Obese Mice Lacking Inducible Nitric Oxide Synthase Are Sensitized to the Metabolic Actions of Peroxisome Proliferator–Activated Receptor-γ Agonism
Bibliographic record
Abstract
OBJECTIVE: Synthetic ligands for peroxisome proliferator-activated receptor-gamma (PPAR-gamma) improve insulin sensitivity in obesity, but it is still unclear whether inflammatory signals modulate their metabolic actions. In this study, we tested whether targeted disruption of inducible nitric oxide (NO) synthase (iNOS), a key inflammatory mediator in obesity, modulates the metabolic effects of rosiglitazone in obese mice. RESEARCH DESIGN AND METHODS: iNOS(-/-) and iNOS(+/+) were subjected to a high-fat diet or standard diet for 18 weeks and were then treated with rosiglitazone for 2 weeks. Whole-body insulin sensitivity and glucose tolerance were determined and metabolic tissues harvested to assess activation of insulin and AMP-activated protein kinase (AMPK) signaling pathways and the levels of inflammatory mediators. RESULTS: Rosiglitazone was found to similarly improve whole-body insulin sensitivity and insulin signaling to Akt/PKB in skeletal muscle of obese iNOS(-/-) and obese iNOS(+/+) mice. However, rosiglitazone further improved glucose tolerance and liver insulin signaling only in obese mice lacking iNOS. This genotype-specific effect of rosiglitazone on glucose tolerance was linked to a markedly increased ability of the drug to raise plasma adiponectin levels. Accordingly, rosiglitazone increased AMPK activation in muscle and liver only in obese iNOS(-/-) mice. PPAR-gamma transcriptional activity was increased in adipose tissue of iNOS(-/-) mice. Conversely, treatment of 3T3-L1 adipocytes with a NO donor blunted PPAR-gamma activity. CONCLUSIONS: Our results identify the iNOS/NO pathway as a critical modulator of PPAR-gamma activation and circulating adiponectin levels and show that invalidation of this key inflammatory mediator improves the efficacy of PPAR-gamma agonism in an animal model of obesity and insulin resistance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".