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  • 1
    Online Resource
    Online Resource
    Autophagic control of cell ‘stemness’
    EMBO ; 2013
    In:  EMBO Molecular Medicine Vol. 5, No. 3 ( 2013-03), p. 327-331
    Details
    In: EMBO Molecular Medicine, EMBO, Vol. 5, No. 3 ( 2013-03), p. 327-331
    Type of Medium: Online Resource
    ISSN: 1757-4676 , 1757-4684
    URL: Issue
    URL: Article
    DOI: 10.1002/emmm.v5.3
    DOI: 10.1002/emmm.201201999
    Language: English
    Publisher: EMBO
    Publication Date: 2013
    detail.hit.zdb_id: 2485479-7
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  • 2
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    Therapeutic Effects and Metabolic Spectrum of Traditional Chinese Medicine Hengqing II Prescription on Alzheimer’s Disease
    Hindawi Limited ; 2022
    In:  Evidence-Based Complementary and Alternative Medicine Vol. 2022 ( 2022-8-2), p. 1-12
    Details
    In: Evidence-Based Complementary and Alternative Medicine, Hindawi Limited, Vol. 2022 ( 2022-8-2), p. 1-12
    Abstract: Alzheimer’s disease (AD) seriously damages elders’ social and daily abilities around the world. Traditional Chinese medicine (TCM), a rich drug resource bank, could help research AD. In order to explore the role of TCM in AD treatment, 86 AD patients were recruited from the hospital, then treated with Hengqing II prescription and donepezil hydrochloride. The cognitive and serum lipid levels were investigated before and after treatment. The patient’s urine was collected after three months of treatment. Metabolites in the urine samples were extracted with methanol and detected on the UHPLC-MS platform. Results proved that Hengqing II can improve cognitive levels and reduce the levels of Hcy, D-D, FIB, Apo B, TC, and LDL-C compared with donepezil hydrochloride ( P 〈 0.05 ). The results of multivariate statistical analysis revealed that the metabolism of HQII was significantly different compared with Control groups. A total of 66 differential metabolites were found in this comparison (50 were down-regulated and 16 were up-regulated). Four amino acid pathways and one linoleic acid pathway were found through these metabolites. After receiver operating characteristic analysis, it was suggested that palmitic acid, palmitoleic acid, linoleic acid, oleic acid, SAH, and methionine can be used as biomarkers for treating AD, while the effects of daidzein, genistein, and naringenin on the treatment of AD need to be further studied.
    Type of Medium: Online Resource
    ISSN: 1741-4288 , 1741-427X
    URL: Article
    DOI: 10.1155/2022/5912396
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2148302-4
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  • 3
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    Abstract 701: Atherosclerosis Is A Smooth Muscle Cell-driven Tumor-like Disease
    Ovid Technologies (Wolters Kluwer Health) ; 2023
    In:  Arteriosclerosis, Thrombosis, and Vascular Biology Vol. 43, No. Suppl_1 ( 2023-05)
    Details
    In: Arteriosclerosis, Thrombosis, and Vascular Biology, Ovid Technologies (Wolters Kluwer Health), Vol. 43, No. Suppl_1 ( 2023-05)
    Abstract: Background: Atherosclerosis, the leading cause of cardiovascular disease (CVD), is a chronic inflammatory disease involving pathological activation of multiple cell types, such as immunocytes (e.g., macrophage, T cells), smooth muscle cells (SMCs), endothelial cells, etc. Multiple lines of evidence have suggested that SMC “phenotypic switching” plays a central role in atherosclerosis development and complications. Yet, how SMCs and SMC-derived cells (SDCs) modulate atherosclerosis progression and clinical CVD remains poorly understood. Methods: We applied SMC lineage tracing mice and implemented comprehensive molecular and cellular biology, histological, computational, and pharmacological studies to reveal how tumor cell-like activities of SDCs drive the development of atherosclerosis. Results: Oxidative DNA damage occurs during SMC phenotypic switching and increases with the progression of atherosclerosis. Extensive DNA damage-induced genomic instability accumulates in both mouse and human atherosclerosis, especially in SDCs. Indeed, SDCs in atherosclerosis harbor multiple tumor cell-like features, including escape of replicative senescence, clonogenicity, invasive capacity, and ex vivo formation of three-dimensional (3D) spheroids like cancer stem cells. Multiple cancer-associated signaling pathways (e.g., p53, TNFa, NFkB, VEGF) are activated in SDCs. SMC-specific expression of oncogenic Kras G12D accelerates SMC phenotypic switching and exacerbates atherosclerosis. Moreover, we provide proof of concept in mouse models that niraparib, an anti-cancer drug targeting DNA damage repair, attenuates atherosclerosis progression and regresses lesions in advanced disease. Conclusions: Our studies in human and mouse models provide the first systematic evidence that SDCs in atherosclerosis share extensive commonalities with tumor, which deepens our understanding of the disease and opens prospects for novel targeted strategies to prevent and treat atherosclerotic CVD.
