Fibroblast Growth Factor-2 and Receptor-1α(IIIc) Regulate Postnatal Rat Lung Cell Apoptosis
Bibliographic record
Abstract
RATIONALE: Fibroblast growth factor receptor-1alpha(IIIc) [FGF-R1alpha(IIIc)] regulates recovery of neonatal rat lung growth, after 95% oxygen-mediated growth arrest. Its role in normal postnatal alveologenesis is unknown. OBJECTIVE: To determine if FGF-R1alpha(IIIc) regulates normal postnatal alveologenesis. METHODS: Truncated soluble FGF-R1alpha(IIIc) or neutralizing antibodies to FGF-1 or FGF-2 were injected intraperitoneally into 3-d-old rats. The pups were killed at Day 7 for studies of alveolar development. MEASUREMENTS AND MAIN RESULTS: Injected, truncated soluble FGF-R1alpha(IIIc) inhibited phosphorylation of the endogenous FGF-R1, and downstream pathway, and paradoxically increased lung DNA content and tissue fraction while inhibiting lung cell DNA synthesis. The increase in tissue thickness was due to reduced apoptosis, as indicated by reductions in cleaved effector caspases 3 and 7. Inhibition of the intrinsic apoptosis pathway was suggested by decreases in the proapoptotic protein Bax and mitochondrial cytochrome c release, and an increase in the antiapoptotic protein Bcl-x(L). Injected antibodies to FGF-1 and FGF-2 had no effect on DNA synthesis, but both increased Bcl-x(L) content and decreased cytochrome c release and cleaved caspase-7 protein expression. However, only injection of the antibody to FGF-2 replicated the increased tissue fraction and inhibited apoptosis observed with the injection of truncated soluble FGF-R1alpha(IIIc). CONCLUSIONS: Inhibition of ligand binding, most likely of FGF-2, to the FGF-R1alpha(IIIc) inhibits normal postnatal lung cell apoptosis.
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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) | 0.001 | 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 | 0.001 |
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".