Characterization of Developmental Pathway of Natural Killer Cells from Embryonic Stem Cells In Vitro
Bibliographic record
Abstract
In vitro differentiation of embryonic stem (ES) cells is often used to study hematopoiesis. However, the differentiation pathway of lymphocytes, in particular natural killer (NK) cells, from ES cells is still unclear. Here, we used a multi-step in vitro ES cell differentiation system to study lymphocyte development from ES cells, and to characterize NK developmental intermediates. We generated embryoid bodies (EBs) from ES cells, isolated CD34(+) EB cells and cultured them on OP9 stroma with a cocktail of cytokines to generate cells we termed ES-derived hematopoietic progenitors (ES-HPs). EB cell subsets, as well as ES-HPs derived from EBs, were tested for NK, T, B and myeloid lineage potentials using lineage specific cultures. ES-HPs derived from CD34(+) EBs differentiated into NK cells when cultured on OP9 stroma with IL-2 and IL-15, and into T cells on Delta-like 1-transduced OP9 (OP9-DL1) with IL-7 and Flt3-L. Among CD34(+) EB cells, NK and T cell potentials were detected in a CD45(-) subset, whereas CD45(+) EB cells had myeloid but not lymphoid potentials. Limiting dilution analysis of ES-HPs generated from CD34(+)CD45(-) EB cells showed that CD45(+)Mac-1(-)Ter119(-) ES-HPs are highly enriched for NK progenitors, but they also have T, B and myeloid potentials. We concluded that CD45(-)CD34(+) EB cells have lymphoid potential, and they differentiate into more mature CD45(+)Lin(-) hematopoietic progenitors that have lymphoid and myeloid potential. NK progenitors among ES-HPs are CD122(-) and they rapidly acquire CD122 as they differentiate along the NK 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 | 0.001 |
| 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".