<scp>l</scp>-Thyroxine promotes a proliferative airway smooth muscle phenotype in the presence of TGF-β1
Bibliographic record
Abstract
Hypothyroidism may reduce, whereas hyperthyroidism may aggravate, asthma symptoms. The mechanisms underlying this relationship are largely unknown. Since thyroid hormones have central roles in cell growth and differentiation, we hypothesized that airway remodeling, in particular increased airway smooth muscle (ASM) mass, may be involved. To address this hypothesis, we investigated the effects of triiodothyronine (T3) and l-thyroxine (T4) in the absence and presence of the profibrotic transforming growth factor (TGF)-β1 on human ASM cell phenotype switching. T3 (1-100 nM) and T4 (1-100 nM) did not affect basal ASM proliferation. However, when combined with TGF-β1 (2 ng/ml), T4 synergistically increased the proliferative response, whereas only a minor effect was observed for T3. In line with a switch from a contractile to a proliferative ASM phenotype, T4 reduced the TGF-β1-induced contractile protein expression by ∼50%. Cotreatment with T3 reduced TGF-β1-induced contractile protein expression by ∼25%. The synergistic increase in proliferation was almost fully inhibited by the integrin αvβ3 antagonist tetrac (100 nM), whereas no significant effects of the thyroid receptor antagonist 1-850 (3 μM) were observed. Inhibition of MEK1/2, downstream of the integrin αvβ3, also inhibited the T4- and TGF-β1-induced proliferative responses. Collectively, the results indicate that T4, and to a lesser extent T3, promotes a proliferative ASM phenotype in the presence of TGF-β1, which is predominantly mediated by the membrane-bound T4 receptor αvβ3. These results indicate that thyroid hormones may enhance ASM remodeling in asthma, which could be of relevance for hyperthyroid patients with this disease.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".