Evaluation Systems for Clinical Governance Development: a Comparative Study by Elaheh Hooshmand, Sogand Tourani, Hamid Ravaghi, Hossein Ebrahimipour

“…The evaluated models of clinical governance development were Australian, NHS, SPOCK and OPTIGOV. The final aspects extracted from these models were Responsiveness, Policies and Strategies, Organizational Structure, Allocating Resources, Education and Occupational Development, Performance Evaluation, External Evaluation, Patient Oriented Approach, Risk Management, Personnel's Participation, Information Technology, Human Resources, Research and Development, Evidence Based Medicine, Clinical Audit, Health Technology Assessment and Quality. …”
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Whole-genome analysis of temporal gene expression during early transdifferentiation of human lung alveolar epithelial type 2 cells in vitro. by Helena Morales Johansson, Donna R Newman, Philip L Sannes

“…Selected novel genes further validated by qRT-PCR, protein expression analysis, and/or cellular localization included SPOCK2, PLEKHO1, SPRED1, RAB11FIP1, PTRF/CAVIN-1 and RAP1GAP. …”
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Molecular Mechanisms Underlying the Progression of Aortic Valve Stenosis: Bioinformatic Analysis of Signal Pathways and Hub Genes by Taiki Tojo, Minako Yamaoka-Tojo

“…PPI network analysis identified 10 hub genes: <i>VCAM1</i>, <i>FHL2</i>, <i>RUNX1</i>, <i>TNFSF10</i>, <i>PLAU</i>, <i>SPOCK1</i>, <i>CD74</i>, <i>SIPA1L2</i>, <i>TRIB1</i>, and <i>CXCL12</i>. …”
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Aromatic amino acid metabolites alter interferon signaling and influenza pathogenesis by Gautam Anand, Colin Clark-Dinovo, Alexandra M. Perry, Victoria M. Goodwin, Emma St. Raymond, Sonia Sakleshpur, Ashley L. Steed

“…Single gene silencing of significantly upregulated genes identified by RNA sequencing (EGR2, ATP6VD02, SPOCK1, and IL31RA) did not completely abrogate the metabolite induced decrease in IFN signaling. …”
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<i>PLEK2</i>, <i>RRM2</i>, <i>GCSH</i>: A Novel <i>WWOX</i>-Dependent Biomarker Triad of Glioblastoma at the Crossroads of Cytoskeleton Reorganization and Metabolism Alterations by Żaneta Kałuzińska, Damian Kołat, Andrzej K. Bednarek, Elżbieta Płuciennik

“…Other genes important in the context of cytoskeleton (<i>BMP4, CCL11, CUX2, DUSP7, FAM92B, GRIN2B, HOXA1, HOXA10, KIF20A, NF2, SPOCK1, TTR, UHRF1,</i> and <i>WT1</i>), metabolism (<i>MTHFD2</i>), or correlation with <i>WWOX</i> (<i>COL3A1, KIF20A, RNF141,</i> and <i>RXRG</i>) were also discovered. …”
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Epigenetic analysis in placentas from sickle cell disease patients reveals a hypermethylation profile by Gislene Pereira Gil, Galina Ananina, Mariana Maschietto, Sheila Coelho Soares Lima, Sueli Matilde da Silva Costa, Leticia de Carvalho Baptista, Mirta Tomie Ito, Fernando Ferreira Costa, Maria Laura Costa, Mônica Barbosa de Melo

“…The gene expression analysis showed differential expression for the PTGFR (-2.97-fold) and GPR56 (3.0-fold) genes in the HbSS group, and for the SPOCK1 (-2.40-fold) and ADCY4 (1.80-fold) genes in the HbSC group. …”
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Proximity extension assay testing reveals novel diagnostic biomarkers of atypical parkinsonian syndromes by Jabbari, E, Woodside, J, Guo, T, Magdalinou, N, Chelban, V, Athauda, D, Lees, A, Foltynie, T, Houlden, H, Church, A, Hu, M, Rowe, J, Zetterberg, H, Morris, H

