Inflammatory cytokines, goblet cell hyperplasia and altered lung mechanics in Lgl1 +/- mice
Bibliographic record
Abstract
BACKGROUND: Neonatal lung injury, a leading cause of morbidity in prematurely born infants, has been associated with arrested alveolar development and is often accompanied by goblet cell hyperplasia. Genes that regulate alveolarization and inflammation are likely to contribute to susceptibility to neonatal lung injury. We previously cloned Lgl1, a developmentally regulated secreted glycoprotein in the lung. In rat, O2 toxicity caused reduced levels of Lgl1, which normalized during recovery. We report here on the generation of an Lgl1 knockout mouse in order to determine whether deficiency of Lgl1 is associated with arrested alveolarization and contributes to neonatal lung injury. METHODS: An Lgl1 knockout mouse was generated by introduction of a neomycin cassette in exon 2 of the Lgl1 gene. To evaluate the pulmonary phenotype of Lgl1+/- mice, we assessed lung morphology, Lgl1 RNA and protein, elastin fibers and lung function. We also analyzed tracheal goblet cells, and expression of mucin, interleukin (IL)-4 and IL-13 as markers of inflammation. RESULTS: Absence of Lgl1 was lethal prior to lung formation. Postnatal Lgl1+/- lungs displayed delayed histological maturation, goblet cell hyperplasia, fragmented elastin fibers, and elevated expression of TH2 cytokines (IL-4 and IL-13). At one month of age, reduced expression of Lgl1 was associated with elevated tropoelastin expression and altered pulmonary mechanics. CONCLUSION: Our findings confirm that Lgl1 is essential for viability and is required for developmental processes that precede lung formation. Lgl1+/- mice display a complex phenotype characterized by delayed histological maturation, features of inflammation in the post-natal period and altered lung mechanics at maturity. Lgl1 haploinsufficiency may contribute to lung disease in prematurity and to increased risk for late-onset respiratory disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".