Induction of early growth-response factor 1 by platelet-derived growth factor in human airway smooth muscle
Bibliographic record
Abstract
Platelet-derived growth factors (PDGF) may contribute to the activation and growth of smooth muscle that is characteristic of airway remodeling in asthmatic patients. Early growth response 1 (EGR-1) is a transcription factor that is induced in several cell types by PDGF and may mediate some of the effects of PDGF. We show that human airway smooth muscle cells in cell culture express EGR-1 1 h after addition of PDGF. Analysis of the EGR-1 promoter indicates that a serum response element located between 663 and 654 bp 5' to the ATG start site is essential for this induction. Serum response factor, E26 transcription factor-like protein 1, and serum protein 1 bind to this region. PDGF causes phosphorylation of ERK1/2 and is temporally associated with E26 transcription factor-like protein 1 phosphorylation. Finally, the specific ERK1/2 inhibitor U-0126 abolishes PDGF-induced expression of EGR-1 in these cells. On the basis of these data, we speculated that EGR-1 would be increased in airway smooth muscle of asthmatic patients compared with nonasthmatic controls. Using immunohistochemistry, we found that EGR-1 protein was expressed in airway smooth muscle cells and epithelial cells of asthmatic patients and nonasthmatic controls; however, there was no significant difference in the intensity of staining between groups. EGR-1 was similarly expressed in the lungs of mice with and without ovalbumin-induced airway inflammation; however, there was no difference between groups by immunohistochemistry and quantitative PCR. Although EGR-1 is induced by PDGF in human airway smooth muscle cells in cell culture, the role of EGR-1 in airway remodeling and asthma remains to be established.
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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".