Publications by authors named "Eric Sun"

Old age is associated with a decline in cognitive function and an increase in neurodegenerative disease risk. Brain ageing is complex and is accompanied by many cellular changes. Furthermore, the influence that aged cells have on neighbouring cells and how this contributes to tissue decline is unknown.

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Focal gene amplifications are among the most common cancer-associated mutations but have proven challenging to engineer in primary cells and model organisms. Here we describe a general strategy to engineer large (more than 1 Mbp) focal amplifications mediated by extrachromosomal DNAs (ecDNAs) in a spatiotemporally controlled manner in cells and in mice. By coupling ecDNA formation with expression of selectable markers, we track the dynamics of ecDNA-containing cells under physiological conditions and in the presence of specific selective pressures.

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The native membrane environment profoundly influences every aspect of membrane protein (MP) biology. Despite this, the most prevalent method of studying MPs uses detergents to disrupt and remove this vital membrane context, impeding our ability to decipher the local molecular context and its effect. Here we develop a membrane proteome-wide platform that enables rapid spatially resolved extraction of target MPs directly from cellular membranes into native nanodiscs that maintain the local membrane context, using a library of membrane-active polymers.

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Mutations in methyl-CpG-binding protein 2 (MeCP2) cause Rett syndrome. MeCP2 is thought to regulate gene transcription by binding to methylated DNA broadly across the genome. Here, using cleavage under target and release under nuclease (CUT&RUN) assays in the adult mouse cortex, we show that MeCP2 strongly binds to specific gene enhancers that we call MeCP2-binding hotspots (MBHs).

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Ageing impairs the ability of neural stem cells (NSCs) to transition from quiescence to proliferation in the adult mammalian brain. Functional decline of NSCs results in the decreased production of new neurons and defective regeneration following injury during ageing. Several genetic interventions have been found to ameliorate old brain function, but systematic functional testing of genes in old NSCs-and more generally in old cells-has not been done.

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Old age is associated with a decline in cognitive function and an increase in neurodegenerative disease risk. Brain aging is complex and accompanied by many cellular changes. However, the influence that aged cells have on neighboring cells and how this contributes to tissue decline is unknown.

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Motivation: Spatially resolved single-cell transcriptomics have provided unprecedented insights into gene expression in situ, particularly in the context of cell interactions or organization of tissues. However, current technologies for profiling spatial gene expression at single-cell resolution are generally limited to the measurement of a small number of genes. To address this limitation, several algorithms have been developed to impute or predict the expression of additional genes that were not present in the measured gene panel.

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Partial reprogramming (pulsed expression of reprogramming transcription factors) improves the function of several tissues in old mice. However, it remains largely unknown how partial reprogramming impacts the old brain. Here we use single-cell transcriptomics to systematically examine how partial reprogramming influences the subventricular zone neurogenic niche in aged mouse brains.

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Background: Key goals during intracranial surgery are to facilitate rapid emergence and extubation for early neurologic evaluation. Longer-acting opioids are often avoided or administered at subtherapeutic doses due to their perceived risk of sedation and delayed emergence. However, inadequate analgesia and increased postoperative pain are common after intracranial surgery.

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Single-cell data integration can provide a comprehensive molecular view of cells, and many algorithms have been developed to remove unwanted technical or biological variations and integrate heterogeneous single-cell datasets. Despite their wide usage, existing methods suffer from several fundamental limitations. In particular, we lack a rigorous statistical test for whether two high-dimensional single-cell datasets are alignable (and therefore should even be aligned).

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Article Synopsis
  • * A new high-throughput platform utilizes membrane-active polymers to extract membrane proteins directly into native nanodiscs, preserving their local environment and allowing for analysis from various organellar membranes.
  • * An accompanying open-access database provides extraction variability data for over 2,000 mammalian membrane proteins, optimizing conditions for researchers and facilitating the study of multiprotein complexes and structural interactions.
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Whole-transcriptome spatial profiling of genes at single-cell resolution remains a challenge. To address this limitation, spatial gene expression prediction methods have been developed to infer the spatial expression of unmeasured transcripts, but the quality of these predictions can vary greatly. Here we present Transcript Imputation with Spatial Single-cell Uncertainty Estimation (TISSUE) as a general framework for estimating uncertainty for spatial gene expression predictions and providing uncertainty-aware methods for downstream inference.

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Background: Operating room (OR) expenditures and waste generation are a priority, with several professional societies recommending the use of reprocessed or reusable equipment where feasible. The aim of this analysis was to compare single-use pulse oximetry sensor stickers ("single-use stickers") versus reusable pulse oximetry sensor clips ("reusable clips") in terms of annual cost savings and waste generation across all ORs nationally.

Methods: This study did not involve patient data or research on human subjects.

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Dimensionality reduction (DR) is commonly used to project high-dimensional data into lower dimensions for visualization, which could then generate new insights and hypotheses. However, DR algorithms introduce distortions in the visualization and cannot faithfully represent all relations in the data. Thus, there is a need for methods to assess the reliability of DR visualizations.

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Background: Regional anesthesia for total knee arthroplasty has been deemed high priority by national and international societies, and its use can serve as a measure of healthcare equity. The association between utilization of regional anesthesia for postoperative pain and (1) race and (2) hospital in patients undergoing total knee arthroplasty was estimated. The hypothesis was that Black patients would be less likely than White patients to receive regional anesthesia, and that variability in regional anesthesia would more likely be attributable to the hospital where surgery occurred than race.

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The regenerative potential of brain stem cell niches deteriorates during aging. Yet the mechanisms underlying this decline are largely unknown. Here we characterize genome-wide chromatin accessibility of neurogenic niche cells in vivo during aging.

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Background: Insured patients who receive out-of-network care may receive a "balance bill" for the difference between the practitioner's charge and their insurer's contracted rate. In 2017, California banned balance billing for anesthesia care. This study examined the association between California's law and subsequent payments for anesthesia care.

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Whole-transcriptome spatial profiling of genes at single-cell resolution remains a challenge. To address this limitation, spatial gene expression prediction methods have been developed to infer the spatial expression of unmeasured transcripts, but the quality of these predictions can vary greatly. Here we present TISSUE (Transcript Imputation with Spatial Single-cell Uncertainty Estimation) as a general framework for estimating uncertainty for spatial gene expression predictions and providing uncertainty-aware methods for downstream inference.

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The diversity of cell types is a challenge for quantifying aging and its reversal. Here we develop 'aging clocks' based on single-cell transcriptomics to characterize cell-type-specific aging and rejuvenation. We generated single-cell transcriptomes from the subventricular zone neurogenic region of 28 mice, tiling ages from young to old.

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