Serotonin stimulates proliferation of ionocytes via the 5-HT2A receptor in zebrafish larvae
Bibliographic record
Abstract
Osmoregulation is an essential process in all living organisms. For aquatic organisms, such as freshwater fishes whose natural environment is hypoosmotic, specialized cells, called ionocytes, are present in the skin during developmental stages and contribute to the maintenance of osmotic homeostasis. Such cells are known to proliferate in response to osmotic or ionic stress, but the molecular mechanism by which that process is regulated remains poorly characterized. In this study, using immunohistochemistry and confocal microscopy, we demonstrate that cutaneous ionocytes in developing zebrafish (Danio rerio) express serotonin 2A (5-HT2A) receptors by co-labelling with other known ionocyte markers, such as the Na+/K+-ATPase, Concanavalin A and Mitotracker. Furthermore, by quantifying ionocyte number through early stages of development, we implicate 5-HT2A receptors in initiating ionocyte proliferation. Exposure of zebrafish embryos and larvae to acidic pH, or exogenous 5-HT, increased the number of cutaneous ionocytes. The effects of both stimuli were abolished in the presence of the 5-HT2A receptor-specific antagonist, ketanserin. Moreover, activation of 5-HT2A receptors led to increased detection of ionocytes with phosphorylated extracellular signal-regulated kinase (ERK), a key regulator of cell division and differentiation linked with 5-HT2A. We used tetrabenazine, an inhibitor of vesicular monoamine transporter 2 (vmat2) and 5-HT storage, to deplete potential sources of 5-HT. Tetrabenazine treatment in fish exposed to acidic pH reduced ionocyte proliferation, implicating a source of 5-HT that uses vmat2 in the regulation of ionocyte populations. These results demonstrate the importance of a pathway initiated by 5-HT2A activation that regulates ionocyte proliferation in developing zebrafish exposed to environmental acidification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".