Anxiolytic effects of diazepam in Trinidadian guppies exposed to chemical cues indicating predation risk
Bibliographic record
Abstract
The fear of predation is pervasive among vertebrate prey species, being characterized by neurobiological and behavioral changes induced by risk exposure. To understand the acquisition and attenuation of fearful phenotypes, such as dimensions of posttraumatic stress, researchers often use animal models, with prey fishes recently emerging as a nontraditional but promising model. Much is known about fear acquisition in prey fishes such as the Trinidadian guppy, Poecilia reticulata, which inhabit high and low predation sites. Little is known, however, about whether a guppy model shows fear attenuation via therapeutic treatments, such as commonly prescribed anxiolytic drugs, like benzodiazepines. In this study, we used Trinidadian guppies from wild populations to explore the interactive effects of exposure to the anxiolytic drug, diazepam, and exposure to predation risk in the form of injured conspecific cues (i.e. alarm cues) that reliably indicate a predator attack. In Experiment 1, juvenile guppies from both high- and low-predation populations were given a 10-min exposure to diazepam (160 µg/l), resulting in the loss of fear behavior when simultaneously presented with alarm cues. In Experiment 2, we found that a prior 10-min exposure to diazepam (160 µg/l) for adult guppies significantly reduced their subsequent fear behavior toward a separate exposure to alarm cues, revealing that diazepam was having direct effects on guppy cognition rather than simply inactivating the alarm cues via chemical alteration. These anxiolytic effects thus add to the growing support for the predictive validity of prey fishes as animal models for exploring fear attenuation in humans.
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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".