360 research outputs found

    Identification and characterization of stemlike cells in human esophageal adenocarcinoma and normal epithelial cell lines

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    ObjectiveRecent studies have suggested that human solid tumors may contain subpopulations of cancer stem cells with the capacity for self-renewal and the potential to initiate and maintain tumor growth. The aim of this study was to use human esophageal cell lines to identify and characterize putative esophageal cancer stem cell populations.MethodsTo enrich stemlike cells, Het-1A (derived from immortalized normal esophageal epithelium), OE33, and JH-EsoAd1 (each derived from primary esophageal adenocarcinomas) were cultured using serum-free media to form spheres. A comprehensive analysis of parent and spheroid cells was performed by flow cytometry, Western blot analysis, immunohistochemistry and polymerase chain reaction array to study cancer stem cell-related genes, colony formation assays to assess clonogenicity, xenotransplantation to assess tumorigenicity, and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays to assess chemosensitivity to 5-fluorouracil and Cisplatin.ResultsFor all cell lines, clonogenicity, tumorigenicity, and chemoresistance to 5-fluorouracil and Cisplatin were significantly higher than for spheroid cells compared with parent cells. Spheroids exhibited an increased frequency of cells expressing integrin α6bri/CD71dim, and Achaete-scute complex homolog 2 messenger RNA and protein were also significantly overexpressed in spheroid cells compared with parent cells.ConclusionsThe higher clonogenicity, tumorigenicity, and drug resistance exhibited by spheroids derived from Het-1A, OE33, and JH-EsoAd1 reflects an enrichment of stemlike cell populations within each esophageal cell line. Esophageal cells enriched for integrin α6bri/CD71dim and/or overexpressing Achaete-scute complex homolog 2 would appear to represent at least a subpopulation of stemlike cells in Het-1A, OE33, and JH-EsoAd1

    Correlations between aesthetic preferences of river and landscape characters

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    Some landscape characters put great influences on the aesthetic preferences of a river. Finding out these characters will provide for river landscape design and management with explicit keystones. In this paper, 23 sample areas of rivers were selected in Xuzhou, China, and 15 landscape characters of rivers were identified. The photos taken at the sample areas were as stimuli, and undergraduate students were respondents. The results demonstrate that the aesthetic preferences of photos judged one-by-one and judged together receive similar results; the preference scores of deflective views are significantly higher than the ones of opposite views; for urban rivers, “river accessibility” and “number of colours” are reliably positive predictors to aesthetic preferences, “wood diversity index” and “plants on water” are negative ones; for rural rivers, “coverage of riparian vegetation”, “perspective” and “wood diversity index” are reliably positive predictors to aesthetic preferences. First published online: 14 Dec 201

    Cardioprotective Effect of the Compound Yangshen Granule in Rat Models with Acute Myocardial Infarction

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    The protective effect of Compound Yangshen Granules was observed in myocardial infarction rat model. Rats were randomly divided into 6 groups: the model group, the control group (sham operated), the positive drug group, and small, medium, and large dosage of the Yangshen granule groups, respectively. The rats in the 3 Yangshen granule groups were orally administrated with 0.7 g/kg, 1.4 g/kg, and 2.8 g/kg for 7 consecutive days, whereas the rats of the positive drug group treated with 0.14 g/kg of Danshen Dropping Pills, and rats in the control and model groups orally administrated with saline. The rat model of acute myocardial infarction was established with ligation of coronary artery. Electrocardiograms at different time points, the blood rheology, myocardial enzymes, infarct size, and myocardial morphologic changes were measured. The results demonstrated that the granules could improve blood rheology, decrease st-segment of electrocardiograms and the activities of LDH and CK in serum, reduce myocardial infarction size, and alleviate myocardial histopathologic changes. In addition, the effect of the granules depended on the dose administrated orally. The results suggest that the Yangshen granules could produce cardioprotection effect and have potential benefits in the prevention of ischemic heart disease

    Effects of lipid regulation using raw and processed radix polygoni multiflori in rats fed a high-fat diet

