ArticlePloS one2010
Peptide-MHC cellular microarray with innovative data analysis system for simultaneously detecting multiple CD4 T-cell responses.
Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- Genetically engineered CD80-pMHC-harboring extracellular vesicles for antigen-specific CD4Frontiers in bioengineering and biotechnology · 2023Article
- Alginate Microencapsulation for Three-Dimensional In Vitro Cell Culture.ACS biomaterials science & engineering · 2021Review
- Frequency and reactivity of antigen-specific T cells were concurrently measured through the combination of artificial antigen-presenting cell, MACS and ELISPOT.Scientific reports · 2017Article
- Immunodominant CD4+ T-cell responses to influenza A virus in healthy individuals focus on matrix 1 and nucleoprotein.Journal of virology · 2014Article
- Identification and HLA-tetramer-validation of human CD4+ and CD8+ T cell responses against HCMV proteins IE1 and IE2.PloS one · 2014Article
- Memory CD4 T cell-mediated immunity against influenza A virus: more than a little helpful.Archivum immunologiae et therapiae experimentalis · 2013Review
- Immunomics in Skin Cancer - Improvement in Diagnosis, Prognosis and Therapy Monitoring.Current proteomics · 2013Article
- Characterization of influenza vaccine immunogenicity using influenza antigen microarrays.PloS one · 2013Article
- Diversity-oriented approaches for interrogating T-cell receptor repertoire, ligand recognition, and function.Immunological reviews · 2012Review
- The utility and limitations of current Web-available algorithms to predict peptides recognized by CD4 T cells in response to pathogen infection.Journal of immunology (Baltimore, Md. : 1950) · 2012Article
- MHC class II tetramers.Journal of immunology (Baltimore, Md. : 1950) · 2012Review
- Hallmarks of CD4 T cell immunity against influenza.Journal of internal medicine · 2011Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundPeptide:MHC cellular microarrays have been proposed to simultaneously characterize multiple Ag-specific populations of T cells. The practice of studying immune responses to complicated pathogens with this tool demands extensive knowledge of T cell epitopes and the availability of peptide:MHC complexes for array fabrication as well as a specialized data analysis approach for result interpretation. METHODOLOGY/PRINCIPAL
findingsWe co-immobilized peptide:DR0401 complexes, anti-CD28, anti-CD11a and cytokine capture antibodies on the surface of chamber slides to generate a functional array that was able to detect rare Ag-specific T cell populations from previously primed in vitro T cell cultures. A novel statistical methodology was also developed to facilitate batch processing of raw array-like data into standardized endpoint scores, which linearly correlated with total Ag-specific T cell inputs. Applying these methods to analyze Influenza A viral antigen-specific T cell responses, we not only revealed the most prominent viral epitopes, but also demonstrated the heterogeneity of anti-viral cellular responses in healthy individuals. Applying these methods to examine the insulin producing beta-cell autoantigen specific T cell responses, we observed little difference between autoimmune diabetic patients and healthy individuals, suggesting a more subtle association between diabetes status and peripheral autoreactive T cells. CONCLUSIONS/SIGNIFICANCE: The data analysis system is reliable for T cell specificity and functional testing. Peptide:MHC cellular microarrays can be used to obtain multi-parametric results using limited blood samples in a variety of translational settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.