Identification and Characterization of Side Population Cells in Embryonic Stem Cell Cultures
Bibliographic record
Abstract
Marker and functional heterogeneity has been described for embryonic stem cells (ESCs). This property has been correlated with the presence of ESC subpopulations resembling pluripotent cell lineages of the embryo. The ability to efflux Hoechst (Ho) displayed by side population (SP) cells has proven valuable as a marker to identify multipotent stem cells from a variety of tissues. Here we report that cultures from different ESC lines consistently show an SP population that displays antigens of undifferentiated ESCs, distinct drug efflux properties, and an expression pattern of ABC transporters, inner cell mass (ICM), and epiblast genes, which distinguish it from the non-SP ESC fraction. This SP population contains pluripotent cells that differentiate into ectoderm, mesoderm, and endoderm in embryoid body and teratoma assays. Further, purified SP cells efficiently integrate into developing morulae and contribute to ICM. Under standard ESC culture conditions, SP and non-SP populations display ability to convert into each other; however, an equilibrium establishes between these fractions. Using protocols customized for SP ESCs, we report that cells with similar efflux properties can be identified in the ICM of peri-implanted blastocysts. Our results indicate that ESCs display heterogeneity for the SP marker, and the SP population of these cultures contains cells that phenotypically and functionally resemble efflux-active ICM cells of the peri-implanted embryo. Our observations suggest an involvement of the SP phenotype in ESC maintenance and early embryo development, and support the idea that ESCs are composed of distinct phenotypic and functional pluripotent subpopulations in dynamic equilibrium.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".