Cellular mechanisms of Cl<sup>−</sup>transport in trout gill mitochondrion-rich cells
Bibliographic record
Abstract
We have studied Cl(-) transport mechanisms in freshwater rainbow trout gill mitochondrion-rich (MR) cells using intracellular pH (pH(i)) imaging. Scanning electron microscopy demonstrated maintenance of cellular polarity in isolated MR cells. MR cell subtypes were identified by Na(+) introduction to the bath, and Cl(-) transport mechanisms were subsequently examined. Cl(-)-free exposure resulted in an alkalinization of pH(i) in both MR cell subtypes, which was dependent on HCO(3)(-) in the bath and inhibited by 1 mM DIDS. Recovery of pH(i) from an acidified state in Na(+)-free conditions was also DIDS sensitive. These results are the first functional evidence for Cl(-)/HCO(3)(-) exchangers in fish gill MR cells. A direct switch from NaCl to Cl(-)-free conditions caused a pH(i) acidification in a subset of MR cells, which was enhanced in the absence of HCO(3)(-). The acidification was replaced by an alkalinization when Cl(-) removal was performed in the presence of NPPB (500 microM) or EIPA (500 microM). Finally, we found that the Na(+)-induced alkalinization of pH(i) found in a previous study is inhibited by EIPA. This inhibitor profile's results suggest the presence of a Cl(-)-dependent Na(+)/H(+) exchange mechanism.
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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 | 0.001 |
| 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".