103 research outputs found
Probiotics: an update on mechanisms of action and clinical applications
Probiotics are live microbial feed supplement and can provide health benefit to the host if administered in sufficient amounts. The most predominant species that have been used as probiotic include Lactobacilli and bifidobacteria. Proper administration of probiotics could be efficient in the treatment of various disorders. However; their mechanism of action is poorly understood. The effects of probiotics may be classified in following modes: reinforcement of the intestinal mucosal barrier against pathogens, competition with pathogens for adherence to the mucosa and epithelium, competitive exclusion of pathogenic microorganisms, production of antimicrobial substances, modulation of the immune system and interference with quorum sensing signaling. Exploration of the clinical features of probiotic strains, their modes of action and investigation based on probiotic therapy may be beneficial in treatment of various diseases
Development of cartographic styling tool to support geospatial data interoperability
Cartographic styling is a technique used to present geographic data layers in various ways, and controls the appearance of geospatial data. Current practices used to maintain and store cartographic styling are through stylesheet formats, such as Styled Layer Descriptor, Esri layer file, and QGIS Style. However, the use of these formats in current geospatial applications is limited, especially in cross-platform applications. Therefore, a geospatial data format called GeoPackage has been used in this study to provide a new technique of maintaining cartographic styling, apart from the current practices. GeoPackage is an emerging geospatial data format introduced by Open Geospatial Consortium (OGC), with features including open-standard, independent, portable, robust, and cross-platform applications. In this study, a styling extension for GeoPackage was designed and developed to support the storage of styling data. The development of styling extension involves creation of data tables that is styling data model into the existing GeoPackage data model. The main function of the styling data model is to store styling records for geographic data layers within the GeoPackage. The capabilities of the new data model were tested in cross-platform applications including Windows, Linux, and Mac operating system. The testing was limited to vector data types such as point, line, and polygon, which represent geographic data layers. Results show that GeoPackage with the built-in styling extension is capable to store styling data, which can be loaded to cross-platform applications without the need for format conversion. In addition, the extension stores styling records together with the geographical data layers in a single file format (i.e. *.gpkg), in contrast to the use of other stylesheets, which store styling records in separate file format. This is possible because GeoPackage is a cross-platform geospatial data format that supports interoperability and thus, only requires single file format. Finally, this study successfully explores the capability of GeoPackage data format in maintaining and storing cartographic styling
Distribution and Antibiotic Resistance Pattern of Bacteria Isolated from Patients with Community-acquired Urinary Tract Infections in Iran: A Cross-sectional Study
Background: Urinary tract infections (UTIs) remain the common infections diagnosed in outpatients as well as hospitalized patients. Multi-drug resistance (MDR) and extensively-drug resistance (XDR) in bacteria is an alarming problem in the world. The aim of this study was to detection of etiologic agents associated with community-acquired urinary tract infections (CA-UTIs) and investigation of antibiotic susceptibility patterns.Methods: This study was performed from September 2014 to March 2015 on outpatients, which referred to Labbafinejad Hospital Clinic, Tehran, Iran. The bacterial pathogenic diversity identified by standard laboratory methods. The antimicrobial resistance rates were performed by Kirby Bauer disc diffusion methods.Results: A total of 303 patients were enrolled in this study, from which 204 (67.3%) were female and 99 (32.5%) were male patients. Escherichia coli was the dominant species (69%), followed by Enterococcus faecalis (12.8%) and Klebsiella pneumoniae (4.6%). High resistance rate to nalidixic acid (73.8%), trimethoprim/Sulfamethoxazole (54.3%), ciprofloxacin (54.3%) in E. coli, and tetracycline (89.7%) in E. faecalis strains and high susceptibility rate to meropenem (96.6%), imipenem (95.2%), amikacin (90.4%), cefoxtin (87.6%), and nitrofurantoin (82.8%) in E. coli, and nitrofurantoin (100%) in E. faecalis strains were observed. In addition, 43.5% of the strains were multidrug-resistant (MDR).Conclusions: This study showed that E. coli was the predominant uropathogen of CA-UTIs in this geographical area. It also demonstrated the empirical treatment of urinary tract infections may be difficult due to high resistance to commonly used antibiotics. Continuous monitoring of MDR organisms and drug resistance patterns are needed to prevent treatment failure and reduce selective pressure. These findings suggest the use of nitrofurantoin, cefoxitin, and amikacin in this area of the country
