IgE induces proliferation in human airway smooth muscle cells: role of MAPK and STAT3 pathways
Bibliographic record
Abstract
Airway remodeling is not specifically targeted by current asthma medications, partly owing to the lack of understanding of remodeling mechanisms, altogether posing great challenges in asthma treatment. Increased airway smooth muscle (ASM) mass due to hyperplasia/hypertrophy contributes significantly to overall airway remodeling and correlates with decline in lung function. Recent evidence suggests that IgE sensitization can enhance the survival and mediator release in inflammatory cells. Human ASM (HASM) cells express both low affinity (FcεRII/CD23) and high affinity IgE Fc receptors (FcεRI), and IgE can modulate the contractile and synthetic function of HASM cells. IgE was recently shown to induce HASM cell proliferation but the detailed mechanisms remain unknown. We report here that IgE sensitization induces HASM cell proliferation, as measured by 3H-thymidine, EdU incorporation, and manual cell counting. As an upstream signature component of FcεRI signaling, inhibition of spleen tyrosine kinase (Syk) abrogated the IgE-induced HASM proliferation. Further analysis of IgE-induced signaling depicted an IgE-mediated activation of Erk 1/2, p38, JNK MAPK, and Akt kinases. Lastly, lentiviral-shRNA-mediated STAT3 silencing completely abolished the IgE-mediated HASM cell proliferation. Collectively, our data provide mechanisms of a novel function of IgE which may contribute, at least in part, to airway remodeling observed in allergic asthma by directly inducing HASM cell proliferation.
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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) | 0.002 | 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".