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Efficient and Rapid Generation of Neural Stem Cells by Direct Conversion Fibroblasts with Single microRNAs.
Stem Cells
January 2025
Medicine and Pharmacy Research Center, and Yantai Key Laboratory for Stem Cell Biology and Regenerative Medicine, Binzhou Medical University, 346 Guanhai Road, Yantai, Shandong 264003, China.
Neural stem cells (NSCs) have great potentials in the application of neurodegenerative disease therapy, drug screening, and disease modeling. However, current approaches for induced NSCs (iNSCs) generation from somatic cells are still slow and inefficient. Here we establish a rapid and efficient method of iNSCs generation from human and mouse fibroblasts by single microRNAs (miR-302a).
View Article and Find Full Text PDFAnimal models of kabuki syndrome and their applicability to novel drug discovery.
Expert Opin Drug Discov
January 2025
Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA.
Introduction: Kabuki Syndrome (KS) is a rare genetic disorder characterized by distinctive facial features, intellectual disability, and multiple congenital anomalies. It is caused by pathogenic variants in the and genes. Despite its significant disease burden, there are currently no approved therapies for KS, highlighting the need for advanced research and therapeutic development.
View Article and Find Full Text PDFThe developmental lipidome of Nippostrongylus brasiliensis.
Parasit Vectors
January 2025
Department of Veterinary Biosciences, Melbourne Veterinary School, Faculty of Science, The University of Melbourne, Parkville, VIC, 3010, Australia.
Background: Nippostrongylus brasiliensis-a nematode of rodents-is commonly used as a model to study the immunobiology of parasitic nematodes. It is a member of the Strongylida-a large order of socioeconomically important parasitic nematodes of animals. Lipids are known to play essential roles in nematode biology, influencing cellular membranes, energy storage and/or signalling.
View Article and Find Full Text PDFHDN-DDI: a novel framework for predicting drug-drug interactions using hierarchical molecular graphs and enhanced dual-view representation learning.
BMC Bioinformatics
January 2025
School of Computer Science and Technology, University of Science and Technology of China, 443 Huangshan Road, Hefei, 230027, China.
Background: Drug-drug interactions (DDIs) especially antagonistic ones present significant risks to patient safety, underscoring the urgent need for reliable prediction methods. Recently, substructure-based DDI prediction has garnered much attention due to the dominant influence of functional groups and substructures on drug properties. However, existing approaches face challenges regarding the insufficient interpretability of identified substructures and the isolation of chemical substructures.
View Article and Find Full Text PDFBlood-based epigenome-wide association study and prediction of alcohol consumption.
Clin Epigenetics
January 2025
Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait.
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