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Search Results: 1 - 10 of 82183 matches for " Zhuo Liu "
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Application of Dual-Energy CT Non-Linear Fusion Technology in Improving CTA Image Quality of Renal Cancer  [PDF]
Shuiqing Zhuo, Xiaoling Chen, Jingping Yu, Sihui Zeng, Lizhi Liu
Open Journal of Medical Imaging (OJMI) , 2018, DOI: 10.4236/ojmi.2018.83009
Abstract: Objective: To explore the significance of dual-energy CT non-linear fusion technique in improving the quality of CTA image of renal cancer. Methods: The CTA images of 100 patients who had been confirmed by pathology as renal cancer were collected and were randomly divided into experimental group and control group with 50 cases respectively. The two groups of patients were treated with iodine concentration of 300 mg/ml and 350 mg/ml non-ionic contrast agent, with a dosage of 1.5 ml/kg and an injection rate of 4 ml/s. The contrast agent intelligently tracking method was adopted bolus. The control group used the conventional CTA scanning, with a reference tube voltage/tube current of 100 kv/ref150 mas. The experimental group adopted the double energy scanning, with ball tube A and ball tube B. The reference tube voltage/tube current was 100 kv/ref250 mas and sn150 kv/ref125 mas respectively. The images of the experimental group were non-linear fused to obtain the Mono+ 55 kev single-energy images. The CT value, SNR contrast ratio of the abdominal aorta, renal artery and
Significance of an Advanced Image-Based Virtual Monoenergetic Reconstruction of Dual Source Dual-Energy CT Data at Low keV Increases Image Quality for Portal Vein System of Pancreatic Cancer Patients  [PDF]
Shuiqing Zhuo, Sihui Zeng, Jingping Yu, Lizhi Liu
Journal of Cancer Therapy (JCT) , 2018, DOI: 10.4236/jct.2018.910068
Abstract: Purpose: To explore the significance of dual-source computed tomography (DECT) virtual monoenergetic reconstructions technology in improving image quality for portal vein system of pancreatic cancer patients. Materials and methods: 47 patients with clinically suspected pancreatic cancer (all confirmed by pathology) were collected. Routine plain scan was performed with Siemens Force dual-source dual-energy CT followed by 3 scans respectively carried out in arterial phase, portal phase and delayed phase. Traditional virtual monoenergetic reconstructions (Mono_E) and new generation of virtual monoenergetic reconstructions (Mono+) were respectively performed on portal vein images to obtain virtual single energy images including Mono_ E70 keV, Mono_E 55 keV and Mono+ 70 keV and Mono+ 55 keV. The signal-to-noise ratio (SNR) and noise of portal vein, normal pancreatic tissues and pancreatic lesions of 100 kV, Mono_E and Mono+ images were compared. In addition, the contrast noise ratio of portal vein and lesions as well as pancreatic tissues and lesions (CNR PV, CNRtumor) were also compared. At the same time, two imaging physicians with rich clinical experiences read the films and scored the images of each group by using the 5-point scoring method. Results: Mono+ 55 keV images including SNRpv, SNRpanc, SNRtumor, Noise, CNRpv, CNRtumor were statistically different from 100 KV images and Mono_E images (P < 0.05). As for the
Development of a Nongenetic Mouse Model of Type 2 Diabetes
Elizabeth R. Gilbert,Zhuo Fu,Dongmin Liu
Experimental Diabetes Research , 2011, DOI: 10.1155/2011/416254
Abstract: Insulin resistance and loss of β-cell mass cause Type 2 diabetes (T2D). The objective of this study was to generate a nongenetic mouse model of T2D. Ninety-six 6-month-old C57BL/6N males were assigned to 1 of 12 groups including (1) low-fat diet (LFD; low-fat control; LFC), (2) LFD with 1 i.p. 40 mg/kg BW streptozotocin (STZ) injection, (3), (4), (5), (6) LFD with 2, 3, 4, or 5 STZ injections on consecutive days, respectively, (7) high-fat diet (HFD), (8) HFD with 1 STZ injection, (9), (10), (11), (12) HFD with 2, 3, 4, or 5 STZ injections on consecutive days, respectively. After 4 weeks, serum insulin levels were reduced in HFD mice administered at least 2 STZ injections as compared with HFC. Glucose tolerance was impaired in mice that consumed HFD and received 2, 3, or 4 injections of STZ. Insulin sensitivity in HFD mice was lower than that of LFD mice, regardless of STZ treatment. Islet mass was not affected by diet but was reduced by 50% in mice that received 3 STZ injections. The combination of HFD and three 40 mg/kg STZ injections induced a model with metabolic characteristics of T2D, including peripheral insulin resistance and reduced β-cell mass.
