Endotoxin Mediated-iNOS Induction Causes Insulin Resistance via ONOO− Induced Tyrosine Nitration of IRS-1 in Skeletal Muscle
Bibliographic record
Abstract
BACKGROUND: It is believed that the endotoxin lipopolysaccharide (LPS) is implicated in the metabolic perturbations associated with both sepsis and obesity (metabolic endotoxemia). Here we examined the role of inducible nitric oxide synthase (iNOS) in skeletal muscle insulin resistance using LPS challenge in rats and mice as in vivo models of endotoxemia. METHODOLOGY/PRINCIPAL FINDINGS: Pharmacological (aminoguanidine) and genetic strategies (iNOS⁻/⁻ mice) were used to counter iNOS induction in vivo. In vitro studies using peroxynitrite (ONOO⁻) or inhibitors of the iNOS pathway, 1400 W and EGCG were conducted in L6 myocytes to determine the mechanism by which iNOS mediates LPS-dependent insulin resistance. In vivo, both pharmacological and genetic invalidation of iNOS prevented LPS-induced muscle insulin resistance. Inhibition of iNOS also prevented insulin resistance in myocytes exposed to cytokine/LPS while exposure of myocytes to ONOO⁻ fully reproduced the inhibitory effect of cytokine/LPS on both insulin-stimulated glucose uptake and PI3K activity. Importantly, LPS treatment in vivo and iNOS induction and ONOO⁻ treatment in vitro promoted tyrosine nitration of IRS-1 and reduced insulin-dependent tyrosine phosphorylation. CONCLUSIONS/SIGNIFICANCE: Our work demonstrates that iNOS-mediated tyrosine nitration of IRS-1 is a key mechanism of skeletal muscle insulin resistance in endotoxemia, and presents nitrosative modification of insulin signaling proteins as a novel therapeutic target for combating muscle insulin resistance in inflammatory settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".