Mesenchymal stem cells protect from hypoxia-induced alveolar epithelial-mesenchymal transition
Bibliographic record
Abstract
Administration of bone marrow-derived human mesenchymal stem cells (hMSC) reduces lung inflammation, fibrosis, and mortality in animal models of lung injury, by a mechanism not completely understood. We investigated whether hMSC would prevent epithelial-mesenchymal transition (EMT) induced by hypoxia in primary rat alveolar epithelial cell (AEC). In AEC cultured on semipermeable filters, prolonged hypoxic exposure (1.5% O2 for up to 12 days) induced phenotypic changes consistent with EMT, i.e., a change in cell morphology, a decrease in transepithelial resistance (Rte) and in the expression of epithelial markers [zonula occludens-1 (ZO-1), E-cadherin, AQP-5, TTF-1], together with an increase in mesenchymal markers [vimentin, α-smooth muscle actin (α-SMA)]. Expression of transcription factors driving EMT such as SNAIL1, ZEB1, and TWIST1 increased after 2, 24, and 48 h of hypoxia, respectively. Hypoxia also induced TGF-β1 mRNA expression and the secretion of active TGF-β1 in apical medium, and the expression of connective tissue growth factor (CTGF), two inducers of EMT. Coculture of AEC with hMSC partially prevented the decrease in Rte and in ZO-1, E-cadherin, and TTF-1 expression, and the increase in vimentin expression induced by hypoxia. It also abolished the increase in TGF-β1 expression and in TGF-β1-induced genes ZEB1, TWIST1, and CTGF. Finally, incubation with human recombinant KGF at a concentration similar to what was measured in hMSC-conditioned media restored the expression of TTF-1 and prevented the increase in TWIST1, TGF-β1, and CTGF in hypoxic AEC. Our results indicate that hMSC prevent hypoxia-induced alveolar EMT through the paracrine modulation of EMT signaling pathways and suggest that this effect is partly mediated by KGF.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".