Influence of ALDH2 Polymorphism on Ethanol Kinetics and Pulmonary Effects in Male and Female Rats Exposed to Ethanol Vapors
Bibliographic record
Abstract
Ethanol is being added in various proportions to fuel in order to reduce greenhouse gas emissions. This is likely to result in involuntary exposure to ethanol vapors. Whether or not such exposure might cause health effects is still unknown. Acetaldehyde, an important metabolite of ethanol detoxified by aldehyde dehydrogenase (ALDH2) is more toxic that ethanol. This study assessed the impact of genetic ALDH2 polymorphism in male and female Sprague-Dawley rats on ethanol kinetics and pulmonary effects following sub-chronic exposure to ethanol vapors. Homozygote rats ALDH2(Q)/2(Q) (fast ALDH2 activity) and ALDH2(R)/2(R) (ALDH2 deficiency) were exposed to 1000 or 3000 ppm, 6 h/day, 5 days/week for 13 weeks. Blood ethanol concentrations (BEC) were measured at various post-exposure times. Cellularity in bronchoalveolar lavages (BAL) and lung histological evaluation were performed at week 13. Results showed that BEC in males were systematically lower than in females, e.g. BEC in ALDH2(Q)/2(Q) males (2 min, 1,000 ppm, day 1) was significantly (p < 0.05) lower (66.8 +/- 10.7 microM) compared to females (87.6 +/- 15.3 microM). BEC for ALDH2(Q)/2(Q) rats were different from ALDH2(R)/2(R) only for males exposed for more than 64 days. Repeated exposures resulted in a significant decrease of BEC, e.g. for ALDH2(Q)/2(Q) males (3,000 ppm) BEC on day 1 and day 85 were 324.6 +/- 102.6 microM and 187.5 +/- 32.1 microM, respectively. BAL and histological evaluation revealed no pulmonary toxicity for all groups. Overall, results showed that 3,000 ppm of ethanol vapors represents no observed adverse effect level (NOAEL) for pulmonary toxicity in the rat.
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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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".