Transient Receptor Potential Ion Channels Mediate Adherens Junctions Dysfunction in a Toluene Diisocyanate-Induced Murine Asthma Model
Bibliographic record
Abstract
Disruption of epithelial cell-cell junctions is essential for the initiation and perpetuation of airway inflammation in asthma. We've previously reported compromised epithelial barrier integrity in a toluene diisocyanate (TDI)-induced occupational asthma model. This study is aimed to explore the role of transient receptor potential vanilloid 4 (TRPV4) and transient receptor potential ankyrin 1 (TRPA1) in the dysfunction of adherens junctions in TDI-induced asthma. Mice were sensitized and challenged with TDI for a chemical-induced asthma model. Selective blockers of TRPV4 glycogen synthase kinase (GSK)2193874, 5 and 10 mg/kg) and TRPA1 (HC030031, 10 and 20 mg/kg) were intraperitoneally given to the mice. Immunohistochemistry revealed different expression pattern of TRPV4 and TRPA1 in lung. TDI exposure increased TRPV4 expression in the airway, which can be suppressed by GSK2193874, while treatment with neither TDI alone nor TDI together with HC030031 led to changes of TRPA1 expression in the lung. Blocking either TRPV4 or TRPA1 blunted TDI-induced airway hyperreactivity, airway neutrophilia and eosinophilia, as well as Th2 responses in a dose-dependent manner. At the same time, membrane levels of E-cadherin and β-catenin were significantly decreased after TDI inhalation, which were inhibited by GSK2193874 or HC030031. Moreover, GSK2193874 and HC030031 also suppressed serine phosphorylation of glycogen synthase kinase 3β, tyrosine phosphorylation of β-catenin, as well as activation and nuclear transport of β-catenin in mice sensitized and challenged with TDI. Our study suggested that both TRPV4 and TRPA1 contribute critically to E-cadherin and β-catenin dysfunction in TDI-induced asthma, proposing novel therapeutic targets for asthma.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".