Complete genome sequence of hepatitis B virus identified from a patient suffering from chronic kidney disease in Bangladesh.

Hepatitis B virus (HBV) infection is reported as a risk factor for chronic kidney disease (CKD). In this study, we sequenced the complete genome of an HBV strain identified in a CKD patient in Bangladesh, followed by genomic characterization and mutational analyses.

Development of membrane protein-based vaccine against lumpy skin disease virus (LSDV) using immunoinformatic tools.

INTRODUCTION: Lumpy skin disease, an economically significant bovine illness, is now found in previously unheard-of geographic regions. Vaccination is one of the most important ways to stop its further spread. AIM: Therefore, in this study, we applied advanced immunoinformatics approaches to design and develop an effective lumpy skin disease virus (LSDV) vaccine. METHODS: The membrane glycoprotein was selected for prediction of the different B- and T-cell epitopes by using the immune epitope database. The selected B- and T-cell epitopes were combined with the appropriate linkers and adjuvant resulted in a vaccine chimera construct. Bioinformatics tools were used to predict, refine and validate the 2D, 3D structures and for molecular docking with toll-like receptor 4 using different servers. The constructed vaccine candidate was further processed on the basis of antigenicity, allergenicity, solubility, different physiochemical properties and molecular docking scores. RESULTS: The in silico immune simulation induced significant response for immune cells. In silico cloning and codon optimization were performed to express the vaccine candidate in Escherichia coli. This study highlights a good signal for the design of a peptide-based LSDV vaccine. CONCLUSION: Thus, the present findings may indicate that the engineered multi-epitope vaccine is structurally stable and can induce a strong immune response, which should help in developing an effective vaccine towards controlling LSDV infection.

Determinants of household adoption of clean energy with its rural-urban disparities in Bangladesh.

This study aims to investigate factors influencing the adoption of clean energy among households in Bangladesh, using Blinder-Oaxaca decomposition and extended probit regression model with data from the 2019 Bangladesh multiple indicator cluster survey. Small households, primarily Muslim and urban dwellers, who speak the Bengali language and are Internet and mobile users, were likelier to adopt cleaner fuels than their counterparts. On the contrary, households residing in the Barisal, Khulna, Rajshahi, and Rangpur divisions, belonging to poor and middle-class households, with household heads aged 15-64 and without formal education, were less likely to adopt cleaner fuels than their counterparts. The concentration curve revealed socioeconomic inequality in the adoption of clean energy, particularly favouring richer households in urban and rural areas. Further analysis using the Blinder-Oaxaca decomposition showed that urban residents showed a higher probability of adopting clean energy, with a significant difference of 0.508 compared to rural areas. Regarding the endowment effect, poor wealth quintile contributed the most, followed by the ownership of rented dwellings and the middle wealth quintile. The Bengali differential effect made the largest contribution to this aspect of the disparity, followed by the exposure of the Internet and the influence of the Dhaka and Chattogram divisions. The detailed analysis provides valuable insights for policymakers and practitioners on the issue of disparities in the adoption of clean energy between urban and rural areas in Bangladesh.

Appraisal of stormwater-induced runoff quality influenced by site-specific land use patterns in the south-eastern region of Bangladesh.

