Toxicogenomic Analysis of Mainstream Tobacco Smoke-Exposed Mice Reveals Repression of Plasminogen Activator Inhibitor-1 Gene in Heart
Bibliographic record
Abstract
Tobacco smoking is associated with cardiovascular pathology. However, the molecular mechanisms of tobacco smoke exposure that lead to initiation or exacerbation of cardiovascular disease are unclear. In this study, the effects of mainstream tobacco smoke (MTS) on global transcription in the heart were investigated. Male C57B1/CBA mice were exposed to MTS from 2 cigarettes daily, 5 days/wk for 6 or 12 wk. Mice were sacrificed immediately, or 6 wk following the last cigarette. High-density DNA microarrays were used to characterize global gene expression changes in whole heart. Fifteen genes were significantly differentially expressed following exposure to MTS. Among these genes, cytochrome P-450 1A1 (Cyp1A1) was upregulated by 12-fold, and Serpine-1 (plasminogen activator inhibitor-1, PAI-1) was downregulated by 1.7-fold. Concomitant increase in Cyp1A1 protein levels and decrease in total and active PAI-1 protein was observed in tissue extracts by Western blot assay and enzyme-linked immunosorbent assay (ELISA), respectively. Observed changes were transient and were partially reversed during break periods. Thus, gene expression profiling of heart tissue revealed a novel cardiovascular mechanism operating in response to MTS. Our results suggest a potential role for PAI-1 in MTS-induced cardiovascular pathology.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".