Identification of Vesicular Monoamine Transporter 2 (vmat2)‐Containing O <sub>2</sub> Chemoreceptors in the Gills of Zebrafish
Bibliographic record
Abstract
All vertebrates “sense” changes in oxygen (O 2 ) via specialized cells, called chemoreceptors, associated with the peripheral nervous system. Aquatic vertebrates are especially prone to fluctuations in environmental O 2 levels. Thus it is essential for them to readily detect low O 2 and make appropriate ventilatory adjustments. Teleost species, such as zebrafish, have O 2 chemoreceptive neuroepithelial cells (NECs) embedded in the gill epithelium. These cells exhibit membrane depolarization and vesicular recycling upon exposure to hypoxia, and express the monoamine neurotransmitter, serotonin (5‐HT). Our research objectives are to identify gill O 2 chemoreceptors in live tissue preparations and determine the role of intracellular Ca 2+ in O 2 sensing. We are currently employing a transgenic zebrafish line, expressing green fluorescent protein (GFP) under the control of vesicular monoamine transporter 2 (vmat2) regulatory elements, in order to identify NECs and characterize their hypoxic responses in vitro and in situ . Immunohistochemistry and confocal microscopy were used to determine the distribution and identity of GFP‐positive cells in gills. Our results show that the population of GFP‐positive cells in our transgenic line significantly overlaps with serotonergic NECs in the gill filaments. Preliminary studies using fura 2‐based imaging indicate that isolated GFP‐positive cells stimulated by hypoxia undergo an increase in intracellular Ca 2+ concentration. Identification of NECs both in vitro and in situ using a vital marker will have a great impact on future work addressing the physiological properties of these cells. Support or Funding Information This research project is funded by Natural Sciences and Engineering Research Council of Canada (NSERC).
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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".