Obestatin and growth hormone reveal the interaction of central obesity and other cardiometabolic risk factors of metabolic syndrome
Bibliographic record
Abstract
Metabolic syndrome (MetS) is a multi-factorial disorder including central obesity (CO), insulin resistance, hyperglycemia, dyslipidemia and hypertension which increases the risk of diabetes mellitus and cardiovascular diseases. CO is considered as an essential component of MetS according to International Diabetes Federation (IDF), which may further modulate distinct signalling pathways compared with the other four MetS risk factors. Given that ghrelin signalling and the growth hormone/insulin-like growth factor-1 (GH/IGF-1) axis regulates energy balance and metabolic homeostasis, this study examined the changes in various ghrelin products and circulating hormones in response to the interaction between CO and other MetS components including blood pressure, fasting blood glucose, triglycerides, and high-density lipoprotein cholesterol in 133 Hong Kong Chinese adults. Circulating obestatin and GH were increased and reduced, respectively, by either CO or the other 4-risk factor cluster. These changes were further augmented by the presence of all MetS risk factors. However, changes of ghrelin levels were not mediated by CO but the other MetS risk factors. Our findings suggest that CO does not predict all the dysregulation of signalling pathways in individuals with MetS. Although CO and other MetS may share common signalling targets (i.e., obestatin and GH), CO does not contribute to the perturbation of ghrelin signalling.
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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".