Relationship between topology and functions in metabolic network evolution
Zhuo Wang,Qi Chen,Lei Liu
Chinese Science Bulletin , 2009, DOI: 10.1007/s11434-009-0072-z
Abstract: What is the relationship between the topological connections among enzymes and their functions during metabolic network evolution? Does this relationship show similarity among closely related organisms? Here we investigated the relationship between enzyme connectivity and functions in metabolic networks of chloroplast and its endosymbiotic ancestor, cyanobacteria (Synechococcus sp. WH8102). Also several other species, including E. coli, Arabidopsis thaliana and Cyanidioschyzon merolae, were used for the comparison. We found that the average connectivity among different functional pathways and enzyme classifications (EC) was different in all the species examined. However, the average connectivity of enzymes in the same functional classification was quite similar between chloroplast and one representative of cyanobacteria, syw. In addition, the enzymes in the highly conserved modules between chloroplast and syw, such as amino acid metabolism, were highly connected compared with other modules. We also discovered that the isozymes of chloroplast and syw often had higher connectivity, corresponded to primary metabolism and also existed in conserved module. In conclusion, despite the drastic re-organization of metabolism in chloroplast during endosymbiosis, the relationship between network topology and functions is very similar between chloroplast and its precursor cyanobacteria, which demonstrates that the relationship may be used as an indicator of the closeness in evolution.
Discrete element simulations of two wetting effects on granular materials
ZhongZhi Fu,SiHong Liu,Zhuo Li
Chinese Science Bulletin , 2011, DOI: 10.1007/s11434-011-4831-2
Abstract: To explore the microscopic responses of granular materials to wetting, the inter-particle lubrication effect and particle breakage in an odometer were simulated using a two-dimensional discrete element method. The lubrication effect was modeled by reduction of the inter-particle friction coefficient and particle breakage was initiated by decreasing the particle strength. Once the strength of the particles decreased to a threshold value, the particles began to break so that new contacts could be established to transfer the external loads. Numerical simulations successfully reproduced the additional compaction of the material and the intensification of the horizontal stress in addition to the microscopic responses of the granular assemblies. The microscopic interpretation of the earth pressure coefficient at rest and the evolution of the grain number distribution during particle breaking were also investigated.
Relationship between topology and functions in metabolic network evolution

Zhuo Wang,Qi Chen,Lei Liu,

科学通报(英文版) , 2009,
Abstract: What is the relationship between the topological connections among enzymes and their functions during metabolic network evolution? Does this relationship show similarity among closely related organisms? Here we investigated the relationship between enzyme connectivity and functions in metabolic networks of chloroplast and its endosymbiotic ancestor, cyanobacteria (Synechococcus sp. WH8102). Also several other species, including E. coli, Arabidopsis thaliana and Cyanidioschyzon merolae, were used for the comparison. We found that the average connectivity among different functional pathways and enzyme classifications (EC) was different in all the species examined. However, the average connectivity of enzymes in the same functional classification was quite similar between chloroplast and one representative of cyanobacteria, syw. In addition, the enzymes in the highly conserved modules between chloroplast and syw, such as amino acid metabolism, were highly connected compared with other modules. We also discovered that the isozymes of chloroplast and syw often had higher connectivity, corresponded to primary metabolism and also existed in conserved module. In conclusion, despite the drastic re-organization of metabolism in chloroplast during endosymbiosis, the relationship between network topology and functions is very similar between chloroplast and its precursor cyanobacteria, which demonstrates that the relationship may be used as an indicator of the closeness in evolution. Supported by National Key Basic Research and Development Program of China (Grant Nos. 2006CB0D1203, 2006CB0D1205 and 2006CB910700), and National Natural Science Fundation of China (Grant No. 30800199)
A Survey on Connected Dominating Set Construction Algorithm for Wireless Sensor Networks
Zhuo Liu,Bingwen Wang,Lejiang Guo
Information Technology Journal , 2010,
Abstract: In Wireless Sensor Network (WSN), all nodes are energy constrained. Clustering is a kind of energy efficient algorithm, while using a virtual backbone to organize the nodes is a better way. Although, there is no physical backbone infrastructure, a virtual backbone can be formed by constructing a Connected Dominating Set (CDS). The CDS of a graph representing a network has a significant impact on an efficient design of routing algorithms in WSN. A good CDS should first and foremost be small, additionally, it should have other characteristics such as robustness to node failures and low stretch. In this paper, we present a taxonomy and general classification of CDS construction algorithms. We survey different CDS construction algorithms for WSNs.
