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Thermal Insulation Materials of Alumina Based Porous Ceramics

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China's Refractories 2015年第3期24卷 29-33页

作者： YUAN Bo chen kuo HAN Jianshen DONG Binbin WANG Gang LI Hongxia State Key Laboratory of Advanced Refractories Sinosteel Luoyang Institute of Refractories Research Co.Ltd.

Significant energy saving effects can be made through the improvement of furnace refractories,especially the thermal insulation refractories. In this study,the preparation and the application of different alumina based porous ceramics were briefly introduced. Alumina based porous ceramics were prepared combined foaming method with gelcasting,sol- gel process or cement curing process. The influences of different preparation methods on the sintering shrinkage, porosity, phase composition, microstructure, compressive strength and thermal conductivity were discussed. Alumina based porous ceramics with relatively high strength and low thermal conductivity could be obtained through the above mentioned methods. Compared with the traditional lining materials,about 40% energy could be saved when they were used as the furnace wall.

关键词： thermal insulation alumina based porous ceramics energy saving

Diagnosis of Helicobacter pylori infection: Current options and developments

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World Journal of Gastroenterology 2015年第40期21卷 11221-11235页

作者： Yao-Kuang Wang Fu-chen kuo Chung-Jung Liu Meng-Chieh Wu Hsiang-Yao Shih Sophie SW Wang Jeng-Yih Wu Chao-Hung kuo Yao-Kang Huang Deng-Chyang Wu Department of Internal Medicine Kaohsiung Municipal Hsiao-Kang Hospital Division of Gastroenterology Department of Internal MedicineKaohsiung Medical University Hospital School of Medicine College of MedicineE-Da HospitalI-Shou University Department of Internal Medicine Kaohsiung Municipal Ta-Tung Hospital Cancer for Stem Cell Research Kaohsiung Medical University Center for Infectious Disease and Cancer Research Kaohsiung Medical University Division of Gastroenterology Department of Internal MedicineTen Chan Hospital

Accurate diagnosis of Helicobacter pylori(H. pylori) infection is a crucial part in the effective management of many gastroduodenal diseases. Several invasive and non-invasive diagnostic tests are available for the detection of H. pylori and each test has its usefulness and limitations in different clinical situations. Although none can be considered as a single gold standard in clinical practice,several techniques have been developed to give the more reliable results. Invasive tests are performed via endoscopic biopsy specimens and these tests include histology,culture,rapid urease test as well as molecular methods. Developments of endoscopic equipment also contribute to the real-time diagnosis of H. pylori during endoscopy. Urea breathingtest and stool antigen test are most widely used noninvasive tests,whereas serology is useful in screening and epidemiological studies. Molecular methods have been used in variable specimens other than gastric mucosa. More than detection of H. pylori infection,several tests are introduced into the evaluation of virulence factors and antibiotic sensitivity of H. pylori,as well as screening precancerous lesions and gastric cancer. The aim of this article is to review the current options and novel developments of diagnostic tests and their applications in different clinical conditions or for specific purposes.

关键词： Helicobacter pylori Diagnosis Invasive Noninvasive

CYP2C19 polymorphism influences Helicobacter pylori eradication

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World Journal of Gastroenterology 2014年第43期20卷 16029-16036页

作者： Chao-Hung kuo Chien-Yu Lu Hsiang-Yao Shih Chung-Jung Liu Meng-Chieh Wu Huang-Ming Hu Wen-Hung Hsu Fang-Jung Yu Deng-Chyang Wu Fu-chen kuo Division of Gastroenterology Department of Internal MedicineKaohsiung Medical University Hospital Department of Medicine Faculty of MedicineCollege of Medicine and Center for Stem Cell ResearchKaohsiung Medical University Department of Internal Medicine Kaohsiung Municipal Hsiao-Kang Hospital Graduate Institute of Public Health Kaohsiung Medical University School of Medicine College of MedicineE-Da HospitalI-Shou University

