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Search Results: 1 - 10 of 46525 matches for " Jing Hu "
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Evil Human Nature: From the Perspectives of St. Augustineand Hsun Tzu  [PDF]
Xiajun Hu, Jing Guo
Open Journal of Philosophy (OJPP) , 2011, DOI: 10.4236/ojpp.2011.12011
Abstract: The view of evil human nature is important in Chinese and western cultures. The thesis chooses evil human in St. Augustine’s thoughts and Hsun Tzu’s thoughts to compare and analyze evil in these two. St. Augustine, who is called “the Saint of God”, views the definition of evil, the resource of it, and salvations of it from the aspect of religious beliefs. He considers that evil is the privation of goodness and is not created by God. Because God is omnipotent and all-good, it is impossible for God to create evil. Evil results from the free will of human beings themselves. If people want to attain their salvations, they should use their free will to choose good will and follow the goodness given by God. Hsun Tzu, one of Confucian scholars, puts forward evil human nature which is totally different from good human nature in Confucianism. He views the definition of evil, the source of it, and ways to change evil into good from the angle of social reality in Warring States Period. In Hsun Tzu’s views, evil results from the uninhibited extension of sound physical needs and desires for living. Hsun Tzu believes that human nature is evil and goodness comes from nurture, therefore, converting evil into good is to change human nature through nurturing. By further comparison and analysis, the thesis further looks into these two perspectives from their differences and similarities. It states their differences from five aspects: backgrounds, ways to change evil to good, categories, historical status, and positions of human beings. Apart from those, the thesis also refers to their similarities to complement the comparative analysis. From comparison and analysis, we can draw two conclusions: first, evil human nature from Hsun Tzu is simple in connotation and relatively objective compared with the view of St. Augustine; second, St. Augustine thinks that human beings are equal in front of evil, which has positive significance compared with the ideas posed by Hsun Tzu who insists on the distinction between saint and ordinary people, between monarchs and their subjects.
Polymer Delivery of Hydroxycamptothecin against C6 Glioma  [PDF]
Jing Hu, Huafei Tang, Songqing Liu
Journal of Cancer Therapy (JCT) , 2014, DOI: 10.4236/jct.2014.510098
Abstract:

Hydroxycamptothecin is a potent antineoplastic agent that has shown efficacy against multiple tumor lines in vitro. This is the first study to investigate the release, distribution, and efficacy of hydroxycamptothecin which was incorporated into the biodegradable polymer Polylactic Acid (PLA), and implant into brain directly. In vitro release curve generated showed that a large initial release occurred over the first three days and was followed by a steady, but considerably slower rate of release over the next 25 days. After implanting the discs into 40 male SD rats, the animals were followed up to 28 days, where the concentration in brain tissue was far higher than that in peripheral blood at the each of the eight time-points evaluated, and it was also within the therapeutic range for C6 cells tested in vitro. The in vivoefficacy of the discs was evaluated with rats inoculated intracranially with C6 glioma and treated with hydroxycamptothecin polymer compared to intravenous as well as intratumoral injections; the median survival is 21.1, 13.9, 14.9 days, respectively. Given these data, we conclude that the biodegradable polymer PLA releases hydroxycamptothecin, producing tumoricidal levels in brain tissues and prolonging survival in a rat glioma model.

Research Advances in Photocatalysis of Inorganic Hollow Spheres  [PDF]
Ting Tian, Jing Hu, Zuobing Xiao
World Journal of Nano Science and Engineering (WJNSE) , 2014, DOI: 10.4236/wjnse.2014.44015
Abstract: Inorganic hollow spheres have shown their superiority in photocatalytic area due to the large specific surface area, controllable structure and their own special optical, electrical, magnetic properties. According to the classification of inorganic hollow spheres as photocatalysts, recent research progress and application status have been summarized in this paper. At last, the future developments of inorganic hollow spheres in photocatalytic field have been discussed.
