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Record W4405056347 · doi:10.1126/science.adl4237

Programming tissue-sensing T cells that deliver therapies to the brain

2024· article· en· W4405056347 on OpenAlexaff
Milos Simic, Payal Watchmaker, Sasha Gupta, Yuan Wang, Sharon A. Sagan, Jason Duecker, Chanelle Shepherd, David Diebold, Psalm Pineo-Cavanaugh, Jeffrey Haegelin, Robert Zhu, Ben Ng, Wei Yu, Yurie Tonai, Lia Cardarelli, Nishith R. Reddy, Sachdev S. Sidhu, Olga G. Troyanskaya, Stephen L. Hauser, Michael R. Wilson, Scott S. Zamvil, Hideho Okada, Wendell A. Lim

Bibliographic record

VenueScience · 2024
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsUniversity of Waterloo
FundersCancer MoonshotMoonshot Research and Development ProgramUniversity of California, San FranciscoHelen Diller Family Comprehensive Cancer Center, University of California, San FranciscoNational Institute of Neurological Disorders and StrokeNational Cancer InstituteAdvanced Research Projects AgencyNational Institutes of HealthMultiple Sclerosis SocietyValhalla FoundationParker Institute for Cancer ImmunotherapyEmerson CollectiveSandler Foundation
KeywordsNeuroinflammationCentral nervous systemChimeric antigen receptorAntigenBiologyCell biologyExtracellularExtracellular matrixNeuroscienceClearanceReceptorImmunologyImmunotherapyMedicineInflammationImmune system

Abstract

fetched live from OpenAlex

To engineer cells that can specifically target the central nervous system (CNS), we identified extracellular CNS-specific antigens, including components of the CNS extracellular matrix and surface molecules expressed on neurons or glial cells. Synthetic Notch receptors engineered to detect these antigens were used to program T cells to induce the expression of diverse payloads only in the brain. CNS-targeted T cells that induced chimeric antigen receptor expression efficiently cleared primary and secondary brain tumors without harming cross-reactive cells outside of the brain. Conversely, CNS-targeted cells that locally delivered the immunosuppressive cytokine interleukin-10 ameliorated symptoms in a mouse model of neuroinflammation. Tissue-sensing cells represent a strategy for addressing diverse disorders in an anatomically targeted manner.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.047
GPT teacher head0.363
Teacher spread0.316 · 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 teacher head, 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

Citations78
Published2024
Admission routes1
Has abstractyes

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