Using Two-stage Network to Segment Kidneys and Kidney Tumors

There are many new cases of kidney cancer each year, and surgery is the most common treatment. To assist doctors in surgical planning, an accurate and automatic kidney and tumor segmentation method is helpful in the clinical practice. In this paper, we propose a deep learning framework for the segmentation of kidneys and tumors in abdominal CT images. The key idea is using a two-stage strategy. First, for each case, we use a 3d U-shape convolution network to get the localization of each kidney. Then using next 3d U-shape convolution network we obtain the precise segmentation results of each kidney. Finally, merge the results to obtain the complete segmentation. Also, we try some tricks to improve the performance

Comparison of Analysis and Spectral Nudging Techniques for Dynamical Downscaling with the WRF Model over China

To overcome the problem that the horizontal resolution of global climate models may be too low to resolve features which are important at the regional or local scales, dynamical downscaling has been extensively used. However, dynamical downscaling results generally drift away from large-scale driving fields. The nudging technique can be used to balance the performance of dynamical downscaling at large and small scales, but the performances of the two nudging techniques (analysis nudging and spectral nudging) are debated. Moreover, dynamical downscaling is now performed at the convection-permitting scale to reduce the parameterization uncertainty and obtain the finer resolution. To compare the performances of the two nudging techniques in this study, three sensitivity experiments (with no nudging, analysis nudging, and spectral nudging) covering a period of two months with a grid spacing of 6 km over continental China are conducted to downscale the 1-degree National Centers for Environmental Prediction (NCEP) dataset with the Weather Research and Forecasting (WRF) model. Compared with observations, the results show that both of the nudging experiments decrease the bias of conventional meteorological elements near the surface and at different heights during the process of dynamical downscaling. However, spectral nudging outperforms analysis nudging for predicting precipitation, and analysis nudging outperforms spectral nudging for the simulation of air humidity and wind speed

Integrating Growth and Environmental Parameters to Discriminate Powdery Mildew and Aphid of Winter Wheat Using Bi-Temporal Landsat-8 Imagery

Monitoring and discriminating co-epidemic diseases and pests at regional scales are of practical importance in guiding differential treatment. A combination of vegetation and environmental parameters could improve the accuracy for discriminating crop diseases and pests. Different diseases and pests could cause similar stresses and symptoms during the same crop growth period, so combining growth period information can be useful for discerning different changes in crop diseases and pests. Additionally, problems associated with imbalanced data often have detrimental effects on the performance of image classification. In this study, we developed an approach for discriminating crop diseases and pests based on bi-temporal Landsat-8 satellite imagery integrating both crop growth and environmental parameters. As a case study, the approach was applied to data during a period of typical co-epidemic outbreak of winter wheat powdery mildew and aphids in the Shijiazhuang area of Hebei Province, China. Firstly, bi-temporal remotely sensed features characterizing growth indices and environmental factors were calculated based on two Landsat-8 images. The synthetic minority oversampling technique (SMOTE) algorithm was used to resample the imbalanced training data set before model construction. Then, a back propagation neural network (BPNN) based on a new training data set balanced by the SMOTE approach (SMOTE-BPNN) was developed to generate the regional wheat disease and pest distribution maps. The original training data set-based BPNN and support vector machine (SVM) methods were used for comparison and testing of the initial results. Our findings suggest that the proposed approach incorporating both growth and environmental parameters of different crop periods could distinguish wheat powdery mildew and aphids at the regional scale. The bi-temporal growth indices and environmental factors-based SMOTE-BPNN, BPNN, and SVM models all had an overall accuracy high than 80%. Meanwhile, the SMOTE-BPNN method had the highest G-means among the three methods. These results revealed that the combination of bi-temporal crop growth and environmental parameters is essential for improving the accuracy of the crop disease and pest discriminating models. The combination of SMOTE and BPNN could effectively improve the discrimination accuracy of the minor disease or pest

Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology

Novel Paper-Based Fluorescent Sensor Based on N-Doped Carbon Quantum Dots (N-CQDs) and Cotton Fiber Paper (CFP) with High Selectivity and Sensitivity for the Visual Determination of Mercury (II) in Environmental Waters

A highly selective solid-state fluorescent sensor based on N-doped carbon quantum dots (N-CQDs) and cotton fiber paper (CFP) is reported for the determination of trace mercury (II)(Hg2+). The N-doped carbon quantum dots on cotton fiber paper (N-CQDs@CFP) was synthesized using a facile one-step microwave hydrothermal method. Multiple approaches were employed to fully investigate the morphology and chemical structure of the paper-based fluorescent sensor. The N-CQDs were chemically bonded onto the CFP, which offers good reproducibility and stability of the sensor. The N-CQDs@CFP showed high-intensity blue emission in dark-field imaging, and the fluorescence was quenched by Hg2+. The Hg2+ in aqueous samples was easily determined and visually monitored. There was good linearity from 0 to 250 μM, and the limit of detection was 34 nM. The paper-based fluorescent sensor provided accurate and rapid determination of Hg2+ upon comparison with flame atomic absorption spectrophotometry (FAAS). The simple preparation, rapid detection (< 5 min), low cost, and easy-handling illustrate that the reported sensor has a significant value in environmental monitoring.</p

