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Record W4220995363 · doi:10.3389/fimmu.2022.732977

Anti-FcαRI Monoclonal Antibodies Resolve IgA Autoantibody-Mediated Disease

2022· article· en· W4220995363 on OpenAlexaff
Amélie Bos, Esil Aleyd, Lydia P. E. van der Steen, Paula J. Winter, Niels Heemskerk, Stephan M. Pouw, Louis Boon, René J. P. Musters, Jantine E. Bakema, Cassian Sitaru, Michel Cogné, Marjolein van Egmond

Bibliographic record

VenueFrontiers in Immunology · 2022
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Bullous Skin Diseases
Canadian institutionsInstitute of Infection and Immunity
FundersVrije Universiteit AmsterdamAmsterdam University Medical Centers
KeywordsImmunologyAutoantibodyAntibodyInflammationImmune systemImmunoglobulin AMonoclonal antibodyAutoimmune diseaseMedicineAutoimmunityImmunoglobulin G

Abstract

fetched live from OpenAlex

Immunoglobulin A (IgA) is generally considered as a non-inflammatory regulator of mucosal immunity, and its importance in diversifying the gut microbiota is increasingly appreciated. IgA autoantibodies have been found in several autoimmune or chronic inflammatory diseases, but their role in pathophysiology is ill-understood. IgA can interact with the Fc receptor FcαRI on immune cells. We now established a novel IgA autoimmune blistering model, which closely resembles the human disease linear IgA bullous disease (LABD) by using genetically modified mice that produce human IgA and express human FcαRI. Intravital microscopy demonstrated that presence of IgA anti-collagen XVII, - the auto-antigen in LABD-, resulted in neutrophil activation and extravasation from blood vessels into skin tissue. Continued exposure to anti-collagen XVII IgA led to massive neutrophil accumulation, severe tissue damage and blister formation. Importantly, treatment with anti-FcαRI monoclonal antibodies not only prevented disease, but was also able to resolve existing inflammation and tissue damage. Collectively, our data reveal a novel role of neutrophil FcαRI in IgA autoantibody-mediated disease and identify FcαRI as promising new therapeutic target to resolve chronic inflammation and tissue damage.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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.

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

Citations11
Published2022
Admission routes1
Has abstractyes

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