Epileptic Seizure Prediction by a System of Particle Filter Associated with a Neural Network
Derong Liu,Zhongyu Pang,Zhuo Wang
EURASIP Journal on Advances in Signal Processing , 2009, DOI: 10.1155/2009/638534
Abstract: None of the current epileptic seizure prediction methods can widely be accepted, due to their poor consistency in performance. In this work, we have developed a novel approach to analyze intracranial EEG data. The energy of the frequency band of 4–12 Hz is obtained by wavelet transform. A dynamic model is introduced to describe the process and a hidden variable is included. The hidden variable can be considered as indicator of seizure activities. The method of particle filter associated with a neural network is used to calculate the hidden variable. Six patients' intracranial EEG data are used to test our algorithm including 39 hours of ictal EEG with 22 seizures and 70 hours of normal EEG recordings. The minimum least square error algorithm is applied to determine optimal parameters in the model adaptively. The results show that our algorithm can successfully predict 15 out of 16 seizures and the average prediction time is 38.5 minutes before seizure onset. The sensitivity is about 93.75% and the specificity (false prediction rate) is approximately 0.09 FP/h. A random predictor is used to calculate the sensitivity under significance level of 5%. Compared to the random predictor, our method achieved much better performance.
Surface Characterisation of a Ferroelectric Single Crystal by Kelvin Probe Force Microscopy  [PDF]
Kenny Lau, Yun Liu, Qian Li, Zhenrong Li, Ray L. Withers, Zhuo Xu
Journal of Surface Engineered Materials and Advanced Technology (JSEMAT) , 2013, DOI: 10.4236/jsemat.2013.33026
Abstract:

We investigated the surface potential dynamics of a ferroelectric Pb(In1/2Nb1/2)O3-Pb(Mg1/3Nb2/3)O3-PbTiO3 (PIMNT) single crystal using Kelvin probe force microscopy (KPFM). The initial surface potential is a function of the applied bias since it reflects the interplay between the polarisation and screen charges. It is suggested that the different rates of tip injected charges are responsible for the asymmetric behaviour of the initial surface potential dependent on the sign of the applied bias. The polarisation, screen and tip injected charges are considered to explain the difference in surface potential dynamics.

Development of a Nongenetic Mouse Model of Type 2 Diabetes
Elizabeth R. Gilbert,Zhuo Fu,Dongmin Liu
Journal of Diabetes Research , 2011, DOI: 10.1155/2011/416254
Abstract: Insulin resistance and loss of β-cell mass cause Type 2 diabetes (T2D). The objective of this study was to generate a nongenetic mouse model of T2D. Ninety-six 6-month-old C57BL/6N males were assigned to 1 of 12 groups including (1) low-fat diet (LFD; low-fat control; LFC), (2) LFD with 1 i.p. 40?mg/kg BW streptozotocin (STZ) injection, (3), (4), (5), (6) LFD with 2, 3, 4, or 5 STZ injections on consecutive days, respectively, (7) high-fat diet (HFD), (8) HFD with 1 STZ injection, (9), (10), (11), (12) HFD with 2, 3, 4, or 5 STZ injections on consecutive days, respectively. After 4 weeks, serum insulin levels were reduced in HFD mice administered at least 2 STZ injections as compared with HFC. Glucose tolerance was impaired in mice that consumed HFD and received 2, 3, or 4 injections of STZ. Insulin sensitivity in HFD mice was lower than that of LFD mice, regardless of STZ treatment. Islet mass was not affected by diet but was reduced by 50% in mice that received 3 STZ injections. The combination of HFD and three 40?mg/kg STZ injections induced a model with metabolic characteristics of T2D, including peripheral insulin resistance and reduced β-cell mass. 1. Introduction It is estimated that 23.6 million or 8% of the American population suffers from diabetes [1]. Almost the same numbers have prediabetes. While the availability of novel drugs, techniques, and surgical intervention has improved the survival rate of individuals with diabetes, the prevalence of diabetes still rises in Americans, and the number of people with diabetes is projected to double by 2025 [2]. These alarming statistics underscore the need for research aimed at discovering novel therapeutic strategies for the prevention or treatment of this disease. For the study of Type 2 diabetes (T2D) there are a variety of inbred mouse strains that serve as popular models [3]. Genetic obese diabetic mice, including leptin and leptin receptor knockouts (ob/ob and db/db, resp.), are commonly used T2D models for developing new treatments for this disease [3]. However, T2D is a disease stemming from a combination of cumulative polygenic traits and interactions with environmental stressors [4]. A diet-induced model can be used to more closely resemble the gradual progression from obesity to insulin resistance and T2D, the hallmarks of the human phenotype [4]. The development of a nongenetic mouse model for T2D involves establishment of insulin resistance, a period of compensatory insulin release to maintain glucose homeostasis. The pathogenesis of T2D then involves a combination of factors including
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