Transforming Growth Factor- <i>β</i> Induces Differentiation of the Labyrinthine Trophoblast Stem Cell Line SM10
Bibliographic record
Abstract
The mammalian placenta consists of different trophoblast cell types that assist in the variety of functions required for the maintenance of pregnancy. In rodents, labyrinthine trophoblasts of the placenta are especially important, because they are capable of differentiating into fused labyrinthine cells, which form the feto-maternal exchange surface. Even though the molecular signals triggering labyrinthine trophoblast differentiation are poorly understood, transforming growth factor-beta (TGF-beta) has been shown to be present in the placental environment and alter trophoblast development. In this study, we investigated the effects of TGF-beta on the differentiation of the labyrinthine trophoblast stem cell lines SM10 and HRP-1. RT-PCR analyses demonstrated that while the molecular expression of labyrinthine-specific lineage markers (Esx1, Tfeb, and Tec) was maintained in TGF-beta-treated SM10 and HRP-1 cells, TGF-beta induced the down-regulation of trophoblast stem cell markers Id2 and Cdx2. In contrast, TGF-beta induced the expression of a marker of differentiated labyrinthine trophoblasts, Gcm1, only in the SM10 cell line. Furthermore, we demonstrated an increased glucose uptake in the TGF-beta-treated SM10 cells, indicative of functional differentiation. Finally, cell fusion in TGF-beta-treated SM10 and HRP-1 cells was investigated by western blotting analysis of placental alkaline phosphatase and cadherin-11 and by microscopic analyses of cell morphology using green fluorescent protein (GFP) and rhodamine phalloidin staining. The western blotting and morphological analyses indicate TGF-beta-induced cell fusion and morphological differentiation in the SM10 cell line. The SM10 cell line will provide a new and unique model for detailed analysis of TGF-beta-induced molecular events associated with labyrinthine trophoblast differentiation and function.
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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) | 0.002 | 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".