Identification of deleterious non-synonymous single nucleotide polymorphisms using sequence-derived information
Jing Hu, Changhui Yan
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-297
Abstract: We compiled a set of 686 features that were derived from protein sequence. For each feature, the distance between the wild-type residue and mutant-type residue was computed. Then a greedy approach was used to select the features that were useful for the classification of SAPs. 10 features were selected. Using the selected features, a decision tree method can achieve 82.6% overall accuracy with 0.607 Matthews Correlation Coefficient (MCC) in cross-validation. When tested on an independent set that was not seen by the method during the training and feature selection, the decision tree method achieves 82.6% overall accuracy with 0.604 MCC. We also evaluated the proposed method on all SAPs obtained from the Swiss-Prot, the method achieves 0.42 MCC with 73.2% overall accuracy. This method allows users to make reliable predictions when protein structures are not available. Different from previous studies, in which only a small set of features were arbitrarily chosen and considered, here we used an automated method to systematically discover useful features from a large set of features well-annotated in public databases.The proposed method is a useful tool for the classification of SAPs, especially, when the structure of the protein is not available.It is estimated that around 90% of human genetic variations are differences in single bases of DNA, known as single nucleotide polymorphisms (SNPs) [1]. Among them, non-synonymous single nucleotide polymorphisms (nsSNPs), also known as single amino acid polymorphism (SAPs), that cause amino acid changes in proteins have the potential to affect both protein structure and protein function [2]. Some of the mutations in SAP sites are not associated with any changes in phenotype and are considered functional neutral, but others bringing deleterious effects to protein function and are responsible for many human genetic diseases [3,4]. Recent years have seen an explosion in the number of SAPs in public databases, such as dbSNP [5], HG
A tool for calculating binding-site residues on proteins from PDB structures
Jing Hu, Changhui Yan
BMC Structural Biology , 2009, DOI: 10.1186/1472-6807-9-52
Abstract: In this study, we have developed a tool for calculating binding-site residues on proteins, TCBRP http://yanbioinformatics.cs.usu.edu:8080/ppbindingsubmit webcite. For an input protein, TCBRP can quickly find all binding-site residues on the protein by automatically combining the information obtained from all PDB structures that consist of the protein of interest. Additionally, TCBRP presents the binding-site residues in different categories according to the interaction type. TCBRP also allows researchers to set the definition of binding-site residues.The developed tool is very useful for the research on protein binding site analysis and prediction.Proteins perform various functions through interactions with other molecules, such as DNA, RNA, proteins, carbohydrates, and ligands. To understand the mechanisms of these interactions, many studies have been performed to analyze the properties of binding sites on proteins, such as residue composition, secondary structure, geometric shape, electrostatic potentials, etc [1-10]. To perform such an analysis, researchers must first identify the amino acid residues (referred to as binding-site residues) that are involved in the interactions. In other studies where the goal is to build computational predictors for predicting functional sites on proteins (e.g. DNA-binding sites, RNA-binding sites, protein-protein binding sites), researchers also need to identify binding-site residues on the training and test sets to train and evaluate their predictors [11-17].In most, if not all, of the above-mentioned studies, the binding-site residues are calculated from the 3-dimensional (3D) structures deposited in Protein Data Bank (PDB) [18]. Usually, researchers collected a non-redundant set of PDB structures, and then calculated binding-sites based on the PDB structures. However, one serious problem with this approach is that a protein may have multiple binding sites that interact with different interacting partners, but one PDB structure
Natural killer cells are crucial for the efficacy of Icon (factor VII/human IgG1 Fc) immunotherapy in human tongue cancer
Zhiwei Hu, Jing Li
BMC Immunology , 2010, DOI: 10.1186/1471-2172-11-49
