Comparison of combined disc synergy test and double disc synergy test for phenotypic detection of metallo-ß-lactamase among the clinical isolates of gram-negative bacilli

Background: Metallo-β-lactamases (MBL) have a wide spectrum of activity and they confer a higher level of resistance to all β-lactams antibiotics including Carbapenem. The active site in MBLs contains either 1 or 2 Zn2+ ions for their catalytic mechanism. All MBLs share a common feature of being inhibited by EDTA. Metallo-β-lactamase-producing gram-negative bacteria are the most important nosocomial pathogens. The present study was conducted to detect Metallo-β-lactamase (MBL) production in gram-negative bacilli by Combined Disc Synergy Test (CDST) and Double Disc Synergy Test (DDST) with 0.1M EDTA as a chelator and to see their antibiotic susceptibility pattern of them.Methods: The cross-sectional observational study was carried out in the Department of Microbiology, Chittagong Medical College, during the period of July 2015 to June 2016. Samples were collected from patients admitted to CMCH. Standard Microbiological procedures and biochemical tests were carried out for the isolation and identification of MBL. SPSS software is used for data analysis.Results: When 66 screening positive MBL isolates were subjected to the phenotypic confirmatory test CDST detected 50 (25.4%) and DDST detected 48 (24.4%) as MBL producers. Among these isolates, we found Acinetobacter spp. 7 (100%), as the leading MBL producer followed by Pseudomonas spp. 16 (32.6%), E. coli 10 (20%) and Klebsiella spp. 15 (17.4%).Conclusions: In a laboratory where multiplex PCR molecular set-up is not available CDST and DDST are convenient phenotypic methods and can be implemented in routine microbiological laboratories as well as in primary health care setup for daily application to monitor the production of MBLs

Relationship between weather variables and new daily covid-19 cases in Dhaka, Bangladesh

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. The present study investigated the relationship between the transmission of COVID-19 infections and climate indicators in Dhaka, Bangladesh, using coronavirus infections data available from the Institute of Epidemiology, Disease Control and Research (IEDCR), Bangladesh. The Spearman rank correlation test was carried out to study the association of seven climate indicators, including humidity, air quality, minimum temperature, precipitation, maximum temperature, mean temperature, and wind speed with the COVID-19 outbreak in Dhaka, Bangladesh. The study found that, among the seven indicators, only two indicators (minimum temperature and average temperature) had a significant relationship with new COVID-19 cases. The study also found that air quality index (AQI) had a strong negative correlation with cumulative cases of COVID-19 in Dhaka city. The results of this paper will give health regulators and policymakers valuable information to lessen the COVID-19 spread in Dhaka and other countries around the world

Efficacy of pre- and post-emergence herbicide combinations on weed control in no-till mechanically transplanted rice

No-till mechanized-transplanted rice was evaluated for different combinations of pre- and post-emergence herbicides to determine feasible, economically viable weed management options to control complex weed flora in rice fields. All pre-emergence herbicides significantly reduced the population of grassy weeds; of these, pendimethalin resulted in the greatest reductions (83%) at 15 days after transplanting (DAT). Among five post-emergence herbicide treatments, the combination of bispyribac-sodium (10%SP) + pyrazosulfuron (10%WP) was found to be the most effective in controlling all weed flora at both 35 and 55 DAT. The sequential application of pendimethalin (pre-emergence) followed bispyribac-sodium + pyrazosulfuron (post-emergence) resulted in significantly higher rice grain yield (4.4 t-ha−1) and relative gross-margin (417 USD-ha−1) than all other treatments. A strong negative correlation was observed between rice grain yield and weed biomass, and a strong positive correlation between rice grain yield and weed control efficiency. Our findings demonstrate the potential to combine pre- and post-emergence herbicides in no-till mechanized-transplanted rice; these findings have applications globally in regions where rice is established by no-till or mechanized transplanting

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Additional file 4: of Globular domain structure and function of restriction-like-endonuclease LINEs: similarities to eukaryotic splicing factor Prp8