Study of flagellin profiling in multidrug resistant Pseudomonas aeruginosa (MDRPA) isolated from burn wound infections, Tehran, Iran
Nosocomial infections of multidrug-resistant Pseudomonas aeruginosa (MDRPA) are a growing concern in hospitalized patients in burn centers. The aim of this study was to investigate the flagellin profiling and antibiotic susceptibility of P. aeruginosa isolated from burn wound infections. During 8 month study, 73 clinically P. aeruginosa isolates collected from patients hospitalized in burn ward. P. aeruginosa isolates were identified using standard laboratory procedures. In vitro susceptibility of clinical isolates of P. aeruginosa to 6 antimicrobial agents were investigated by Clinical and Laboratory Standards Institute (CLSI 2012) Kirby-Bauer disk diffusion assay. The frequency of different type of flagellin was investigated by using specific primers and by PCR method. The resistance rates of our isolates to 6 tested antimicrobial agents were relatively high. Imipenem has good activity while tobramycin and ciprofloxacin do not have any effect on P. aeruginosa isolates. Of 73 isolates 59 (80.8%) were multidrug resistant. Twenty eight of 73 isolates were resistant to all antibiotics. Agarose gel electrophoresis of chromosomal DNA exhibited that 59 isolates (80.8%) of P. aeruginosa had type A flagellin while only 14 isolates (19.2%) had type b flagellin. Given the antibiotic failure treatment, it appears that alternative ways such as immunity to prevent of these infections could be informative. Our survey of flagellin profiling of multidrug-resistant P. aeruginosa isolates exhibited high frequency of type a flagellin as a major virulence factor has important role of immunity against infections caused by MDRPA. Functional surveillance of multidrug-resistant P. aeruginosa in order to prevention of resistance dissemination is necessary.
Distribution and Antibiotic Resistance Pattern of Bacteria Isolated from Patients with Community-acquired Urinary Tract Infections in Iran: A Cross-sectional Study
Background: Urinary tract infections (UTIs) remain the common infections diagnosed in outpatients as well as hospitalized patients. Multi-drug resistance (MDR) and extensively-drug resistance (XDR) in bacteria is an alarming problem in the world. The aim of this study was to detection of etiologic agents associated with community-acquired urinary tract infections (CA-UTIs) and investigation of antibiotic susceptibility patterns.Methods: This study was performed from September 2014 to March 2015 on outpatients, which referred to Labbafinejad Hospital Clinic, Tehran, Iran. The bacterial pathogenic diversity identified by standard laboratory methods. The antimicrobial resistance rates were performed by Kirby Bauer disc diffusion methods.Results: A total of 303 patients were enrolled in this study, from which 204 (67.3%) were female and 99 (32.5%) were male patients. Escherichia coli was the dominant species (69%), followed by Enterococcus faecalis (12.8%) and Klebsiella pneumoniae (4.6%). High resistance rate to nalidixic acid (73.8%), trimethoprim/Sulfamethoxazole (54.3%), ciprofloxacin (54.3%) in E. coli, and tetracycline (89.7%) in E. faecalis strains and high susceptibility rate to meropenem (96.6%), imipenem (95.2%), amikacin (90.4%), cefoxtin (87.6%), and nitrofurantoin (82.8%) in E. coli, and nitrofurantoin (100%) in E. faecalis strains were observed. In addition, 43.5% of the strains were multidrug-resistant (MDR).Conclusions: This study showed that E. coli was the predominant uropathogen of CA-UTIs in this geographical area. It also demonstrated the empirical treatment of urinary tract infections may be difficult due to high resistance to commonly used antibiotics. Continuous monitoring of MDR organisms and drug resistance patterns are needed to prevent treatment failure and reduce selective pressure. These findings suggest the use of nitrofurantoin, cefoxitin, and amikacin in this area of the country
Adaptive background reconstruction for street surveillance
