Venlafaxine in Embryos Stimulates Neurogenesis and Disrupts Larval Behavior in Zebrafish
Bibliographic record
Abstract
Venlafaxine, a widely prescribed antidepressant, is a selective serotonin and norepinephrine reuptake inhibitor in humans, and this drug is prevalent in municipal wastewater effluents. While studies have shown that this drug affects juvenile fish behavior, little is known about the developmental impact on nontarget aquatic animals. We tested the hypothesis that venlafaxine deposition in the egg, mimicking maternal transfer of this antidepressant, disrupts developmental programming using zebrafish (Danio rerio) as a model. Embryos (1-4 cell stage) were microinjected with either 1 or 10 ng venlafaxine, which led to a rapid reduction (90%) of this drug in the embryo at hatch. There was a concomitant increase in the concentration of the major metabolite o-desmethylvenlafaxine during the same period. Embryonic exposure to venlafaxine accelerated early development, increased hatching rate and produced larger larvae at 5 days post fertilization. Also, there was an increase in neuronal birth in the hypothalamus, dorsal thalamus, posterior tuberculum, and the preoptic region, and this corresponded with a higher spatial expression of nrd4, a key marker of neurogenesis. The venlafaxine-exposed larvae were less active and covered shorter distance in a light and dark behavioral test compared to the controls. Overall, zygotic exposure to venlafaxine disrupts early development, including brain function, and compromises larval behavior, suggesting impact of this drug on developmental programming in zebrafish.
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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 | 0.001 |
| 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".