MétaCan
Menu
Back to cohort
Record W4327591598 · doi:10.1038/s41467-023-37205-5

B cell class switch recombination is regulated by DYRK1A through MSH6 phosphorylation

2023· article· en· W4327591598 on OpenAlexfundno aff
Liat Stoler‐Barak, Ethan Harris, Ayelet Peres, Hadas Hezroni, Mirela Kuka, Pietro Di Lucia, Amalie Grenov, Neta Gurwicz, Meital Kupervaser, Bon Ham Yip, Matteo Iannacone, Gur Yaari, John D. Crispino, Ziv Shulman

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
FundersBenoziyo Endowment Fund for the Advancement of ScienceAzrieli FoundationIsrael Science FoundationGerald O. Mann Charitable FoundationEuropean Molecular Biology Organization
KeywordsImmunoglobulin class switchingDYRK1AGerminal centerBiologyPhosphorylationCell biologyIsotypeB cellAntibodyGenetics

Abstract

fetched live from OpenAlex

Protection from viral infections depends on immunoglobulin isotype switching, which endows antibodies with effector functions. Here, we find that the protein kinase DYRK1A is essential for B cell-mediated protection from viral infection and effective vaccination through regulation of class switch recombination (CSR). Dyrk1a-deficient B cells are impaired in CSR activity in vivo and in vitro. Phosphoproteomic screens and kinase-activity assays identify MSH6, a DNA mismatch repair protein, as a direct substrate for DYRK1A, and deletion of a single phosphorylation site impaired CSR. After CSR and germinal center (GC) seeding, DYRK1A is required for attenuation of B cell proliferation. These findings demonstrate DYRK1A-mediated biological mechanisms of B cell immune responses that may be used for therapeutic manipulation in antibody-mediated autoimmunity.

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 score0.004

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)0.0010.001

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 head0.013
GPT teacher head0.280
Teacher spread0.268 · 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

Citations13
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicDNA Repair MechanismsFrench-language works237,207