Project description:We seek to discover small RNA biomarkers of autoimmune activity andor beta cell damage in type 1 diabetes. Pilot studies showed that heparinized plasma failed analyses, but that EDTA and citrated plasma did well, so 353 appropriate plasma samples average 11 per subject prospectively collected every 1 to 3 months from 32 high risk MAB or newly diabetic children and adolescents were collected, and the first 94 analyzed, for circulating small regulatory RNAs. 92 of 94 resulting cDNA libraries gave adequate numbers of miRNA mapped reads, but QC using spiked RNA internal standards showed abnormally high small RNA levels in 8 mildly hemolyzed plasma samples, leaving 84 of 94 with analyzable data. Equal numbers of EDTA and citrated plasma were analyzed successfully. Over the next period we will complete series on another 6 subjects, sequence the remaining 26070340 samples, and analyze the data for patterns of disease association with small RNA molecules in the prediabetic, perionset, and immediate post onset period. These patterns may identify biomarker small RNA predictive of autoimmune flares or beta cell loss, including predicting impending clinical onset.
Project description:Fasting blood samples were collected from 27 stroke patients in EDTA tubes mean 19 days post-stroke, plasma was extracted and frozen at -80C, then 200uL of plasma sent for qPCR.
Project description:Studies of miRNA profiling in the plasma of patients between ISR and non-ISR Venous blood was collected in EDTA in the ward or the cardiac catheterization laboratory before the angiography procedure and heparin administration. Plasma was harvested by centrifugation and stored at -80°C until assayed. Identical volumes of plasma from the 6 patients with ISR and 4 patients with non-ISR were pooled to reach a final volume of 1500µL for each patient. Total RNA was extracted using miRVana isolation kit, dephosphorylated and labeled using miRNA Complete Labeling kit. Scanning was achieved with the illumina iScan System. The result were acquired with the Genome Studio (GenomeStudioV2009.1).
Project description:High-throughput sequencing of the miRNAs present in plasma of COVID-19 patients at an early stage of the disease including non-SARS-CoV2 infected patients. This study allowed us to identify and functionally characterize human miRNAs associated with a worse evolution of the disease and a greater mortality. Samples were collected at hospital entry or within the first days after hospitalization and before treatment with immunotherapy for IL6 (e.g. Tocilizumab), interferon beta, corticoids and ribavirin, among others. Plasma samples were obtained from peripheral blood extracted in EDTA tubes after centrifugation. Total RNA, including small RNAs, was isolated from 400μl of plasma with the miRNeasy Serum Plasma Advanced kit (Qiagen). RNA quality and quantity were evaluated by the Bioanalyzer 2100 with Agilent RNA 6000 Nano Kit.
Project description:Peripheral blood was collected from 3 patients in two types of tubes, EDTA and Streck. After removing plasma, DNA was extracted from the remaining blood and subjected to array profiling
Project description:Advancing Negative Ion Mode Proteomics. The main objective of the project is the exploration of the unconvetional negative ion mode for proteomics studies. In this work, we thoroughly studied the best chromatographic conditions for negative ion mode proteomics before testing different enzymatic digestion. The final goal is to establish the best working conditions in the negative polarity for negative ion mode. The method also refrains from any fragmentation events, which are unpredictable in negative ion mode.
Project description:Elite controllers maintain HIV-1 viral loads below the limit of detection. The mechanisms responsible for this phenomenon are poorly understood. As microRNAs (miRNAs) are regulators of gene expression and some of them modulate HIV infection, we have studied the miRNA profile in plasma from HIV elite controllers and chronically infected individuals and compared against healthy donors. Several miRNAs correlate with CD4+ T cell count or with the known time of infection. No significant differences were observed between elite controllers and healthy donors; however, 16 miRNAs were different in the plasma of chronic infected versus healthy donors. In addition, levels of hsa-miR-29b-3p, hsa-miR-33a-5p and hsa-miR-146a-5p were higher in plasma from elite controllers than chronic infected and hsa-miR-29b-3p and hsa-miR-33a-5p overexpression significantly reduced the viral production in MT2 cells. Therefore, levels of circulating miRNAs might be of diagnostic and/or prognostic value for HIV infection. Additionally, hsa-miR-29b-3p and miR-33a-5p may be used in therapeutic strategies. An exploratory cross-sectional study of microRNA levels in EDTA plasma samples. Plasma samples were obtained from 24 subjects and were classified in 3 groups, 9 Elite Controllers (defined as individuals with plasma viral load (PVL) < 50 copies/ml, CD4 count >350/ml), 9 chronic HIV patients (CH) under anti-retroviral treatment and 6 healthy HIV negative donors (HD). This study was approved by the HuM-CM-)sped Foundation Ethics Committee and informed consent was obtained from all subjects.
Project description:<p><strong>OBJECTIVE:</strong> This study aimed to investigate the plasma metabolic profile of patients with extracranial arteriovenous malformations (AVM).</p><p><strong>METHOD:</strong> Plasma samples were collected from 32 AVM patients and 30 healthy controls (HC). Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) was employed to analyze the metabolic profiles of both groups. Metabolic pathway enrichment analysis was performed through Kyoto Encyclopedia of Genes and Genomes (KEGG) database and MetaboAnalyst. Additionally, machine learning algorithms such as Least Absolute Shrinkage and Selection Operator (LASSO) and random forest (RF) were conducted to screen characteristic metabolites. The effectiveness of the serum biomarkers for AVM was evaluated using a receiver-operating characteristics (ROC) curve.</p><p><strong>RESULT:</strong> In total, 184 differential metabolites were screened in this study, with 110 metabolites in positive ion mode and 74 metabolites in negative mode. Lipids and lipid-like molecules were the predominant metabolites detected in both positive and negative ion modes. Several significant metabolic pathways were enriched in AVMs, including lipid metabolism, amino acid metabolism, carbohydrate metabolism and protein translation. Through machine learning algorithms, 9 metabolites were identify as characteristic metabolites, including hydroxy-proline, L-2-Amino-4-methylenepentanedioic acid, piperettine, 20-hydroxy-PGF2a, 2,2,4,4-tetramethyl-6-(1-oxobutyl)-1,3,5-cyclohexanetrione, DL-tryptophan, 9-oxoODE, alpha-Linolenic acid and dihydrojasmonic acid.</p><p><strong>CONCLUSION:</strong> Patients with extracranial AVMs exhibited significantly altered metabolic patterns compared to healthy controls, which could be identified using plasma metabolomics. These findings suggest that metabolomic profiling can aid in the understanding of AVM pathophysiology and potentially inform clinical diagnosis and treatment.</p>