Amniotic fluid stem cell extracellular vesicles promote lung development via TGF-beta modulation in a fetal rat model of oligohydramnios
Bibliographic record
Abstract
Abstract Oligohydramnios (decreased amniotic fluid volume for gestational age) is a severe condition associated with high morbidity and mortality mainly due to fetal pulmonary hypoplasia. Currently, there are limited treatment options to promote fetal lung development. Administration of stem cells and their derivates have shown promising regenerative properties for several fetal and neonatal diseases related to arrested lung development. Herein, we first characterized pulmonary hypoplasia secondary to oligohydramnios in a surgical rat model. Experimental induction of oligohydramnios led to impaired lung growth, branching morphogenesis (fewer airspaces with decreased Fgf10 , Nrp1 , Ctnnb1 expression), proximal/distal progenitor cell patterning (decreased Sox2 and Sox9 expression), and TGF-β signaling. We then tested antenatal administration of extracellular vesicles derived from amniotic fluid stem cells (AFSC- EVs). In oligohydramnios lungs, AFSC-EV administration improved lung branching morphogenesis and airway progenitor cell patterning at least in part through the release of miR-93-5p. Our experiments suggest that AFSC-EV miR-93-5p blocked SMAD 7, resulting in upregulation of pSMAD2/3 and restoration of TGF-β signaling. Conversely, oligohydramnios lungs treated with antagomir 93-5p transfected AFSC- EVs had decreased branching morphogenesis and TGF-β signaling. This is the first study reporting that antenatal administration of stem cell derivatives could be a potential therapy to rescue lung development in fetuses with oligohydramnios. Highlights Pulmonary hypoplasia secondary to oligohydramnios in fetal rats is characterized by impaired TGF-β signaling. AFSC-EV administration improves fetal lung branching morphogenesis and airway progenitor cell patterning. AFSC-EV effects are mediated at least in part via modulation of TGF-β signaling by the release of miR-93-5p from AFSC-EVs.
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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 | 0.000 |
| 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 | 0.000 |
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".