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CAR T Cells Produced in vivo to Treat Cardiac Injury

2023· book-chapter· en· W4319984037 on OpenAlexaff
Joel G. Rurik, István Tombácz, Amir Yadegari, Pedro O. Méndez Fernández, Swapnil V. Shewale, Li Li, Tōru Kimura, Ousamah Younoss Soliman, Tyler E. Papp, Ying K. Tam, Barbara L. Mui, Steven Μ. Albelda, Ellen Puré, Carl H. June, Haig Aghajanian, Drew Weissman, Hamideh Parhiz, Jonathan A. Epstein

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsAcuitas Therapeutics (Canada)
Fundersnot available
KeywordsIn vivoSpleenChimeric antigen receptorMessenger RNAFibrosisEx vivoAntigenCardiac fibrosisImmunologyMedicineCancer researchCell biologyBiologyT cellPathologyImmune systemGene

Abstract

fetched live from OpenAlex

Fibrosis affects millions of people with cardiac disease. We developed a therapeutic approach to generate transient antifibrotic chimeric antigen receptor (CAR) T cells in vivo by delivering modified messenger RNA (mRNA) in T cell–targeted lipid nanoparticles (LNPs). The efficacy of these in vivo–reprogrammed CAR T cells was evaluated by injecting CD5-targeted LNPs into a mouse model of heart failure. Efficient delivery of modified mRNA encoding the CAR to T lymphocytes was observed, which produced transient, effective CAR T cells in vivo. Antifibrotic CAR T cells exhibited trogocytosis and retained the target antigen as they accumulated in the spleen. Treatment with modified mRNA-targeted LNPs reduced fibrosis and restored cardiac function after injury. In vivo generation of CAR T cells may hold promise as a therapeutic platform to treat various diseases.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.508
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.004

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.

Opus teacher head0.038
GPT teacher head0.317
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreOther

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".

Quick stats

Citations21
Published2023
Admission routes1
Has abstractyes

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