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Record W2021390186 · doi:10.1177/0961203314548248

The dual role of innate immunity in antiphospholipid syndrome and systemic lupus erythematosus

2014· article· en· W2021390186 on OpenAlexafffund
Dylan P. Salem, Rebecca Subang, P. Laplante, JS Levine, Joyce Rauch

Bibliographic record

VenueLupus · 2014
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsAntiphospholipid syndromeInnate immune systemImmunologyAutoantibodyMedicineAcquired immune systemImmune systemAntibody

Abstract

fetched live from OpenAlex

Antiphospholipid syndrome (APS), as a primary disease or a secondary syndrome in systemic lupus erythematosus (SLE), is characterized by the presence of antiphospholipid antibodies (aPL) and a clinical event. It is likely that both genetic and environmental factors lead to the development of aPL and progression to disease. However, the precise mechanisms are not known. We hypothesize that innate immune activation plays a dual role in APS and SLE, both in the production of aPL (i.e. "initiation" phase) and in the development of a clinical event (i.e. "effector" phase). We have shown that mice immunized with certain phospholipid-binding proteins (e.g. β2-glycoprotein I (β2GPI)), plus a concomitant trigger of innate immunity (e.g. a toll-like receptor 4 (TLR4) ligand), produce a strong β2GPI-reactive T cell response, resulting in high levels of aPL as well as other SLE autoantibodies. We propose that β2GPI, through its interaction with apoptotic cells, permits B cell epitope spread to multiple SLE autoantibodies. Innate immune activation is also implicated in a murine model of aPL-enhanced thrombus formation. This dual role of innate immune activation provides new insight into the mechanisms involved in the initiation of aPL and other SLE-related autoantibodies, as well as the development of aPL-mediated 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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.010
GPT teacher head0.255
Teacher spread0.244 · 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

Citations13
Published2014
Admission routes2
Has abstractyes

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