Mechanosensitive signalling in fish gill and other ion transporting epithelia
Bibliographic record
Abstract
Epithelia involved in vectorial salt transport respond to apical and basolateral changes in osmotic activity by moderating the transmural solute transport rate simultaneously with underlying volume regulatory mechanisms involved in regulatory volume increase (RVI) and decrease (RVD). This review examines rapid osmotic responses in salt secreting epithelia of marine and euryhaline teleost fish, with inclusion of recent results from other ion transporting epithelia that also respond rapidly to osmotic shock. Mitochondrion-rich chloride secreting cells of marine teleost fish gills and skin, when exposed to hypertonic shock, activate NaCl secretion via phosphorylation of Na(+), K(+), 2Cl(-) cotransporter (NKCC1) in the basolateral membrane and activation of anion channels in the apical membrane. Conversely, NaCl secretion is inhibited when chloride secreting cells are swollen osmotically. Mammalian airway epithelial cells also possess NKCC1 basally and apical anion channels [Cystic Fibrosis Transmembrane conductance Regulator (CFTR)]; with hypotonic shock, this epithelium releases ATP and NaCl secretion is stimulated via purinergic receptors, while hypertonic shock inhibits Na(+) uptake. In the eye, the ciliary epithelium activates Cl(-) channels in response to hypotonic shock as RVD, an effect that modulates transepithelial fluid transport rates. In the renal A6 cell line, K(+) and Cl(-) effluxes activate during RVD and RVI Na(+) transepithelial absorption. A common theme in these systems is ATP release in hypotonic shock with subsequent RVD-effective mechanisms such as NKCC1 inhibition and K(+) and Cl(-) efflux, but there are different effects of osmotic changes on transepithelial transport, apparently depending on the role of the epithelial system.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".