Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Expression and biological function of rhotekin in gastric cancer through regulating p53 pathway

Meng-Yao Sun,1,* Hong Zhang,2,* Jie Tao,1 Zhen-Hua Ni,1 Qiu-Xue Wu,1 Qing-Feng Tang1 1Department of Clinical Laboratory and Central Laboratory, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200062, China; 2Center for Innovative Chinese Medicine Research, Institute of Interdisciplinary Medical Sciences, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China *These authors contributed equally to this work Background/aim: Gastric cancer (GC) is one of a most threatening cancer globally. Rhotekin (RTKN), a Rho effector, has been reported to be upregulated in GC tissues. This study aimed to investigate the underlying regulatory roles of RTKN in the biological behavior of GC. Methods: Real-time PCR and Western blotting were carried out to detect the mRNA and protein expression, respectively. Cell Counting Kit-8 and xenograft nude mice model were used to evaluate cell proliferation. Flow cytometry analysis was performed to assess cell cycle distribution and cell apoptosis. Results: RTKN had high expression level in GC compared with normal tissues. RTKN expression strongly associated with tumor size, TNM stage, lymphnode metastasis and the poor prognosis of patients with GC. Downregulation of RTKN significantly repressed GC cell proliferation, but increased cell population in G1/S phase and induced cell apoptosis. Moreover, the RTKN expression level was related to the p53 signaling pathway and histone deacetylase (HDAC) Class I pathway. RTKN knockdown caused a notable increment in the acetylation level of p53 (Lys382), and the expression of p53-target genes (p21, Bax, and PUMA), as well as a reduction in the expression of a potential deacetylase for p53, HDAC1. Notably, downregulation of HDAC1 had similar effects as RTKN knockdown, and RTKN overexpression could hardly abrogate the effects of HDAC1 knockdown on GC cells. Conclusion: RTKN could work as an oncogene via regulating HDAC1/p53 and may become a promising treatment strategy for GC. Keywords: RTKN, gastric cancer, proliferation, invasion, HDAC1/p5

Image classification-based defect detection of railway tracks using fiber Bragg grating ultrasonic sensors

202307 bcchVersion of RecordRGCOthersNational Rail Transit Electrification and Automation Engineering Technology Research Center; Innovation and Technology Commission; Science, Technology and Innovation Commission of Shenzhen MunicipalityPublishe