Hyperosmotic and isosmotic shrinkage differentially affect protein phosphorylation and ion transport
Bibliographic record
Abstract
In the present work, we compared the outcome of hyperosmotic and isosmotic shrinkage on ion transport and protein phosphorylation in C11-MDCK cells resembling intercalated cells from collecting ducts and in vascular smooth muscle cells (VSMC) from the rat aorta. Hyperosmotic shrinkage was triggered by cell exposure to hypertonic medium, whereas isosmotic shrinkage was evoked by cell transfer from an hypoosmotic to an isosmotic environment. Despite a similar cell volume decrease of 40%-50%, the consequences of hyperosmotic and isosmotic shrinkage on cellular functions were sharply different. In C11-MDCK and VSMC, hyperosmotic shrinkage completely inhibited Na(+),K(+)-ATPase and Na(+),P(i) cotransport. In contrast, in both types of cells isosmotic shrinkage slightly increased rather than suppressed Na(+),K(+)-ATPase and did not change Na(+),P(i) cotransport. In C11-MDCK cells, phosphorylation of JNK1/2 and Erk1/2 mitogen-activated protein kinases was augmented in hyperosmotically shrunken cells by ∼7- and 2-fold, respectively, but was not affected in cells subjected to isosmotic shrinkage. These results demonstrate that the data obtained in cells subjected to hyperosmotic shrinkage cannot be considered as sufficient proof implicating cell volume perturbations in the regulation of cellular functions under isosmotic conditions.
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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".