The known factors that have contributed to the decline of Helicobacter pylori (H. pylori) eradication rate include antibiotic resistance, poor compliance, high gastric acidity, high bacterial load, and cytochrome P450 2C19 (CYP2C19) polymorphism. Proton pump inhibitor (PPI) is important in the eradication regimen. The principal enzyme implicated in the metabolism of PPIs is CYP2C19. The effects of PPI depend on metabolic enzyme, cytochrome P450 enzymes, and CYP2C19 with genetic differences in the activity of this enzyme (the homozygous EM, heterozygous EM (HetEM), and poor metabolizer). The frequency of the CYP2C19 polymorphism is highly varied among different ethnic populations. The CYP2C19 genotype is a cardinal factor of H. pylori eradication in patients taking omeprazole- based or lansoprazole-based triple therapies. In contrast, the CYP2C19 polymorphism has no significant effect on the rabeprazole-based or esomeprazole-based triple therapies. The efficacy of levofloxacin-based rescue triple therapy might be also affected by the CYP2C19 polymorphism, but CYP2C19 genotypes did not show obvious impact on other levofloxacin-based rescue therapies. Choice of different PPIs and/or increasing doses of PPIs should be individualized based on the pharmacogenetics background of each patient and pharmacological profile of each drug. Other possible factors influencing gastric acid secretion (e.g., IL-1β- 511 polymorphism) would be also under consideration.

关键词： Helicobacter pylori CYP2C19 Polymorphism Eradication Rabeprazole Omeprazole Lansoprazole Pantoprazole Esomeprazole

pLoc_Deep-mGpos: Predict Subcellular Localization of Gram Positive Bacteria Proteins by Deep Learning

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Journal of Biomedical Science and Engineering 2020年第5期13卷 55-65页

作者： Zhe Lu kuo-chen Chou Computer Science Jingdezhen Ceramic Institute Jingdezhen China Gordon Life Science Institute Boston MA USA

The recent worldwide spreading of pneumonia-causing virus, such as Coronavirus, COVID-19, and H1N1, has been endangering the life of human beings all around the world. In order to really understand the biological process within a cell level and provide useful clues to develop antiviral drugs, information of Gram positive bacteria protein subcellular localization is vitally important. In view of this, a CNN based protein subcellular localization predictor called “pLoc_Deep-mGpos” was developed. The predictor is particularly useful in dealing with the multi-sites systems in which some proteins may simultaneously occur in two or more different organelles that are the current focus of pharmaceutical industry. The global absolute true rate achieved by the new predictor is over 99% and its local accuracy is around 92% - 99%. Both are transcending other existing state-of-the-art predictors significantly. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://***/pLoc_Deep-mGpos/, which will become a very powerful tool for developing effective drugs to fight pandemic coronavirus and save the mankind of this planet.

关键词： Pandemic Coronavirus Multi-Label System Gram Positive Proteins Learning at Deeper Level Five-Steps Rule PseAAC

iATC_Deep-mISF: A Multi-Label Classifier for Predicting the Classes of Anatomical Therapeutic Chemicals by Deep Learning

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Advances in Bioscience and Biotechnology 2020年第5期11卷 153-159页

作者： Zhe Lu kuo-chen Chou Computer Science Jingdezhen Ceramic Institute Jingdezhen China Gordon Life Science Institute Boston MA 02478 USA

The recent worldwide spreading of pneumonia-causing virus, such as Coronavirus, COVID-19, and H1N1, has been endangering the life of human beings all around the world. To provide useful clues for developing antiviral drugs, information of anatomical therapeutic chemicals is vitally important. In view of this, a CNN based predictor called “iATC_Deep-mISF” has been developed. The predictor is particularly useful in dealing with the multi-label systems in which some chemicals may occur in two or more different classes. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://***/iATC_Deep-mISF/, which will become a very powerful tool for developing effective drugs to fight pandemic coronavirus and save the mankind of this planet.

关键词： Pandemic Coronavirus Multi-Label System Anatomical Therapeutic Chemicals Learning at Deeper Level Five-Steps Rule

Cell-PLoc 2.0: an improved package of web-servers for predicting subcellular localization of proteins in various organisms

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Natural Science 2010年第10期2卷 1090-1103页

