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Record W3213324499 · doi:10.1016/j.xpro.2021.100956

Production of human CAR-NK cells with lentiviral vectors and functional assessment in vitro

2021· article· en· W3213324499 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSTAR Protocols · 2021
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsChimeric antigen receptorFlow cytometryCell biologyEx vivoTransgeneTransduction (biophysics)Janus kinase 3BiologyIn vitroImmune systemEffectorInterleukin 21T cellImmunologyGeneGenetics

Abstract

fetched live from OpenAlex

Although natural killer (NK) cells have become a promising immune effector cell for chimeric antigen receptor (CAR)-based therapy, generating human CAR-NK cells with high transgene efficiency has been challenging. In this protocol, we describe how to generate CAR-NK cells with transduction efficiencies >15% from healthy donor ex vivo expanded NK cells using third generation lentiviral vectors (LVs). We also show how to assess CAR-NK cell anti-tumor function in vitro using a flow cytometry-based killing assay. For complete details on the use and execution of this protocol, please refer to Portillo et al. (2021).

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.

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 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 score0.061
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.044
GPT teacher head0.365
Teacher spread0.321 · 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