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Recent sequencing studies of clear cell (conventional) renal cell carcinoma (ccRCC) have identified inactivating point mutations in the chromatin-modifying genes PBRM1, KDM6A/UTX, KDM5C/JARID1C, SETD2, MLL2 and BAP1. To investigate whether aberrant hypermethylation is a mechanism of inactivation of these tumor suppressor genes in ccRCC, we sequenced the promoter region within a bona fide CpG island of PBRM1, KDM6A, SETD2 and BAP1 in bisulfite-modified DNA of a representative series of 50 primary ccRCC, 4 normal renal parenchyma specimens and 5 RCC cell lines. We also interrogated the promoter methylation status of KDM5C and ARID1A in the Cancer Genome Atlas (TCGA) ccRCC Infinium data set. PBRM1, KDM6A, SETD2 and BAP1 were unmethylated in all tumor and normal specimens. KDM5C and ARID1A were unmethylated in the TCGA 219 ccRCC and 119 adjacent normal specimens. Aberrant promoter hypermethylation of PBRM1, BAP1 and the other chromatin-modifying genes examined here is therefore absent or rare in ccRCC.  相似文献   
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Feature selection (FS) is a real-world problem that can be solved using optimization techniques. These techniques proposed solutions to make a predictive model, which minimizes the classifier's prediction errors by selecting informative or important features by discarding redundant, noisy, and irrelevant attributes in the original dataset. A new hybrid feature selection method is proposed using the Sine Cosine Algorithm (SCA) and Genetic Algorithm (GA), called SCAGA. Typically, optimization methods have two main search strategies; exploration of the search space and exploitation to determine the optimal solution. The proposed SCAGA resulted in better performance when balancing between exploitation and exploration strategies of the search space. The proposed SCAGA has also been evaluated using the following evaluation criteria: classification accuracy, worst fitness, mean fitness, best fitness, the average number of features, and standard deviation. Moreover, the maximum accuracy of a classification and the minimal features were obtained in the results. The results were also compared with a basic Sine Cosine Algorithm (SCA) and other related approaches published in literature such as Ant Lion Optimization and Particle Swarm Optimization. The comparison showed that the obtained results from the SCAGA method were the best overall the tested datasets from the UCI machine learning repository.

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The incidence of rebleeding was studied prospectively in 177 patients with acute gastrointestinal haemorrhage from peptic ulceration with reference to the degree of haemodynamic insult on admission and the presence of endoscopic signs of recent haemorrhage on initial endoscopy. Rebleeding occurred in two (2%) of 114 patients without shock, in seven (18%) of 38 with tachycardia (pulse rate greater than 100 beats/min, systolic blood pressure greater than 100 mm Hg), and in 12 (48%) of 25 with shock (systolic blood pressure less than 100 mm Hg). A similar gradient was noted with the presence of endoscopic signs alone. Rebleeding occurred in four (5%) of 79 patients with no endoscopic signs, in none of 40 with black spot only, in 11 (23%) of 48 with a clot, and in five (50%) of 10 with a visible vessel on endoscopy. When the incidence of rebleeding was assessed in shocked patients, however, it was significantly higher in those with important signs (clot or visible vessel), in 11 (79%) out of 14 patients, than in those with no signs, in one (9%) out of 11 (p less than 0.001). These data suggest that the association of shock with important endoscopic signs is a stronger predictor of rebleeding than either shock or important signs alone. More aggressive treatment may be warranted in this small group of patients.  相似文献   
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