Retinol-Binding Protein 4 in Human Obesity
Bibliographic record
Abstract
Studies in mice suggest that adipocytes serve as glucose sensors and regulate systemic glucose metabolism through release of serum retinol-binding protein 4 (RBP4). This model has not been validated in humans. RBP4 was highly expressed in isolated mature human adipocytes and secreted by differentiating human adipocytes. In contrast to the animal data, RBP4 mRNA was downregulated in subcutaneous adipose tissue of obese women, and circulating RBP4 concentrations were similar in normal weight, overweight, and obese women (n = 74). RBP4 was positively correlated with GLUT4 expression in adipose tissue, independent of any obesity-associated variable. Five percent weight loss slightly decreased adipose RBP4 expression but did not influence circulating RBP4. In another set of experiments, we stratified patients (n = 14) by low or high basal fasting interstitial glucose concentrations, as determined by the microdialysis technique. Venous glucose concentrations were similar throughout oral glucose tolerance testing, and basal RBP4 expression in adipose tissue and serum RBP4 concentrations were similar in the groups with higher and lower interstitial glucose levels. Our findings point to profound differences between rodents and humans in the regulation of adipose or circulating RBP4 and challenge the notion that glucose uptake by adipocytes has a dominant role in the regulation of RBP4.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".