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  • Open Access

    ARTICLE

    Single-cell RNA sequencing reveals classical monocytes are the major precursors of rat osteoclasts

    JIRUI WEN1,#, WENCHAO WU2,#, MIN TANG1, MINGYUE BAO1, XUELING HE3, XINGHONG YAO1, LIANG LI1,*

    BIOCELL, Vol.46, No.3, pp. 655-665, 2022, DOI:10.32604/biocell.2022.016915

    Abstract To dissect which subset of bone marrow monocyte is the major precursor of osteoclast, 3-month-old rat bone marrow was obtained for single-cell RNA sequencing. A total of 6091 cells were acquired for detailed analysis, with a median number of 1206 genes detected per cell and 17,959 genes detected in total. A total of 19 cell clusters were recognized, with the main lineages identified as B cells, Granulocytes, Monocytes, T cells, Erythrocytes and Macrophages. Monocytes were further divided into classical monocytes and non-classical monocytes. Compared with non-classical monocytes, classical monocytes highly expressed osteoclast differentiation related genes Mitf, Spi1, Fos and Csf1r.… More >

  • Open Access

    VIEWPOINT

    Single-cell systems neuroscience: A growing frontier in mental illness

    SEAN J. O’SULLIVAN1,2,*

    BIOCELL, Vol.46, No.1, pp. 7-11, 2022, DOI:10.32604/biocell.2022.017680

    Abstract The development of effective treatments for psychiatric disease has been disappointing in recent decades given the advancements in neuroscience. Moreover, rising rates of mental illness such as addiction and depression compel scientists and physicians to discover novel and creative solutions. One such approach that has proven effective is systems neuroscience: A focus on networks as opposed to mechanism. Further, investigation at the single-cell and circuit level is likely to be fruitful in such endeavors as this resolution describes the functional psychopathology that allows for intervention. More >

  • Open Access

    VIEWPOINT

    Aneuploidy: An opportunity within single-cell RNA sequencing analysis

    JOE R. DELANEY*

    BIOCELL, Vol.45, No.5, pp. 1167-1170, 2021, DOI:10.32604/biocell.2021.017296

    Abstract Single-cell sequencing data has transformed the understanding of biological heterogeneity. While many flavors of single-cell sequencing have been developed, single-cell RNA sequencing (scRNA-seq) is currently the most prolific form in published literature. Bioinformatic analysis of differential biology within the population of cells studied relies on inferences and grouping of cells due to the spotty nature of data within individual cell scRNA-seq gene counts. One biologically relevant variable is readily inferred from scRNA-seq gene count tables regardless of individual gene representation within single cells: aneuploidy. Since hundreds of genes are present on chromosome arms, high-quality inferences of aneuploidy can be made… More >

  • Open Access

    ARTICLE

    Expression profiling of immune cells in systemic lupus erythematosus by single-cell RNA sequencing

    XIANLIANG HOU1,2,3,#, DONGE TANG1,#, FENGPING ZHENG1,#, MINGLIN OU3, YONG XU1, HUIXUAN XU1, XIAOPING HONG4, XINZHOU ZHANG1, WEIER DAI5, DONGZHOU LIU4,*, YONG DAI1,*

    BIOCELL, Vol.44, No.4, pp. 559-582, 2020, DOI:10.32604/biocell.2020.011022

    Abstract Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterized by abnormal cellular and humoral immune responses and excessive autoantibody production. The precise pathologic mechanism of SLE remains elusive. The advent of single-cell RNA sequencing (scRNA-seq) enables unbiased analysis of the molecular differences of cell populations at the single-cell level. We used scRNA-seq to profile the transcriptomes of peripheral blood mononuclear cells from an SLE patient compared with a healthy control (HC). A total of 16,021 cells were analyzed and partitioned into 12 distinct clusters. The marker genes of each cluster and the four major immune cell types (B cells,… More >

  • Open Access

    ABSTRACT

    Engineering Zap70 Biosensor Through Directed Evolution for Applications in Single-Cell Imaging and Immunotherapy

    Longwei Liu1, Praopim Limsakul1, Shaoying (Kathy) Lu1, Peter Yingxiao Wang1,*

    Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 82-82, 2019, DOI:10.32604/mcb.2019.07360

    Abstract Genetically-encoded biosensors based on Fluorescence Resonance Energy Transfer (FRET biosensors) have been widely used to dynamically track the activity of Protein Tyrosine Kinases (PTKs) in living cells because of their sensitive ratiometric fluorescence readout, high spatiotemporal resolution. However, the limitation in sensitivity, specificity, and dynamic range of these biosensors have hindered their broader applications, and there was a lack of efficient ways to optimize FRET biosensors. Here we established a rapid, systematic and universal approach for FRET biosensor optimization through directed evolution which involves generating genetic diversity and screening for protein variants with desired properties at the same time and… More >

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