Role of Adiponectin in Modulating Insulin Resistance in Visceral Obesity-Associated Type 2 Diabetes Mellitus
Bibliographic record
Abstract
Background: Visceral obesity is a key determinant of insulin resistance and pathogenesis of type 2 diabetes mellitus (T2DM). Adiponectin is an adipokine predominantly secreted by visceral adipose tissue, characterized by potent anti-inflammatory and insulin-sensitizing properties. The reduction of adiponectin in obesity may contribute to metabolic dysfunction. A comprehensive understanding of its regulatory functions offers valuable insights into the underlying pathophysiology. The aim of the study was to evaluate the role of serum adiponectin in modulating insulin resistance among patients with visceral obesity-associated T2DM and to examine its association with anthropometric and metabolic parameters. Methods: This cross-sectional study included 140 adults (aged 30 - 65) with T2DM and confirmed visceral obesity (waist circumference (WC) ≥ 90 cm in men, ≥ 80 cm in women). Serum adiponectin, fasting glucose and insulin levels were measured using enzyme-linked immunosorbent assay and chemiluminescent immunoassay. Insulin resistance was assessed via the homeostatic model assessment for insulin resistance (HOMA-IR) index. Spearman correlations and multivariate regression analyses were performed. Results: Serum adiponectin levels were significantly lower in individuals with elevated HOMA-IR (P < 0.01). Adiponectin showed a strong inverse correlation with HOMA-IR (ρ = -0.45, P < 0.001), body mass index (BMI, ρ = -0.17, P = 0.041), WC (ρ = -0.23, P = 0.006) and fasting glucose (ρ = -0.79, P < 0.001). Multivariate regression confirmed adiponectin as an independent predictor of insulin resistance after adjusting for age, gender, WC and BMI. Conclusion: Adiponectin is a key modulator of insulin resistance in visceral obesity-associated T2DM. Its inverse relationship with HOMA-IR, central adiposity and dyslipidemia underscores its role as a sensitive biomarker and potential therapeutic target for improving metabolic health.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".