“…Disease-specific analyses revealed lower group levels of FGF-5, FGF-19 and SPOCK1 in multiple system atrophy compared with progressive supranuclear palsy and corticobasal syndrome. …”

Genome-wide identification of potential odontogenic genes involved in the dental epithelium-mesenchymal interaction during early odontogenesis by Jiawen Chen, Tianyu Sun, Yan You, Binbin Lin, Buling Wu, Jingyi Wu

“…In addition, 9 proteoglycans showed dynamic expression changes between these two tissue compartments. Gpc4, Sdc2, Spock2, Dcn and Lum were expressed at higher levels in the dental epithelium at E11.5, whereas their expression was significantly higher in the dental mesenchyme at E13.5, which coincides with the odontogenic potential shift. …”
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Epigenetic analysis in placentas from sickle cell disease patients reveals a hypermethylation profile. by Gislene Pereira Gil, Galina Ananina, Mariana Maschietto, Sheila Coelho Soares Lima, Sueli Matilde da Silva Costa, Leticia de Carvalho Baptista, Mirta Tomie Ito, Fernando Ferreira Costa, Maria Laura Costa, Mônica Barbosa de Melo

“…The gene expression analysis showed differential expression for the PTGFR (-2.97-fold) and GPR56 (3.0-fold) genes in the HbSS group, and for the SPOCK1 (-2.40-fold) and ADCY4 (1.80-fold) genes in the HbSC group. …”
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Bioinformatics-based analysis of the roles of basement membrane-related gene AGRN in systemic lupus erythematosus and pan-cancer development by Rundong Lv, Lei Duan, Jie Gao, Jigang Si, Chen Feng, Jun Hu, Xiulan Zheng, Xiulan Zheng

“…Finally, we sourced pan-cancer expression profiles from the TCGA and GTEx databases and performed pan-cancer analysis.ResultsWe screened six feature genes (AGRN, PHF13, SPOCK2, TGFBI, COL4A3, and COLQ) to construct an SLE diagnostic model. …”
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A protein complex of LCN2, LOXL2 and MMP9 facilitates tumour metastasis in oesophageal cancer by Qiaoxi Xia, Zepeng Du, Mantong Chen, Xiao Zhou, Wenjing Bai, Xiaoqi Zheng, Ling Lin, Yan Zhao, Jiyu Ding, Zhisheng Wu, Haiying Zou, Shaohong Wang, Liyan Xu, Enmin Li, Bingli Wu

“…In addition, the LCN2/LOXL2/MMP9 ternary complex promoted the expression of testican‐1 (SPOCK1), and abnormally activated the FAK/AKT/GSK3β signalling pathway. …”
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Integrated analysis of plasma proteome and cortex single-cell transcriptome reveals the novel biomarkers during cortical aging by Rui-Ze Niu, Wan-Qing Feng, Qing-Shan Yu, Lan-Lan Shi, Qing-Min Qin, Jia Liu

“…Afterward, plasma proteomics data from 2,925 plasma proteins across 4,263 young adults to nonagenarians (18–95 years old) were combined with the outcomes from snRNA-seq data to obtain 12 differential genes/proteins (GPC5, CA10, DGKB, ST6GALNAC5, DSCAM, IL1RAPL2, TMEM132C, VCAN, APOE, PYH1R, CNTN2, SPOCK3). Finally, we verified the 12 differential genes by ELISA and found that the expression trends of five biomarkers (DSCAM, CNTN2, IL1RAPL2, CA10, GPC5) were correlated with brain aging.ConclusionFive differentially expressed proteins (DSCAM, CNTN2, IL1RAPL2, CA10, GPC5) can be considered as one of the screening indicators of brain aging, and provide a scientific basis for clinical diagnosis and intervention.…”
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miR-124 as a Liquid Biopsy Prognostic Biomarker in Small Extracellular Vesicles from NSCLC Patients by Darío Sanchez-Cabrero, Álvaro Garcia-Guede, Miranda Burdiel, Olga Pernía, Julián Colmenarejo-Fernandez, Laura Gutierrez, Oliver Higuera, Isabel Esteban Rodriguez, Rocío Rosas-Alonso, Carlos Rodriguez-Antolín, Itsaso Losantos-García, Olga Vera, Javier De Castro-Carpeño, Inmaculada Ibanez de Caceres

