Correlation of circulating full‐length visfatin (PBEF/NAMPT) with metabolic parameters in subjects with and without diabetes: a cross‐sectional study
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Here we use a novel ELISA that is specific for full-length visfatin (PBEF/NAMPT), compare it with the existing C-terminal based assay and use it to investigate associations of visfatin with metabolic parameters. DESIGN, PATIENTS AND MEASUREMENTS: We established the specificity and effectiveness of the new ELISA and evaluated the associations of full-length visfatin with clinical, anthropometric and metabolic parameters in a cross-sectional study of 129 Thai subjects, consisting of 50 outpatients with type 2 diabetes and 79 healthy volunteers. RESULTS: The new ELISA accurately recovered full-length recombinant visfatin and detected visfatin secreted by primary human and rat adipocytes. We found serum full-length visfatin was significantly higher in subjects with diabetes compared to their nondiabetic peers (median 2.75 vs. 2.22 ng/ml, P = 0.0142). After adjustment for age, gender and traditional metabolic risk factors, adjusted mean visfatin remained significantly higher in the diabetes group (3.80 vs. 2.10 ng/ml, P = 0.0021). On Spearman univariate correlation analysis, visfatin was significantly associated with resistin (r = 0.30, P = 0.0011), but not with any other anthropometric or metabolic variables, including adiponectin multimers. On multiple linear regression analysis, the only covariates independently associated with visfatin were diabetes (t = 3.11, P = 0.0024) and log resistin (t = 2.68, P = 0.0086). CONCLUSIONS: Circulating visfatin is independently associated with diabetes and resistin concentration, but is not related to adiponectin multimers or other metabolic covariates. These data are suggestive of a potential role of visfatin in subclinical inflammatory states.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it