Brain MRI Super Resolution Using 3D Deep Densely Connected Neural Networks

Magnetic resonance image (MRI) in high spatial resolution provides detailed anatomical information and is often necessary for accurate quantitative analysis. However, high spatial resolution typically comes at the expense of longer scan time, less spatial coverage, and lower signal to noise ratio (SNR). Single Image Super-Resolution (SISR), a technique aimed to restore high-resolution (HR) details from one single low-resolution (LR) input image, has been improved dramatically by recent breakthroughs in deep learning. In this paper, we introduce a new neural network architecture, 3D Densely Connected Super-Resolution Networks (DCSRN) to restore HR features of structural brain MR images. Through experiments on a dataset with 1,113 subjects, we demonstrate that our network outperforms bicubic interpolation as well as other deep learning methods in restoring 4x resolution-reduced images.Comment: Accepted by ISBI'1

Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network

High-resolution (HR) magnetic resonance images (MRI) provide detailed anatomical information important for clinical application and quantitative image analysis. However, HR MRI conventionally comes at the cost of longer scan time, smaller spatial coverage, and lower signal-to-noise ratio (SNR). Recent studies have shown that single image super-resolution (SISR), a technique to recover HR details from one single low-resolution (LR) input image, could provide high-quality image details with the help of advanced deep convolutional neural networks (CNN). However, deep neural networks consume memory heavily and run slowly, especially in 3D settings. In this paper, we propose a novel 3D neural network design, namely a multi-level densely connected super-resolution network (mDCSRN) with generative adversarial network (GAN)-guided training. The mDCSRN quickly trains and inferences and the GAN promotes realistic output hardly distinguishable from original HR images. Our results from experiments on a dataset with 1,113 subjects show that our new architecture beats other popular deep learning methods in recovering 4x resolution-downgraded im-ages and runs 6x faster.Comment: 10 pages, 2 figures, 2 tables. MICCAI 201

Robust prognostic model based on immune infiltration-related genes and clinical information in ovarian cancer

Immune infiltration of ovarian cancer (OV) is a critical factor in determining patient's prognosis. Using data from TCGA and GTEx database combined with WGCNA and ESTIMATE methods, 46 genes related to OV occurrence and immune infiltration were identified. Lasso and multivariate Cox regression were applied to define a prognostic score (IGCI score) based on 3 immune genes and 3 types of clinical information. The IGCI score has been verified by K-M curves, ROC curves and C-index on test set. In test set, IGCI score (C-index = 0.630) is significantly better than AJCC stage (C-index = 0.541, p < 0.05) and CIN25 (C-index = 0.571, p < 0.05). In addition, we identified key mutations to analyse prognosis of patients and the process related to immunity. Chi-squared tests revealed that 6 mutations are significantly (p < 0.05) related to immune infiltration: BRCA1, ZNF462, VWF, RBAK, RB1 and ADGRV1. According to mutation survival analysis, we found 5 key mutations significantly related to patient prognosis (p < 0.05): CSMD3, FLG2, HMCN1, TOP2A and TRRAP. RB1 and CSMD3 mutations had small p-value (p < 0.1) in both chi-squared tests and survival analysis. The drug sensitivity analysis of key mutation showed when RB1 mutation occurs, the efficacy of six anti-tumour drugs has changed significantly (p < 0.05).Peer reviewe

Ganoderma Lucidum Polysaccharide Peptide Alleviates Hepatoteatosis via Modulating Bile Acid Metabolism Dependent on FXR-SHP/FGF

Background/Aims: Non-alcoholic fatty liver disease (NAFLD) encompasses a series of pathologic changes ranging from steatosis to steatohepatitis, which may progress to cirrhosis and hepatocellular carcinoma. The purpose of this study was to determine whether ganoderma lucidum polysaccharide peptide (GLPP) has therapeutic effect on NAFLD. Methods: Ob/ ob mouse model and ApoC3 transgenic mouse model were used for exploring the effect of GLPP on NAFLD. Key metabolic pathways and enzymes were identified by metabolomics combining with KEGG and PIUmet analyses and key enzymes were detected by Western blot. Hepatosteatosis models of HepG2 cells and primary hepatocytes were used to further confirm the therapeutic effect of GLPP on NAFLD. Results: GLPP administrated for a month alleviated hepatosteatosis, dyslipidemia, liver dysfunction and liver insulin resistance. Pathways of glycerophospholipid metabolism, fatty acid metabolism and primary bile acid biosynthesis were involved in the therapeutic effect of GLPP on NAFLD. Detection of key enzymes revealed that GLPP reversed low expression of CYP7A1, CYP8B1, FXR, SHP and high expression of FGFR4 in ob/ob mice and ApoC3 mice. Besides, GLPP inhibited fatty acid synthesis by reducing the expression of SREBP1c, FAS and ACC via a FXR-SHP dependent mechanism. Additionally, GLPP reduced the accumulation of lipid droplets and the content of TG in HepG2 cells and primary hepatocytes induced by oleic acid and palmitic acid. Conclusion: GLPP significantly improves NAFLD via regulating bile acid synthesis dependent on FXR-SHP/FGF pathway, which finally inhibits fatty acid synthesis, indicating that GLPP might be developed as a therapeutic drug for NAFLD