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    Raw and processed Radix Polygoni Multiflori have been used in the prevention and treatment of nonalcoholic fatty liver disease (NAFLD), hyperlipidemia, and related diseases in Asian counties for centuries. The lipid regulation ability of raw and processed Poligoni Multiflori Radix were compared in high-fat diet fed rats in this research. Total cholesterol (TC) and low density lipoprotein-cholesterol (LDL-C) in blood and liver tissue were all significantly higher in model rats. However, triglyceride (TG) contents increased only in liver tissue, not in the blood samples. The rats fed the high-fat diets were considered the model of type IIa hyperlipidemia and early-stage nonalcoholic fatty liver disease. Both Radix Polygoni Multiflori (RPM) and Radix Polygoni Multiflori Praeparata (RPMP) revealed TC-lowing effects, and middling doses of RPMP displayed the most significant TC-lowing effects, as indicated by blood samples. Neither RPM nor RPMP was found to reduce LDL-C in rats' blood. Nevertheless, RPM showed dose-dependent TC-and TG-lowing effects in the liver tissue samples. In conclusion, RPM showed more pronounced effects on lipid regulation in liver samples in the treatment of early-stage NAFLD. RPMP, however, displayed better effects in regulating lipids in circulating blood for the treatment of hyperlipidemia

    STGC-GNNs: A GNN-based traffic prediction framework with a spatial-temporal Granger causality graph

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    The key to traffic prediction is to accurately depict the temporal dynamics of traffic flow traveling in a road network, so it is important to model the spatial dependence of the road network. The essence of spatial dependence is to accurately describe how traffic information transmission is affected by other nodes in the road network, and the GNN-based traffic prediction model, as a benchmark for traffic prediction, has become the most common method for the ability to model spatial dependence by transmitting traffic information with the message passing mechanism. However, existing methods model a local and static spatial dependence, which cannot transmit the global-dynamic traffic information (GDTi) required for long-term prediction. The challenge is the difficulty of detecting the precise transmission of GDTi due to the uncertainty of individual transport, especially for long-term transmission. In this paper, we propose a new hypothesis\: GDTi behaves macroscopically as a transmitting causal relationship (TCR) underlying traffic flow, which remains stable under dynamic changing traffic flow. We further propose spatial-temporal Granger causality (STGC) to express TCR, which models global and dynamic spatial dependence. To model global transmission, we model the causal order and causal lag of TCRs global transmission by a spatial-temporal alignment algorithm. To capture dynamic spatial dependence, we approximate the stable TCR underlying dynamic traffic flow by a Granger causality test. The experimental results on three backbone models show that using STGC to model the spatial dependence has better results than the original model for 45 min and 1 h long-term prediction.Comment: 14 pages, 16 figures, 4 table

    Motion-aware Memory Network for Fast Video Salient Object Detection

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    Previous methods based on 3DCNN, convLSTM, or optical flow have achieved great success in video salient object detection (VSOD). However, they still suffer from high computational costs or poor quality of the generated saliency maps. To solve these problems, we design a space-time memory (STM)-based network, which extracts useful temporal information of the current frame from adjacent frames as the temporal branch of VSOD. Furthermore, previous methods only considered single-frame prediction without temporal association. As a result, the model may not focus on the temporal information sufficiently. Thus, we initially introduce object motion prediction between inter-frame into VSOD. Our model follows standard encoder--decoder architecture. In the encoding stage, we generate high-level temporal features by using high-level features from the current and its adjacent frames. This approach is more efficient than the optical flow-based methods. In the decoding stage, we propose an effective fusion strategy for spatial and temporal branches. The semantic information of the high-level features is used to fuse the object details in the low-level features, and then the spatiotemporal features are obtained step by step to reconstruct the saliency maps. Moreover, inspired by the boundary supervision commonly used in image salient object detection (ISOD), we design a motion-aware loss for predicting object boundary motion and simultaneously perform multitask learning for VSOD and object motion prediction, which can further facilitate the model to extract spatiotemporal features accurately and maintain the object integrity. Extensive experiments on several datasets demonstrated the effectiveness of our method and can achieve state-of-the-art metrics on some datasets. The proposed model does not require optical flow or other preprocessing, and can reach a speed of nearly 100 FPS during inference.Comment: 12 pages, 10 figure

    Persistence in Mutual Fund Returns: Evidence from China

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