Generation of Trophoblast-Like Cells From Hypomethylated Porcine Adult Dermal Fibroblasts
Bibliographic record
Abstract
The first differentiation event in mammalian embryos is the formation of the trophectoderm, which is the progenitor of the outer epithelial components of the placenta, and which supports the fetus during the intrauterine life. However, the epigenetic and paracrine controls at work in trophectoderm differentiation are still to be fully elucidated and the creation of dedicated in vitro models is desirable to increase our understanding. Here we propose a novel approach based on the epigenetic conversion of adult dermal fibroblasts into trophoblast-like cells. The method combines the use of epigenetic erasing with an ad hoc differentiation protocol. Dermal fibroblasts are erased with 5-azacytidine (5-aza-CR) that confers cells a transient high plasticity state. They are then readdressed toward the trophoblast (TR) phenotype, using MEF conditioned medium, supplemented with bone morphogenetic protein 4 (BMP4) and inhibitors of the Activin/Nodal and FGF2 signaling pathways in low O2 conditions. The method here described allows the generation of TR-like cells from easily accessible material, such as dermal fibroblasts, that are very simply propagated in vitro. Furthermore, the strategy proposed is free of genetic modifications that make cells prone to instability and transformation. The TR model obtained may also find useful application in order to better characterize embryo implantation mechanisms and developmental disorders based on TR defects.
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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".