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Record W4206716689 · doi:10.1126/science.abm0594

CAR T cells produced in vivo to treat cardiac injury

2022· article· en· W4206716689 on OpenAlexaff

Bibliographic record

VenueScience · 2022
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsAcuitas Therapeutics (Canada)
FundersNational Institute of Allergy and Infectious DiseasesNational Heart, Lung, and Blood Institute
KeywordsIn vivoChimeric antigen receptorCardiac fibrosisFibrosisCardiac function curveEx vivoAntigenMessenger RNA

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.022
GPT teacher head0.335
Teacher spread0.313 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1,241
Published2022
Admission routes1
Has abstractyes

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