Low-Oxygen Tension and IGF-I Promote Proliferation and Multipotency of Placental Mesenchymal Stem Cells (PMSCs) from Different Gestations via Distinct Signaling Pathways
Bibliographic record
Abstract
The microenvironment of placental mesenchymal stem cells (PMSCs) is dynamic throughout gestation and determines changes in cell fate. In vivo, PMSCs initially develop in low-oxygen tension and low IGF-I concentrations, and both increase gradually with gestation. The impact of varying concentrations of IGF-I and changing oxygen tension on PMSC signaling and multipotency was investigated in PMSCs from early (preterm) and late (term) gestation human placentae. Preterm PMSCs had greater proliferative response to IGF-I, which was further enhanced by low-oxygen tension. Low-oxygen tension alone was sufficient to induce ERK1/2 phosphorylation, whereas IGF-I was required for AKT (protein kinase B) phosphorylation. Low-oxygen tension prolonged ERK1/2 and AKT phosphorylation with a slowed phosphorylation decay even in presence of IGF-I. Low-oxygen tension maintained higher levels of IGF-I receptor and insulin receptor substrate 1 that were otherwise decreased by exposure to IGF-I and induced a differential phosphorylation pattern on IGF-I receptorβ and insulin receptor substrate 1. Phosphorylation of ERK1/2 and AKT was different between the preterm and term PMSCs, and phospho-AKT, and not phospho-ERK1/2, was the major determinant of PMSC proliferation and octamer-4 levels. These studies demonstrate that low-oxygen tension regulates the fate of PMSCs from early and late gestations in response to IGF-I, both independently and dependently, via specific signal transduction mechanisms.
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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".