Urban stormwater runoff is considered as one of the major contributors to nonpoint source that contributes to the pollution of all water resources in the surrounding environment. Pollutant concentrations of urban stormwater runoff are directly or indirectly linked with land use types in a catchment that is quite different in different places, and hence, site-specific studies are necessary, unless otherwise the modelling of runoff quality using modelling tools may not be rationally reflected the actual field scenarios. This paper portrays the influence of land use types on stormwater runoff physicochemical quality in Chattogram city, where land use's demarcation is often complicated due to the different natural and human-induced anthropogenic factors. The stormwater runoff samples were collected from the residential, commercial, institutional, and industrial land use types, in the city of Chattogram, Bangladesh, during the period from July to September 2020. The standard laboratory protocol for elemental concentrations and principal component analysis was performed in addition to basic statistics to identify the influence of urban surface characteristics on the quality of stormwater runoff. In general, pollutant concentrations were identified by analysing key physical and chemical quality parameters including colour, temperature, turbidity, total suspended solids (TSS), total dissolved solids (TDS), electrical conductivity (EC), salinity, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD5), chemical oxygen demand (COD) and ammonia nitrogen (NH3-N) and exhibited 2 to 3 times higher concentrations than reported elsewhere. Furthermore, the present study reported the greater concentrations of few pollutants, such as TSS, BOD5, and EC, derived from the residential land uses compared to other land use types that are surprising; however, it confirmed the distinct complexity of unplanned land use patterns that should not be overlooked rather discussed. The strong correlation between land use types and stormwater runoff quality indicates the site-specific influences of runoff quality. The outcomes of this study would be particularly helpful in calibrating water quality models considering different land use types. Additionally, datasets and information obtained from this research will assist engineers and practitioners in developing decision-making tools for effective stormwater management.

Keystroke Dynamics based Hybrid Nanogenerators for Biometric Authentication and Identification using Artificial Intelligence.

Cyberattack is one of the severe threats in the digital world as it encompasses everything related to personal information, health, finances, intellectual properties, and even national security. Password-based authentication is the most practiced authentication system, however, is vulnerable to several attacks such as dictionary attack, shoulder surfing attack, and guessing attack. Here, a new keystroke dynamics-based hybrid nanogenerator for biometric authentication and identification integrated with artificial intelligence (AI) is reported. Keystroke dynamics offer behavioral and contextual information that can distinguish and authorize the individuals based on their typing rhythms. The hybrid electromagnetic-triboelectric nanogenerators/sensors efficiently convert the keystroke mechanical energy into electrical signals, which are fed into an artificial neural network based AI system. The self-powered hybrid sensors-based biometric authentication system integrated with a neural network achieves an accuracy of 99% and offers a promising hybrid security layer against password vulnerability.

First Detection of Batrachochytrium dendrobatidis in Wild Frogs from Bangladesh.

Global amphibian populations are facing a novel threat, chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis (Bd), which is responsible for the severe decline of a number of species across several continents. Chytridiomycosis in Asia is a relatively recent discovery yet there have been no reports on Bd-presence in Bangladeshi amphibians. We conducted a preliminary study on 133 wild frogs from seven sites in Bangladesh between April and July 2018. Nested PCR analysis showed 20 samples (15.04%) and 50% of the tested taxa (9 species from 6 genera and 4 families) as Bd-positive. Eight of the nine species are discovered as newly infected hosts. Analysis of Bd-positive samples shows prevalence does not significantly vary among different land cover categories, although the occurrence is higher in forested areas. The prevalence rate is similar in high and low disturbed areas, but the range of occurrence is statistically higher in low disturbance areas. Maximum entropy distribution modeling indicates high probabilities of Bd occurrence in hilly and forested areas in southeast and central-north Bangladesh. The Bd-specific ITS1-5.8S-ITS2 ribosomal gene sequence from the Bd-positive samples tested is completely identical. A neighbor-joining phylogenetic tree reveals that the identified strain shares a common ancestry with strains previously discovered in different Asian regions. Our results provide the first evidence of Bd-presence in Bangladeshi amphibians, inferring that diversity is at risk. The effects of environmental and climatic factors along with quantitative PCR analysis are required to determine the infection intensity and susceptibility of amphibians in the country.

Knowledge, Attitudes and Practices Regarding Antibiotic Use and Resistance among Veterinary Students in Bangladesh.

