Relationship Between HLA Polymorphisms and Gamma Interferon and Interleukin-10 Cytokine Production in Healthy Individuals after Rubella Vaccination
Clinical and Vaccine Immunology(2007)
Mayo Vaccine Research Group | Mayo Clin & Mayo Fdn
Abstract
ABSTRACTWe studied the association between HLA alleles and rubella-specific gamma interferon (IFN-γ) (Th1) and interleukin-10 (IL-10) (Th2) cytokine responses among 106 healthy children (ages, 14 to 17 years) previously immunized with two doses of rubella vaccine. Antibody titers and cytokine responses to rubella vaccination were not sex or age dependent. Several class I HLA-A (*0201, *2402, *6801) alleles were significantly associated with rubella vaccine-induced IFN-γ secretion. Several class II HLA-DRB1 (*0101) and HLA-DQB1 (*0501) alleles were also suggestive of an association with IFN-γ secretion. Alleles with potential associations with rubella-specific IL-10 production included HLA-A (*0201, *6801), HLA-B (*4901), and HLA-DRB1 (*1302). The class I A*0201 and A*6801 alleles were associated with both IFN-γ and IL-10 secretion. These tentative associations need to be validated in larger studies with subjects of differing ethnicities. These results provide additional evidence that HLA genes may influence Th1- and Th2-specific cytokine response(s) following rubella immunization, which in turn can influence both cellular and humoral immune responses to rubella vaccination.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
Genetic Basis for Variation of Vaccine Response: Our Studies with Rubella Vaccine.
Paediatrics and Child Health 2009
被引用13
BMC Immunology 2010
被引用35
Cytokine 2010
被引用30
Vaccine 2009
被引用29
The Journal of Infectious Diseases 2010
被引用59
A Qualitative and Quantitative Comparison of Two Rubella Virus-Specific IgG Antibody Immunoassays.
Viral immunology 2010
被引用11
Journal of Virology 2010
被引用47
Association of HLA Alleles with Plasmodium Falciparum Severity in Malian Children
Tissue Antigens 2011
被引用42
The Journal of Infectious Diseases 2011
被引用35
Vaccinomics and a New Paradigm for the Development of Preventive Vaccines Against Viral Infections.
OMICS A Journal of Integrative Biology 2011
被引用83
CLINICAL PHARMACOLOGY & THERAPEUTICS 2007
被引用179
Correlation Between Rubella Antibody Levels and Cytokine Measures of Cell-Mediated Immunity.
Viral Immunology 2009
被引用17
Vaccine 2014
被引用72
International Journal of Pharmaceutics 2015
被引用20
Immunogenetics 2015
被引用19
Vaccine 2015
被引用11
BIOSCIENCE REPORTS 2017
被引用10
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest