Cellular redox state directs differentiation of induced pluripotent stem cells (iPSC) by energy metabolism control and ROS generation. As oxidative stress and mitochondrial dysfunction have been extensively reported in Down syndrome (DS), we evaluated mitochondrial phenotypes and energy metabolism during neural differentiation of DS iPSCs to neural progenitor cells (NPCs). Our results indicate early maturation of mitochondrial networks and elevated NADPH oxidase 4 (NOX4) expression in DS iPSCs. DS cells also fail to transition from glycolysis to oxidative phosphorylation during differentiation. Specifically, DS NPCs show an increased energetic demand that is limited in their mitochondrial and glycolytic response to mitochondrial distress. Additionally, DS iPSC and NPC non-mitochondrial oxygen consumption was significantly impacted by NOX inhibition. Together, these data build upon previous evidence of accelerated neural differentiation in DS that correlates with cellular redox state. We demonstrate the potential for mitochondrial and non-mitochondrial ROS sources to impact differentiation timing in the context of DS, which could contribute to developmental deficits in this condition.
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http://dx.doi.org/10.1016/j.freeradbiomed.2023.01.009 | DOI Listing |
Neuroradiol J
January 2025
Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Iran.
Introduction: The prevalence of neurodegenerative diseases has significantly increased, necessitating a deeper understanding of their symptoms, diagnostic processes, and prevention strategies. Frontotemporal dementia (FTD) and Alzheimer's disease (AD) are two prominent neurodegenerative conditions that present diagnostic challenges due to overlapping symptoms. To address these challenges, experts utilize a range of imaging techniques, including magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), functional MRI (fMRI), positron emission tomography (PET), and single-photon emission computed tomography (SPECT).
View Article and Find Full Text PDFJ Neural Transm (Vienna)
January 2025
Department of Neurology, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul National University of College of Medicine, Seoul, Republic of Korea.
To investigate the clinical impact of mild behavioral impairment (MBI) in a predefined cohort with Lewy body disease (LBD) continuum. Eighty-four patients in the LBD continuum participated in this study, including 35 patients with video-polysomnography-confirmed idiopathic REM sleep behavior disorder (iRBD) and 49 clinically established LBD. Evaluations included the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS), neuropsychological tests, and MBI Checklist (MBI-C).
View Article and Find Full Text PDFAlzheimers Dement
December 2024
German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
Background: Differences in task-fMRI activation have recently been found to be related to neuropathological hallmarks of AD. However, the evolution of fMRI-based activation throughout AD disease progression and its relationship with other biomarkers remains elusive. Applying a disease progression model (DPM) to a multicentric cohort with up to four annual task-fMRI visits, we hope to provide a deeper insight into these relationships.
View Article and Find Full Text PDFBackground: Recent advancements in automatic language and speech analysis, coupled with machine learning (ML) methods, showcase the effectiveness of digital biomarkers in non-invasively detecting subtle changes in cognitive status. While successfully distinguishing between Alzheimer's Disease (AD) and Normal Control (NC) individuals, classifying Mild Cognitive Impairment (MCI) proves to be a more challenging task. MCI can progress to AD or result from various factors, including affective disorders, necessitating multiple expert examinations for accurate detection.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
Background: Recent technological advancements have revolutionized our approach to healthcare, enabling us to harness the potential of smartphones and wearables to collect data that can be used to characterize Alzheimer's disease (AD) heterogeneity and to develop digital biomarkers. Our focus is to create comprehensive cross-domain digital datasets and establish an infrastructure that allows for seamless data sharing. Central to accelerating the potential of digital biomarkers for more accurate and early detection is privacy-protecting data access, which when combined with deep molecular phenotyping, will enhance our understanding of the biological mechanisms underlying clinical expression.
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