<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Groathouse NA</submitter><funding>NIAID NIH HHS</funding><pagination>6458-66</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC1695501</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>74(11)</volume><pubmed_abstract>Although the global prevalence of leprosy has decreased over the last few decades due to an effective multidrug regimen, large numbers of new cases are still being reported, raising questions as to the ability to identify patients likely to spread disease and the effects of chemotherapy on the overall incidence of leprosy. This can partially be attributed to the lack of diagnostic markers for different clinical states of the disease and the consequent implementation of differential, optimal drug therapeutic strategies. Accordingly, comparative bioinformatics and Mycobacterium leprae protein microarrays were applied to investigate whether leprosy patients with different clinical forms of the disease can be categorized based on differential humoral immune response patterns. Evaluation of ser</pubmed_abstract><journal>Infection and immunity</journal><pubmed_title>Use of protein microarrays to define the humoral immune response in leprosy patients and identification of disease-state-specific antigenic profiles.</pubmed_title><pmcid>PMC1695501</pmcid><funding_grant_id>R01 AI055298</funding_grant_id><funding_grant_id>N01-AI75320</funding_grant_id><funding_grant_id>R01 AI047197</funding_grant_id><funding_grant_id>R01-AI47197</funding_grant_id><funding_grant_id>N01-AI25469</funding_grant_id><funding_grant_id>R01-AI055298</funding_grant_id><funding_grant_id>N01 AI025469</funding_grant_id><pubmed_authors>Groathouse NA</pubmed_authors><pubmed_authors>Marques MA</pubmed_authors><pubmed_authors>Brennan PJ</pubmed_authors><pubmed_authors>Belisle JT</pubmed_authors><pubmed_authors>Spencer JS</pubmed_authors><pubmed_authors>Knudson DL</pubmed_authors><pubmed_authors>Gelber R</pubmed_authors><pubmed_authors>Slayden RA</pubmed_authors><pubmed_authors>Amin A</pubmed_authors></additional><is_claimable>false</is_claimable><name>Use of protein microarrays to define the humoral immune response in leprosy patients and identification of disease-state-specific antigenic profiles.</name><description>Although the global prevalence of leprosy has decreased over the last few decades due to an effective multidrug regimen, large numbers of new cases are still being reported, raising questions as to the ability to identify patients likely to spread disease and the effects of chemotherapy on the overall incidence of leprosy. This can partially be attributed to the lack of diagnostic markers for different clinical states of the disease and the consequent implementation of differential, optimal drug therapeutic strategies. Accordingly, comparative bioinformatics and Mycobacterium leprae protein microarrays were applied to investigate whether leprosy patients with different clinical forms of the disease can be categorized based on differential humoral immune response patterns. Evaluation of ser</description><dates><release>2006-01-01T00:00:00Z</release><publication>2006 Nov</publication><modification>2026-05-01T12:13:45.99Z</modification><creation>2019-03-27T01:46:27Z</creation></dates><accession>S-EPMC1695501</accession><cross_references><pubmed>16966411</pubmed><doi>10.1128/iai.00041-06</doi><doi>10.1128/IAI.00041-06</doi></cross_references></HashMap>