Antigen Presenting Cell Mimetic Lipid Nanoparticles for Rapid mRNA CAR T Cell Cancer Immunotherapy
Bibliographic record
Abstract
Chimeric antigen receptor (CAR) T cell therapy has achieved remarkable clinical success in the treatment of hematological malignancies. However, producing these bespoke cancer-killing cells is a complicated ex vivo process involving leukapheresis, artificial T cell activation, and CAR construct introduction. The activation step requires the engagement of CD3/TCR and CD28 and is vital for T cell transfection and differentiation. Though antigen-presenting cells (APCs) facilitate activation in vivo, ex vivo activation relies on antibodies against CD3 and CD28 conjugated to magnetic beads. While effective, this artificial activation adds to the complexity of CAR T cell production as the beads must be removed prior to clinical implementation. To overcome this challenge, this work develops activating lipid nanoparticles (aLNPs) that mimic APCs to combine the activation of magnetic beads and the transfection capabilities of LNPs. It is shown that aLNPs enable one-step activation and transfection of primary human T cells with the resulting mRNA CAR T cells reducing tumor burden in a murine xenograft model, validating aLNPs as a promising platform for the rapid production of mRNA CAR T cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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 teacher head, 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".