101
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Zhou J, Wang Y, Ding X, Liang J, Yan D, Marples B, Dilworth J. SU-F-T-382: Volumetric Modulated Arc Therapy (VMAT) Beam Angle Optimization in Pulsed Partial Brain Irradiation (PPBI) for Newly Diagnosed Glioblastoma. Med Phys 2016. [DOI: 10.1118/1.4956567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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102
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Li X, Zhang J, Qin A, Liang J, Zhou J, Yan D, Chen P, Krauss D, Ding X. SU-F-T-205: Effectiveness of Robust Treatment Planning to Account for Inter- Fractional Variation in Intensity Modulated Proton Therapy for Head Neck Cancer. Med Phys 2016. [DOI: 10.1118/1.4956342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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103
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Ding X, Li X, Zhang J, Kabolizadeh P, Stevens C, Yan D. TH-CD-209-10: Scanning Proton Arc Therapy (SPArc) - The First Robust and Delivery-Efficient Spot Scanning Proton Arc Therapy. Med Phys 2016. [DOI: 10.1118/1.4958204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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104
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Yan D, Chen S, Krauss D, Chen P, Wilson G. SU-F-J-59: Assessment of Dose Response Distribution in Individual Human Tumor. Med Phys 2016. [DOI: 10.1118/1.4955967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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105
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Zhu J, Liang J, Chen S, Qin A, Yan D. SU-F-J-86: Method to Include Tissue Dose Response Effect in Deformable Image Registration. Med Phys 2016. [DOI: 10.1118/1.4955994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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106
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Stanhope C, Liang J, Drake D, Yan D. TH-AB-201-12: Using Machine Log-Files for Treatment Planning and Delivery QA. Med Phys 2016. [DOI: 10.1118/1.4958041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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107
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Chen S, Yan D, Wilson G, Krauss D, Chen P. TH-CD-202-10: Tumor Metabolic Control Probability & Dose Response Mapping for Adaptive Dose Painting by Number. Med Phys 2016. [DOI: 10.1118/1.4958166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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108
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Zhou J, Ding X, Liang J, Zhang J, Wang Y, Yan D. SU-F-T-191: 4D Dose Reconstruction of Intensity Modulated Proton Therapy (IMPT) Based On Breathing Probability Density Function (PDF) From 4D Cone Beam Projection Images: A Study for Lung Treatment. Med Phys 2016. [DOI: 10.1118/1.4956328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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109
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Liu G, Qin A, Zhang J, Li X, Zhou J, Yan D, Teo B, Chen P, Krauss D, Kabolizadeh P, Guerrero T, Stevens C, Liang J, Ding X. SU-F-J-192: A Quick and Effective Method to Validate Patient's Daily Setup and Geometry Changes Prior to Proton Treatment Delivery Based On Water Equivalent Thickness Projection Imaging (WETPI) for Head Neck Cancer (HNC) Patient. Med Phys 2016. [DOI: 10.1118/1.4956100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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110
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Yee S, Chinnaiyan P, Wloch J, Pirkola M, Yan D. SU-D-207A-02: Possible Characterization of the Brain Tumor Vascular Environment by a Novel Strategy of Quantitative Analysis in Dynamic Contrast Enhanced MR Imaging: A Combination of Both Patlak and Logan Analyses. Med Phys 2016. [DOI: 10.1118/1.4955649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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111
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Qin A, Liang J, Zhu J, Ding X, Castillo E, Guerrero T, Yan D. SU-F-J-60: Impact of DIR Method On Treatment Dose Wrapping. Med Phys 2016. [DOI: 10.1118/1.4955968] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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112
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Mason CC, Khorashad JS, Tantravahi SK, Kelley TW, Zabriskie MS, Yan D, Pomicter AD, Reynolds KR, Eiring AM, Kronenberg Z, Sherman RL, Tyner JW, Dalley BK, Dao KH, Yandell M, Druker BJ, Gotlib J, O'Hare T, Deininger MW. Age-related mutations and chronic myelomonocytic leukemia. Leukemia 2015; 30:906-13. [PMID: 26648538 DOI: 10.1038/leu.2015.337] [Citation(s) in RCA: 106] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Revised: 11/17/2015] [Accepted: 11/23/2015] [Indexed: 01/18/2023]
Abstract
Chronic myelomonocytic leukemia (CMML) is a hematologic malignancy nearly confined to the elderly. Previous studies to determine incidence and prognostic significance of somatic mutations in CMML have relied on candidate gene sequencing, although an unbiased mutational search has not been conducted. As many of the genes commonly mutated in CMML were recently associated with age-related clonal hematopoiesis (ARCH) and aged hematopoiesis is characterized by a myelomonocytic differentiation bias, we hypothesized that CMML and aged hematopoiesis may be closely related. We initially established the somatic mutation landscape of CMML by whole exome sequencing followed by gene-targeted validation. Genes mutated in ⩾10% of patients were SRSF2, TET2, ASXL1, RUNX1, SETBP1, KRAS, EZH2, CBL and NRAS, as well as the novel CMML genes FAT4, ARIH1, DNAH2 and CSMD1. Most CMML patients (71%) had mutations in ⩾2 ARCH genes and 52% had ⩾7 mutations overall. Higher mutation burden was associated with shorter survival. Age-adjusted population incidence and reported ARCH mutation rates are consistent with a model in which clinical CMML ensues when a sufficient number of stochastically acquired age-related mutations has accumulated, suggesting that CMML represents the leukemic conversion of the myelomonocytic-lineage-biased aged hematopoietic system.
