Similar to genomic and proteomic platforms, metabolomic data acquisition and analysis is becoming a routine approach for investigating biological systems. However, computational approaches for metabolomic data analysis and integration are still maturing. Metabox is a bioinformatics toolbox for deep phenotyping analytics that combines data processing, statistical analysis, functional analysis and integrative exploration of metabolomic data within proteomic and transcriptomic contexts. With the number of options provided in each analysis module, it also supports data analysis of other 'omic' families. The toolbox is an R-based web application, and it is freely available at http://kwanjeeraw.github.io/metabox/ under the GPL-3 license.
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J Pharm Biomed Anal
January 2025
State Key Laboratory of Discovery and Utilization of Functional Components in Traditional Chinese Medicine, The MOE Key Laboratory of Standardization of Chinese Medicines, the SATCM Key Laboratory of New Resources and Quality Evaluation of Chinese Medicines and Shanghai Key Laboratory of Compound Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China. Electronic address:
Bile acids (BAs) are essential signaling molecules that engage in host and gut microbial metabolism, playing a crucial role in maintaining organismal stability. Liquid chromatography-mass spectrometry (LC-MS) is a widely employed technique for metabolite analysis in biological samples due to its high sensitivity, excellent specificity, and low detection limits. This method has emerged as the mainstream approach for the detection and analysis of BAs.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Purpose: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.
Methods: We trained a generative model on Tc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis.
Curr Alzheimer Res
January 2025
Student's Scientific Research Center, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Background: Alzheimer's disease (AD) is a progressive neurodegenerative condition with rising prevalence due to the aging global population. Existing methods for diagnosing AD are struggling to detect the condition in its earliest and most treatable stages. One early indicator of AD is a substantial decrease in the brain's glucose metabolism.
View Article and Find Full Text PDFGastro Hep Adv
September 2024
Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Background And Aims: Steatotic liver disease (SLD) is the most common chronic liver disease strongly associated with metabolic dysfunction, but its pathogenesis remains incompletely understood. Exploring plasma circulating metabolites may help in elucidating underlying mechanisms and identifying new biomarkers for SLD.
Methods: We examined cross-sectionally the association between plasma metabolites and SLD as well as liver enzymes using data from 4 population-based cohort studies (Rotterdam study, Avon Longitudinal Study of Parents and Children, The Insulin Resistance Atherosclerosis Family Study, and Study of Latinos).
Heliyon
January 2025
Guangdong Provincial Biotechnology Research Institute (Guangdong Provincial Laboratory Animals Monitoring Center), Guangzhou, Guangdong, 510663, China.
Spondyloarthritis is a prevalent and persistent condition that significantly impacts the quality of life. Its intricate pathological mechanisms have led to a scarcity of animal models capable of replicating the disease progression in humans, making it a prominent area of research interest in the field. To delve into the pathological and physiological traits of spontaneous non-human primate spondyloarthritis, this study meticulously examined the disease features of this natural disease model through an array of techniques including X-ray imaging, MRI imaging, blood biochemistry, markers of bone metabolism, transcriptomics, proteomics, and metabolomics.
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