    Type of Medium: Online Resource
    ISSN: 1079-5642 , 1524-4636
    URL: Article
    DOI: 10.1161/atvb.43.suppl_1.701
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2023
    detail.hit.zdb_id: 1494427-3
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  • 4
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    Abstract 212: Transcriptional Profiling Of Vascular Smooth Muscle Cell-foam Cells In Atherosclerotic Lesions
    Ovid Technologies (Wolters Kluwer Health) ; 2023
    In:  Arteriosclerosis, Thrombosis, and Vascular Biology Vol. 43, No. Suppl_1 ( 2023-05)
    Details
    In: Arteriosclerosis, Thrombosis, and Vascular Biology, Ovid Technologies (Wolters Kluwer Health), Vol. 43, No. Suppl_1 ( 2023-05)
    Abstract: Background: One of the hallmarks of atherosclerosis progression is the uptake of oxidized lipids by cells to become Foam/Foamy cells - the most prominent being vascular smooth muscle cells (VSMC)-foam cells. Although studies have identified the ability of VSMC to become VSMC-foam cells, their transcriptomic profile and the phenotypic modulations which distinguish them from contractile VSMC remain poorly defined and understood. Hypothesis: We hypothesize that VSMC-foamy cells differ from contractile VSMC not only by modulation of genes shared by both cell types, but also by the expression of a unique set of genes which contribute to their formation and maintenance within atherosclerotic lesions. Method: To address this, we performed bulk RNA sequencing of atherosclerotic plaques from conditional VSMC-lineage tracing mice models on high fat diet. VSMC and VSMC-foam cells were isolated and sequenced at specific time points reflective of late and advanced atherosclerosis disease progression. Computational analysis enabled us identify differentially expressed genes, biological pathways and molecular functions which distinguished VSMC from VSMC-foam cells. Result and Conclusion: Our computational analysis identified differential genes and pathways unique to VSMC-foam cells which might be associated with disease progression. From our analysis, VSMC showed a lower expression of contractile VSMC marker genes and a higher expression of genes in synthetic/intermediary multipotent state, we term “SEM” state. Our study also showed that VSMC-foam cells also expressed unique genes which distinguished them from contractile VSMC. These genes not only serve as potential genetic markers, but might further explain the nuclear composition, as well as the inflammatory and metabolic profile of VSMC-foam cells. Defining and understanding the molecular mechanisms and drivers which promote VSMC-foam cell formation and maintenance in atherosclerosis, would aid in our understanding of the disease with potentials for more effective therapeutic solutions.
    Type of Medium: Online Resource
    ISSN: 1079-5642 , 1524-4636
    URL: Article
    DOI: 10.1161/atvb.43.suppl_1.212
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2023
    detail.hit.zdb_id: 1494427-3
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  • 5
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    Online Resource
    SIRT6 safeguards human mesenchymal stem cells from oxidative stress by coactivating NRF2
    Springer Science and Business Media LLC ; 2016
    In:  Cell Research Vol. 26, No. 2 ( 2016-2), p. 190-205
    Details
    In: Cell Research, Springer Science and Business Media LLC, Vol. 26, No. 2 ( 2016-2), p. 190-205
    Type of Medium: Online Resource
    ISSN: 1001-0602 , 1748-7838
    URL: Article
    DOI: 10.1038/cr.2016.4
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2016
    detail.hit.zdb_id: 2082402-6
    SSG: 12
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  • 6
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    Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis
    Springer Science and Business Media LLC ; 2020
    In:  Nature Communications Vol. 11, No. 1 ( 2020-05-11)
    Details
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 11, No. 1 ( 2020-05-11)
    Abstract: Single-cell RNA sequencing (scRNA-seq) can characterize cell types and states through unsupervised clustering, but the ever increasing number of cells and batch effect impose computational challenges. We present DESC, an unsupervised deep embedding algorithm that clusters scRNA-seq data by iteratively optimizing a clustering objective function. Through iterative self-learning, DESC gradually removes batch effects, as long as technical differences across batches are smaller than true biological variations. As a soft clustering algorithm, cluster assignment probabilities from DESC are biologically interpretable and can reveal both discrete and pseudotemporal structure of cells. Comprehensive evaluations show that DESC offers a proper balance of clustering accuracy and stability, has a small footprint on memory, does not explicitly require batch information for batch effect removal, and can utilize GPU when available. As the scale of single-cell studies continues to grow, we believe DESC will offer a valuable tool for biomedical researchers to disentangle complex cellular heterogeneity.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    URL: Article