Glu C mapping data (internal peptides). (PDF 541 kb

Additional file 5: of Globular domain structure and function of restriction-like-endonuclease LINEs: similarities to eukaryotic splicing factor Prp8

List of Glu C and Lys C sites with early vs. later designations. (XLSX 482 kb

BONIK: A Blockchain Empowered Chatbot for Financial Transactions

A Chatbot is a popular platform to enable users to interact with a software or website to gather information or execute actions in an automated fashion. In recent years, chatbots are being used for executing financial transactions, however, there are a number of security issues, such as secure authentication, data integrity, system availability and transparency, that must be carefully handled for their wide-scale adoption. Recently, the blockchain technology, with a number of security advantages, has emerged as one of the foundational technologies with the potential to disrupt a number of application domains, particularly in the financial sector. In this paper, we forward the idea of integrating a chatbot with blockchain technology in the view to improve the security issues in financial chatbots. More specifically, we present BONIK, a blockchain empowered chatbot for financial transactions, and discuss its architecture and design choices. Furthermore, we explore the developed Proof-of-Concept (PoC), evaluate its performance, analyse how different security and privacy issues are mitigated using BONIK.Peer reviewe

Comparative and network-based proteomic analysis of low dose ethanol- and lipopolysaccharide-induced macrophages

<div><p>Macrophages are specialized phagocytes that play an essential role in inflammation, immunity, and tissue repair. Profiling the global proteomic response of macrophages to microbial molecules such as bacterial lipopolysaccharide is key to understanding fundamental mechanisms of inflammatory disease. Ethanol is a widely abused substance that has complex effects on inflammation. Reports have indicated that ethanol can activate or inhibit the lipopolysaccharide receptor, Toll-like Receptor 4, in different settings, with important consequences for liver and neurologic inflammation, but the underlying mechanisms are poorly understood. To profile the sequential effect of low dose ethanol and lipopolysaccharide on macrophages, a gel-free proteomic technique was applied to RAW 264.7 macrophages. Five hundred four differentially expressed proteins were identified and quantified with high confidence using ≥ 5 peptide spectral matches. Among these, 319 proteins were shared across all treatment conditions, and 69 proteins were exclusively identified in ethanol-treated or lipopolysaccharide-stimulated cells. The interactive impact of ethanol and lipopolysaccharide on the macrophage proteome was evaluated using bioinformatics tools, enabling identification of differentially responsive proteins, protein interaction networks, disease- and function-based networks, canonical pathways, and upstream regulators. Five candidate protein coding genes (PGM2, ISYNA1, PARP1, and PSAP) were further validated by qRT-PCR that mostly related to glucose metabolism and fatty acid synthesis pathways. Taken together, this study describes for the first time at a systems level the interaction between ethanol and lipopolysaccharide in the proteomic programming of macrophages, and offers new mechanistic insights into the biology that may underlie the impact of ethanol on infectious and inflammatory disease in humans.</p></div

Synthesis and characterization of reduced graphene oxide and their application in dye-sensitized solar cells

Reduced graphene oxide has certain unique qualities that make them versatile for a myriad of applications. Unlike graphene oxide, reduced graphene oxide is a conductive material and well suited for use in electrically conductive materials, such as solar cell devices. In this study, we report on the synthesis of graphene oxide as well as the fabrication and characterization of dye-sensitized solar cells with a photoanode which is an amalgam of reduced graphene oxide and titanium dioxide. The synthesized reduced graphene oxide and the corresponding photoanode were fully characterized using Ultraviolet-visible, Fourier transform infrared (FTIR), and Raman Spectrometry. The morphology of the sample was assessed using Atomic Force Microscopy, Field Emission Scanning Electron Microscopy, Transmission Electron Microscopy, and Energy Dispersive X-ray Spectroscopy. The photovoltaic characteristics were determined by photocurrent and photo-voltage measurements of the fabricated solar cells. The electrical impedances of both sets of devices were also evaluated. Overall, the solar to electric power efficiency of the device with reduced graphene oxide was observed to be higher (2.02%) than the device without the reduced graphene oxide (1.61%)