作者： kuo-chen Chou Hong-Bin Shen 不详

Cell-PLoc 2.0 is a package of web-servers evolved from Cell-PLoc (Chou, K.C. & Shen, H.B., Nature Protocols, 2008, 2:153-162) by a top-down approach to improve the power for predicting subcellular localization of proteins in various organisms. It contains six predictors: Euk-mPLoc 2.0, Hum-mPLoc 2.0, Plant-mPLoc, Gpos-mPLoc, Gneg-mPLoc, and Virus-mPLoc, specialized for eukaryotic, human, plant, Gram- positive bacterial, Gram-negative bacterial, and virus proteins, respectively. Compared with Cell-PLoc, the predictors in the Cell-PLoc 2.0 have the following advantageous features: (1) they all have the capacity to deal with the multiplex proteins that can simultaneiously exist, or move between, two or more subcellular location sites;(2) no accession number is needed for the input of a query protein even if using the “high- level” GO (gene ontology) prediction engine;(3) the functional domain information and sequential evolution information are fused into the “ab initio” sequence-based prediction engine to enhance its accuracy. In this protocol, a step- to-step guide is provided for how to use the web server predictors in the Cell-PLoc 2.0 package, which is freely accessible to the public at http://***/bioinf/Cell-PLoc-2/.

关键词： Euk-mPLoc 2.0 Hum-mPLoc 2.0 Plant-mPLoc Gpos-mPLoc Gneg-mPLoc Virus-mPLoc Higher-level GO approach Ab-initio approach Functional domain Sequential evolution

pLoc_Deep-mAnimal: A Novel Deep CNN-BLSTM Network to Predict Subcellular Localization of Animal Proteins

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Natural Science 2020年第5期12卷 281-291页

作者： Yu-Tao Shao kuo-chen Chou Computer Science Jingdezhen Ceramic Institute Jingdezhen China Gordon Life Science Institute Boston MA USA

Current coronavirus pandemic has endangered mankind life. The reported cases are increasing exponentially. Information of animal protein subcellular localization can provide useful clues to develop antiviral drugs. To cope with such a catastrophe, a CNN based animal protein subcellular localization predictor called “pLoc_Deep-mAnimal” was developed. The predictor is particularly useful in dealing with the multi-sites systems in which some proteins may simultaneously occur in two or more different organelles that are the current focus of pharmaceutical industry. The global absolute true rate achieved by the new predictor is over 92% and its local accuracy is over 95%. Both have substantially exceeded the other existing state-of-the-art predictors. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://***/pLoc_Deep-mAnimal/, which will become a very useful tool for fighting pandemic coronavirus and save the mankind of this planet.

关键词： Pandemic Coronavirus Multi-Label System Animal Proteins Learning at Deeper Level Five Steps Rule PseAAC

REVIEW : Recent advances in developing web-servers for predicting protein attributes

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Natural Science 2009年第2期1卷 63-92页

作者： kuo-chen Chou Hong-Bin Shen 不详

Recent advance in large-scale genome se-quencing has generated a huge volume of pro-tein sequences. In order to timely utilize the in-formation hidden in these newly discovered sequences, it is highly desired to develop com- putational methods for efficiently identifying their various attributes because the information thus obtained will be very useful for both basic research and drug development. Particularly, it would be even more useful and welcome if a user-friendly web-server could be provided for each of these methods. In this minireview, a sy- stematic introduction is presented to highlight the development of these web-servers by our group during the last three years.

关键词： Cell-PLoc Signal-CF Signal-3L MemType-2L EzyPred HIVcleave GPCR-CA ProtIdent QuatIdent FoldRate

pLoc_Deep-mGneg: Predict Subcellular Localization of Gram Negative Bacterial Proteins by Deep Learning

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Advances in Bioscience and Biotechnology 2020年第5期11卷 141-152页

作者： Xin-Xin Liu kuo-chen Chou Computer Science Jingdezhen Ceramic Institute Jingdezhen China Gordon Life Science Institute Boston MA 02478 USA

The recent worldwide spreading of pneumonia-causing virus, such as Coronavirus, COVID-19, and H1N1, has been endangering the life of human beings all around the world. In order to really understand the biological process within a cell level and provide useful clues to develop antiviral drugs, information of Gram negative bacterial protein subcellular localization is vitally important. In view of this, a CNN based protein subcellular localization predictor called “pLoc_Deep-mGnet” was developed. The predictor is particularly useful in dealing with the multi-sites systems in which some proteins may simultaneously occur in two or more different organelles that are the current focus of pharmaceutical industry. The global absolute true rate achieved by the new predictor is over 98% and its local accuracy is around 94% - 100%. Both are transcending other existing state-of-the-art predictors significantly. To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://***/pLoc_Deep-mGneg/, which will become a very useful tool for fighting pandemic coronavirus and save the mankind of this planet.

关键词： Pandemic Coronavirus Multi-Label System Gram Negative Bacterial Proteins Learning at Deeper Level Five-Steps Rule PseAAC