Serotype Distribution and Antimicrobial Resistance of Streptococcus pneumoniae Isolates Causing Invasive and Noninvasive Pneumococcal Diseases in Korea from 2008 to 2014

Introduction. Streptococcus pneumoniae is an important pathogen with high morbidity and mortality rates. The aim of this study was to evaluate the distribution of common serotypes and antimicrobial susceptibility of S. pneumoniae in Korea. Methods. A total of 378 pneumococcal isolates were collected from 2008 through 2014. We analyzed the serotype and antimicrobial susceptibility for both invasive and noninvasive isolates. Results. Over the 7 years, 3 (13.5%), 35 (10.8%), 19A (9.0%), 19F (6.6%), 6A (6.1%), and 34 (5.6%) were common serotypes/serogroups. The vaccine coverage rates of PCV7, PCV10, PCV13, and PPSV23 were 21.4%, 23.3%, 51.9%, and 62.4% in all periods. The proportions of serotypes 19A and 19F decreased and nonvaccine serotypes increased between 2008 and 2010 and 2011 and 2014. Of 378 S. pneumoniae isolates, 131 (34.7%) were multidrug resistant (MDR) and serotypes 19A and 19F were predominant. The resistance rate to levofloxacin was significantly increased (7.2%). Conclusion. We found changes of pneumococcal serotype and antimicrobial susceptibility during the 7 years after introduction of the first pneumococcal vaccine. It is important to continuously monitor pneumococcal serotypes and their susceptibilities

Optimization of an Empirical Model for Microorganism-Immobilized Media to Predict Nitrogen Removal Efficiency

The purpose of this study was to develop a model to predict the total nitrogen (T-N) concentration in treated wastewater effluent when microorganism-immobilized media are applied. The operational data for this study were obtained using synthetic wastewater and actual wastewater within a lab-scale reactor. The organic matter removal, nitrification, and denitrification rates were 81.8, 87, and 82.9%, respectively. These rates adequately satisfied the effluent water quality standard. The observed parameters from the lab-scale reactor operation were applied to develop the optimization model, and the model showed correlation coefficients as 0.9785 and 0.9811 for nitrification and denitrification efficiencies, respectively. The model predicted that T-N concentration could be reduced to <10 mg/L with the injection of the external carbon source. The predicted value for the T-N concentration was higher than the observed value from the lab-scale reactor, which operated under the same conditions. The model showed comparable values to the observed data, and the model seems to be useful for predicting related parameters in effluent water quality, with further development of the specifications required in the treatment facilities under various operating conditions

The Framework for Adaptive ERP Systems Using the Ontology Model of a Manufacturing Supply Chain

Recently, an ERP (Enterprise resource Planning) system has been becoming an essential S/W tool for companies to manage their business processes and manufacturing resources. As the information exchange becomes more complex, not only corporate companies but also small- and mid- sized enterprises (SMEs) are required to build an ERP system. However, for small- and middle- sized companies, the adoption of ERP systems becomes challenging due to high cost and long installation time of the system. This paper presents a novel concept of an adaptive ERP system incorporating the ontology structure of the business supply chain information. The proposed ERP installation methodology is illustrated with an example of a door-trim manufacturing company in the automotive supply chain.clos

Bayesian affordance-based agent model for wayfinding behaviors in evacuation problems

In this paper, we propose a modeling framework of rational human actions in human-environment systems by evaluating probable human actions in physical and psychological dimensions. In the affordance theoretic perspective, an environment offers certain physical and psychological limitations to filter a finite number of feasible human actions that lead to desired system states in a spatio-temporal dimension. By integrating physical and psychological constraints in human decision making processes, a value-based Bayesian-affordance model is proposed using Markov Decision Model. To this ends, two different types of filters, &apos;F1&apos; and &apos;F2&apos; are proposed, where &apos;F1&apos; is a preference-based numerical filter conceived at the planning level for psychological constraints and &apos;F2&apos; an affordance-based numerical filter at the execution level in which agent&apos;s perception of physical action availability plays a big role. Finally, a simple example based on the proposed model is illustrated to verify the proposed framework and the analysis results are discussed

Mitigation of Gastric Damage Using <i>Cinnamomum cassia</i> Extract: Network Pharmacological Analysis of Active Compounds and Protection Effects in Rats

Gastritis is a common disease worldwide that is caused by various causes such as eating habits, smoking, severe stress, and heavy drinking, as well as Helicobacter pylori infections and non-steroidal anti-inflammatory drugs. Cinnamomum cassia is a tropical aromatic evergreen tree commonly used as a natural medicine in Asia and as a functional food ingredient. Studies have reported this species’ anti-obesity, anti-diabetic, and cardiovascular disease suppression effects. We evaluated the potential effects of C. cassia using non-steroidal anti-inflammatory drugs (NSAIDs), ethanol (EtOH), and ethanol/hydrochloric acid (HCl)-induced gastric mucosal injury models. C. cassia extracts reduced the area of gastric mucosa injury caused by indomethacin, NSAID, EtOH, and EtOH/HCl. We also applied a network pharmacology-based approach to identify the active compounds, potential targets, and pharmacological mechanisms of C. cassia against gastritis. Through a network pharmacology analysis, 10 key components were predicted as anti-gastritis effect-related compounds of C. cassia among 51 expected active compounds. The NF-κB signaling pathway, a widely known inflammatory response mechanism, comprised a major signaling pathway within the network pharmacology analysis. These results suggest that the anti-gastritis activities of C. cassia may be induced via the anti-inflammatory effects of key components, which suppress the inflammation-related genes and signaling pathways identified in this study

Serotype Distribution and Antimicrobial Resistance of Streptococcus pneumoniae Isolates Causing Invasive and Noninvasive Pneumococcal Diseases in Korea from 2008 to 2014

Introduction. Streptococcus pneumoniae is an important pathogen with high morbidity and mortality rates. The aim of this study was to evaluate the distribution of common serotypes and antimicrobial susceptibility of S. pneumoniae in Korea. Methods. A total of 378 pneumococcal isolates were collected from 2008 through 2014. We analyzed the serotype and antimicrobial susceptibility for both invasive and noninvasive isolates. Results. Over the 7 years, 3 (13.5%), 35 (10.8%), 19A (9.0%), 19F (6.6%), 6A (6.1%), and 34 (5.6%) were common serotypes/serogroups. The vaccine coverage rates of PCV7, PCV10, PCV13, and PPSV23 were 21.4%, 23.3%, 51.9%, and 62.4% in all periods. The proportions of serotypes 19A and 19F decreased and nonvaccine serotypes increased between 2008 and 2010 and 2011 and 2014. Of 378 S. pneumoniae isolates, 131 (34.7%) were multidrug resistant (MDR) and serotypes 19A and 19F were predominant. The resistance rate to levofloxacin was significantly increased (7.2%). Conclusion. We found changes of pneumococcal serotype and antimicrobial susceptibility during the 7 years after introduction of the first pneumococcal vaccine. It is important to continuously monitor pneumococcal serotypes and their susceptibilities