In recent years, adaptive background reconstruction works have found interest in many researchers. However, the existing algorithms that have been proposed by other researchers still in the early stage of development and many aspects need to be improved. In this paper, an adaptive background reconstruction is presented. Past pixel observation is used. The proposed algorithm also has eliminated the need of the pre-training of non-moving objects in the background. The proposed algorithm is capable of reconstructing the background with moving objects in video sequence. Experimental results show that the proposed algorithms are able to reconstruct the background correctly and handle illumination and adverse weather that modifies the background
Geopackage as future ubiquitous GIS data format: a review
The emerging geospatial technologies in earth and space science informatics have led to the advancement in developing international standards for geospatial interoperability. In the last few years, two main trends are making disruptions in geospatial applications; mobile and context sharing. Geospatial data format used in mobile GIS to support advance mobile application is challenged. This is due to the lack of interoperability, open-standard, cross platform and standard APIs for access and management. For instance, most mobile GIS developments are application-dependent, contains redundant geospatial data, consume large storage capacity, and require custom applications for data translation. Based on these issues, new OGC file format named GeoPackage will enable greater geospatial data sharing on mobile and web platform. This data format is an open standard, non-proprietary, platform-independent, container for distribution, and direct use of all kinds of geospatial data will increase cross-platform interoperability, geospatial applications and web services. This presents a comprehensive review of mobile GIS hence, the concept of GeoPackage as a modern geospatial tool was discussed, while its relevance in contemporary geospatial technology are highlighted
Analysis on background subtraction for street surveillance
Background subtraction is a well-known technique used in computer vision applications. However, in public surveillance system, the utilization of background subtraction still new and far from being solved. Insufficient analysis of the background subtraction algorithms made the situation getting worse. The analysis of the commonly-used algorithms is presented in this paper. Experiments are conducted to quantitatively evaluate the performance of the algorithms by using three video sequences. The more suitable algorithm for various conditions is expected to be presented as the results in this paper
Moving object detection and classification using neuro-fuzzy approach
Public surveillance monitoring is rapidly finding its way into Intelligent Surveillance System. Street crime is increasing in recent years, which has demanded more reliable and intelligent public surveillance system. In this paper, the ability and the accuracy of an Adaptive Neuro-Fuzzy Inference System (ANFIS) was investigated for the classification of moving objects for street scene applications. The goal of this paper is to classify the moving objects prior to its communal attributes that emphasize on three major processes which are object detection, discriminative feature extraction, and classification of the target. The intended surveillance application would focus on street scene, therefore the target classes of interest are pedestrian, motorcyclist, and car. The adaptive network based on Neuro-fuzzy was independently developed for three output parameters, each of which constitute of three inputs and 27 Sugeno-rules. Extensive experimentation on significant features has been performed and the evaluation performance analysis has been quantitatively conducted on three street scene dataset, which differ in terms of background complexity. Experimental results over a public dataset and our own dataset demonstrate that the proposed technique achieves the performance of 93.1% correct classification for street scene with moving objects, with compared to the solely approaches of neural network or fuzzy
Intelligent surveillance system for street surveillance
CCTV surveillance systems are widely used as a street monitoring tool in public and private areas. This paper presents a novel approach of an intelligent surveillance system that consists of adaptive background modelling, optimal trade-off features tracking and detected moving objects classification. The proposed system is designed to work in real-time. Experimental results show that the proposed background modelling algorithms are able to reconstruct the background correctly and handle illumination and adverse weather that modifies the background. For the tracking algorithm, the effectiveness between colour, edge and texture features for target and candidate blobs were analysed. Finally, it is also demonstrated that the proposed object classification algorithm performs well with different classes of moving objects such as, cars, motorcycles and pedestrians
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