98%
921
2 minutes
20
The Korea MetAbolomics data rePository (KMAP), available at https://kbds.re.kr/KMAP , is a public repository for metabolomics datasets developed as a part of the Korea BioData Station (K-BDS). KMAP archives metabolomics data and metadata generated from government-funded research projects in Korea, regardless of sample origin or analytical techniques. While data collection is nationally coordinated, data sharing is intended to be global. Here, we present our recent efforts to align KMAP with international standards for QA/QC and interoperability with other repositories.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12183127 | PMC |
http://dx.doi.org/10.1007/s11306-025-02285-5 | DOI Listing |
J Clin Invest
September 2025
The University of Texas at Austin, Austin, United States of America.
Background: Following SARS-CoV-2 infection, ~10-35% of COVID-19 patients experience long COVID (LC), in which debilitating symptoms persist for at least three months. Elucidating biologic underpinnings of LC could identify therapeutic opportunities.
Methods: We utilized machine learning methods on biologic analytes provided over 12-months after hospital discharge from >500 COVID-19 patients in the IMPACC cohort to identify a multi-omics "recovery factor", trained on patient-reported physical function survey scores.
J Neurooncol
September 2025
Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Purpose: NOTCH3 is increasingly implicated for its oncogenic role in many malignancies, including meningiomas. While prior work has linked NOTCH3 expression to higher-grade meningiomas and treatment resistance, the metabolic phenotype of NOTCH3 activation remains unexplored in meningioma.
Methods: We performed single-cell RNA sequencing on NOTCH3 + human meningioma cell lines.
Chem Rev
September 2025
Center for Computational Life Sciences, Lerner Research Institute, The Cleveland Clinic, Cleveland, Ohio 44195, United States.
Computational methods have revolutionized NMR spectroscopy, driving significant advancements in structural biology and related fields. This review focuses on recent developments in quantum chemical and machine learning approaches for computational NMR, emphasizing their role in enhancing accuracy, efficiency, and scalability. QM methods provide precise predictions of NMR parameters, enabling detailed structural characterization of diverse systems.
View Article and Find Full Text PDFMedicine (Baltimore)
September 2025
Laboratory Department of Laoshan Hospital, Affiliated Hospital of Qingdao University, Qingdao, Shandong Province, P.R. China.
Background And Objectives: The objective of this study was to investigate the changes in fecal microbial diversity and metabolic product levels in patients with stage IV colorectal cancer (CRC). The aim was to provide new research strategies for the diagnosis and treatment of CRC.
Methods: Fecal and blood samples were collected from both stage IV CRC patients and healthy individuals.
J Proteome Res
September 2025
Center for Proteomics and Metabolomics, Leiden University Medical Center, Postbus 9600, 2300 RC Leiden, The Netherlands.
Plasma proteomics has regained attention in recent years through advancements in mass spectrometry instrumentation and sample preparation as well as new high-throughput affinity-based technologies. Here, we evaluate the analytical performance of the new Olink Reveal platform, a proximity extension assay (PEA)-based technology quantifying 1034 proteins and covering many biological pathways, in particular immune system processes. Using spiked-in recombinant Interleukin-10 (IL-10) and vascular endothelial growth factor D (VEGF-D) in the NIST SRM 1950 plasma standard, we assessed the linearity, sensitivity, precision, and accuracy of the Olink Reveal assay.
View Article and Find Full Text PDF