Hyperosmotic stress activates Rho: differential involvement in Rho kinase-dependent MLC phosphorylation and NKCC activation
Bibliographic record
Abstract
Hyperosmotic stress initiates adaptive responses, including phosphorylation of myosin light chain (MLC) and concomitant activation of Na+-K+-Cl- cotransporter (NKCC). Because the small GTPase Rho is a key regulator of MLC phosphorylation, we investigated 1) whether Rho is activated by hyperosmotic stress, and if so, what the triggering factors are, and 2) whether the Rho/Rho kinase (ROK) pathway is involved in MLC phosphorylation and NKCC activation. Rho activity was measured in tubular epithelial cells by affinity pulldown assay. Hyperosmolarity induced rapid (<1 min) and sustained (>20 min) Rho activation that was proportional to the osmotic concentration and reversed within minutes upon restoration of isotonicity. Both decreased cell volume at constant ionic strength and elevated total ionic strength at constant cell volume were capable of activating Rho. Changes in [Na+] and [K+] at normal total salinity failed to activate Rho, and Cl- depletion did not affect the hyperosmotic response. Thus alterations in cellular volume and ionic strength but not individual ion concentrations seem to be the critical triggering factors. Hyperosmolarity induced mono- and diphosphorylation of MLC, which was abrogated by the Rho-family blocker Clostridium toxin B. ROK inhibitor Y-27632 suppressed MLC phosphorylation under isotonic conditions and prevented its rise over isotonic levels in hypertonically stimulated cells. ML-7 had a smaller inhibitory effect. In contrast, it abolished the hypertonic activation of NKCC, whereas Y-27632 failed to inhibit this response. Thus hyperosmolarity activates Rho, and Rho/ROK pathway contributes to basal and hyperosmotic MLC phosphorylation. However, the hypertonic activation of NKCC is ROK independent, implying that the ROK-dependent component of MLC phosphorylation can be uncoupled from NKCC activation.
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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 | 0.001 |
| 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".