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113
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Yao X, Yan D, Zeng H, Liu D, Li H. 215P Concurrent sorafenib therapy extends the interval to subsequent TACE for patients with unresectable hepatocellular carcinoma. Ann Oncol 2015. [DOI: 10.1093/annonc/mdv523.76] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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114
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Yan D, Dou QL, Wang Z, Wei YY. Establishment of a hepatocyte steatosis model using Chang liver cells. GENETICS AND MOLECULAR RESEARCH 2015; 14:15224-32. [PMID: 26634485 DOI: 10.4238/2015.november.25.10] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
The objective of this study was to explore the experimental conditions for hepatocellular steatosis models of Chang liver cells induced by oleic acid (OA). For that, Chang liver cells were induced by different concentrations of OA for different periods. The MTT assay was used to detect hepatic cell activity, the Oil Red O staining was used to observe intracellular lipid droplets accumulation, and the glycerol phosphate oxidase method was used to detect the triglyceride (TG) content in the Chang liver cell. The hepatocellular steatosis models of Chang liver cell were established successfully by inducing with 0.2 mM OA for 24h. TG content in model cells was 379.98 ± 23.19 mg/g, which is significantly different from control cells (185.03 ± 12.68 mg/g; P < 0.01). These were considered proper conditions for establishing hepatocellular steatosis models of Chang liver cells, producing a reliable model for nonalcoholic fatty liver disease research.
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115
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Grills I, Johnson M, Sura K, Ye H, Wloch J, Prausa S, Gustafson G, Yan D. Advanced Radiation Therapy (RT) Planning and Delivery Methods Impact Survival in Locally Advanced (LA) NSCLC. Int J Radiat Oncol Biol Phys 2015. [DOI: 10.1016/j.ijrobp.2015.07.1594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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116
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Blas K, Brown M, Wallace M, Tonlaar N, Stone B, Chen P, Gustafson G, Brabbins D, Yan D, Ye H, Krauss D. A Matched Comparison of High-Risk Prostate Cancer Patients Treated With Dose-Escalated, Image Guided Adaptive External Beam Radiation Therapy (EBRT) Versus Pelvic EBRT Plus High-Dose-Rate Brachytherapy Boost. Int J Radiat Oncol Biol Phys 2015. [DOI: 10.1016/j.ijrobp.2015.07.290] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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117
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Chen J, Bai M, Ning C, Xie B, Zhang J, Liao H, Xiong J, Tao X, Yan D, Xi X, Chen X, Yu Y, Bast RC, Zhang Z, Feng Y, Zheng W. Gankyrin facilitates follicle-stimulating hormone-driven ovarian cancer cell proliferation through the PI3K/AKT/HIF-1α/cyclin D1 pathway. Oncogene 2015; 35:2506-17. [PMID: 26364616 DOI: 10.1038/onc.2015.316] [Citation(s) in RCA: 76] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2015] [Revised: 06/04/2015] [Accepted: 07/21/2015] [Indexed: 12/20/2022]
Abstract
Gankyrin is a regulatory subunit of the 26kD proteasome complex. As a novel oncoprotein, gankyrin is expressed aberrantly in cancers from several different sites and has been shown to contribute to oncogenesis in endometrial and cervical carcinomas. Neither gankyrin's contribution to the development of epithelial ovarian cancer nor its interaction with follicle-stimulating hormone (FSH)-driven proliferation in ovarian cancer has been studied. Here we have found that gankyrin is overexpressed in ovarian cancers compared with benign ovarian cystadenomas and that gankyrin regulates FSH upregulation of cyclin D1. Importantly, gankyrin regulates PI3K/AKT signaling by downregulating PTEN. Prolonged AKT activation by FSH stimulation of the FSH receptor (FSHR) promotes gankyrin expression, which, in turn, enhances AKT activation by inhibiting PTEN. Overexpression of gankyrin decreases hypoxia inducible factor-1α (HIF-1α) protein levels, but has little effect on HIF-1α mRNA levels, which could be attributed to gankyrin mediating HIF-1α protein stability via the ubiquitin-proteasome pathway. Reduction in HIF-1α protein stability led to attenuation of the binding with cyclin D1 promoter, resulted in abolishment of the negative regulation of cyclin D1 by HIF-1α, which promotes proliferation of ovarian cancer cells. Our results document that gankyrin regulates HIF-1α protein stability and cyclin D1 expression, ultimately mediating FSH-driven ovarian cancer cell proliferation.
