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Record W2982525250 · doi:10.1038/s41467-019-12902-2

Increased yields and biological potency of knob-into-hole-based soluble MHC class II molecules

2019· article· en· W2982525250 on OpenAlexafffund
Pau Serra, Nahir Garabatos, Santiswarup Singha, César Fandos, Josep Garnica, Patricia Solé, Daniel Parras, Jun Yamanouchi, Jesús Blanco, Meritxell Tort, Mireia Ortega, Yang Yang, Kristofor K. Ellestad, Pere Santamaría

Bibliographic record

VenueNature Communications · 2019
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of Calgary
FundersCIHR Skin Research Training CentreInstituto de Salud Carlos IIICanadian Institutes of Health ResearchGeneralitat de CatalunyaDiabetes CanadaGovernment of CanadaCentres de Recerca de CatalunyaEuropean Foundation for the Study of DiabetesEli Lilly and Company
KeywordsAvidityMajor histocompatibility complexFlow cytometryT-cell receptorPeptideAntigenChemistryReprogrammingComputational biologyCell biologyRecombinant DNAFusion proteinBiologyBiochemistryMolecular biologyT cellCellImmune systemImmunology

Abstract

fetched live from OpenAlex

T cells in biological samples and, in some configurations, their reprogramming in vivo. Unfortunately, current MHCII-αβ chain heterodimerization strategies are typically associated with low production yields and require the use of foreign affinity tags for purification, precluding therapeutic applications in humans. Here, we show that fusion of peptide-tethered or empty MHCII-αβ chains to the IgG1-Fc mutated to form knob-into-hole structures results in the assembly of highly stable pMHCII monomers. This design enables the expression and rapid purification of challenging pMHCII types at high yields without the need for leucine zippers and purification affinity tags. Importantly, this design increases the antigen-receptor signaling potency of multimerized derivatives useful for therapeutic applications and facilitates the detection and amplification of low-avidity T cell specificities in biological samples using flow cytometry.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.032
GPT teacher head0.337
Teacher spread0.304 · 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

Citations30
Published2019
Admission routes2
Has abstractyes

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