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Polymorphism of -765G > C COX-2 is a risk factor for gastric adenocarcinoma and peptic ulcer disease in addition to H pylori infection:A study from northern India

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World Journal of Gastroenterology 2008年第10期14卷 1498-1503页

作者： Ashish Saxena kashi nath prasad Uday Chand Ghoshal Monty Roshan Bhagat Narendra Krishnani Nuzhat Husain Department of Microbiology Sanjay Gandhi Postgraduate Institute of Medical Sciences Lucknow 226014 India Department of Gastroenterology Sanjay Gandhi Postgraduate Institute of Medical Sciences Lucknow 226014 India Department of Gastroenterology CentralCommand Hospital Lucknow 226002 India Department of Pathology Sanjay GandhiPostgraduate Institute of Medical Sciences Lucknow 226014India Department of Pathology Chhatrapati Shahu Ji Maharaj Medical University Lucknow 226001 India

AIM: To investigate -765G > C COX-2 polymorphism and H pylori infection in patients with gastric adenocarcinoma, peptic ulcer disease (PUD) and non- ulcer dyspepsia (NUD). METHODS: We enrolled 348 adult patients (62 gastric adenocarcinoma, 45 PUD and 241 NUD) undergoing upper gastrointestinal endoscopy at two referral centers between September, 2002 and May, 2007. H pylori infection was diagnosed when any of the four tests (RUT, culture, histopathology and PCR) were positive. Genotyping for -765G > C polymorphism of COX-2 was performed by PCR-RFLP analysis. RESULTS: Frequency of C carrier had significantassociation with gastric adenocarcinoma as compared to NUD [77.4% vs 29%, P C COX-2 polymorphism with or without H pylori could be a marker for genetic susceptibility to gastric adenocarcinoma. COX-2 polymorphism in presence of H pylori infection might be useful in predicting the risk of PUD.

关键词： COX-2 polymorphism Gastric adenocarcinoma Peptic ulcer disease Helicobacter pylori infection

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Role of Helicobacter pylori in gastric cancer:Updates

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World Journal of Gastrointestinal Oncology 2016年第2期8卷 147-158页

作者： Jahanarah Khatoon Ravi Prakash Rai kashi nath prasad department of microbiology sanjay gandhi postgraduate institute of medical sciencesLucknowUttar Pradesh 226014India

Helicobacter pylori(H. pylori) infection is highly prevalent in human,affecting nearly half of the world's population; however,infection remains asymptomatic in majority of population. During its co-existence with humans,H. pylori has evolved various strategies to maintain a mild gastritis and limit the immune response of host. On the other side,presence of *** is also associated with increased risk for the development of various gastric pathologies including gastric cancer(GC). A complex combination of host genetics,environmental agents,and bacterial virulence factors are considered to determine the susceptibility as well as the severity of outcome in a subset of individuals. GC is one of the most common cancers and considered as the third most common cause of cancer related death worldwide. Many studies had proved H. pylori as an important risk factor in the development of non-cardia GC. Although both H. pylori infection and GC are showing decreasing trends in the developed world,they still remain a major threat to human population in the developing countries. The current review attempts to highlight recent progress in the field of research on H. pylori induced GC and aims to provide brief insight into H. pylori pathogenesis,the role of major virulence factors of H. pylori that modulates the host environment and transform the normal gastric epithelium to neoplastic one. This review also emphasizes on the mechanistic understanding of how colonization and various virulence attributes of H. pylori as well as the host innate and adaptive immune responses modulate the diverse signaling pathways that leads to different disease outcomes including GC.

关键词： Cag pathogenicity island Gastric cancer Gastric mucosa Helicobacter pylori Type Ⅳ secretionsystem

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Forecasting of Software Reliability Using Neighborhood Fuzzy Particle Swarm Optimization Based Novel Neural Network

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IEEE/CAA Journal of Automatica Sinica 2019年第6期6卷 1365-1383页

作者： Pratik Roy Ghanshaym Singha Mahapatra kashi nath Dey Department of Computer Science and Engineering University of CalcuttaKolkata-700106India Department of Mathematics National Institute of TechnologyPuducherryKaraikal-609609India

This paper proposes an artificial neural network(ANN) based software reliability model trained by novel particle swarm optimization(PSO) algorithm for enhanced forecasting of the reliability of software. The proposed ANN is developed considering the fault generation phenomenon during software testing with the fault complexity of different levels. We demonstrate the proposed model considering three types of faults residing in the software. We propose a neighborhood based fuzzy PSO algorithm for competent learning of the proposed ANN using software failure data. Fitting and prediction performances of the neighborhood fuzzy PSO based proposed neural network model are compared with the standard PSO based proposed neural network model and existing ANN based software reliability models in the literature through three real software failure data sets. We also compare the performance of the proposed PSO algorithm with the standard PSO algorithm through learning of the proposed ANN. Statistical analysis shows that the neighborhood fuzzy PSO based proposed neural network model has comparatively better fitting and predictive ability than the standard PSO based proposed neural network model and other ANN based software reliability models. Faster release of software is achievable by applying the proposed PSO based neural network model during the testing period.

关键词： Artificial neural network(ANN) fuzzy particle swarm optimization(PSO) reliability prediction software reliability

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