The role of TASK-2 channels in CO<sub>2</sub>sensing in zebrafish (<i>Danio rerio</i>)
Bibliographic record
Abstract
Peripheral chemosensitivity in fishes is thought to be mediated by serotonin-enriched neuroepithelial cells (NECs) that are localized to the gills of adults and the integument of larvae. In adult zebrafish ( Danio rerio), branchial NECs are presumed to mediate the cardiorespiratory reflexes associated with hypoxia or hypercapnia, whereas in larvae, there is indirect evidence linking cutaneous NECs to hypoxic hyperventilation and hypercapnic tachycardia. No study yet has examined the ventilatory response of larval zebrafish to hypercapnia, and regardless of developmental stage, the signaling pathways involved in CO2sensing remain unclear. In the mouse, a background potassium channel (TASK-2) contributes to the sensitivity of chemoreceptor cells to CO2. Zebrafish possess two TASK-2 channel paralogs, TASK-2 and TASK-2b, encoded by kcnk5a and kcnk5b, respectively. The present study aimed to determine whether TASK-2 channels are expressed in NECs of larval zebrafish and whether they are involved in CO2sensing. Using immunohistochemical approaches, TASK-2 protein was observed on the surface of NECs in larvae. Exposure of larvae to hypercapnia caused cardiac and breathing frequencies to increase, and these responses were blunted in fish experiencing TASK-2 and/or TASK-2b knockdown. The results of these experiments suggest that TASK-2 channels are involved in CO2sensing by NECs and contribute to the initiation of reflex cardiorespiratory responses during exposure of larvae to hypercapnia.
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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".