Zebrafish models of major depressive disorders
Bibliographic record
Abstract
The zebrafish (Danio rerio) has emerged as a model species for translational research in various neuroscience areas, including depressive disorders. Because of their physiological (neuroanatomical, neuroendocrine, neurochemical) and genetic homology to mammals, robust phenotypes, and value in high-throughput genetic and chemical genetic screens, zebrafish are ideal for developing valid experimental models of major depression and discovering novel therapeutics. Behavioral testing approaches, such as approach-avoidance, cognitive, and social paradigms, are available in zebrafish and have utility in identifying depression-like indices in zebrafish in response to physiological, genetic, environmental, and/or psychopharmacological alterations. In addition, the high sensitivity of zebrafish to commonly prescribed psychotropic drugs supports the use of this model as an invaluable tool for pharmacological research and drug screening. This Review outlines the benefits of using the zebrafish model for depression studies and summarizes the current research in this field.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".