    DOI: 10.1038/s41467-020-15851-3
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2553671-0
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  • 7
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    Single-Cell Genomics Reveals a Novel Cell State During Smooth Muscle Cell Phenotypic Switching and Potential Therapeutic Targets for Atherosclerosis in Mouse and Human
    Ovid Technologies (Wolters Kluwer Health) ; 2020
    In:  Circulation Vol. 142, No. 21 ( 2020-11-24), p. 2060-2075
    Details
    In: Circulation, Ovid Technologies (Wolters Kluwer Health), Vol. 142, No. 21 ( 2020-11-24), p. 2060-2075
    Abstract: Smooth muscle cells (SMCs) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC dedifferentiation, migration, and transdifferentiation into other cell types. Yet how SMCs contribute to the pathophysiology of atherosclerosis remains elusive. Methods: To reveal the trajectories of SMC transdifferentiation during atherosclerosis and to identify molecular targets for disease therapy, we combined SMC fate mapping and single-cell RNA sequencing of both mouse and human atherosclerotic plaques. We also performed cell biology experiments on isolated SMC-derived cells, conducted integrative human genomics, and used pharmacological studies targeting SMC-derived cells both in vivo and in vitro. Results: We found that SMCs transitioned to an intermediate cell state during atherosclerosis, which was also found in human atherosclerotic plaques of carotid and coronary arteries. SMC-derived intermediate cells, termed “SEM” cells (stem cell, endothelial cell, monocyte), were multipotent and could differentiate into macrophage-like and fibrochondrocyte-like cells, as well as return toward the SMC phenotype. Retinoic acid (RA) signaling was identified as a regulator of SMC to SEM cell transition, and RA signaling was dysregulated in symptomatic human atherosclerosis. Human genomics revealed enrichment of genome-wide association study signals for coronary artery disease in RA signaling target gene loci and correlation between coronary artery disease risk alleles and repressed expression of these genes. Activation of RA signaling by all-trans RA, an anticancer drug for acute promyelocytic leukemia, blocked SMC transition to SEM cells, reduced atherosclerotic burden, and promoted fibrous cap stability. Conclusions: Integration of cell-specific fate mapping, single-cell genomics, and human genetics adds novel insights into the complexity of SMC biology and reveals regulatory pathways for therapeutic targeting of SMC transitions in atherosclerotic cardiovascular disease.
    Type of Medium: Online Resource
    ISSN: 0009-7322 , 1524-4539
    URL: Article
    DOI: 10.1161/CIRCULATIONAHA.120.048378
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2020
    detail.hit.zdb_id: 1466401-X
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  • 8
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    Online Resource
    Abstract 12293: Retinoic Acid Signaling Regulates Smooth Muscle Cell Phenotypic Switching in Atherosclerosis Through Epigenetic Modulation of Gene Expression
    Ovid Technologies (Wolters Kluwer Health) ; 2022
    In:  Circulation Vol. 146, No. Suppl_1 ( 2022-11-08)
    Details
    In: Circulation, Ovid Technologies (Wolters Kluwer Health), Vol. 146, No. Suppl_1 ( 2022-11-08)
    Abstract: Background: Smooth muscle cells (SMCs) substantially contribute to atherosclerosis through “phenotypic switching.” Our previous work identified an intermediate SMC-derived cell type, termed “SEM” cells, which was multipotent and activated in inflammatory response. Activation of retinoic acid (RA) signaling by all-trans retinoic acid (ATRA) attenuated atherosclerosis in mice coincident with dramatic suppression of SEM cell formation from SMCs. However, the regulatory mechanisms by which RA signaling modulates SMC transition to SEM cells are largely unknown. Methods: We employed molecular and cell biology techniques, SMC-linage tracing and atheroprone mouse models, and next-generation sequencing (e.g., RNA-seq, ChIP-seq) to reveal how RA signaling modulates SMC transition to SEM cells. Results: Activation of RA signaling with ATRA significantly