Effects of cortisol and prolactin on Na<sup>+</sup>and Cl<sup>-</sup>transport in cultured branchial epithelia from FW rainbow trout
Bibliographic record
Abstract
The electrophysiological and ion-transporting properties of cultured gill epithelia from freshwater (FW) rainbow trout were examined in the presence of cortisol and prolactin as media supplements. Epithelia were of the double-seeded insert (DSI) type containing both pavement cells (PVCs) and mitochondria-rich cells (MRCs) and were grown in Leibovitz's L15 media on filters allowing exposure to different apical media conditions. Experiments were carried out in two series after 7-9 days symmetrical (L15 apical-L15 basolateral) culture. In both series, 100% L15 was maintained as the basolateral medium throughout and supplemented with physiologically relevant doses of either prolactin (50 ng/ml), cortisol (500 ng/ml), or cortisol + prolactin (500 + 50 ng/ml, respectively). In series 1, epithelia were exposed to progressively diluted apical media (100, 75, 50, 25, 12.5% L15, and FW) at 24-h intervals. The preparations retained integrity [high transepithelial resistance (TER); low ion efflux rates] during this prolonged dilution protocol. Cortisol, or cortisol + prolactin, resulted in a greater TER and reduced ion efflux rates during dilution, likely an effect on junctional permeability of PVCs, but did not promote active Na+ and Cl- uptake from apical FW. In series 2, epithelia were directly exposed to apical FW and ion fluxes measured over the first 6 h. Under these conditions, cortisol or cortisol + prolactin promoted active uptake of both Na+ and Cl- simultaneously from apical FW, probably attributable to actions on the MRCs. However, Na+-K+-ATPase activities were not significantly altered by any of the treatments in either series. Overall, prolactin alone did not appear to promote FW adaptation but exhibited synergism with cortisol. These results provide further support for the cultured DSI epithelium as an in vitro model for ion transport in FW fish.
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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 | 0.001 |
| 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".