Gene Expression Profiling of Embryo-Derived Stem Cells Reveals Candidate Genes Associated With Pluripotency and Lineage Specificity
Bibliographic record
Abstract
Large-scale gene expression profiling was performed on embryo-derived stem cell lines to identify molecular signatures of pluripotency and lineage specificity. Analysis of pluripotent embryonic stem (ES) cells, extraembryonic-restricted trophoblast stem (TS) cells, and terminally-differentiated mouse embryo fibroblast (MEF) cells identified expression profiles unique to each cell type, as well as genes common only to ES and TS cells. Whereas most of the MEF-specific genes had been characterized previously, the majority (67%) of the ES-specific genes were novel and did not include known differentiated cell markers. Comparison with microarray data from embryonic material demonstrated that ES-specific genes were underrepresented in all stages sampled, whereas TS-specific genes included known placental markers. Investigation of four novel TS-specific genes showed trophoblast-restricted expression in cell lines and in vivo, whereas one uncharacterized ES-specific gene, Esg-1, was found to be exclusively associated with pluripotency. We suggest that pluripotency requires a set of genes not expressed in other cell types, whereas lineage-restricted stem cells, like TS cells, express genes predictive of their differentiated lineage.
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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".