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A role of IgM antibodies in monosodium urate crystal formation and associated adjuvanticity (135.71)

2009· article· en· W4313348129 on OpenAlexaff
Uliana Kanevets, Karan Sharma, Karen Dresser, Yan Shi

Bibliographic record

VenueThe Journal of Immunology · 2009
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsUric acidChemistryAntibodyAdjuvantGoutAntigenInflammationBiochemistryImmunologyBiology

Abstract

fetched live from OpenAlex

Abstract Uric acid is a product of purine metabolism that is secreted from injured or dying cells and can act as an endogenous adjuvant. However, uric acid must crystallize to monosodium urate (MSU) before it can activate dendritic cells and cause gouty inflammation. At normal serum uric acid levels, crystallization of uric acid is not observed in vitro. The crucial question therefore is how the crystals form and cause inflammation. It has been reported that serum from rabbits immunized with MSU, increased uric acid precipitation rates. When C57BL6 or Balb/c mice were immunized with MSU, they produced serum factors which bind to MSU crystals, a phenomenon absent in mu chain deficient IgH (or muMT) mice. These observations show that antibodies may be involved in MSU crystallization. Antibodies produced via B cell hybridomas, were observed to precipitate uric acid in vitro, with the variable region acting as the binding domain. Most importantly, the presence of antibody was instrumental in significantly increasing the basal level of inflammation and mediating the adjuvant effect of uric acid in antigen dependent T cell cytotoxicity in B cell deficient mice. Therefore, we have identified a factor in determining uric acid precipitation and possibly its ability to function as an endogenous adjuvant. This finding suggests a new mechanism of the pathogenesis of gouty arthritis and uric acid induced immune activation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.009
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 source (direct Gemma or distilled Codex), 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

Citations4
Published2009
Admission routes1
Has abstractyes

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