Breast cancer is the most common malignancy and the leading cause of cancer deaths in women worldwide. While specific genetic mutations have been linked to 5–10% of breast cancer cases, other environmental and epigenetic factors influence the development and progression of the cancer. Since unique mutations patterns have been observed in individual cancer samples, identification and characterization of the distinctive breast cancer molecular profile is needed to develop more effective target therapies. Until recently, identifying genetic cancer mutations via personalized DNA sequencing was impractical and expensive. The recent technological advancements in next-generation DNA sequencing, such as the semiconductor-based Ion Torrent sequencing platform, has made DNA sequencing cost and time effective with more reliable results. Using the Ion Torrent Ampliseq Cancer Panel, we sequenced 737 loci from 45 cancer-related genes to identify genetic mutations in 105 human breast cancer samples. The sequencing analysis revealed missense mutations in PIK3CA, and TP53 genes in the breast cancer samples of various histologic types. Thus, this study demonstrates the necessity of sequencing individual human cancers in order to develop personalized drugs or combination therapies to effectively target individual, breast cancer-specific mutations.

Colorectal cancer (CRC) is widespread with significant mortality. Both inherited and sporadic mutations in various signaling pathways influence the development and progression of the cancer. Identifying genetic mutations in CRC is important for optimal patient treatment and many approaches currently exist to uncover these mutations, including next-generation sequencing (NGS) and commercially available kits. In the present study, we used a semiconductor-based targeted DNA-sequencing approach to sequence and identify genetic mutations in 91 human rectal cancer samples. Analysis revealed frequent mutations in KRAS (58.2%), TP53 (28.6%), APC (16.5%), FBXW7 (9.9%) and PIK3CA (9.9%), and additional mutations in BRAF, CTNNB1, ERBB2 and SMAD4 were also detected at lesser frequencies. Thirty-eight samples (41.8%) also contained two or more mutations, with common combination mutations occurring between KRAS and TP53 (42.1%), and KRAS and APC (31.6%). DNA sequencing for individual cancers is of clinical importance for targeted drug therapy and the advantages of such targeted gene sequencing over other NGS platforms or commercially available kits in sensitivity, cost and time effectiveness may aid clinicians in treating CRC patients in the near future.

ObjectivesGenome-wide association studies (GWAS) have demonstrated that the single nucleotide polymorphism (SNP) MAP3K1 rs889312 is a genetic susceptibility marker significantly associated with a risk of hormone-related tumors such as breast cancer. Considering steroid hormone-mediated signaling pathways have an important role in the progression of gastric cancer, we hypothesized that MAP3K1 rs889312 may be associated with survival outcomes in gastric cancer. The purpose of this study was to test this hypothesis.MethodsWe genotyped MAP3K1 rs889312 using TaqMan in 884 gastric cancer patients who received subtotal or total gastrectomy. Kaplan-Meier survival analysis and Cox proportional hazard regression were used to analyze the association between MAP3K1 rs889312 genotypes and survival outcomes of gastric cancer.ResultsOur findings reveal that the rs889312 heterozygous AC genotype was significantly associated with an increased rate of mortality among patients with diffuse-type gastric cancer (log-rank P = 0.028 for AC versus AA/CC, hazard ratio [HR] = 1.32, 95% confidence interval [CI] = 1.03–1.69), compared to those carrying the homozygous variant genotypes (AA/CC). Additionally, univariate and multivariate Cox regression analysis demonstrate that rs889312 polymorphism was an independent risk factor for poor survival in these patients.ConclusionsIn conclusion, we demonstrate that MAP3K1 rs889312 is closely correlated with outcome among diffuse-type gastric cancer. This raises the possibility for rs889312 polymorphisms to be used as an independent indicator for predicting the prognosis of diffuse-type gastric cancer within the Chinese population.

Objective To explore the application value of PDCA cycle combined with intensive maintenance quality management mode in hospital medical devices maintenance management. Methods In order to improve the maintenance management level of medical devices, PDCA cycle combined with intensive maintenance quality management mode was adopted in hospital medical devices maintenance, and the management efficiency of the maintenance quality management mode was verified. Results After PDCA cycle combined with intensive maintenance quality management mode, the stain-free rate of medical device surfaces and the integrity rate of maintenance registration information were significantly improved (2=37.425,2=21.218; P<0.01), the pass rate of the first inspection was improved (2=5.684; P < 0.05). The maintenance quality satisfaction and maintenance timeliness satisfaction of medical staff to clinical medical engineers were significantly improved (t=-4.066,t=-6.902; P < 0.01). Conclusions PDCA cycle combined with intensive maintenance quality management mode can improve the quality and efficiency of maintenance service and improve the satisfaction of medical staff on maintenance service. PDCA cycle combined with intensive maintenance quality management mode is an effective method for hospital medical devices maintenance management.

This paper proposes a novel approach to monitor the depth of anesthesia by predicting the response to incision during isoflurane anaesthesia using mutual information(M1) time series of electroencephalograms(EEGs) and their complexity analysis. The MI between four lead electrodes was first computed using the EEG time series. The Lempel-Ziv complexity measures, C(i?)s, were extracted from the MI time series. Prediction was made by means of artificial neural network (ANN). Training and testing the ANN used the 'dropone-patient' method. 98 consenting patient experiments show the system was able to correctly classify purposeful response in average accuracy of 91.84% of the cases and the method has a better performance than other methods, such as spectral edge frequency, median frequency, and bispectral analysis. This method is computationally fast and acceptable real-time clinical performance was obtained.