Regulation of the nitric oxide system in human adipose tissue
Bibliographic record
Abstract
Nitric oxide (NO) is involved in adipose tissue biology by influencing adipogenesis, insulin-stimulated glucose uptake, and lipolysis. The enzymes responsible for NO formation in adipose cells are endothelial NO synthase (eNOS) and inducible NO synthase (iNOS), whereas neuronal NO synthase (bNOS) is not expressed in adipocytes. We characterized the expression pattern and the influence of adipogenesis, obesity, and weight loss on genes belonging to the NO system in human subcutaneous adipose cells by combining in vivo and in vitro studies. Expression of most of the genes known to belong to the NO system (eNOS, iNOS, subunits of the soluble guanylate cyclase, and both genes encoding cGMP-dependent protein kinases) in human adipose tissue and isolated human adipocytes was detected. In vitro adipogenic differentiation increased the expression level of iNOS significantly, whereas eNOS expression levels were not influenced. The genes encoding eNOS, iNOS, and cGMP-dependent protein kinase 1 were expressed at higher levels in obese women. Expression of these genes, however, was not influenced by 5% weight loss. Insulin and angiotensin II (Ang II) increased NO production by human preadipocytes in vitro. Increased eNOS and iNOS expression in adipocytes and local effects of insulin and Ang II may increase adipose tissue production of NO in obesity.
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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 | 0.000 | 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 | 0.001 |
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".