Visceral adipose tissue zinc finger protein 36 mRNA levels are correlated with insulin, insulin resistance index, and adiponectinemia in women
Bibliographic record
Abstract
INTRODUCTION: Adipose tissue is now recognized as an endocrine organ and secretes numerous molecules and proteins potentially involved in the physiopathology of the metabolic syndrome. Recently, we have determined the transcriptome of omental adipose tissue, leading to the identification of a new candidate gene for obesity-related metabolic complications, zinc finger protein 36 (ZFP36), which is known to down-regulate tumor necrosis factor-alpha TNF-alpha) expression. OBJECTIVE: The objective of this study was to further examine the relationship between ZFP36 gene expression levels, obesity-related phenotypes, and adipokines. METHODS: Abdominal subcutaneous and omental adipose tissue samples were obtained from 46 women undergoing elective gynecological surgery. Adipose tissue ZFP36 mRNA abundance was assessed by quantitative real-time PCR. Body fat accumulation and distribution were measured by dual X-ray absorptiometry and computed tomography. Fasting blood levels of glucose, insulin, and lipids, and circulating TNF-alpha, interleukin-6 (IL-6), resistin, and adiponectin were also measured. RESULTS: No correlation was observed between s.c. ZFP36 mRNA levels and any of the phenotypes tested. However, although omental ZFP36 mRNA levels were not correlated with measures of body fatness and lipid profile, they were negatively correlated with fasting insulin levels (R = -0.31; P = 0.05), the insulin resistance index (HOMA-IR; R = -0.31; P = 0.05), and 2-h post-glucose insulinemia (R = -0.32; P = 0.05). Omental ZFP36 mRNA abundance was also positively correlated with adiponectinemia (R = 0.35; P = 0.03) but not with circulating TNF-alpha, IL-6, and resistin concentrations. CONCLUSION: These results suggest that ZFP36 gene expression in omental adipose tissue, but not in abdominal s.c. fat, may offer partial protection against the development of insulin resistance and diabetes.
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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".