Expression profile of androgen-modulated microRNAs in the fetal murine lung
Bibliographic record
Abstract
BACKGROUND: Androgens are known to delay lung development. As a consequence, the incidence and morbidity of respiratory distress syndrome of the neonate are higher for male than for female premature infants. We previously reported that many genes were expressed with a sex difference in the mouse developing lung and that several genes were under the control of androgens in the male fetal lung. microRNAs are small non-coding RNAs known to negatively regulate the expression of specific genes. In this study, we examined whether murine miRNAs are under the control of androgens in the male developing lung. METHODS: Expression profiling of microRNAs was performed by microarrays using RNA extracted from male fetal lungs isolated on gestational day (GD) 17.0 and GD 18.0 after daily injection of pregnant mice from GD 10.0 with the antiandrogen flutamide or vehicle only. To identify putative miRNA target genes, the data obtained here were combined with gene profiling data reported previously using the same RNA preparations. qPCR was used to confirm microarray data with fetal lungs from other litters than those used in microarrays. RESULTS: Flutamide induced downregulation and upregulation of several miRNAs on GD 17.0 and GD 18.0. Of the 43 mature miRNAs modulated by flutamide on GD 17.0, 60 % were downregulated, whereas this proportion was only of 34 % for the 35 mature miRNAs modulated on GD 18.0. For 29 and 26 flutamide-responsive miRNAs, we found a corresponding target inversely regulated by androgens on GD 17.0 and 18.0, respectively. The androgen-regulated target genes were involved in several biological processes (lipid metabolism, cell proliferation, and lung development) and molecular functions, mainly transcription factor binding. CONCLUSIONS: Regulation of male lung development involves several miRNAs that are under androgen modulation in vivo.
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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) | 0.000 | 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 | 0.000 |
| 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".