Plasma resistin, adiponectin and leptin levels in lean and obese subjects: correlations with insulin resistance
Bibliographic record
Abstract
OBJECTIVE: Adipose tIssue regulates insulin sensitivity via the circulating adipocytokines, leptin, resistin and adiponectin. The objective of this study was to compare the levels of resistin, adiponectin and leptin in lean and obese subjects and determine the relationship between circulating adipocytokines and insulin resistance. METHODS: We examined plasma levels of resistin, adiponectin and leptin in 17 lean subjects with a mean body mass index (BMI) of approximately 23 and 34 non-diabetic obese individuals with a mean BMI approximately 33. Insulin resistance was assessed using the homeostasis model assessment ratio (HOMA-R) formula derived from fasting insulin and glucose levels. RESULTS: Resistin levels were not significantly different between the two groups but were significantly higher in women compared with men, 35.4+/-6.5 (s.e.) vs 15.4+/-2.9 microg/L, P<0.01. Resistin did not correlate with BMI but did significantly correlate with HOMA-R, P<0.01, and this correlation remained significant after adjustment for gender and BMI. Adiponectin levels were significantly lower in obese compared with lean subjects, P<0.005, and higher in women, P<0.001, but showed no significant correlation with HOMA-R. Leptin levels were significantly higher in obese subjects and women and correlated with HOMA-R and resistin. DISCUSSION: In this small group of patients we demonstrated that insulin resistance correlated most strongly with leptin levels. A significant correlation between resistin levels and insulin resistance was also observed. Although a similar trend was apparent for adiponectin, the correlation with insulin resistance did not achieve statistical significance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.002 | 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".