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Polymorphisms of toll-like receptor 2 and 4 genes in Chagas disease

2008· article· en· W2044626381 on OpenAlexaff
Germán Zafra, Oscar Flórez-Vargas, Carlos A. Morillo, Luis Eduardo Echeverría, Javier Martı́n, Clara Isabel González

Bibliographic record

VenueMemórias do Instituto Oswaldo Cruz · 2008
Typearticle
Languageen
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBiologyGenotypeGenotypingChagas diseaseImmunologyAllele frequencyAllelePopulationGeneticsGeneMedicine

Abstract

fetched live from OpenAlex

The aim of this study was to test the possible implication of toll-like receptor 2 (TLR2) and TLR4 gene polymorphisms in determining the susceptibility to Chagas' disease. Genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism in 475 individuals from Colombia, 143 seropositive with chagasic cardiomyopathy, 132 seropositive asymptomatic and 200 seronegative. The TLR2 arginine to glutamine substitution at residue 753(Arg753Gln) polymorphism was absent in the groups analyzed. The TLR4 Asp299Gly and Thr399Ile polymorphisms are in linkage disequilibrium and we observed a very low frequency of these polymorphisms in our study population (2.6% and 1.8% respectively). The overall TLR2 and TLR4 alleles and genotype distribution in seronegative and seropositive were not significantly different. We compared the frequencies between asymptomatic patients and those with chagasic cardiomyopathy and we did not observe any significant differences in the distribution of alleles or genotypes. In summary, this study corroborates the low frequency of TLR2 and TLR4 polymorphisms observed in other populations and suggest that these do not play an important role in Chagas' disease. The validation of these findings in independent cohorts is needed to firmly establish a role for TLR2 and TLR4 variants in Chagas' 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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.036
GPT teacher head0.285
Teacher spread0.248 · 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

Citations30
Published2008
Admission routes1
Has abstractyes

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