Webinar among Indonesian academics during Covid-19, embracing the audiences.

This research aims to find out the phenomenon of webinar competition from the viewpoint of the audience. Covid-19 pandemic makes webinars a means for knowledge dissemination. Many events offered turned out to be a tight competition among organizers and caused a different response for the audience. Academics participants' responses had never been known in depth so that they could be the basis for determining the strategy for the organizers. Using quantitative data through online surveys to further interpreted with the help of previous literature. The independent variables gender, age, frequency, cost, and place are used to determine their effect on loyalty, which is represented by the length of duration in participating in each webinar. The effectiveness of webinars as a means of disseminating ideas in the pandemic era still faces various challenges. Among academics, the loyalty at the webinar event is influenced by gender and age. It is important for organizers to effectively communicate to webinar participants so that they get the message they want to convey.

High abundance of the colistin resistance gene mcr-1 in chicken gut-bacteria in Bangladesh.

Colistin is considered a last-resort reserved drug for the treatment of critical human infections by Gram-negative bacteria. Phenotypic colistin-resistance is strongly associated with plasmid-mediated mobile colistin resistance (mcr) genes. The mcr-bearing Enterobacteriaceae have been detected in many countries from environments, animals, and humans. This study investigated phenotypic colistin-resistance and the distribution of mcr-1, mcr-2, mcr-3, mcr-4, and mcr-5 genes in chicken-gut bacteria in Bangladesh. Bacteria were isolated from poultry- and native-chicken droppings, and their susceptibilities to colistin were determined by agar dilution and E-test minimal inhibitory concentration (MIC) measurements. Multiplex polymerase chain reactions detected mcr-1 to mcr-5 genes. Overall, 61.7% (92/149) of the isolates showed colistin resistance by agar dilution assessment (MIC > 2.0 µg/mL). The phenotypic resistance was observed considerably higher in poultry-chicken isolates (64.6%, 64/99) than in native-chicken isolates (56%, 28/50; p = 0.373). All the resistant isolates showed MIC levels between > 2 and > 128 µg/mL. The mcr-genes (mcr-1and mcr-2 combined) were detected more in poultry gut bacteria (36.4%) than native-chicken isolates (20%, p = 0.06). Despite bacteria sources, mcr-genes appeared to be significantly associated with phenotypic colistin-resistance phenomena (p < 0.001). Prior colistin usage led to a substantial increase in the proportion of bacteria with mcr-genes and phenotypic resistance (p < 0.001).

Genotypic to Phenotypic Resistance Discrepancies Identified Involving ß-Lactamase Genes, blaKPC, blaIMP, blaNDM-1, and blaVIM in Uropathogenic Klebsiella pneumoniae.

INTRODUCTION: Klebsiella pneumoniae carbapenemase (KPC) belongs to the Group-A ß-lactamases that incorporate serine at their active site and hydrolyze various penicillins, cephalosporins, and carbapenems. Metallo-beta-lactamases (MBLs) are group-B enzymes that contain one or two essential zinc ions in the active sites and hydrolyze almost all clinically available ß-lactam antibiotics. Klebsiella pneumoniae remains the pathogen with the most antimicrobial resistance to KPC and MBLs. METHODS: This research investigated the blaKPC, and MBL genes, namely, blaIMP, blaVIM, and blaNDM-1 and their phenotypic resistance to K. pneumoniae isolated from urinary tract infections (UTI) in Bangladesh. Isolated UTI K. pneumoniae were identified by API-20E and 16s rDNA gene analysis. Their phenotypic antimicrobial resistance was examined by the Kirby-Bauer disc diffusion method, followed by minimal inhibitory concentration (MIC) determination. blaKPC, blaIMP, blaNDM-1, and blaVIM genes were evaluated by polymerase chain reactions (PCR) and confirmed by sequencing. RESULTS: Fifty-eight K. pneumoniae were identified from 142 acute UTI cases. Their phenotypic resistance to amoxycillin-clavulanic acid, cephalexin, cefuroxime, ceftriaxone, and imipenem were 98.3%, 100%, 96.5%, 91.4%, 75.1%, respectively. Over half (31/58) of the isolates contained either blaKPC or one of the MBL genes. Individual prevalence of blaKPC, blaIMP, blaNDM-1, and blaVIM were 15.5% (9), 10.3% (6), 22.4% (13), and 19% (11), respectively. Of these, eight isolates (25.8%, 8/31) were found to have two genes in four different combinations. The co-existence of the ESBL genes generated more resistance than each one individually. Some isolates appeared phenotypically susceptible to imipenem in the presence of blaKPC, blaIMP, blaVIM, and blaNDM-1 genes, singly or in combination. CONCLUSION: The discrepancy of genotype and phenotype resistance has significant consequences for clinical bacteriology, precision in diagnosis, the prudent selection of antimicrobials, and rational prescribing. Heterogeneous phenotypes of antimicrobial susceptibility testing should be taken seriously to avoid inappropriate diagnostic and therapeutic decisions.

An Accurate QRS complex and P wave Detection in ECG Signals using Complete Ensemble Empirical Mode Decomposition Approach.

We developed a novel method for QRS complex and P wave detection in the electrocardiogram (ECG) signal. The approach reconstructs two different signals for the purpose of QRS and P wave detection from the modes obtained by the complete ensemble empirical mode decomposition with adaptive noise, taking only those modes that best represent the signal dynamics. This approach eliminates the need for conventional filtering. We first detect QRS complex locations, followed by removal of QRS complexes from the reconstructed signal to enable P wave detection. We introduce a novel method of P wave detection from both the positive and negative amplitudes of the ECG signal and an adaptive P wave search approach to find the true P wave. Our detection method automatically identifies P waves without prior information. The proposed method was validated on two well-known annotated databases-the MIT BIH Arrythmia database (MITDB) and The QT database (QTDB). The QRS detection algorithm resulted in 99.96% sensitivity, 99.9% positive predictive value, and an error of 0.13% on all validation databases. The P wave detection method had better performance when compared to other well-known methods. The performance of our P wave detection on the QTDB showed a sensitivity of 99.96%, a positive predictive value of 99.47%, and the mean error in P peak detection was less than or equal to one sample (4 ms) on average.