The mineralocorticoid receptor contributes to barrier function of a model fish gill epithelium
Bibliographic record
Abstract
Cortisol-induced epithelial tightening of a primary cultured rainbow trout gill epithelium model occurs in association with reduced paracellular permeability and increased abundance of select barrier-forming TJ proteins. Corticosteroid receptor (CR) pharmacological blocker studies have suggested that to produce this tightening effect, cortisol acts on the mineralocorticoid receptor (MR) as well as glucocorticoid receptors (GRs). This study considered how cortisol influenced model gill epithelium permeability and TJ properties by transcriptional knockdown of the gene encoding MR (mr-KD) using double-stranded RNA. Following mr-KD a significant reduction in MR protein abundance was observed in the epithelium. The mr-KD epithelium demonstrated reduced transepithelial resistance (TER) and increased the paracellular flux of [3H] polyethylene glycol (MW 400 kDa, PEG-400). Concurrently, mRNA abundance of gr2 and 11βhsd increased, indicating a possible compensatory response to mr-KD. Transcript abundance of claudin (cldn) -6, -8d, 23a and -28b decreased while cldn-20a increased in mr-KD preparations. Cortisol-induced epithelial tightening was enhanced in mr-KD preparations, suggesting that alterations in CRs and TJ composition augmented model epithelium barrier function in response to lowered MR abundance. Cortisol treatment significantly increased the transcript and protein abundance of TJ proteins such as cldn/Cldn -8d, and -28b. However, in mr-KD preparations, Cldn-28b protein abundance did not significantly alter in response to cortisol treatment, while Cldn-8d significantly elevated. Data suggest that mr-KD compromises normal barrier function of a primary cultured rainbow trout gill epithelium both in the presence and absence of cortisol and that Cldn-28b protein abundance may be modulated by cortisol via the MR only.
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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".