Delivery of CAR-T Cells in a Transient Injectable Stimulatory Hydrogel Niche Improves Treatment of Solid Tumors
Bibliographic record
Abstract
Abstract Adoptive cell therapy (ACT) has proven to be highly effective in treating blood cancers such as B cell malignancies, but traditional approaches to ACT are poorly effective in treating the multifarious solid tumors observed clinically. Locoregional cell delivery methods have shown promising results in treating solid tumors compared to standard intravenous delivery methods, but the approaches that have been described to date have several critical drawbacks ranging from complex manufacturing and poor modularity to challenging adminstration. In this work, we develop a simple-to-implement self-assembled and injectable hydrogel material for the controlled co-delivery of CAR-T cells and stimulatory cytokines that improves treatment of solid tumors. We evaluate a range of hydrogel formulations to optimize the creation of a transient inflammatory niche that affords sustained exposure of CAR-T cells and cytokines. This facile approach yields increased CAR-T cell expansion, induces a more tumor-reactive CAR-T phenotype, and improves efficacy in treating solid tumors in mice.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".