Adipocyte-specific Nos2 deletion improves insulin resistance and dyslipidemia through brown fat activation in diet-induced obese mice
Bibliographic record
Abstract
Inducible nitric oxide (NO) synthase (NOS2) is a well-documented inflammatory mediator of insulin resistance in obesity. NOS2 expression is induced in both adipocytes and macrophages within adipose tissue during high-fat (HF)-induced obesity. Eight-week-old male mice with adipocyte selective deletion of the Nos2 gene (Nos2AD−KO) and their wildtype littermates (Nos2fl/fl) were subjected to chow or high-fat high-sucrose (HFHS) diet for 10 weeks followed by metabolic phenotyping and determination of brown adipose tissue (BAT) thermogenesis. The direct impact of NO on BAT mitochondrial respiration was also assessed in brown adipocytes. HFHS-fed Nos2AD−KO mice had improved insulin sensitivity as compared to Nos2fl/fl littermates. Nos2AD−KO mice were also protected from HF-induced dyslipidemia and exhibited increased energy expenditure compared with Nos2fl/fl mice. This was linked to the activation of BAT in HFHS-fed Nos2AD−KO mice as shown by increased Ucp1 and Ucp2 gene expression and augmented respiratory capacity of BAT mitochondria. Furthermore, mitochondrial respiration was inhibited by NO, or upon cytokine-induced NOS2 activation, but improved by NOS2 inhibition in brown adipocytes. These results demonstrate the key role of adipocyte NOS2 in the development of obesity-linked insulin resistance and dyslipidemia, partly through NO-dependent inhibition of BAT mitochondrial bioenergetics.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".