Cortisol regulates epithelial permeability and sodium losses in zebrafish exposed to acidic water
Bibliographic record
Abstract
The effects of cortisol on epithelial permeability and sodium (Na(+)) handling during acid exposure were investigated in larval zebrafish (Danio rerio). The results demonstrated that the whole-body absorption of the paracellular permeability marker polyethylene glycol-4000 (PEG-4000) decreased with increasing levels of exogenous cortisol. Western blot analysis revealed that the abundance of the epithelial tight junction proteins occludin-a and claudin-b was increased after cortisol treatment. Furthermore, translational gene knockdown of claudin-b using an antisense morpholino oligonucleotide caused an increase in the permeability to PEG-4000, which was mitigated by cortisol treatment, further suggesting a role for cortisol in reducing paracellular permeability. Exposure to acidic water (pH 4.0 vs 7.6) caused an expected increase in the diffusive loss of Na(+) and a decrease in whole-body Na(+) levels. These disruptive effects of acute acid exposure on Na(+) balance were reduced by treatment of larvae with exogenous cortisol. Translational knockdown of the glucocorticoid receptor (GR) abolished the effects of cortisol on epithelial PEG permeability, suggesting that activation of GR was probably the major signaling pathway for reducing epithelial permeability. During acid exposure, the epithelial PEG permeability in the GR morphants was significantly higher than in the control fish. Additionally, GR morphants exhibited a more pronounced diffusive loss of Na(+) than the control fish during acid exposure. These findings suggest that cortisol may help to minimize the negative consequences of acid exposure on Na(+) homoeostasis via GR-mediated reductions in epithelial permeability and paracellular Na(+) loss.
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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 | 0.001 |
| 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".