The effect of highly alkaline water (pH 9.5) on the morphology and morphometry of chloride cells and pavement cells in the gills of the freshwater rainbow trout: relationship to ionic transport and ammonia excretion
Bibliographic record
Abstract
Exposure of rainbow trout (Oncorhynchus mykiss) to alkaline water (pH 9.5) impairs ammonia excretion (JAmm) and gill-mediated ion-exchange processes, as characterized by decreased Cl-(JC1in) and Na+influx (JNain) across the gill. Scanning electron microscopy suggested that the depression of JC1inwas concomitant with an early decrease in the population of the most active chloride cells (CCs), partly compensated for by an increasing number of immature CCs. However, within 72 h after the onset of exposure to alkaline water, there was a 2-fold increase in the fractional apical surface area of CCs that paralleled complete recovery of the maximal Cl-influx rate (JC1max). These results suggest that recovery of JC1maxwas associated with greater CC surface area, resulting in more transport sites on the gill epithelium. Morphometric analysis of the outermost layer of pavement cells on the lamellar epithelium showed a greater density of microvilli during exposure to alkaline water, which may have contributed to partial restoration of the number of Na+transport sites (JNamax). Finally, the blood-to-water gill-diffusion distance decreased by 27% after 72 h at pH 9.5, and likely contributed to progressive restoration of ammonia excretion in alkaline water.
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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".