Transgenic Glucocorticoid Receptor Expression Driven by the SP-C Promoter Reduces Neonatal Lung Cellularity and Midkine Expression in GR<sup>hypo</sup> Mice
Bibliographic record
Abstract
BACKGROUND: Congenital truncation of the glucocorticoid receptor (GR) is known to lead to lethal lung immaturity in newborn mice associated with increased lung cellularity (ratio of tissue to airspace) and, as we previously showed, prolonged expression of the retinoid-responsive growth factor midkine. OBJECTIVES: We sought to determine if these changes would be reversed by transgenic expression of GR exclusively in the distal airway epithelium. METHODS: Mice were generated with expression of transgenic rat (r) GR driven by the human (h) SP-C promoter, on a background of congenital GR truncation. RESULTS: Transgenic epithelial GR expression reduced lung cellularity and midkine expression to levels comparable to wild-type littermates. Nevertheless, the newborn transgenic mice still displayed respiratory failure. Moreover, epithelial expression of the GR transgene did not alter expression of a number of important markers of lung maturation. CONCLUSIONS: Our data demonstrating normalization of the lung tissue to airspace ratio in neonatal mice expressing transgenic GR in the distal airway epithelium is consistent with the concept that normal mesenchymal cell loss is due to GR-responsive stimulation from epithelial cells. However, we could find no evidence of altered apoptotic activity between the groups of mice. We speculate that correction of the severe neonatal lung phenotype of GR-deficient mice will require expression of normal GR in non-epithelial as well as epithelial tissues.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".