TRPV4: an exciting new target to promote alveolocapillary barrier function
Bibliographic record
Abstract
Transient receptor potential (TRP) channels are emerging as important players and drug targets in respiratory disease. Amongst the vanilloid-type TRP channels (which includes the six members of the TRPV family), target diseases include cough, asthma, cancer, and more recently, pulmonary edema associated with acute respiratory distress syndrome. Here, we critically evaluate a recent report that addresses TRPV4 as a candidate target for the management of acute lung injury that develops as a consequence of aspiration of gastric contents, or acute chlorine gas exposure. By use of two new TRPV4 inhibitors (GSK2220691 or GSK2337429A) and a trpv4(-/-) mouse strain, TRPV4 was implicated as a key mediator of pulmonary inflammation after direct chemical insult. Additionally, applied therapeutically, TRPV4 inhibitors exhibited vasculoprotective effects after chlorine gas exposure, inhibiting vascular leakage, and improving blood oxygenation. These observations underscore TRPV4 channels as candidate therapeutic targets in the management of lung injury, with the added need to balance these against the potential drawbacks of TRPV4 inhibition, such as the danger of limiting the immune response in settings of pathogen-provoked 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".