Oligodendrocytes are the main glial cell type in the central nervous system supporting the axonal part of neurons via myelin and lactate delivery. Both the conductive myelin formation and the energy support via lactate can be affected in diseases, such as multiple sclerosis and amyotrophic lateral sclerosis, respectively. Therefore, human disease modeling is needed to gain more mechanistic insights to drive drug discovery research. Here, patient-derived induced pluripotent stem cells (iPSCs) serve as a necessary tool providing an infinite cell source for patient-specific disease modeling, which allows investigation of oligodendrocyte involvement in human disease.Small molecule-based differentiation protocols to generate oligodendrocytes from pluripotent stem cells can last more than 90 days. Here, we provide a transcription factor-based, fast and efficient protocol for generating O4 oligodendrocytes in just 20-24 days. After a neural induction phase of 8-12 days, SOX10 is overexpressed either with the use of lentiviral vectors or via engineered iPSCs, which inducibly overexpress SOX10 after doxycycline addition. Using this last method, a pure O4 cell population is achieved after keeping the SOX10-overexpressing neural stem cells in culture for an additional 10 days. Furthermore, these O4 cells can be co-cultured with iPSC-derived cortical neurons in 384-well format, allowing pro-myelinating drug screens. In conclusion, we provide a fast and efficient oligodendrocyte differentiation protocol allowing both in vitro human disease modeling and a high-throughput co-culture system for drug discovery.
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http://dx.doi.org/10.1007/978-1-0716-1601-7_11 | DOI Listing |
FASEB J
January 2025
Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, 200011, China.
With the global rise in advanced maternal age (AMA) pregnancies, the risk of gestational diabetes mellitus (GDM) increases. However, few GDM prediction models are tailored for AMA women. This study aims to develop a practical risk prediction model for GDM in AMA women.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Key Laboratory of Polyoxometalate and Reticular Material Chemistry of Ministry of Education, Chemistry, Renmin Street, 130024, Changchun, CHINA.
High capacity, selective recovery and separation of precious metals from complex aqueous solutions is essential but remains a challenge in practical applications. Here, we prepared a thiophene-modified aromatic porous organic cage (T-PAC) with high stability for precise recognition and recovery of gold. T-PAC exhibits an outstanding gold uptake capacity of up to 2260 mg/g with fast adsorption kinetics and high adsorption selectivity.
View Article and Find Full Text PDFEvol Comput
January 2025
Chair of Algorithms for Intelligent Systems, University of Passau, Passau, Germany
Evolutionary algorithms make countless random decisions during selection, mutation and crossover operations. These random decisions require a steady stream of random numbers. We analyze the expected number of random bits used throughout a run of an evolutionary algorithm and refer to this as the cost of randomness.
View Article and Find Full Text PDFSimulating large molecular systems over long timescales requires force fields that are both accurate and efficient. In recent years, E(3) equivariant neural networks have lifted the tension between computational efficiency and accuracy of force fields, but they are still several orders of magnitude more expensive than established molecular mechanics (MM) force fields. Here, we propose Grappa, a machine learning framework to predict MM parameters from the molecular graph, employing a graph attentional neural network and a transformer with symmetry-preserving positional encoding.
View Article and Find Full Text PDFIntroduction: Simulation has become an integral part of health care education curricula that is used to teach a variety of topics, from emergency situations to physical diagnoses. Without further reinforcement, the skills learned through the simulation are subject to deterioration over time. Rapid Cycle Deliberate Practice (RCDP) is a teaching method that was developed to resist this deterioration and achieve mastery of skills.
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