ABSTRACT
Klebsiella pneumoniae is a common bacterial pathogen causes wide range of infections all over the world. The antimicrobial resistance of K. pneumoniae is a global concern and expresses several virulence factors contributing to the pathogenesis. The incidences of bacterial co-infection in viral pneumonia are common. Increased risk of K. pneumoniae co-infection in viral respiratory tract infection should be alerted in COVID-19 pandemic period. The study aims to detect the association between antimicrobial resistance and factors causing pathogenicity of K. pneumoniae. For the current study, 108 K. pneumoniae clinical isolates were included. Antimicrobial susceptibility test was done by Kirby-Bauer disc diffusion method according to CLSI guidelines. Virulence factors such as biofilm formation, haemagglutination, haemolysins, hypermucoviscocity, siderophore, amylase, and gelatinase production were determined by phenotypic method. In this study K. pneumoniae showed high level of antimicrobial resistance towards ampicillin (92.59%) followed by amoxicillin-clavulanic acid (67.59%) and cotrimoxazole (47,22%). An important association between biofilm formation and antimicrobial resistance was found to be statistically significant for cotrimoxazole (P-value 0.036) and amoxicillin-clavulanic acid (P-value 0.037). Other virulence factors like hypermucoviscocity, haemagglutination, amylase, and siderophore production were also showed a statistically significant relation (P-value <0.05) with antimicrobial resistance. Further molecular studies are necessary for the identification of virulence and antimicrobial resistance genes, for the effective control of drug-resistant bacteria.
ABSTRACT
Today our whole world is entangled with the most dreadful disease Corona which is caused by the successor of SARS known as SARS-Cov-2 virus. Coronavirus is the influenza-like respiratory disease causing damage to the respiratory system of the humans through the ACE2 receptors which acts as an entry gate for the virus to enter. The Corona virus was identified in late 2019 in the city of Wuhan, China which later spread to the most of the territories in China. The spread was first identified by the Bluedot which is a Saas service designed to track and detect the spread of infectious disease. When the other countries came to know the severity of the virus they made various steps to prevent the spread of the virus. The initial symptoms of coronavirus are rise in temperature, loss of taste and smell and short breathness. As the entry level check many institutions and offices, checks the body temperature of the people and checks whether the person is wearing a mask or not. To make this process fully automatic without human intervention the use of AI enabled IR camera sensor with the Arduino UNO is made. The detection of temperature can be made possible by the use of the computer leveraging vision techniques which is equipped with the Raspberry-pi camera module. The process is based on the thermal imaging of the person which can detect the elevated temperature of the person and prevents them from entering into the institution or offices thereby the spread due to the possibly affected persons can be avoided thereby the spread can be controlled. The system not only identifies the person with high temperature but also checks whether the person is wearing a mask or not. The real time analysis of the system is the major advantage of the proposed system.