Shear Stress Regulates TRPV4 Channel Clustering and Translocation from Adherens Junctions to the Basal Membrane
Bibliographic record
Abstract
influx via TRPV4 on the surface of endothelial cells greatly influences endothelial adaptation to blood flow, but how mechanical stress from blood flow controls TRPV4 integration into this physiological function is not fully understood. Here, we studied the spatial organization of TRPV4 and its relationship to the adherens junction component β-catenin using single- and dual-color direct stochastic optical reconstruction microscopy (dSTORM). In non-stimulated endothelial cells, TRPV4 is clustered in small protein islands, as is β-catenin. Using dual-color imaging, we found that TRPV4 and β-catenin reside in similar islands and can be found at both the basolateral and basal membranes. Following shear stress stimulation, TRPV4 molecules formed smaller clusters, with the majority residing outside of clusters. Further shear stress stimulation changed the molecular distribution of TRPV4 molecules, limiting them to the basal membrane. This redistribution and the smaller clusters resulted in the segregation of TRPV4 from β-catenin. Furthermore, TRPV4 trafficking was controlled by focal adhesion kinase and activation of the α5ß1 integrin. These highly differentiated spatial redistributions suggest that mechanotransduction of blood flow is controlled via a more complex hierarchy than previously thought.
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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 | 0.001 |
| 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".