TGF-β receptor II in epithelia<i>versus</i>mesenchyme plays distinct roles in the developing lung
Bibliographic record
Abstract
Transforming growth factor (TGF)-beta signalling plays important roles in regulating lung development. However, the specific regulatory functions of TGF-beta signalling in developing lung epithelial versus mesenchymal cells are still unknown. By immunostaining, the expression pattern of the TGF-beta type II receptor (TbetaRII) was first determined in the developing mouse lung. The functions of TbetaRII in developing lung were then determined by conditionally knocking out TbetaRII in the lung epithelium of floxed-TbetaRII/surfactant protein C-reverse tetracycline transactivator/TetO-Cre mice versus mesenchyme of floxed-TbetaRII/Dermo1-Cre mice. TbetaRII was expressed only in distal airway epithelium at early gestation (embryonic day (E)11.5), but in both airway epithelium and mesenchyme from mid-gestation (E14.5) to post-natal day 14. Abrogation of TbetaRII in mouse lung epithelium resulted in retardation of post-natal lung alveolarisation, with markedly decreased type I alveolar epithelial cells, while no abnormality in prenatal lung development was observed. In contrast, blockade of TbetaRII in mesoderm-derived tissues, including lung mesenchyme, resulted in mildly abnormal lung branching and reduced cell proliferation after mid-gestation, accompanied by multiple defects in other organs, including diaphragmatic hernia. The primary lung branching defect was verified in embryonic lung explant culture. The novel findings of the present study suggest that transforming growth factor-beta type II receptor-mediated transforming growth factor-beta signalling plays distinct roles in lung epithelium versus mesenchyme to differentially control specific stages of lung development.
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 | 0.001 | 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".