Neuroepithelial cells and associated innervation of the zebrafish gill: A confocal immunofluorescence study
Bibliographic record
Abstract
Peripheral chemoreceptors responsive to hypoxia have been well characterized in air-breathing vertebrates, but poorly in water-breathers. The present study examined the distribution of five populations of neuroepithelial cells (NECs), putative O(2) chemoreceptors, and innervation patterns in the zebrafish gill using whole-mounts and confocal immunofluorescence. Nerve bundles and fibers of the gill were labeled with zn-12 (a zebrafish-specific neuronal marker) and SV2 antisera and NECs were characterized by serotonin (5-HT) immunoreactivity (IR), SV2-IR and the purinoceptor P2X(3)-IR. A zn-12-IR nerve bundle extended the length of the gill filament and gave rise to a nerve plexus surrounding the efferent filament artery (eFA) and a rich network of fibers that innervated both serotonergic and nonserotonergic NECs of the filament and lamellar epithelium. Three populations of serotonergic, SV2-IR neurons intrinsic to the gill filaments are described, one of which provided innervation to NECs of the filament epithelium. Degeneration of nerve fibers in gill arches maintained in explant culture for 2 days revealed the extrinsic origin of nerve fibers of the plexus and lamellae and the innervation of filament NECs by both intrinsic and extrinsic fibers. Intrinsic innervation surrounding the eFA survived in explant cultures, suggesting a mechanism of local vascular control within the gill. In addition, NECs survived in explants after degeneration of extrinsic nerve fibers. Thus, NECs of the zebrafish gill are organized in a manner reminiscent of O(2) chemoreceptors of mammalian vertebrates, suggesting a role in respiratory regulation.
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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".