GEC-derived SFRP5 Inhibits Wnt5a-Induced Macrophage Chemotaxis and Activation

<div><p>Aberrant macrophage infiltration and activation has been implicated in gastric inflammation and carcinogenesis. Overexpression of Wnt5a and downregulation of SFRP5, a Wnt5a antagonist, were both observed in gastric cancers recently. This study attempted to explore whether Wnt5a/SFRP5 axis was involved in macrophage chemotaxis and activation. It was found that both Wnt5a transfection and recombinant Wnt5a (rWnt5a) treatment upregulated CCL2 expression in macrophages, involving JNK and NFκB signals. Conditioned medium from Wnt5a-treated macrophages promoted macrophage chemotaxis mainly dependent on CCL2. SFRP5 from gastric epithelial cells (GECs) inhibited Wnt5a-induced CCL2 expression and macrophage chemotaxis. In addition, Wnt5a treatment stimulated macrophages to produce inflammatory cytokines and COX-2/PGE₂, which was also suppressed by SFRP5 from GECs. These results demonstrate that Wnt5a induces macrophage chemotaxis and activation, which can be blocked by GEC-derived SFRP5, suggesting that Wnt5a overproduction and SFRP5 deficiency in gastric mucosa may together play an important role in gastric inflammation and carcinogenesis.</p></div

Schema: GEC-derived SFRP5 inhibits Wnt5a-induced macrophage chemotaxis and activation.

<p>Wnt5a chemoattracts macrophages by upregulate CCL2 expression, and activates macrophages to secrete cytokines, which are blocked by GEC-derived SFRP5.</p

CCL2 upregulation by Wnt5a in macrophages.

<p>(A) and (B) Real-time PCR and ELISA showed that CCL2 mRNA expression and protein secretion was upregulated by transfection with Wnt5a expression vector, *<i>P</i><0.01. (C) and (D) Real-time PCR and ELISA showed that CCL2 mRNA expression and protein secretion was stimulated by rWnt5a (0.1 µg/ml, 0.5 µg/ml, 1 µg/ml, respectively), *<i>P</i><0.01. (E) Immunofluorescence showed that both Wnt5a transfection and rWnt5a treatment increased CCL2 production. Control V, transfection with control vector; Wnt5a V, transfection with Wnt5a expression vector. Data are expressed as mean±SD, n = 3.</p

Macrophage chemotaxis induced by conditioned medium from Wnt5a-treated macrophages.

<p>(A) Transwell assay showed that conditioned-medium from macrophages treated with Wnt5a expression vector promoted cell migration; the induction in cell migration was suppressed by CCL2 neutralizing antibody AF-479-NA (0.1 µg/ml). *<i>P</i><0.01. (B) Transwell assay showed that conditioned-medium from macrophages treated with rWnt5a (0.5 µg/ml) increased cell migration; the increased cell migration was abrogated when CCL2 expression was silenced by CCL2 siRNA in macrophages. *<i>P</i><0.01. (C) Transwell assay showed that conditioned-medium from macrophages treated with Wnt5a expression vector promoted cell invasion; the induction in cell invasion was suppressed by CCL2 neutralizing antibody AF-479-NA (0.1 µg/ml). *<i>P</i><0.01. (D) Conditioned-medium from macrophages treated with Wnt5a expression vector induced cytoskeletal changes. Cont, control; ContV, control vector; WntV, Wnt5a vector; rWnt, rWnt5a; CCLsiR, CCL2 siRNA; ContsiR, control siRNA; AF, AF-479-NA. Data are expressed as mean±SD, n = 3.</p

Inhibition of Wnt5a-induced CCL2 expression and macrophage chemotaxis by SFRP5.

<p>(A) and (B) Real-time PCR and ELISA showed that conditioned medium from SFRP5-positive GES-1 inhibited Wnt5a-induced CCL2 expression in macrophages; the inhibitory effect of the condition medium was abolished when SFRP5 expression was knocked down in GES-1. *<i>P</i><0.01. (C) and (D) Real-time PCR and ELISA showed that conditioned medium from SFRP5-transfected BGC-803 suppressed Wnt5a-induced CCL2 expression in macrophages. *<i>P</i><0.01. (E) and (F) Real-time PCR and ELISA showed that rSFRP5 inhibited CCL2 induction by Wnt5a transfection in a dose-dependent manner. *<i>P</i><0.01. (G) Transwell assay showed that cell migration induced by conditioned medium from Wnt5a-transfected macrophages was suppressed by co-culture of Wnt5a-transfected macrophages with GES-1 or SFRP5-transfected BGC-803. *<i>P</i><0.01. (H) Transwell assay showed that cell migration induced by conditioned medium from Wnt5a-transfected macrophages was inhibited by pretreatment of macrophages with rSFRP5. *<i>P</i><0.01. Cont, control; ContV, control vector; WntV, Wnt5a vector; GES, GES-1; SFsiR, SFRP5 siRNA; ContsiR, control siRNA; BGC, BGC-803; SFV, SFRP5 vector; ContV, control vector. Data are expressed as mean±SD, n = 3.</p