WNT-5A and WNT-11 as novel regulators of the contractile airway smooth muscle phenotype
Bibliographic record
Abstract
Increased contractility is an important feature of the remodeled airway smooth muscle (ASM) bundle in asthma. The regulation of contractile phenotype marker expression by TGF-β signaling constitutes a key mechanism; however, the underlying molecular mechanisms are poorly understood. Non-canonical WNT signaling is a major regulator of cytoskeletal remodeling and regulates cell movements and polarity during development. Here, we investigated the role of non-canonical WNT signaling in contractile phenotype expression in ASM cells. We used cultured primary and immortalized human ASM cells. Gene expression was analyzed by PCR whereas western blotting and immunocytochemistry were employed for protein expression studies. Serum deprivation or TGF-β treatment induced a contractile ASM phenotype accompanied by an increase in α-sm-actin and calponin. Interestingly, contractile myocytes were markedly enriched in WNT-5A and -11. Knock-down of WNT-5A or -11 using specific siRNA attenuated the TGF-β-induced increase in α-sm-actin protein abundance by 44% and 51%, respectively. Notably, recombinant WNT-5A and -11 were not sufficient to induce contractile phenotype expression in the absence of TGF-β. Further, whereas Smad3 signaling inhibitor (SIS3; 3 μM) reduced TGF-β induced α-sm-actin protein abundance, it did not attenuate WNT-5A and -11 expression, suggesting the cooperative regulation by Smad and WNT-5A/-11 signaling. In conclusion, our data suggest a novel role of WNT-5A and -11 in the regulation of contractile phenotype expression in ASM and provide insight into the mechanisms of airway remodeling.
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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 | 0.000 |
| 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".