In this paper,the authors elaborated the difficulties of schistosomiasis control and analyzed shortages and problems of the skills currently used.In order to consolidate the progress in schistosomiasis control and reach the transmission-blocking target,research priorities on the disease control technologies are proposed.

Objective: To construct effective short hairpin RNA (shRNA) recombinant plasmids targeting humanDystrophin Dp71 gene, and evaluate their interference effciency. Methods: hTree pairs of siRNA sequences targeting human Dp71 gene and one pair of control siRNA sequence were designed, synthesized, and then inserted into the pRNAT-U6.1/Neo vector. hTe shRNA recombinant vectors were evaluated by enzyme digestion and sequencing. Dp71-shRNA and control shRNA plasmids were transfected into human normal gastric epithelial cells (GES-1) and humanbronchial epithelium (HBE). Western blot was used to evaluate its interfering effciency. Results: Restriction enzyme digestion and sequencing showed that the Dp71-shRNA vectors were successfully constructed. Western blot displayed that Dp71 protein expression was reduced to a signiifcant degree atfer transfection with the 3 Dp71-shRNA plasmids, and Dp71-shRNA2 plasmid inhibit the Dp71 expression most effciently. Conclusion: Dp71-shRNA vectors have been successfully constructed. The 3 Dp71-shRNA plasmids can inhibit Dp71 expression in GES-1 and HBEC, with Dp71-shRNA2 plasmid displaying the highest inhibition effciency.

BACKGROUND: Previous research has indicated that graphite carbon nanoparticles have a strong adsorbability. While, when the concentration is effectively controlled, graphite carbon nanoparticles also have well compatibility and sensitizing effect. OBJECTIVE: To observe the morphology of graphite carbon nanoparticles, and to investigate the effects of graphite carbon nanoparticles on cell proliferation and ultramicrostructure.METHODS: Graphite carbon nanoparticles (0.5 g) were put in 100 mL triple distilled water to obtain graphite carbon nanoparticle mother liquid after oscillation and microfiltration. HepG2 cells, L02 cells, HI7702 cells, and 3T3 cells in the logarithmic phase were adjusted to the concentration of 5×10~7/L and inoculated in 6-well culture plate with 0.5 mL per well. Thereafter, the cells were cultured with RPMI-1640 culture media (1.5 mL) containing fetal bovine serum, penicillin, and streptomycin. The original culture solution was removed after 24 hours. The 1-5 wells were considered as the experimental group, and 25, 10, 7.5, 5, 0.25 mg/Lgraphite carbon nanoparticles (2.0 mL) were respectively added into each well; while, the sixth well was considered as the blank control group without graphite carbon nanoparticles. The cells in the blank control group were cultured for 24 hours. Particle diameter was measured using atomic force microscopy; morphology was observed using electron microscope; effect of different concentrations of graphite carbon nanoparticles on cell number was detected using hemacytometry under optic microscope; the effect of 7.5 mg/L graphite carbon nanoparticles on ultramicrostructure was observed under transmission electron microscope. RESULTS AND CONCLUSION: Graphite carbon nanoparticles were around and 20 nm diameter. Compared with the blank control group, cell numbers except HepG2 cells were increased, especially the effect of 7.5 mg/L graphite carbon nanoparticles was greatest (P < 0.05). Transmission electron microscope indicated that graphite carbon nanoparticles were distributed into cells, including cytoplasm, nucleus, and mitochondrion; while, subcellular structure damage and cell apoptosis and necrosis were absent. Graphite carbon nanoparticles have no side effects on in vitro cultured cells and can promote cell proliferation, showing a dose-dependence correlation, especially the concentration of 7.5 mg/L.

Objective:To establish a radiomics-based biomarker for predicting pathological response after preoperative neoadjuvant chemoradiotherapy (nCRT) in locally advanced esophageal cancer.Methods:From 2008 to 2018, 112 patients with locally advanced esophageal cancer who received nCRT were enrolled. All patients were treated with preoperative nCRT combined with surgery. Enhanced CT images and clinical information before nCRT were collected. A lesion volume of interest was manually delineated. In total, 670 radiomics features (including tumor intensity, shape and size, texture and wavelet characteristics) were extracted using the pyradiomics package in PYTHON. The stepwise regression combined with the best subset were employed to select the features, and finally the Logistic regression model was adopted to establish the prediction model. The performance of the classifier was evaluated by the area under the ROC curve (AUC). Results:The pathological complete remission (pCR) rate was 58.0%(65/112). 10 radiomics features were included in the final model, The most relevant radiomics feature was the gray feature (the texture information of the image), followed by the shape and voxel intensity-related features. In the training set, the AUC was 0.750 with a sensitivity of 0.711 and a specificity of 0.778, the corresponding values in the testing set were 0.870, 0.757 and 0.900, respectively.Conclusions:Models based on radiomics features from CT images can be utilized to predict the pathological response to nCRT in esophageal cancer. As it is efficient, non-invasive and economic model, it could serve as a promising tool for individualized treatment when validated by further prospective trials in the future.