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Record W3016234837 · doi:10.1016/j.jtauto.2020.100053

The effect of sex on immune responses to a homocitrullinated peptide in the DR4-transgenic mouse model of Rheumatoid Arthritis

2020· article· en· W3016234837 on OpenAlexafffund
Ewa Cairns, Sheri Saunders, David Bell, Garth Blackler, Patrick Lac, Lillian Barra

Bibliographic record

VenueJournal of Translational Autoimmunity · 2020
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British ColumbiaWestern University
FundersCanadian Institutes of Health Research
KeywordsAutoantibodyImmune systemImmunologyAntigenRheumatoid arthritisCytokineSplenocyteAntibodyBiologyMedicineEndocrinology

Abstract

fetched live from OpenAlex

Rheumatoid Arthritis (RA) is more common and severe in women compared to men. Both women and men with RA express autoantibodies to post-translationally modified antigens, including citrullinated and homocitrullinated proteins or peptides. These autoantibodies are strongly linked with the HLA-DR4 gene. The objective of this study was to determine sex differences in immune responses to homocitrullinated antigens. We used a humanized animal model of RA, DR4-transgenic mice and immunized them with a homocitrullinated peptide called HomoCitJED. Immune responses in these mice were measured for splenocyte proliferation by tritiated thymidine incorporation, serum autoantibody production by ELISA and cytokine levels by multiplex. We found that T cell and antibody responses to homocitrullinated antigens were similar in male and female mice. However, we found sex differences in serum cytokine profiles with female mice having higher ratio of IL-1α to IL-5, suggesting imbalances in immune regulation. This is the first study to report that immune responses to homocitrullinated antigens can be differentiated by sex.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.023
GPT teacher head0.285
Teacher spread0.262 · 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

Citations5
Published2020
Admission routes2
Has abstractyes

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Same venueJournal of Translational AutoimmunitySame topicRheumatoid Arthritis Research and TherapiesFrench-language works237,207