Efficient Generation of Murine Chimeric Antigen Receptor (CAR)-T Cells
Bibliographic record
Abstract
Engineered cell therapies utilizing chimeric antigen receptor (CAR)-T cells have achieved remarkable effectiveness in individuals with hematological malignancies and are presently undergoing development for the treatment of diverse solid tumors. So far, the preliminary evaluation of novel CAR-T cell products has predominantly taken place in xenograft tumor models using immunodeficient mice. This approach is chosen to facilitate the successful engraftment of human CAR-T cells in the experimental setting. However, syngeneic mouse models, in which tumors and CAR-T cells are derived from the same mouse strain, allow evaluation of new CAR technologies in the context of a functional immune system and comprehensive tumor microenvironment (TME). The protocol described here aims to streamline the process of mouse CAR-T cell generation by presenting standardized methods for retroviral transduction and ex vivo T cell culture. The methods described in this protocol can be applied to other CAR constructs beyond the ones used in this study to enable routine evaluation of new CAR technologies in immune-competent systems.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".