Ovine surfactant protein cDNAs: use in studies on fetal lung growth and maturation after prolonged hypoxemia
Bibliographic record
Abstract
cDNAs for ovine surfactant-associated protein (SP) A, SP-B, and SP-C have been cloned and shown to possess strong similarity to cDNAs for surfactant apoproteins in other species. These reagents were employed to examine the effect of fetal hypoxia on the induction of surfactant apoprotein expression in the fetal lamb. Postnatal lung function is dependent on adequate growth and maturation during fetal development. Insulin-like growth factor (IGF) I and IGF-II, which are present in all fetal tissues studied, possess potent mitogenic and proliferative actions, and their effects can be modulated by IGF-specific binding proteins (IGFBPs). Hypoxia can lead to increases in circulating cortisol and catecholamines that can influence lung maturation. Therefore, the effects of mild hypoxia in chronically catheterized fetal lambs at gestational days 126-130 and 134-136 (term 145 days) on the expression of pulmonary surfactant apoproteins and IGFBPs were examined. Mild hypoxia for 48 h resulted in an increase in plasma cortisol that was more pronounced at later gestation, and in these animals, there was a twofold increase in SP-A mRNA. SP-B mRNA levels also increased twofold, but this was not significant. SP-C mRNA was not altered. No significant changes in apoprotein mRNA were observed with the younger fetuses. However, these younger animals selectively exhibited reduced IGFBP-5 mRNA levels. IGF-I mRNA was also reduced at 126-130 days, although this conclusion is tentative due to low abundance. IGF-II levels were not affected at either gestational age. We conclude that these data suggest that mild prolonged fetal hypoxia produces alterations that could affect fetal cellular differentiation early in gestation and can induce changes consistent with lung maturation closer to term.
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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 | 0.001 |
| 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".