Bariatric surgery relieves type 2 diabetes and modulates inflammatory factors and coronary endothelium eNOS/iNOS expression in <i>db/db</i> mice
Bibliographic record
Abstract
Overexpression of endothelial nitric oxide synthetase (eNOS)/inducible nitric oxide synthase (iNOS) and inhibition of inflammatory factors can improve vascular function. We hypothesized that bariatric (gastric bypass) surgery could inhibit inflammatory factors and improve the eNOS/iNOS expression of coronary arterioles in the db/db mice. The animals were randomly allocated to the following groups: sham-operated lean mice, lean mice that underwent surgery, sham-operated db/db mice, and db/db mice that underwent surgery (5, 10, 20, and 30 days post-operation). The plasma levels of adiponectin, ghrelin, and IL-6, as well as the protein expression of eNOS/iNOS in coronary arterioles were measured with Western blot. Bariatric surgery decreased body mass and blood glucose levels in db/db mice. Ghrelin receptor and GHS-R1a expression in the hypothalamus were increased in db/db mice, but surgery attenuated GHS-R1a expression. Bariatric surgery elevated plasma concentration and protein expression of adiponectin and ghrelin, and attenuated plasma concentration and protein expression of IL-6. Coronary protein expression of eNOS and SOD2 was lower in the sham-operated db/db mice, and bariatric surgery increased eNOS and SOD2 expression. Gastric bypass surgery upregulates ghrelin and adiponectin expression, and decreases IL-6 expression, which might induce up-regulation of eNOS and SOD2, and down-regulation of iNOS. These interactions could counteract the endothelium dysfunction in type 2 diabetes mellitus.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".