BackgroundAlthough gastric cancer is a malignancy with high morbidity and mortality in China, the survival rate of patients with early gastric cancer (EGC) is high after surgical resection. To strengthen diagnosing and screening is the key to improve the survival and life quality of patients with EGC. This study applied data mining methods to improve screening for the risk of EGC on the basis of noninvasive factors, and displayed important influence factors for the risk of EGC.MethodsThe dataset was derived from a project of the First Hospital Affiliated Guangdong Pharmaceutical University. A series of questionnaire surveys, serological examinations and endoscopy plus pathology biopsy were conducted in 618 patients with gastric diseases. Their risk of EGC was categorized into low and high risk of EGC by the results of endoscopy plus pathology biopsy. The synthetic minority oversampling technique (SMOTE) was used to solve imbalance categories of the risk of EGC. Four classification models of the risk of EGC was established, including logistic regression (LR) and three data mining algorithms.ResultsThe three data mining models had higher accuracy than the LR model. Gain curves of the three data mining models were convexes more closer to ideal curves by contrast with that of the LR model. AUC of the three data mining models were larger than that of the LR model as well. The three data mining models predicted the risk of EGC more effectively in comparison with the LR model. Moreover, this study found 16 important influence factors for the risk of EGC, such as occupations, helicobacter pylori infection, drinking hot water and so on.ConclusionsThe three data mining models have optimal predictive behaviors over the LR model, therefore can effectively evaluate the risk of EGC and assist clinicians in improving the diagnosis and screening of EGC. Sixteen important influence factors for the risk of EGC were illustrated, which may helpfully assess gastric carcinogenesis, and remind to early prevention and early detection of gastric cancer. This study may also be conducive to clinical researchers in selecting and conducting the optimal predictive models.

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Twenty C-7 modified flavonoids were designed and synthesized. Biological evaluation in vitro indicated that compounds generated by SYBYL-X with high scores also showed good inhibitory activities against TyrRS.Compounds containing the nargenin core exhibit better enzyme inhibitory activities than other flavonoid cores, with (S)-5-hydroxy-4 0 -hydroxy-7-(2-morpholino-2-oxoethoxy)-2,3-dihydroflavone (b1) being the most active (IC 50 ¼ 0.10 AE 0.01 mM) in all assayed compounds. All compounds were also assayed for antimicrobial activities against Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa, and b1 also displayed excellent activity, showing 6-fold more potent than the marketed antibiotic ciprofloxacin. In comparison with Gram-positive organism, all these derivatives exhibited better activity against Gram-negative organism, and did not displayed significant differences between the two assayed Gram-negative strains (E. coli ATCC 8739 and P. aeruginosa ATCC 9027). Fig. 2 Scaffold hopping and library design. Superpositions of tyrosyl adenylate (white) with a 7-O-graft flavonoid derivative (light purple) and 5-O-graft flavonoid derivative (light brown) generated by Surflex Sim suite of SYBYL-X 2.1.1. 6194 | RSC Adv., 2017, 7, 6193-6201 This journal is

Nickel (Ni) is ubiquitous in the environment and evidence has suggested that Ni can cause ocular surface inflammation, especially in fine particulate matter and personal products. Continuous daily exposure to Ni-containing dust may adversely impact the human cornea, whereas the underlying mechanism of this phenomenon remains not fully understood. Here, human corneal epithelial cells (HCEC) were employed to analyze the toxicity of Ni via detections of cell morphology, cell viability, reactive oxygen species production, cell apoptosis rate, and apoptotic gene expression levels after exposure for 24 h to uncover the damage of Ni to the cornea. A concentration-dependent inhibition of HCECs’ viability and growth was observed. In particular, Ni at 100 μM significantly decreased cell viability to 76%, and many cells displayed an abnormal shape and even induced oxidative damage of HCEC by increasing ROS to 1.2 times, and further led to higher apoptosis (24%), evidenced by up-regulation of apoptotic genes Caspase-8, Caspase-9, NF-κB, IL-1β, and Caspase-3, posing a risk of dry eye. Our study suggested that Ni induces apoptosis of HCEC through oxidative damage. Therefore, Ni pollution should be comprehensively considered in health risks or toxic effects on the ocular surface.