Exposure to diesel exhaust upregulates COX-2 expression in ApoE knockout mice
Bibliographic record
Abstract
INTRODUCTION: We have shown that diesel exhaust (DE) inhalation caused progression of atherosclerosis; however, the mechanisms are not fully understood. We hypothesize that exposure to DE upregulates cyclooxygenase (COX) expression and activity, which could play a role in DE-induced atherosclerosis. METHODS: ApoE knockout mice (30-week old) fed with regular chow were exposed to DE (at 200 µg/m(3) of particulate matter) or filtered air (control) for 7 weeks (6 h/day, 5 days/week). The protein and mRNA expression of COX-1 and COX-2 were evaluated by immunohistochemistry analysis and quantitative real-time PCR, respectively. To examine COX activity, thoracic aortae were mounted in a wire myograph, and phenylephrine (PE)-stimulated vasoconstriction was measured with and without the presence of COX antagonists (indomethacin). COX-2 activity was further assessed by urine 2,3-dinor-6-keto PGF(1α) level, a major metabolite of prostacyclin I(2) (PGI(2)). RESULTS: Immunohistochemistry analysis demonstrates that DE exposure enhanced COX-2 expression in both thoracic aorta (p < 0.01) and aortic root (p < 0.03), with no modification of COX-1 expression. The increased COX-2 expression was positively correlated with smooth muscle cell content in aortic lesions (R(2) = 0.4081, p < 0.008). The fractional changes of maximal vasoconstriction in the presence of indomethacin was attenuated by 3-fold after DE exposure (p < 0.02). Urine 2,3-dinor-6-keto PGF(1α) level was 15-fold higher in DE group than the control (p < 0.007). The mRNA expression of COX-2 (p < 0.006) and PGI synthase (p < 0.02), but not COX-1, was significantly augmented after DE exposure. CONCLUSION: We show that DE inhalation enhanced COX-2 expression, which is also associated with phenotypic changes of aortic lesion.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".