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Record W2149193891 · doi:10.3899/jrheum.080681

Structural Polymorphisms in the Mannose-Binding Lectin Gene Are Associated with Juvenile Idiopathic Arthritis

2009· article· en· W2149193891 on OpenAlexvenueno aff
P Gergely, Borbála Pazár, Zsolt B. Nagy, Tímea Gombos, Katalin Rajczy, Zsolt J. Balogh, Ilona Orbán, Krisztina Sevcic, Gyula Poór

Bibliographic record

VenueThe Journal of Rheumatology · 2009
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsnot available
FundersHungarian Scientific Research Fund
KeywordsMannan-binding lectinGenotypeArthritisAlleleGenotypingMedicineImmunologyPathogenesisPromoterGeneticsGeneLectinBiologyGene expression

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the possible association between polymorphisms of the mannose-binding lectin gene (MBL2) and susceptibility to juvenile idiopathic arthritis (JIA). METHODS: We performed a case-control association study including 118 Hungarian patients with JIA and 118 sex-matched healthy controls. MBL genotyping for the 3 mutant structural alleles at codons 54 (B), 57 (C), and 52 (D) in exon 1 and the promoter polymorphisms at position -550 (HL) and -221 (YX) were carried out by real-time PCR allelic discrimination. Serum level of MBL was determined by ELISA. RESULTS: Variant allele frequencies of both codon 52 and 57 polymorphisms in the MBL2 gene were significantly overrepresented in JIA (p=0.001 and p=0.004, respectively). The frequency of low MBL genotypes (XA/XA, YA/YO, XA/YO, and YO/YO) in JIA was higher than that in healthy controls (p=0.001). Serum MBL concentrations were found to be significantly lower in JIA patients versus control subjects (p=0.001). The 2 promoter polymorphisms and codon 54 SNP of the MBL2 gene were not associated with JIA. CONCLUSION: Our findings suggest that genetically determined low MBL levels may predispose children to JIA in a Hungarian population. These data warrant further research to investigate the role of the lectin-dependent complement system in the pathogenesis of JIA.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.236
Teacher spread0.221 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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