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Circulating Follicular Regulatory T Cells in Autoimmune Diseases and Their Waning in Multiple Sclerosis

2016· article· en· W2731542311 on OpenAlexaff
Tessa Dhaeze, Niels Hellings

Bibliographic record

VenueCritical Reviews in Immunology · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversité de Montréal
FundersUniversiteit Hasselt
KeywordsGerminal centerImmunologyMultiple sclerosisAutoimmunityDiseaseAutoimmune diseaseAntigenMedicineBiologyImmune systemAntibodyB cellPathology

Abstract

fetched live from OpenAlex

Follicular regulatory T cells (TFRs) are a subset of regulatory T cells that reside in the secondary lymphoid organs and participate in controlling the germinal center (GC) response. The GC response forms the basis of adaptive immunity to foreign protein antigens. In autoimmune diseases, hyperreactivity to self-antigens occurs that may result from an aberrant control of the GC response. TFR dysfunctionality may be one of the factors contributing to this breakdown of self-tolerance. In this review, we discuss how the investigation of circulating TFRs can help us understand their relative contribution to autoimmune-mediated disease processes. Multiple sclerosis is taken as a classical example of autoimmune disease.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.035
GPT teacher head0.252
Teacher spread0.217 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2016
Admission routes1
Has abstractyes

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