Zebrafish Larvae's Response to Electricity is Mediated by Dopaminergic Agonists and Antagonists
Bibliographic record
Abstract
The signaling molecular mechanisms in zebrafish response to electricity are unknown, so here we asked if changes to dopaminergic signaling pathways can affect their electrically-evoked locomotion. To answer this question, the effects of multiple selective and non-selective dopamine compounds on the electric response of zebrafish larvae is investigated. A microfluidic device with enhanced control of experimentation with multiple larvae is used, which features a novel design to immobilize four zebrafish larvae in parallel and expose them to electric current that induces tail locomotion. In 6 days post-fertilization zebrafish larvae, the electric induced locomotor response is quantified in terms of the tail movement duration and beating frequency to discern the effect of non-lethal concentrations of dopaminergic agonists (apomorphine, SKF-81297, and quinpirole), and antagonists (butaclamol, SCH-23390, and haloperidol). All dopamine antagonists decrease locomotor activity, while dopamine agonists do not induce similar behaviours in larvae. The D2- like selective dopamine agonist quinpirole enhances movement. However, exposure to non-selective and D1-selective dopamine agonists apomorphine and SKF-81297 cause no significant change in the electric response. Exposing larvae that were pre-treated with butaclamol and haloperidol to apomorphine and quinpirole, respectively, restores electric locomotion. The results demonstrate a correlation between electric response and the dopamine signalling pathway. We propose that the electrofluidic assay has profound application potential as a chemical screening method when investigating biological pathways, behaviors, and brain disorders.
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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".