Cellular and Molecular Requirements for the Selection of In Vitro–Generated CD8 T Cells Reveal a Role for Notch
Bibliographic record
Abstract
Differentiation of CD8 single-positive (SP) T cells is predicated by the ability of lymphocyte progenitors to integrate multiple signaling cues provided by the thymic microenvironment. In the thymus and the OP9-DL1 system for T cell development, Notch signals are required for progenitors to commit to the T cell lineage and necessary for their progression to the CD4(+)CD8(+) double-positive (DP) stage of T cell development. However, it remains unclear whether Notch is a prerequisite for the differentiation of DP cells to the CD8 SP stage of development. In this study, we demonstrate that Notch receptor-ligand interactions allow for efficient differentiation and selection of conventional CD8 T cells from bone marrow-derived hematopoietic stem cells. However, bone marrow-derived hematopoietic stem cells isolated from Itk(-/-)Rlk(-/-) mice gave rise to T cells with decreased IFN-γ production, but gained the ability to produce IL-17. We further reveal that positive and negative selection in vitro are constrained by peptide-MHC class I expressed on OP9 cells. Finally, using an MHC class I-restricted TCR-transgenic model, we show that the commitment of DP precursors to the CD8 T cell lineage is dependent on Notch signaling. Our findings further establish the requirement for Notch receptor-ligand interactions throughout T cell differentiation, including the final step of CD8 SP selection.
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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 | 0.001 |
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".