activity and exercise is the best nonpharmacological treatment for obesity since these can reduce insulin resistance, counteract the inflammatory state, and improve the lipid profile. There is growing evidence that exercise exerts its beneficial effects partly through alterations in the adipokine profile; that is, exercise increases secretion of anti-inflammatory adipokines and reduces proinflammatory cytokines. In this paper we briefly describe the pathophysiologic role of four important adipokines (adiponectin, leptin, TNF-α, and IL-6) in the metabolic syndrome and review some of the clinical trials that monitored these adipokines as a clinical outcome before and after exercise.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".