Ethanol-Induced ADH Activity in Zebrafish: Differential Concentration-Dependent Effects on High- Versus Low-Affinity ADH Enzymes
Bibliographic record
Abstract
Zebrafish express enzymes that metabolize ethanol in a manner comparable to that of mammals, including humans. We previously demonstrated that acute ethanol exposure increases alcohol dehydrogenase (ADH) activity in an inverted U-shaped dose-dependent manner. It was hypothesized that the biphasic dose-response was due to the increased activity of a high-affinity ADH isoform following exposure to low concentrations of ethanol and increased activity of a low-affinity ADH isoform following exposure to higher concentrations of ethanol. To test this hypothesis, we exposed zebrafish to different concentrations of ethanol (0%, 0.25%, 0.5%, and 1.0% v/v) for 30 min and measured the total ADH activity in the zebrafish liver. However, we also repeated this enzyme activity assay using a low concentration of the substrate (ethanol) to determine the activity of high-affinity ADH isoforms. We found that total ADH activity in response to ethanol induces an inverted U-shaped dose-response similar to our previous study. Using a lower substrate level in our enzyme assay targeting high-affinity isozymes, we found a similar dose-response. However, the difference in activity between the high and low substrate assays (high substrate activity - low substrate activity), which provide an index of activity for low-affinity ADH isoforms, revealed no significant effect of ethanol exposure. Our results suggest that the inverted U-shaped dose-response for total ADH activity in response to ethanol is driven primarily by high-affinity isoforms of ADH.
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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 | 0.000 |
| 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 | 0.001 |
| 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".