Expression of ion transport genes in ionocytes isolated from larval zebrafish (<i>Danio rerio</i>) exposed to acidic or Na<sup>+</sup>-deficient water
Bibliographic record
Abstract
In zebrafish ( Danio rerio), a specific ionocyte subtype, the H+-ATPase-rich (HR) cell, is presumed to be a significant site of transepithelial Na+uptake/acid secretion. During acclimation to environments differing in ionic composition or pH, ionic and acid–base regulations are achieved by adjustments to the activity level of HR cell ion transport proteins. In previous studies, the quantitative assessment of mRNA levels for genes involved in ionic and acid–base regulations relied on measurements using homogenates derived from the whole body (larvae) or the gill (adult). Such studies cannot distinguish whether any differences in gene expression arise from adjustments of ionocyte subtype numbers or transcriptional regulation specifically within individual ionocytes. The goal of the present study was to use fluorescence-activated cell sorting to separate the HR cells from other cellular subpopulations to facilitate the measurement of gene expression of HR cell-specific transporters and enzymes from larvae exposed to low pH (pH 4.0) or low Na+(5 μM) conditions. The data demonstrate that treatment of larvae with acidic water for 4 days postfertilization caused cell-specific increases in H+-ATPase ( atp6v1aa), ca17a, ca15a, nhe3b, and rhcgb mRNA in addition to increases in mRNA linked to cell proliferation. In fish exposed to low Na+, expression of nhe3b and rhcgb was increased owing to HR cell-specific regulation and elevated numbers of HR cells. Thus, the results of this study demonstrate that acclimation to low pH or low Na+environmental conditions is facilitated by HR cell-specific transcriptional control and by HR cell proliferation.
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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".