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https://www.selleckchem.com/products/gsk2795039.html Lysosomal storage diseases (LSDs) with neurological involvement are inherited genetic diseases of the metabolism characterized by lysosomal dysfunction and the accumulation of undegraded substrates altering glial and neuronal function. Often, patients with neurological manifestations present with damage to the gray and white matter and irreversible neuronal decline. The use of animal models of LSDs has greatly facilitated studying and identifying potential mechanisms of neuronal dysfunction, including alterations in availability and function of synaptic proteins, modifications of membrane structure, deficits in docking, exocytosis, recycling of synaptic vesicles, and inflammation-mediated remodeling of synapses. Although some extrapolations from findings in adult-onset conditions such as Alzheimer's disease or Parkinson's disease have been reported, the pathogenetic mechanisms underpinning cognitive deficits in LSDs are still largely unclear. Without being fully inclusive, the goal of this mini-review is to present a discussion on possible mechanisms leading to synaptic dysfunction in LSDs.Transcriptionally profiling minor cellular populations remains an ongoing challenge in molecular genomics. Single-cell RNA sequencing has provided valuable insights into a number of hypotheses, but practical and analytical challenges have limited its widespread adoption. A similar approach, which we term single-cell type RNA sequencing (sctRNA-seq), involves the enrichment and sequencing of a pool of cells, yielding cell type-level resolution transcriptomes. While this approach offers benefits in terms of mRNA sampling from targeted cell types, it is potentially affected by off-target contamination from surrounding cell types. Here, we leveraged single-cell sequencing datasets to apply a computational approach for estimating and controlling the amount of off-target cell type contamination in sctRNA-seq datasets. In datasets obta

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