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Lysosomes play a central role in the degradation of intracellular substances. Through this degradative capacity, lysosomes contribute to biological homeostasis and are particularly critical for the maintenance and function of neurons. Deficiencies in various lysosomal proteins cause a group of conditions known as lysosomal storage disorders, which often present with developmental delay and other neurological symptoms. In addition, defects in lysosomal function and the autophagic pathways that deliver intracellular substrates to lysosomes have been linked to neurodevelopmental disorders. However, the contribution of lysosomal degradative capacity to neurodevelopment has not been well appreciated. In this study, we aimed to examine the relationship between overall lysosomal proteolytic capacity and neuronal development using primary cultured neurons at early developmental stages. We found that lysosomal protein expression and proteolytic activity increased with neuronal maturation, suggesting that lysosomal proteolysis may play an important role in neuronal development. Treatment of cultured neurons with specific inhibitors of lysosomal proteases during development impaired morphogenesis, as indicated by a significant decrease in neurite length and complexity, along with decreased expression of neuronal lineage marker proteins. Furthermore, we observed that neurons with development impaired by lysosomal protease inhibition accumulated aggregated proteins-some of which were ubiquitinated-in the cytoplasm. These aggregates were enriched with various proteins related to neurodevelopment. These findings provide new insights into the previously underappreciated role of lysosomes in neuronal development.
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http://dx.doi.org/10.1016/j.neuint.2025.106048 | DOI Listing |
Sci Transl Med
September 2025
Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., 4070 Basel, Switzerland.
Oligodendrocytes, the myelinating cells of the central nervous system (CNS), are essential for the formation of myelin sheaths and pivotal for maintaining axonal integrity and conduction. Disruption of these cells and the myelin sheaths they produce is a hallmark of demyelinating conditions like multiple sclerosis or those resulting from certain drug side effects, leading to profound neurological impairments. In this study, we created a human brain organoid comprising neurons, astrocytes, and myelinating oligodendrocytes.
View Article and Find Full Text PDFMol Biol Cell
September 2025
Department of Neurobiology & Anatomy, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX 77030 USA.
Autophagy is critical for the homeostasis and function of neurons, as misregulation of autophagy has been implicated in age-related neurodegenerative diseases and neuron-specific knockdown of early autophagy genes results in early neurodegeneration in mice. We previously found that autophagosome formation decreases with age in murine neurons. Sex differences have been intensely studied in neurodegenerative diseases, but whether sex differences influence autophagy at the neuronal level have not been investigated.
View Article and Find Full Text PDFCereb Cortex
August 2025
Section on Functional Imaging Methods & Functional MRI Core Facility, National Institute of Mental Health, 10 Center Drive, Rm 1D80, Bethesda, MD 20892, United States.
Statistical Parametric Mapping (SPM) has been profoundly influential to neuroimaging as it has fostered rigorous, statistically grounded structure for model-based inferences that have led to mechanistic insights about the human brain over the past 30 years. The statistical constructs shared with the world through SPM have been instrumental for deriving meaning from neuroimaging data; however, they require simplifying assumptions which can provide results that, while statistically sound, may not accurately reflect the mechanisms of brain function. A platform that fosters the exploration of the rich and varying neuronal and physiologic underpinnings of the measured signals and their associations to behavior and physiologic measures needs a different set of tools.
View Article and Find Full Text PDFNeuropathol Appl Neurobiol
October 2025
Department of Neuropathology (The Brain Bank for Aging Research), Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan.
Chaos
September 2025
School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Although many real-world time series are complex, developing methods that can learn from their behavior effectively enough to enable reliable forecasting remains challenging. Recently, several machine-learning approaches have shown promise in addressing this problem. In particular, the echo state network (ESN) architecture, a type of recurrent neural network where neurons are randomly connected and only the read-out layer is trained, has been proposed as suitable for many-step-ahead forecasting tasks.
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