Steroid and Oxygen Effects on eIF4F Complex, mTOR, and ENaC Translation in Fetal Lung Epithelia
Bibliographic record
Abstract
Fetal distal lung epithelium (FDLE) must increase amiloride-sensitive epithelial Na(+) channel (ENaC) activity during the perinatal period to increase Na(+) transport and fluid clearance. Glucocorticosteroid (GC) levels increase, there is a 7-fold increase in Po(2) at birth, and we have previously shown that dexamethasone (DEX)-induced alpha-ENaC mRNA is efficiently translated only under postnatal (21%) O(2) (Otulakowski et al., AJRCMB 2006;34:204-212). Translation of mRNAs with long GC-rich 5'UTRs, such as alpha-ENaC mRNA, are sensitive to the amount of eIF4F, the mRNA 5'-cap binding complex composed of eIF4E and eIF4G. We now show, by Western blotting and m(7)GTP-Sepharose pull-down experiments, that in FDLE cultured under 3% O(2), DEX decreases formation of eIF4F and increases association of eIF4E with its inhibitor 4E-BP by changing 4E-BP phosphorylation. Conversely, FDLE cultured at 21% O(2) expressed lower levels of 4E-BP and maintained eIF4E-eIF4G association independent of DEX. Phosphorylation of 4E-BP is regulated by the kinase mTOR. Under 3% O(2), DEX decreased abundance of phosphorylated forms of the mTOR effectors, S6 kinase and ribosomal protein S6. Neither effect was associated with changes in REDD1, an upstream regulator of mTOR. When mTOR was inhibited (3 nM rapamycin) there was reduced 4E-BP phosphorylation, fewer ribosomes on alpha-ENaC mRNA, and decreased amiloride-sensitive short-circuit current, but no change in ribosomal loading onto any of beta- or gamma-ENaC or cytokeratin 18 mRNAs. We speculate that at birth increased Po(2) acts with GC through an mTOR-related pathway to increase alpha-ENaC protein synthesis, thereby promoting lung fluid absorption.
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 | 0.000 | 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".