Overexpression of Trophoblast Stem Cell-Enriched MicroRNAs Promotes Trophoblast Fate in Embryonic Stem Cells
Bibliographic record
Abstract
The first cell fate choice of the preimplantation embryo generates the extraembryonic trophoblast and embryonic epiblast lineages. Embryonic stem cells (ESCs) and trophoblast stem cells (TSCs) can be utilized to investigate molecular mechanisms of this first cell fate decision. It has been established that ESCs can be induced to acquire trophoblast lineage characteristics upon manipulation of lineage-determining transcription factors. Here, we have interrogated the potential of microRNAs (miRNAs) to drive trans-differentiation of ESCs into the trophoblast lineage. Analysis of gene expression data identified a network of TSC-enriched miRNAs that were predicted to target mRNAs enriched in ESCs. Ectopic expression of these miRNAs in ESCs resulted in a stable trophoblast phenotype, supported by gene expression changes and in vivo contribution potential. This process is highly miRNA-specific and dependent on Hdac2 inhibition. Our experimental evidence suggests that these miRNAs promote a mural trophectoderm (TE)-like cell fate with physiological properties that differentiate them from the polar TE.
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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".