“…Our bioinformatics approach identified KPNA4 and SPOCK1 as potential miR-124 targets in NSCLC. miR-124 levels can be used to identify early-stage NSCLC patients at higher risk of relapse.…”
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Colorectal Cancer Early Detection in Stool Samples Tracing CpG Islands Methylation Alterations Affecting Gene Expression by Ana Florencia Vega-Benedetti, Eleonora Loi, Loredana Moi, Sandra Orrù, Pina Ziranu, Andrea Pretta, Eleonora Lai, Marco Puzzoni, Letizia Ciccone, Andrea Casadei-Gardini, Francesco Cabras, Federica Fortunato, Angelo Restivo, Luigi Zorcolo, Mario Scartozzi, Patrizia Zavattari

“…Furthermore, we analysed expression levels of selected genes whose promoter CGIs were hypermethylated in CRC, detecting downregulation at mRNA and protein levels in CRC tissue for GRIA4, VIPR2, SPOCK1 and SLC6A3. Most of these genes were already lowly expressed in colon normal tissues supporting the idea that cancer DNA methylation targets genes already barely expressed in the matched normal tissues. …”
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Identification of candidate genes of intellectual disability by single-gene deletions/amplifications mapping using chromosomal microarray analysis by A. Kashevarova, M. Lopatkina, E. Belyaeva, D. Fedotov, G. Drozdov, L. Nazarenko, I. Lebedev

“…Single-gene aberrations involving the AGBL4 (exon 2), ASMT (exon 9), CYP2C18 (whole gene), DDX10 (promoter, exons 1-13), GYPA (whole gene), LIG4 (exon 1), LSAMP (intron 1), PSD3 (promoter, exons 1-11), SNTB1 (intron 1), SPOCK3 (exons 6-12), STAG2 (exons 7-34), SYT10 (promoter, exons 1-2), TCAF2 (exon 8), TMPRSS15 (promoter, exons 1-12), and ZDHHC7 (promoter, exons 1-4) genes were described by us for the first time. …”
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The Gene Expression Landscape of Prostate Cancer BM Reveals Close Interaction with the Bone Microenvironment by Alireza Saraji, Kang Duan, Christian Watermann, Katharina Hempel, Marie C. Roesch, Rosemarie Krupar, Janine Stegmann-Frehse, Danny Jonigk, Mark Philipp Kuehnel, Wolfram Klapper, Axel S. Merseburger, Jutta Kirfel, Sven Perner, Anne Offermann, Verena Sailer

“…The most significant DEGs include <i>CD36</i>, <i>FOXC2</i>, <i>CHAD</i>, <i>SPP1</i>, <i>MMPs</i>, <i>IBSP</i>, and <i>PTX3</i>, which are more highly expressed in BM, and <i>ACTG2</i>, <i>MYH11</i>, <i>CNN1</i>, <i>FGF2</i>, <i>SPOCK3</i>, and <i>CHRDL1</i>, which have a lower expression. …”
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Dynamic Interplay in Tumor Ecosystems: Communication between Hepatoma Cells and Fibroblasts by Gábor Petővári, Gábor Tóth, Lilla Turiák, Anna L. Kiss, Krisztina Pálóczi, Anna Sebestyén, Adrián Pesti, András Kiss, Kornélia Baghy, Katalin Dezső, Tibor Füle, Péter Tátrai, Ilona Kovalszky, Andrea Reszegi

