Interactive Effects of Venlafaxine and Thermal Stress on Zebrafish ( <i>Danio rerio</i> ) Inflammatory and Heat Shock Responses
Bibliographic record
Abstract
Abstract Venlafaxine (VFX), a commonly prescribed antidepressant often detected in wastewater effluent, and acute temperature elevations from climate change and increased urbanization, are two environmental stressors currently placing freshwater ecosystems at risk. This study focused on understanding if exposure to VFX impacts the agitation temperature (T ag ) and critical thermal maximum (CT max ) of zebrafish ( Danio rerio ). Additionally, we examined the interactive effects of VFX and acute thermal stress on zebrafish heat shock and inflammatory immune responses. A 96 hour 1.0 μg/L VFX exposure experiment was conducted, followed by assessment of thermal tolerance via CT max challenge. Heat shock proteins and pro-inflammatory immune cytokines were quantified through gene expression analysis by quantitative PCR (qPCR) on hsp 70, hsp 90, hsp 47, il-8, tnfα , and il-1β within gill and liver tissue. No significant changes in agitation temperature between control and exposed fish were observed, nor were there any differences in CT max based on treatment. Unsurprisingly, hsp 47, 70, and 90 were all upregulated in groups exposed solely to CT max , while only hsp 47 within gill tissue showed signs of interactive effects, which was significantly decreased in fish exposed to both VFX and CT max . No induction of an inflammatory response occurred. This study demonstrated that environmentally relevant concentrations of VFX have no impact on thermal tolerance performance in zebrafish. However, VFX is capable of causing diminished function of protective heat shock mechanisms, which could be detrimental to freshwater fish populations and aquatic ecosystems as temperature spikes become more frequent from climate change and urbanization near watersheds. Summary Statement This study predicts the effects that climate change and anthropogenic pollutants may have on fish ability to tolerate elevated temperatures, and examines the physiologic challenges these stressors may introduce.
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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) | 0.001 | 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".