Effect of carbon fiber crystallite size on the formation of hafnium carbide coating and the mechanism of the reaction of hafnium with carbon fibers

The effect of carbon source crystallite size on the formation of hafnium carbide (HfC) coating was investigated via direct reaction of hafnium powders with mesophase pitch-based carbon fibers (CFs) heat-treated at various temperatures. X-ray diffraction, scanning electron microscopy and energy dispersive X-ray spectroscopy analyses reveal that uniform and dense HfC coatings are preferentially formed on CFs containing larger and more ordered graphite crystallites. The carbide synthesis temperature and the sizes of crystallites in the CFs have a remarkable influence on the integrity and thickness of the coatings. The formation the HfC coatings can be attributed to the surface diffusion of hafnium and the bi-directional diffusion of hafnium and carbon sources inside the HfC coating. The reaction of HfC coated carbon fibers with zirconium powders leads to the growth of ZrC on the HfC coating and this has been shown to occur by the diffusion of carbon from the carbon fiber core through the carbide coating to its surface

Complex 3D microfluidic architectures formed by mechanically guided compressive buckling.

Microfluidic technologies have wide-ranging applications in chemical analysis systems, drug delivery platforms, and artificial vascular networks. This latter area is particularly relevant to 3D cell cultures, engineered tissues, and artificial organs, where volumetric capabilities in fluid distribution are essential. Existing schemes for fabricating 3D microfluidic structures are constrained in realizing desired layout designs, producing physiologically relevant microvascular structures, and/or integrating active electronic/optoelectronic/microelectromechanical components for sensing and actuation. This paper presents a guided assembly approach that bypasses these limitations to yield complex 3D microvascular structures from 2D precursors that exploit the full sophistication of 2D fabrication methods. The capabilities extend to feature sizes <5 μm, in extended arrays and with various embedded sensors and actuators, across wide ranges of overall dimensions, in a parallel, high-throughput process. Examples include 3D microvascular networks with sophisticated layouts, deterministically designed and constructed to expand the geometries and operating features of artificial vascular networks

Models Analyses for Allelopathic Effects of Chicory at Equivalent Coupling of Nitrogen Supply and pH Level on F. arundinacea, T. repens and M. sativa

Alllelopathic potential of chicory was investigated by evaluating its effect on seed germination, soluble sugar, malondialdehyde (MDA) and the chlorophyll content of three target plants species (Festuca arundinacea, Trifolium repens and Medicago sativa). The secretion of allelochemicals was regulated by keeping the donor plant (chicory) separate from the three target plant species and using different pH and nitrogen levels. Leachates from donor pots with different pH levels and nitrogen concentrations continuously irrigated the target pots containing the seedlings. The allelopathic effects of the chicory at equivalent coupling of nitrogen supply and pH level on the three target plants species were explored via models analyses. The results suggested a positive effect of nitrogen supply and pH level on allelochemical secretion from chicory plants. The nitrogen supply and pH level were located at a rectangular area defined by 149 to 168 mg/l nitrogen supply combining 4.95 to 7.0 pH value and point located at nitrogen supply 177 mg/l, pH 6.33 when they were in equivalent coupling effects; whereas the inhibitory effects of equivalent coupling nitrogen supply and pH level were located at rectangular area defined by 125 to 131 mg/l nitrogen supply combining 6.71 to 6.88 pH value and two points respectively located at nitrogen supply 180 mg/l with pH 6.38 and nitrogen supply 166 mg/l with pH 7.59. Aqueous extracts of chicory fleshy roots and leaves accompanied by treatment at different sand pH values and nitrogen concentrations influenced germination, seedling growth, soluble sugar, MDA and chlorophyll of F. arundinacea, T. repens and M. sativa. Additionally, we determined the phenolics contents of root and leaf aqueous extracts, which were 0.104% and 0.044% on average, respectively