<i>Claudin-10</i>isoform expression and cation selectivity change with salinity in salt-secreting epithelia of<i>F. heteroclitus</i>
Bibliographic record
Abstract
To provide insight into claudin (Cldn) tight junction (TJ) protein contributions to branchial salt secretion in marine teleost fishes, this study examined cldn-10 TJ protein isoforms of a euryhaline teleost (mummichog; Fundulus heteroclitus) in association with salinity change and measurements of transepithelial cation selectivity. Mummichogs were transferred from fresh water (FW) to seawater (SW, 35 ‰) and from SW to hypersaline SW (2SW, 60 ‰) in a time course with transfer control groups (FW to FW and SW to SW). FW to SW transfer increased mRNA abundance of cldn-10d and -10e by 2-fold, whilst cldn-10c and -10f transcripts were unchanged. Transfer from SW to 2SW did not alter cldn-10d, and transiently altered cldn-10e abundance, but increased cldn-10c and -10f by 4-fold. This was coincident with an increased number of single-stranded junctions (observed by TEM). For both salinity transfers; (1) cldn-10e mRNA was acutely responsive (i.e. after 24 h), (2) other responsive cldn-10 isoforms increased later (3-7 days), and (3) cystic fibrosis transmembrane conductance regulator (cftr) mRNA was elevated in accordance with established changes in transcellular Cl− movement. Changes in mRNA encoding cldn-10c and -10f appeared linked, consistent with the tandem repeat locus in the Fundulus genome, whereas mRNA for tandem cldn-10d and -10e seemed independent of each other. Cation selectivity sequence measured by voltage and conductance responses to artificial SW revealed Eisenman sequence VII: Na+>K+>Rb+∼Cs+>Li+. Collectively, these data support the idea that Cldn-10 TJ proteins create and maintain cation-selective pore junctions in salt-secreting tissues of teleost fishes.
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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".