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118
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Troeller A, Soehn M, Grills I, Guckenberger M, Belderbos J, Sonke J, Hope A, Werner-Wasik M, Xiao Y, Yan D. TH-AB-304-06: Investigation of Fractionation Issues in NTCP Modeling of Pneumonitis: An Analysis of Common NTCP Models for Hypo-Fractionated and Standard-Fractionated Data. Med Phys 2015. [DOI: 10.1118/1.4926121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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119
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Sandhu R, Qin A, Yan D. SU-E-J-67: Evaluation of Adaptive MLC Morphing for Online Correction of Prostate Cancer Radiotherapy. Med Phys 2015. [DOI: 10.1118/1.4924154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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120
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Rogers R, Eastham-Anderson J, DeVoss J, Lesch J, Yan D, Xu M, Solon M, Hotzel K, Diehl L, Webster JD. Image Analysis-Based Approaches for Scoring Mouse Models of Colitis. Vet Pathol 2015; 53:200-10. [DOI: 10.1177/0300985815579998] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Mouse models of inflammatory bowel disease are critical for basic and translational research that is advancing the understanding and treatment of this disease. Assessment of these mouse models frequently relies on histologic endpoints. In recent years, whole slide imaging and digital pathology-based image analysis platforms have become increasingly available for implementation into the pathology workflow. These automated image analysis approaches allow for nonbiased quantitative assessment of histologic endpoints. In this study, the authors sought to develop an image analysis workflow using a commercially available image analysis platform that requires minimal training in image analysis or programming, and this workflow was used to score 2 mouse models of colitis that are primarily characterized by immune cell infiltrates in the lamina propria. Although the software was unable to accurately and consistently segment hematoxylin and eosin–stained sections, automated quantification of CD3 immunolabeling resulted in strong correlations with the pathologist’s score in all studies and allowed for the identification of 8 of the 9 differences among treatment groups that were identified by the pathologist. These results demonstrate not only the ability to incorporate solutions based on image analysis into the pathologist’s workflow but also the importance of immunohistochemical or histochemical surrogates for the incorporation of image analysis in histologic assessments.
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121
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Pore D, Bodo J, Danda A, Yan D, Phillips JG, Lindner D, Hill BT, Smith MR, Hsi ED, Gupta N. Identification of Ezrin-Radixin-Moesin proteins as novel regulators of pathogenic B-cell receptor signaling and tumor growth in diffuse large B-cell lymphoma. Leukemia 2015; 29:1857-67. [PMID: 25801911 PMCID: PMC4558318 DOI: 10.1038/leu.2015.86] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2014] [Revised: 03/18/2015] [Accepted: 03/19/2015] [Indexed: 02/07/2023]
Abstract
Diffuse large B-cell lymphoma (DLBCL) is a hematological cancer associated with an aggressive clinical course. The predominant subtypes of DLBCL display features of chronic or tonic B-cell antigen receptor (BCR) signaling. However, it is not known whether the spatial organization of the BCR contributes to the regulation of pro-survival signaling pathways and cell growth. Here, we show that primary DLBCL tumors and patient-derived DLBCL cell lines contain high levels of phosphorylated Ezrin-Radixin-Moesin (ERM) proteins. The surface BCRs in both activated B cell and germinal B cell subtype DLBCL cells co-segregate with phosphoERM suggesting that the cytoskeletal network may support localized BCR signaling and contribute to pathogenesis. Indeed, ablation of membrane-cytoskeletal linkages by dominant-negative mutants, pharmacological inhibition and knockdown of ERM proteins disrupted cell surface BCR organization, inhibited proximal and distal BCR signaling, and reduced the growth of DLBCL cell lines. In vivo administration of the ezrin inhibitor retarded the growth of DLBCL tumor xenografts, concomitant with reduction in intratumor phosphoERM levels, dampened pro-survival signaling and induction of apoptosis. Our results reveal a novel ERM-based spatial mechanism that is coopted by DLBCL cells to sustain tumor cell growth and survival.
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122
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Jawad M, Vance S, Grills I, Ye H, Prausa S, Wloch J, Yan D. Variability of Interfraction Target Motion During Conventional and Hypofractionated Lung Radiation Therapy. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.08.182] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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123
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Zamdborg L, Jawad M, Wobb J, Pietron A, Benedetti L, Dilworth J, Yan D, Grills I. Dosimetric Predictors of Cosmesis in Whole-Breast Irradiation: A Novel Clinically Applicable Constraint. Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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124
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Zhou J, Jawad M, Harb J, Yee S, Yan D, Grills I. Quantifying Follow-up T2-weighted MR Image in Local Failure Spinal Tumors after Stereotactic Body Radiation Therapy (SBRT). Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.079] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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125
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Troeller A, Söhn M, Grills I, Ionascu D, Guckenberger M, Klement R, Belderbos J, Sonke J, Hope A, Bissonnette J, Werner-Wasik M, Xiao Y, Yan D. Are Lung NTCP Models Different In Hypofractionated And Standard Fractionated Radiotherapy? Int J Radiat Oncol Biol Phys 2014. [DOI: 10.1016/j.ijrobp.2014.05.162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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