Long-term failure of alveologenesis after an early short-term exposure to a PDGF-receptor antagonist
Bibliographic record
Abstract
Survivors of moderate-to-severe bronchopulmonary dysplasia have impaired alveologenesis lasting at least into early adult life. The mechanisms underlying this long-term effect are unknown. We hypothesized that short-term inhibition of growth factor-mediated early alveolar formation would result in a long-term impairment of subsequent alveologenesis. Neonatal rats were injected daily with the platelet-derived growth factor (PDGF) receptor antagonist, imatinib mesylate, from day 1-7 of life, to inhibit the early alveolar formation occurring by in-growth of secondary crests into precursor saccules. The pups were then allowed to recover for 7, 14, 21, or 58 days. In imatinib-treated pups, DNA synthesis in total lung cells, and specifically in cells of secondary crests, was reduced at day 8 of life, had rebounded on day 14 of life but was then again reduced by day 28 of life. At day 8 of life, imatinib-treated pups had impaired alveologenesis as reflected by a decrease in secondary crests, an increase in alveolar size, and an overall decrease in both estimated alveolar number and generations compared with age-matched controls. No meaningful recovery was observed, even after a 21- or 58-day recovery period. The lungs of imatinib-treated pups had increased fibulin-5 content and an abnormal deposition of elastin. We conclude that reduced signaling through the PDGF pathways, at an early stage of alveologenesis, can result in long-lasting changes in lung architecture. A likely mechanism is through impaired formation of the elastin scaffold required for alveolarization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".