β-Carotene Increases Activity of Cytochrome P450 2E1 during Ethanol Consumption
Bibliographic record
Abstract
One of the key routes through which ethanol induces oxidative stress appears to be the activation of cytochrome P450 2E1 at different levels of ethanol intake. Our aim was to determine if oral β-carotene intake had an antioxidant effect on CYP2E1 gene expression in mice that had previously consumed ethanol. C57BL/6 mice were used and distributed into: control (C), low-dose alcohol (LA), moderate-dose alcohol (MA), β-carotene (B), low-dose alcohol+β-carotene (LA + B), and moderate-dose alcohol+β-carotene (MA + B). Animals were euthanized at the end of the experiment, and liver tissue was taken from each one. CYP2E1 was measured using qPCR to detect liver damage. The relative expression level of each RNA was estimated using the comparative threshold cycle (Ct) technique (2−ΔΔCT method) by averaging the Ct values from three replicates. The LA+B (2267 ± 0.707) and MA+B (2.307 ± 0.384) groups had the highest CYP2E1 fold change values. On the other hand, the C (1.053 ± 0.292) and LA (1.240 ± 0.163) groups had the lowest levels. These results suggest that ethanol feeding produced a fold increase in CYP2E1 protein in mice as compared to the control group. Increased CYP2E1 activity was found to support the hypothesis that β-carotene might be dangerous during ethanol exposure in animal models. Our findings imply that β-carotene can increase the hepatic damage caused by low and high doses of alcohol. Therefore, the quantity of alcohol ingested, the exposure period, the regulatory mechanisms of alcoholic liver damage, and the signaling pathways involved in the consumption of both alcohol and antioxidant must all be considered.
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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 | 0.000 |
| 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) | 0.000 | 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".