Abstract: We showed that Icon, as a chimeric factor VII and human IgG1 Fc immunoconjugate, could separately induce murine natural killer (NK) cells and activate complement to kill TCA8113 cancer cells in vitro via antibody dependent cell-mediated cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC). However, Icon-NK ADCC had a significantly stronger effect than that of Icon-CDC. Moreover, Icon could completely eradicate established human tongue tumour xenografts in vivo in the CB-17 strain of SCID mice that have functional NK cells at a normal level, whereas it was less effective in SCID/Beige mice that do not have functional NK cells.We conclude that NK cells are crucial for the efficacy of Icon immunotherapy in the treatment of cancer. The results also suggest that impaired NK level/activity could contribute to the resistance to therapeutic antibodies that are currently under investigation in preclinical and clinical studies.Several prevalent diseases such as cancer, exudative (wet) age-related macular degeneration, diabetic retinopathy, and rheumatoid arthritis are associated with abnormal angiogenesis, i.e., formation of pathological neovasculature. It is believed that targeting pathological neovasculature is a better strategy for cancer therapy than targeting tumour cells [1]. In the case of cancer, there are two methods for targeting pathological neovasculature in tumours, namely anti-angiogenesis by anti-angiogenic inhibitors [2] and anti-neovasculature by vascular disrupting agents [3-5]. Because pathological neovasculature usually has formed by the time a diagnosis is reached, eradication of the pathological neovasculature is necessary to achieve optimal therapeutic efficacy. Among those vascular disrupting agents there are several molecules called vascular targeting agents [6]. These vascular targeting agents were designed to bring soluble tissue factor (TF) to tumour endothelial cells by targeting MHC class II, cell adhesion molecules, fibronectin, or pr
BS-KNN: An Effective Algorithm for Predicting Protein Subchloroplast Localization
Jing Hu and Xianghe Yan
Evolutionary Bioinformatics , 2012, DOI: 10.4137/EBO.S8681
Abstract: Chloroplasts are organelles found in cells of green plants and eukaryotic algae that conduct photosynthesis. Knowing a protein’s subchloroplast location provides in-depth insights about the protein’s function and the microenvironment where it interacts with other molecules. In this paper, we present BS-KNN, a bit-score weighted K-nearest neighbor method for predicting proteins’ subchloroplast locations. The method makes predictions based on the bit-score weighted Euclidean distance calculated from the composition of selected pseudo-amino acids. Our method achieved 76.4% overall accuracy in assigning proteins to 4 subchloroplast locations in cross-validation. When tested on an independent set that was not seen by the method during the training and feature selection, the method achieved a consistent overall accuracy of 76.0%. The method was also applied to predict subchloroplast locations of proteins in the chloroplast proteome and validated against proteins in Arabidopsis thaliana. The software and datasets of the proposed method are available at https://edisk.fandm.edu/jing.hu/bsknn/bsknn.html.
HMM_RA: An Improved Method for Alpha-Helical Transmembrane Protein Topology Prediction
Jing Hu,Changhui Yan
Bioinformatics and Biology Insights , 2008,
Abstract:
HMM_RA: An Improved Method for Alpha-Helical Transmembrane Protein Topology Prediction
Jing Hu,Changhui Yan
Bioinformatics and Biology Insights , 2008,
Abstract: α-helical transmembrane (TM) proteins play important and diverse functional roles in cells. The ability to predict the topology of these proteins is important for identifying functional sites and inferring function of membrane proteins. This paper presents a Hidden Markov Model (referred to as HMM_RA) that can predict the topology of α-helical transmembrane proteins with improved performance. HMM_RA adopts the same structure as the HMMTOP method, which has five modules: inside loop, inside helix tail, membrane helix, outside helix tail and outside loop. Each module consists of one or multiple states. HMM_RA allows using reduced alphabets to encode protein sequences. Thus, each state of HMM_RA is associated with n emission probabilities, where n is the size of the reduced alphabet set. Direct comparisons using two standard data sets show that HMM_RA consistently outperforms HMMTOP and TMHMM in topology prediction. Specifically, on a high-quality data set of 83 proteins, HMM_RA outperforms HMMTOP by up to 7.6% in topology accuracy and 6.4% in α-helices location accuracy. On the same data set, HMM_RA outperforms TMHMM by up to 6.4% in topology accuracy and 2.9% in location accuracy. Comparison also shows that HMM_RA achieves comparable performance as Phobius, a recently published method.
APPLICATION OF IMAGE ANALYSIS TO ASSESSING CRITICAL PORE SIZE FOR PERMEABILITY PREDICTION OF CEMENT PASTE
Jing Hu,Piet Stroeven
Image Analysis and Stereology , 2003, DOI: 10.5566/ias.v22.p97-103
Abstract: This paper explores image analysis techniques that provide insight into the nature of pore structure as observed in backscattered electron images of polished sections. On the basis of mathematical morphology, the pore size distribution is characterised and the critical pore size is determined for cement paste at different hydration time. The influence of image resolution is investigated. The permeability of cement paste can be predicted according to General Effective Media (GEM) theory. Comparison between permeability estimation and experiment results reveals good agreement.
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