Genetic mutations in human rectal cancers detected by targeted sequencing.

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.

Non-soluble antibacterial polyurethane based on cation mechanism and functionalized by chitosan and heparin azide.

Nowadays, medical polyurethanes with favorable and durable antibacterial properties received more attention, because of avoiding repeated replacement of interventional materials and reducing patients' pain. In this thesis, non-soluble antibacterial polyurethane (NAPU) based on cation antibacterial mechanism was prepared by photo-grafting chitosan azide and heparin azide into polyurethane (PU). -NH3+of chitosan azide absorbed bacteria, inhibiting and breaking their mobility and structures. Heparin azide prevented cations from penetrating bacteria's membranes and inhibited their growth. The results showed that chitosan azide and heparin azide were successfully grafted into PU. The highest antibacterial rate was 92.07%, cytotoxicity grade ranging from 0-1 (RGR standard) and water contact angle exhibiting 60°, attributing to cation antibacterial effect and -OH existing. Tensile strength was up to 23.91 MPa and was suitable for using as medical materials. NAPU with long-lasting coating both possessed antibacterial properties and persistence, which can solve the problem of medical catheters' long-term using.

[Research and application of supply catalog and encoding identification technology applied to medical consumable materials management].

In this article, medical consumable materials supply catalog technology was introduced through the principle, method and application of topic studies, at the same time bar code tags to tag and identify medical consumable materials were introduced. These two techniques established the correspondence between the real supplies logistics and information flow system, provided foundation for medical supplies all process tracking and traceability management. Supply catalog and encoding identification technology provide a new solution for the effective management of medical consumable materials.

A machine learning prediction model for cancer risk in patients with type 2 diabetes based on clinical tests.

BACKGROUND: The incidence of type 2 diabetes is rapidly increasing worldwide. Studies have shown that it is also associated with cancer-related morbidities. Early detection of cancer in patients with type 2 diabetes is crucial. OBJECTIVE: This study aimed to construct a model to predict cancer risk in patients with type 2 diabetes. METHODS: This study collected clinical data from a total of 5198 patients. A cancer risk prediction model was established by analyzing 261 items from routine laboratory tests. We screened 107 risk factors from 261 clinical tests based on the importance of the characteristic variables, significance of differences between groups (P< 0.05), and minimum description length algorithm. RESULTS: Compared with 16 machine learning classifiers, five classifiers based on the decision tree algorithm (CatBoost, light gradient boosting, random forest, XGBoost, and gradient boosting) had an area under the receiver operating characteristic curve (AUC) of > 0.80. The AUC for CatBoost was 0.852 (sensitivity: 79.6%; specificity: 83.2%). CONCLUSION: The constructed model can predict the risk of cancer in patients with type 2 diabetes based on tumor biomarkers and routine tests using machine learning algorithms. This is helpful for early cancer risk screening and prevention to improve patient outcomes.

[The management of the virtual secondary library for medical consumables and its systematic application and development].

In order to improve of the flow control and flow supervision in the use of medical consumables, from administrative organizing to network management software designing, a scientific and rational approach to equipment use and management was explored which established the management mode of virtual secondary library for the medical equipment to achieve the combination of macro-control and provision practice.

A MAP3k1 SNP predicts survival of gastric cancer in a Chinese population.

OBJECTIVES: Genome-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. METHODS: We 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. RESULTS: Our 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. CONCLUSIONS: In 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.

PIK3CA and TP53 gene mutations in human breast cancer tumors frequently detected by ion torrent DNA sequencing.

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.