reduced SEM cells in established atherosclerosis, as well as downregulated the expression of SEM cell marker genes (e.g., Ly6a , Ly6c1 ) and repressed inflammatory response in ex vivo SEM cells, whereas inhibition of the signaling with antagonist, BMS49334, showed opposite results. RARα occupied the promoter regions of SEM cell marker genes, and ATRA treatment significantly increased the enrichment of NCOR1 at promoters of these genes. These findings suggest that RA signaling suppresses SMC transition to SEM cells via directly repressing the expression of SEM cell marker genes. Furthermore, we found EZH2, one of the subunits of PRC2, physically interacted with RARα in SMCs and occupied the promoters of SEM cell marker genes, and its methyltransferase activity at the promoter regions was responsible for the repression of SEM cell maker genes. Moreover, activation of RA signaling inhibited SEM cell inflammatory response through LXR-mediated suppression of a series of inflammatory genes. Finally, multiple epigenetic signatures (e.g., H3K27me3, H3K27ac, H3K4me3, etc.) at TSS of SEM cell marker genes and inflammatory genes were extensively altered in response to the activation of RA signaling. Conclusions: Our findings indicate that RA signaling modulates maintenance of SEM cell identity and inflammatory function in atherosclerosis by epigenetic regulation of gene expression.
    Type of Medium: Online Resource
    ISSN: 0009-7322 , 1524-4539
    URL: Article
    DOI: 10.1161/circ.146.suppl_1.12293
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2022
    detail.hit.zdb_id: 1466401-X
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  • 9
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    A joint deep learning model enables simultaneous batch effect correction, denoising, and clustering in single-cell transcriptomics
    Cold Spring Harbor Laboratory ; 2021
    In:  Genome Research Vol. 31, No. 10 ( 2021-10), p. 1753-1766
    Details
    In: Genome Research, Cold Spring Harbor Laboratory, Vol. 31, No. 10 ( 2021-10), p. 1753-1766
    Abstract: Recent developments of single-cell RNA-seq (scRNA-seq) technologies have led to enormous biological discoveries. As the scale of scRNA-seq studies increases, a major challenge in analysis is batch effects, which are inevitable in studies involving human tissues. Most existing methods remove batch effects in a low-dimensional embedding space. Although useful for clustering, batch effects are still present in the gene expression space, leaving downstream gene-level analysis susceptible to batch effects. Recent studies have shown that batch effect correction in the gene expression space is much harder than in the embedding space. Methods such as Seurat 3.0 rely on the mutual nearest neighbor (MNN) approach to remove batch effects in gene expression, but MNN can only analyze two batches at a time, and it becomes computationally infeasible when the number of batches is large. Here, we present CarDEC, a joint deep learning model that simultaneously clusters and denoises scRNA-seq data while correcting batch effects both in the embedding and the gene expression space. Comprehensive evaluations spanning different species and tissues showed that CarDEC outperforms Scanorama, DCA + Combat, scVI, and MNN. With CarDEC denoising, non-highly variable genes offer as much signal for clustering as the highly variable genes (HVGs), suggesting that CarDEC substantially boosted information content in scRNA-seq. We also showed that trajectory analysis using CarDEC's denoised and batch-corrected expression as input revealed marker genes and transcription factors that are otherwise obscured in the presence of batch effects. CarDEC is computationally fast, making it a desirable tool for large-scale scRNA-seq studies.
    Type of Medium: Online Resource
    ISSN: 1088-9051 , 1549-5469
    URL: Article
    DOI: 10.1101/gr.271874.120
    RVK:
    XA 10000
    Language: English
    Publisher: Cold Spring Harbor Laboratory
    Publication Date: 2021
    detail.hit.zdb_id: 1483456-X
    SSG: 12
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  • 10
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    A protective smooth muscle cell transition in atherosclerosis
    Springer Science and Business Media LLC ; 2019
    In:  Nature Medicine Vol. 25, No. 8 ( 2019-8), p. 1194-1195
    Details
    In: Nature Medicine, Springer Science and Business Media LLC, Vol. 25, No. 8 ( 2019-8), p. 1194-1195
    Type of Medium: Online Resource
    ISSN: 1078-8956 , 1546-170X
    URL: Article
    DOI: 10.1038/s41591-019-0541-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 1484517-9
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