Quantitative polymerase chain reaction (qPCR) has been used as a standard molecular detection tool in many scientific fields. Unfortunately, there is no standard method for managing published qPCR data, and those currently used generally focus on only managing raw fluorescence data. However, associated with qPCR experiments are extensive sample and assay metadata, often under-examined and under-reported. Here, we present the Molecular Detection Mapping and Analysis Platform for R (MDMAPR), an open-source and fully scalable informatics tool for researchers to merge raw qPCR fluorescence data with associated metadata into a standard format, while geospatially visualizing the distribution of the data and relative intensity of the qPCR results. The advance of this approach is in the ability to use MDMAPR to store varied qPCR data. This includes pathogen and environmental qPCR species detection studies ideally suited to geographical visualization. However, it also goes beyond these and can be utilized with other qPCR data including gene expression studies, quantification studies used in identifying health dangers associated with food and water bacteria, and the identification of unknown samples. In addition, MDMAPR's novel centralized management and geospatial visualization of qPCR data can further enable cross-discipline large-scale qPCR data standardization and accessibility to support research spanning multiple fields of science and qPCR applications.
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http://dx.doi.org/10.7717/peerj.9974 | DOI Listing |
Int J Rheum Dis
January 2025
Hubei Provincial Key Laboratory of Occurrence and Intervention of Rheumatic Disease, Minda Hospital of Hubei Minzu University, Enshi, China.
Osteoarthritis is a systemic disease that primarily damages articular cartilage and also affects the synovium, ligaments, and bone tissues. The key mechanisms involved are chondrocyte death and degradation of the extracellular matrix. This study aims to identify differentially expressed genes (DEGs) associated with ferroptosis and investigate their roles in the development of osteoarthritis.
View Article and Find Full Text PDFJ Inflamm Res
January 2025
Medical Imaging Centre, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, People's Republic of China.
Purpose: Immunometabolism is pivotal in rheumatoid arthritis (RA) pathogenesis, yet the intricacies of its pathological regulatory mechanisms remain poorly understood. This study explores the complex immunometabolic landscape of RA to identify potential therapeutic targets.
Patients And Methods: We integrated genome-wide association study (GWAS) data involving 1,400 plasma metabolites, 731 immune cell traits, and RA outcomes from over 58,000 participants.
RSC Adv
January 2025
Department of Physics and Chemistry, Faculty of Education, Alexandria University Egypt.
A novel series of azo dyes was successfully synthesized by combining amino benzoic acid and amino phenol on the same molecular framework azo linkage. The structural elucidation of these dyes was carried out using various spectroscopic techniques, including UV-vis, FT-IR, NMR spectroscopy, and HRMS. Surprisingly, the aromatic proton in some dyes exhibited exchangeability in DO, prompting a 2D NMR analysis to confirm this phenomenon.
View Article and Find Full Text PDFGenome Med
January 2025
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.
Background: Large-scale pharmacogenomic resources, such as the Connectivity Map (CMap), have greatly assisted computational drug discovery. However, despite their widespread use, CMap-based methods have thus far been agnostic to the biological activity of drugs as well as to the genomic effects of drugs in multiple disease contexts. Here, we present a network-based statistical approach, Pathopticon, that uses CMap to build cell type-specific gene-drug perturbation networks and integrates these networks with cheminformatic data and diverse disease phenotypes to prioritize drugs in a cell type-dependent manner.
View Article and Find Full Text PDFMalar J
January 2025
Aklilu Lemma Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia.
Background: Low malaria parasitaemia is a diagnostic challenge in pregnancy, leading to false negative microscopy and rapid diagnostic test (RDT) results. However, these submicroscopic or subpatent infections could cause adverse pregnancy outcomes. Thus, evaluating the diagnostic performance of microscopy, RDT, and multiplex qPCR in pregnancy is vital for informed decisions.
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