Derivation of T Cells <em>In Vitro</em> from Mouse Embryonic Stem Cells
Bibliographic record
Abstract
The OP9/OP9-DL1 co-culture system has become a well-established method for deriving differentiated blood cell types from embryonic and hematopoietic progenitors of both mouse and human origin. It is now used to address a growing variety of complex genetic, cellular and molecular questions related to hematopoiesis, and is at the cutting edge of efforts to translate these basic findings to therapeutic applications. The procedures are straightforward and routinely yield robust results. However, achieving successful hematopoietic differentiation in vitro requires special attention to the details of reagent and cell culture maintenance. Furthermore, the protocol features technique sensitive steps that, while not difficult, take care and practice to master. Here we focus on the procedures for differentiation of T lymphocytes from mouse embryonic stem cells (mESC). We provide a detailed protocol with discussions of the critical steps and parameters that enable reproducibly robust cellular differentiation in vitro. It is in the interest of the field to consider wider adoption of this technology, as it has the potential to reduce animal use, lower the cost and shorten the timelines of both basic and translational experimentation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.017 |
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".