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Record W2989833047 · doi:10.1038/s41598-019-53756-4

Single variable domains from the T cell receptor β chain function as mono- and bifunctional CARs and TCRs

2019· article· en· W2989833047 on OpenAlexaff
Julyun Oh, Dora Toledo Warshaviak, Mikayel Mkrtichyan, Melanie L. Munguia, Abby Lin, Falene Chai, Craig R. Pigott, Jaspal S. Kang, Michael Gallo, Alexander Kamb

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsInnovative Targeting Solutions (Canada)
Fundersnot available
KeywordsT-cell receptorChimeric antigen receptorJurkat cellsComputational biologyReceptorRecombinant DNAT cellCell biologyComputer scienceBiologyChemistryImmunologyGeneGeneticsImmune system

Abstract

fetched live from OpenAlex

Cell therapy using T cell receptors (TCRs) and chimeric antigen receptors (CARs) represents a new wave of immunotherapies garnering considerable attention and investment. Further progress in this area of medicine depends in part on improving the functional capabilities of the engineered components, while maintaining the overall size of recombinant constructs to ensure their compatibility with existing gene delivery vehicles. We describe a single-variable-domain TCR (svd TCR) that utilizes only the variable domain of the β chain (Vβ). This Vβ module not only works in TCR and CAR formats, but also can be used to create single-chain bispecific CARs and TCRs. Comparison of individual ligand-binding Vβ domains in different formats suggests that the lone Vβ sequence controls the sensitivity and a major part of the specificity of the CAR or TCR construct, regardless of signaling format, in Jurkat and primary 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 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 categoriesInsufficient payload (model declined to judge)
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 score0.901
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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.

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

Citations21
Published2019
Admission routes1
Has abstractyes

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