Directed Differentiation of Embryonic Stem Cells to the T-Lymphocyte Lineage
Bibliographic record
Abstract
Hematopoiesis is the highly regulated and complex process by which blood cells are formed. Hematopoiesis can be achieved in vitro by the differentiation of embryonic stem cells (ESCs) into hematopoietic lineage cells. Differentiation of ESCs initially gives rise to mesoderm colonies that go on to form hemangioblast cells, which possess endothelial and hematopoietic lineage potential. While the differentiation of several hematopoietic lineages from ESCs, such as erythrocytes and macrophages, can be easily recapitulated in vitro, T-cell differentiation requires additional Notch-dependent signals for their generation. Keeping with this, ESCs induced to differentiate with OP-9 cells, a bone marrow-derived stromal cell line, give rise to erythro-myeloid cells and B lymphocytes, while the expression of an appropriate Notch ligand, such as Delta-like 1, on OP-9 cells (OP9-DL1) is required to support the generation of T-cells in vitro. Here, we describe an updated and streamlined protocol for the generation of T-lineage cells from mouse ESCs cultured on OP9-DL1 cells. This approach can facilitate studies aimed to assess the effects of environmental and genetic manipulations at various stages of T-cell development.
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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 | 0.002 |
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".