MétaCan
Menu
Back to cohort
Record W4310053027 · doi:10.1126/sciadv.ade6844

Gammaherpesvirus infection drives age-associated B cells toward pathogenicity in EAE and MS

2022· article· en· W4310053027 on OpenAlexaff
Isobel C. Mouat, Jessica R. Allanach, Naomi M. Fettig, Vina Fan, Anna M. Girard, Iryna Shanina, Lisa C. Osborne, Galina Vorobeychik, Marc S. Horwitz

Bibliographic record

VenueScience Advances · 2022
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsFraser HealthUniversity of CalgaryUniversity of British Columbia
Fundersnot available
KeywordsAutoimmunityImmunologyExperimental autoimmune encephalomyelitisMultiple sclerosisBiologyPhenotypePopulationVirus latencyVirusVirologyImmune systemMedicineViral replicationGenetics

Abstract

fetched live from OpenAlex

While age-associated B cells (ABCs) are known to expand and persist following viral infection and during autoimmunity, their interactions are yet to be studied together in these contexts. Here, we directly compared CD11c + T-bet + ABCs using models of Epstein-Barr virus (EBV), gammaherpesvirus 68 (γHV68), multiple sclerosis (MS), and experimental autoimmune encephalomyelitis (EAE), and found that each drives the ABC population to opposing phenotypes. EBV infection has long been implicated in MS, and we have previously shown that latent γHV68 infection exacerbates EAE. Here, we demonstrate that ABCs are required for γHV68-enhanced disease. We then show that the circulating ABC population is expanded and phenotypically altered in people with relapsing MS. In this study, we show that viral infection and autoimmunity differentially affect the phenotype of ABCs in humans and mice, and we identify ABCs as functional mediators of viral-enhanced 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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.415

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)0.0000.000

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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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 designObservational
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

Citations37
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueScience AdvancesSame topicViral-associated cancers and disordersFrench-language works237,207