The use of antibiotics in animals for both therapeutic and non-therapeutic purposes is a major driver of the emergence and spread of antimicrobial resistance (AMR). While several studies have investigated prescription and consumption patterns in humans, little attention has been paid to the veterinary sector. A cross-sectional study was conducted in 3002 veterinary students (VS) and non-medical students (NMS) from 12 universities in Bangladesh to explore their knowledge, attitudes and practices (KAP) about antibiotics and AMR using a self-administered questionnaire, and assess the influence of the veterinary curriculum. KAP regarding antibiotic use and AMR was significantly higher in veterinary than non-medical students, and in first-year than final-year students. However, gaps in knowledge and practices were highlighted, suggesting deficiencies in training. Moreover, final-year veterinary students were found to be more likely than first-year students to use antibiotics without instructions, which could indicate deficiencies in their curriculum. Although the study suggested a positive impact of the veterinary curriculum on KAP about antibiotics and AMR in Bangladesh, critical gaps remain that are likely to contribute to inadequate use in their future practice. Therefore, there is scope for improving educational programs on AMR in professional curricula.

Molecular Detection of Multidrug Resistant Staphylococcus aureus Isolated from Bovine Mastitis Milk in Bangladesh.

The current study was conducted to isolate and identify multidrug-resistant Staphylococcus aureus (MDR-SA) from mastitis milk samples and to determine their antimicrobial susceptibility pattern. A total of 48 bovine mastitis (BM) milk samples were collected from different parts of the Rangpur division, Bangladesh. After the collection of milk samples, mastitis was confirmed using the California mastitis test. Isolation and identification of Staphylococcus aureus were performed using conventional cultural and biochemical tests as well as using molecular methods of PCR. Nucleotide sequence analysis of the 23S rRNA gene of Staphylococcus aureus was determined. The antibiogram of the isolated bacteria was conducted using the disc diffusion method. Phylogenetic analysis of 23S rRNA was done using MEGA 7, ClustalW multiple sequence alignment, and NCBI-BLAST tools, where the sequence of the isolate showed 98% to 99% identity. Antibiogram test using 15 antimicrobial agents showed that all of the Staphylococcus aureus isolates were classified as multidrug-resistant (MDR). It was found that the isolates were resistant to tetracycline, novobiocin, methicillin, vancomycin, and cephradine, and the isolates were sensitive to ciprofloxacin, azithromycin, norfloxacin, levofloxacin, gentamicin, and amoxicillin. The detection of MDR-SA in mastitis milk is alarming and represents a great public health concern. The findings of the present study help identify Staphylococcus aureus at the molecular level using 23S rRNA gene sequencing and will help select the appropriate and effective antimicrobial agent to control BM in the northern part of Bangladesh.

Isolation of multi-drug resistant Klebsiella sp. from bovine mastitis samples in Rangpur, Bangladesh.

OBJECTIVE: The objective of this study was to identify the multi-drug resistance (MDR) Klebsiella sp. from mastitis milk samples. MATERIALS AND METHODS: In the current research, 48 clinical mastitis milk samples were collected from Rangpur division, Bangladesh. Confirmation of bovine mastitis (BM) was done by the California Mastitis Test (CMT). All the CMT positive isolates were subjected for the identification of Klebsiella sp. using through a series of cultural and biochemical tests. MDR Klebsiella sp. isolates were determined using the disk diffusion method, and minimum inhibitory zones were measured by following Clinical and Laboratory Standards Institute. MDR patterns of the isolates were also subjected to study by using housefly (Musca domestica). RESULTS: Among the isolates, 62.5% (n = 30/48) revealed the presence of Klebsiella sp. Eight antimicrobial agents including Amoxicillin, Novobiocin, Erythromycin, Vancomycin, Cephradine, Tetracycline, Bacitracin, Methicillin, and housefly (M. domestica) showed complete resistance to Klebsiella sp. On the other hand, Chloramphenicol, Gentamicin, Ciprofloxacin, Azithromycin, Norfloxacin, Levofloxacin, and Nalidixic acid showed sensitivity. CONCLUSION: This study helps to treat BM with effective antibiotics and helps in an epidemiological study in Rangpur division as well as helps to create public health awareness.