Neuroepithelial cells and the hypoxia emersion response in the amphibious fish<i>Kryptolebias marmoratus</i>
Bibliographic record
Abstract
Teleost fish have oxygen-sensitive neuroepithelial cells (NECs) in the gills that appear to mediate physiological responses to hypoxia, but little is known about oxygen sensing in amphibious fish. The mangrove rivulus, Kryptolebias marmoratus, is an amphibious fish that respires via the gills and/or the skin. First, we hypothesized that both the skin and gills are sites of oxygen sensing in K. marmoratus. Serotonin-positive NECs were abundant in both gills and skin, as determined by immunohistochemical labelling and fluorescence microscopy. NECs retained synaptic vesicles and were found near nerve fibres labelled with the neuronal marker zn-12. Skin NECs were 42% larger than those of the gill, as estimated by measurement of projection area, and 45% greater in number. Moreover, for both skin and gill NECs, NEC area increased significantly (30-60%) following 7 days of exposure to hypoxia (1.5 mg l(-1) dissolved oxygen). Another population of cells containing vesicular acetylcholine transporter (VAChT) proteins were also observed in the skin and gills. The second hypothesis we tested was that K. marmoratus emerse in order to breathe air cutaneously when challenged with severe aquatic hypoxia, and this response will be modulated by neurochemicals associated chemoreceptor activity. Acute exposure to hypoxia induced fish to emerse at 0.2 mg l(-1). When K. marmoratus were pre-exposed to serotonin or acetylcholine, they emersed at a significantly higher concentration of oxygen than untreated fish. Pre-exposure to receptor antagonists (ketanserin and hexamethonium) predictably resulted in fish emersing at a lower concentration of oxygen. Taken together, these results suggest that oxygen sensing occurs at the branchial and/or cutaneous surfaces in K. marmoratus and that serotonin and acetylcholine mediate, in part, the emersion response.
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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".