<i>In Vivo</i> Role of Platelet-Derived Growth Factor–BB in Airway Smooth Muscle Proliferation in Mouse Lung
Bibliographic record
Abstract
Abstract Airway smooth muscle (ASM) hyperplasia in asthma likely contributes considerably to functional changes. Investigating the mechanisms behind proliferation of these cells may lead to therapeutic benefit. Platelet-derived growth factor (PDGF)-BB is a well known ASM mitogen in vitro but has yet to be directly explored using in vivo mouse models in the context of ASM proliferation and airway responsiveness. To determine the in vivo influence of PDGF-BB on gene transcripts encoding contractile proteins, ASM proliferation, and airway physiology, we used an adenovirus overexpression system and a model of chronic allergen exposure. We used adenovirus technology to selectively overexpress PDGF-BB in the airway epithelium of mice. Outcome measurements, including airway physiology, real time RT-PCR measurements, proliferating cell nuclear antigen staining, and airway smooth muscle quantification, were performed 7 days after exposure. The same outcome measurements were performed 24 hours and 4 weeks after a chronic allergen exposure model. PDGF-BB overexpression resulted in airway hyperresponsiveness, decreased lung compliance, increased airway smooth muscle cell numbers, positive proliferating cell nuclear antigen–stained airway smooth muscle cells, and a reduction in genes encoding contractile proteins. Chronic allergen exposure resulted in elevations in lung lavage PDGF-BB, which were observed in conjunction with changes in gene transcript expression encoding contractile proteins and ASM proliferation. We demonstrate for the first time in vivo that PDGF-BB induces ASM hyperplasia and changes in lung mechanics in mice and that, during periods of allergen exposure changes in lung, PDGF-BB are associated with changes in airway structure and function.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".