Activation of Endothelial TRPV4 Exacerbates Myocardial Ischemia-Reperfusion Injury via Vascular Integrity Impairment
Bibliographic record
Abstract
Background Activation of transient receptor potential vanilloid 4 (TRPV4) exacerbates myocardial ischemia-reperfusion (IR) injury and is highly expressed in vascular endothelial cells. The role of TRPV4 in cardiac endothelial cells (CECs) during IR remains unclear. We hypothesized that endothelial TRPV4 contributes to post-ischemic vascular hyperpermeability and myocardial injury by modulating barrier function and apoptosis. Methods Myocardial IR was induced in C57BL/6 wild-type (WT), global TRPV4 knockout (TRPV4 -/- ), tamoxifen-inducible endothelial TRPV4 knockout (TRPV4 EC-/- ), and tamoxifen-treated controls. Primary cultured CECs (passage 3) were subjected to hypoxia-reoxygenation (HR) and treated with the TRPV4 antagonist GSK2193874 or agonist GSK101790A. Results Mice lacking TRPV4 mice exhibited smaller infarcts, preserved endothelial integrity, decreased vascular permeability, upregulated VE-cadherin, claudin-5, and occludin, and reduced inflammation. GSK2193874 pre-treatment reproduced these protective effects, whereas TRPV4 activation worsened injury. Endothelial-specific TRPV4 knockout provided similar protection. In CECs, TRPV4 inhibition attenuated HR-induced permeability increases and junctional protein loss, while TRPV4 agonist alone increased permeability and reduced VE-cadherin, claudin-5, and occludin. Mechanistically, TRPV4 activation increased CEC permeability via the Ca 2+ /PKC/RhoA/MLC pathway and promoted apoptosis through MAPK-AKT signaling. Conclusions Activation of endothelial TRPV4 CECs exacerbates post-IR vascular hyperpermeability and myocardial injury by impairing barrier integrity and promoting apoptosis. Targeting endothelial TRPV4 may represent a promising therapeutic strategy to mitigate myocardial IR injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".