“…LX2-derived EVs induced over tenfold upregulation of SPOCK1/testican-1 in hepatoma EV cargo. We also identified liver cancer-specific miRNAs in hepatoma EVs, with potential implications for early diagnosis. …”
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Identification of biomarkers for glycaemic deterioration in type 2 diabetes by Slieker, Roderick C., Donnelly, Louise A., Akalestou, Elina, Lopez-Noriega, Livia, Melhem, Rana, Güneş, Ayşim, Azar, Frederic Abou, Efanov, Alexander, Georgiadou, Eleni, Muniangi-Muhitu, Hermine, Sheikh, Mahsa, Giordano, Giuseppe N., Åkerlund, Mikael, Ahlqvist, Emma, Ali, Ashfaq, Banasik, Karina, Brunak, Søren, Barovic, Marko, Bouland, Gerard A., Burdet, Frédéric, Canouil, Mickaël, Dragan, Iulian, Elders, Petra J. M., Fernandez, Celine, Festa, Andreas, Fitipaldi, Hugo, Froguel, Phillippe, Gudmundsdottir, Valborg, Gudnason, Vilmundur, Gerl, Mathias J., van der Heijden, Amber A., Jennings, Lori L., Hansen, Michael K., Kim, Min, Leclerc, Isabelle, Klose, Christian, Kuznetsov, Dmitry, Aly, Dina Mansour, Mehl, Florence, Marek, Diana, Melander, Olle, Niknejad, Anne, Ottosson, Filip, Pavo, Imre, Duffin, Kevin, Syed, Samreen K., Shaw, Janice L., Cabrera, Over, Pullen, Timothy J., Simons, Kai, Solimena, Michele, Suvitaival, Tommi, Wretlind, Asger, Rossing, Peter, Lyssenko, Valeriya, Quigley, Cristina Legido, Groop, Leif, Thorens, Bernard, Franks, Paul W., Lim, Gareth E., Estall, Jennifer, Ibberson, Mark, Beulens, Joline W. J., Hart, Leen M. 't, Pearson, Ewan R., Rutter, Guy A.

“…Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. …”
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Identification of biomarkers for glycaemic deterioration in type 2 diabetes by Roderick C. Slieker, Louise A. Donnelly, Elina Akalestou, Livia Lopez-Noriega, Rana Melhem, Ayşim Güneş, Frederic Abou Azar, Alexander Efanov, Eleni Georgiadou, Hermine Muniangi-Muhitu, Mahsa Sheikh, Giuseppe N. Giordano, Mikael Åkerlund, Emma Ahlqvist, Ashfaq Ali, Karina Banasik, Søren Brunak, Marko Barovic, Gerard A. Bouland, Frédéric Burdet, Mickaël Canouil, Iulian Dragan, Petra J. M. Elders, Celine Fernandez, Andreas Festa, Hugo Fitipaldi, Phillippe Froguel, Valborg Gudmundsdottir, Vilmundur Gudnason, Mathias J. Gerl, Amber A. van der Heijden, Lori L. Jennings, Michael K. Hansen, Min Kim, Isabelle Leclerc, Christian Klose, Dmitry Kuznetsov, Dina Mansour Aly, Florence Mehl, Diana Marek, Olle Melander, Anne Niknejad, Filip Ottosson, Imre Pavo, Kevin Duffin, Samreen K. Syed, Janice L. Shaw, Over Cabrera, Timothy J. Pullen, Kai Simons, Michele Solimena, Tommi Suvitaival, Asger Wretlind, Peter Rossing, Valeriya Lyssenko, Cristina Legido Quigley, Leif Groop, Bernard Thorens, Paul W. Franks, Gareth E. Lim, Jennifer Estall, Mark Ibberson, Joline W. J. Beulens, Leen M ’t Hart, Ewan R. Pearson, Guy A. Rutter

“…Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. …”
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