Modulation of insulin signaling pathway genes by ozone inhalation and the role of glucocorticoids: A multi-tissue analysis
Bibliographic record
Abstract
Air pollution is associated with increased risk of metabolic diseases including type 2 diabetes, of which dysregulation of the insulin-signaling pathway is a feature. While studies suggest pollutant exposure alters insulin signaling in certain tissues, there is a lack of comparison across multiple tissues needed for a holistic assessment of metabolic effects, and underlying mechanisms remain unclear. Air pollution increases plasma levels of glucocorticoids, systemic regulators of metabolic function. The objectives of this study were to 1) determine effects of ozone on insulin-signaling genes in major metabolic tissues, and 2) elucidate the role of glucocorticoids. Male Fischer-344 rats were treated with metyrapone, a glucocorticoid synthesis inhibitor, and exposed to 0.8 ppm ozone or clean air for 4 h, with tissue collected immediately or 24 h post exposure. Ozone inhalation resulted in distinct mRNA profiles in the liver, brown adipose, white adipose and skeletal muscle tissues, including effects on insulin-signaling cascade genes (Pik3r1, Irs1, Irs2) and targets involved in glucose metabolism (Hk2, Pgk1, Slc2a1), cell survival (Bcl2l1), and genes associated with diabetes and obesity (Serpine1, Retn, Lep). Glucocorticoid-dependent regulation was observed in the liver and brown and white adipose tissues, while effects in skeletal muscle were largely unaffected by metyrapone treatment. Gene expression changes were accompanied by altered phosphorylation states of insulin-signaling proteins (BAD, GSK, IR-β, IRS-1) in the liver. The results show that systemic effects of ozone inhalation include tissue-specific regulation of insulin-signaling pathway genes via both glucocorticoid-dependent and independent mechanisms, providing insight into mechanisms underlying adverse effects of pollutants.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".