In the present study, we have established a new methodology to analyze saliva proteins from HIV-1-seropositive patients before highly active antiretroviral therapy (HAART) and seronegative controls. A total of 593 and 601 proteins were identified in the pooled saliva samples from 5 HIV-1 subjects and 5 controls, respectively. Forty-one proteins were found to be differentially expressed. Bioinformatic analysis of differentially expressed salivary proteins showed an increase of antimicrobial proteins and decrease of protease inhibitors upon HIV-1 infection. To validate some of these differentially expressed proteins, a high-throughput quantitation method was established to determine concentrations of 10 salivary proteins in 40 individual saliva samples from 20 seropositive patients before HAART and 20 seronegative subjects. This method was based on limited protein separation within the zone of the stacking gel of the 1D SDS PAGE and using isotope-coded synthetic peptides as internal standards. The results demonstrated that a combination of protein profiling and targeted quantitation is an efficient method to identify and validate differentially expressed salivary proteins. Expression levels of members of the calcium-binding S100 protein family and deleted in malignant brain tumors 1 protein (DMBT1) were up-regulated while that of Mucin 5B was down-regulated in HIV-1 seropositive saliva samples, which may provide new perspectives for monitoring HIV-infection and understanding the mechanism of HIV-1 infectivity.
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http://dx.doi.org/10.1016/j.aca.2013.02.038 | DOI Listing |
Adv Clin Exp Med
January 2025
Luddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, USA.
Background: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). Due to the lack of symptoms until advanced stages, early diagnosis of ccRCC is challenging. Therefore, the identification of novel secreted biomarkers for the early detection of ccRCC is urgently needed.
View Article and Find Full Text PDFAlzheimers Dement
January 2025
UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK.
Introduction: Cerebrovascular dysfunction plays a critical role in the pathogenesis of dementia and related neurodegenerative disorders. Recent omics-driven research has revealed associations between vascular abnormalities and transcriptomic alterations in brain vascular cells, particularly endothelial cells (ECs) and pericytes (PCs). However, the impact of these molecular changes on dementia remains unclear.
View Article and Find Full Text PDFPlant Genome
March 2025
Department of Fundamental Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
The plant Polygonum capitatum (P. capitatum) contains a variety of flavonoids that are distributed differently among different parts. Nevertheless, differentially expressed genes (DEGs) associated with this heterogeneous distribution have not been identified.
View Article and Find Full Text PDFClin Cosmet Investig Dermatol
January 2025
Department of Clinical Laboratory, Central Hospital of Dalian University of Technology, Dalian, 116033, People's Republic of China.
Objective: Juvenile dermatomyositis (JDM) is a complex autoimmune disease, and its pathogenesis remains poorly understood. Building upon previous research on the immunological and inflammatory aspects of JDM, this study aims to investigate the role of pyroptosis in the pathogenesis of JDM using a comprehensive bioinformatics approach.
Methods: Two microarray datasets (GSE3307 and GSE11971) were obtained from the Gene Expression Omnibus database, and a list of 62 pyroptosis-related genes was compiled.
Biochem Biophys Rep
March 2025
Department of Genetics and Molecular Biology, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Introduction: Gastric cancer (GC) is among the deadliest malignancies globally, characterized by hypoxia-driven pathways that promote cancer progression, including stemness mechanisms facilitating invasion and metastasis. This study aimed to develop a prognostic decision tree using genes implicated in hypoxia and stemness pathways to predict outcomes in GC patients.
Materials And Methods: GC RNA-seq data from The Cancer Genome Atlas (TCGA) were analyzed to compute hypoxia and stemness scores using Gene Set Variation Analysis (GSVA) and the mRNA expression-based stemness index (mRNAsi).
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