Increased Vaspin Levels Are Associated with Beneficial Metabolic Outcome Pre- and Post-Bariatric Surgery
Bibliographic record
Abstract
PURPOSE: Vaspin (visceral-adipose-tissue-derived-serine-protease-inhibitor) is a recently identified adipokine with putative insulin-sensitizing properties. Plasma vaspin responses to surgery-induced weight loss are sparse and contradictory. DESIGN AND PARTICIPANTS: We evaluated changes in vaspin levels and relationship to post-operative outcomes in men (n = 22) and women (n = 55) undergoing biliopancreatic-diversion/duodenal-switch bariatric surgery. Body composition and plasma parameters were measured at baseline, acutely (1 and 5 days) and medium-term (6 and 12 months) post-surgery. RESULTS: Fasting preoperative vaspin concentrations were comparable in men vs women. The distribution was biphasic (both men and women) with a nadir of 2.5 ng/ml. Subjects were divided into high (≥2.5 ng/mL, HI-group) and low (<2.5 ng/mL, LO-group) vaspin level. Both groups had comparable sex distribution, age and BMI, but the HI-vaspin group had lower insulin, HOMA, and triglyceride and higher HDL-cholesterol, acylation stimulating protein (ASP) and IL-6 levels (all p<0.05). Post-operatively, both groups decreased BMI comparably over 12 months; the HI-vaspin group maintained high vaspin levels, while the LO-vaspin group gradually increased their levels with weight loss over 12 months. The HI-vaspin group maintained a better glucose, insulin, HOMA, fructosamine, HDL-cholesterol, and triglyceride profile throughout. The HI-vaspin group also had higher gamma-glutamyltransferase and ASP profiles. Finally, baseline vaspin level inversely correlated significantly with baseline and 12-month insulin, HOMA, triglyceride and positively correlated with HDL and ASP. Twelve-month vaspin also correlated similarly, including an inverse correlation with BMI. CONCLUSION: Globally, this study supports the concept of vaspin as a beneficial adipokine in obesity, which may potentially lead to possible therapeutic targets.
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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) | 0.000 | 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) | 0.002 | 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".