Did national holidays accelerate COVID-19 diffusion in Bangladesh? A case study

Bangladesh registered 1573828 confirmed cases of COVID-19 and the death toll crossed the grim milestone of 27946 across the country as of 9th December, 2021. Despite the enforcement of stringent COVID-19 measures, including nationwide lockdowns, travel bans, tighter curbs on nonessential activities, and social distancing, the country witnessed an accelerated diffusion of coronavirus cases during the national events and festivals in 2020. The present study aims to examine the association between the national events / festivals and the transmission dynamics of COVID-19 by looking at the instantaneous reproduction number, Rt, of the 64 districts in Bangladesh. We further illustrate the COVID-19 diffusion explicitly in Dhaka Division at the first phase of the pandemic. The comprehensive analysis shows an escalation of Rt value in Dhaka and in all industrialized cities during the major events such as, Garments reopening and religious holidays in Bangladesh. Based on the analysis, a set of array measurements has been also suggested to evade the future pandemic risks while running the national festival activities. HighlightsO_LIBangladesh confirmed 1573828 coronavirus cases and 27946 deaths due to the current COVID-19 outbreak. C_LIO_LICountry observed significant COVID-19 diffusion in its business hubs during national holidays. C_LIO_LIDhaka, the capital of Bangladesh, is the epicenter of the ongoing pandemic. C_LIO_LICalculated Rt value illustrates its escalation in Dhaka and its neighboring cities at the time of national events. C_LIO_LIBangladesh Government needs to consider interdisciplinary approaches and contextual policies to contain the future pandemic during any national events. C_LI

Hypothetical protein predicted to be tumor suppressor: a protein functional analysis

Litorilituus sediminis is a Gram-negative, aerobic, novel bacterium under the family of Colwelliaceae, has a stunning hypothetical protein containing domain called von Hippel-Lindau that has significant tumor suppressor activity. Therefore, this study was designed to elucidate the structure and function of the biologically important hypothetical protein EMK97_00595 (QBG34344.1) using several bioinformatics tools. The functional annotation exposed that the hypothetical protein is an extracellular secretory soluble signal peptide and contains the von Hippel-Lindau (VHL; VHL beta) domain that has a significant role in tumor suppression. This domain is conserved throughout evolution, as its homologs are available in various types of the organism like mammals, insects, and nematode. The gene product of VHL has a critical regulatory activity in the ubiquitous oxygen-sensing pathway. This domain has a significant role in inhibiting cell proliferation, angiogenesis progression, kidney cancer, breast cancer, and colon cancer. At last, the current study depicts that the annotated hypothetical protein is linked with tumor suppressor activity which might be of great interest to future research in the higher organism.

Challenges in Tracking the Risk of COVID-19 in Bangladesh: Evaluation of A Novel Method

Identifying actual risk zones in a country where the overall test positive rate (TPR) is higher than 5% is crucial to contain the pandemic. However, TPR-based risk zoning methods are debatable since they do not consider the rate of infection in an area and thus, it has been observed to overestimate the risk. Similarly, the rate of infection in an area has been noticed to underestimate the risk of COVID-19 spreading for the zones with higher TPR. In this article, we discuss the shortcomings of currently available risk zoning methods that are followed in the lower-middle-income countries (LMIC), especially in Bangladesh. We then propose to determine a risk zone by combining the rate of infection with TPR and effective reproduction number, Rt in a distinct manner from existing methods. We evaluate the efficacy of the proposed method with respect to the mass-movement events and show its application to track the evolution of COVID-19 pandemic by identifying the risk zones over time. Demo website for the visualization of the analysis can be found at: http://erdos.dsm.fordham.edu:3000 CCS CONCEPTSO_LIApplied computing [->] Health informatics. C_LI ACM Reference FormatMd. Enamul Hoque, Md. Shariful Islam, Arnab Sen Sharma, Rashedul Islam, and Mohammad Ruhul Amin. 2021. Challenges in Tracking the Risk of COVID-19 in Bangladesh: Evaluation of A Novel Method. In Proceedings of August 15 (KDD Workshop on Data-driven Humanitarian Mapping, 27th ACM SIGKDD Conference). ACM, New York, NY, USA, 7 pages.

Sex-specific epidemiological and clinical characteristics of Covid-19 patients in the southeast region of Bangladesh

BackgroundCOVID-19 has become a global pandemic with a high growth rate of confirmed cases. In Bangladesh, both mortality and affected rates are increasing at an alarming rate. Therefore, more comprehensive studies of the epidemiological and clinical characteristics of COVID-19 are required to control this pandemic. PurposeThe present study aimed to compare and analyze the sex-specific epidemiological, clinical characteristics, comorbidities, and other information of confirmed COVID-19 patients from the southeast region in Bangladesh for the first time. Methods385 lab-confirmed cases were studied out of 2,471 tested samples between 5 June and 10 September 2020. RT-PCR was used for COVID-19 identification and SPSS (version 25) for statistical data analysis. ResultsWe found that male patients were roughly affected compared to females patients (male 74.30% vs. female 25.7%) with an average age of 34.86 {+/-} 15.442 years, and B (+ve) blood group has been identified as a high-risk factor for COVID-19 infection. Workplace, local market, and bank were signified as sex-specific risk zone (p < 0.001). Pre-existing medical conditions such as diabetes, hypertension, cardiovascular and respiratory diseases were identified among the patients. Less than half of the confirmed COVID-19 cases in the southeast region were asymptomatic (37.73%) and more prevalent among females than males (male vs. female: 36.84% vs. 40.51%, p = 0.001). ConclusionsThe findings may help health authorities and the government take necessary steps for identification and isolation, treatment, prevention, and control of this global pandemic.

SICaRiO: short indel call filtering with boosting.

Despite impressive improvement in the next-generation sequencing technology, reliable detection of indels is still a difficult endeavour. Recognition of true indels is of prime importance in many applications, such as personalized health care, disease genomics and population genetics. Recently, advanced machine learning techniques have been successfully applied to classification problems with large-scale data. In this paper, we present SICaRiO, a gradient boosting classifier for the reliable detection of true indels, trained with the gold-standard dataset from 'Genome in a Bottle' (GIAB) consortium. Our filtering scheme significantly improves the performance of each variant calling pipeline used in GIAB and beyond. SICaRiO uses genomic features that can be computed from publicly available resources, i.e. it does not require sequencing pipeline-specific information (e.g. read depth). This study also sheds lights on prior genomic contexts responsible for the erroneous calling of indels made by sequencing pipelines. We have compared prediction difficulty for three categories of indels over different sequencing pipelines. We have also ranked genomic features according to their predictivity in determining false positives.

No lockdown policy for COVID-19 epidemic in Bangladesh: Good, bad or ugly?

Bangladesh has been combating the COVID-19 pandemic with limited financial resources and poor health infrastructure since March, 2020. Although the government has imposed several restricted measures to curb the progression of the outbreak, these arrays of measures are not sustainable in the long run. In this study, we assess the impact of lift of flexible lockdown on the COVID-19 dynamics in Bangladesh. Our analysis demonstrates that the country might experience second infection peak in 6-7 months after the withdrawal of current lockdown. Moreover, a prolonged restrictions until January, 2021 will shift the infection peak towards August, 2021 and will reduce approximately 20 % COVID-19 cases in Bangladesh. What we knowO_LIBangladesh has been going through COVID-19 crisis and in response, the Government has implemented restricted array of measures to curb the COVID-19 outbreak in Bangladesh. C_LI What this article addsO_LIThe impact of no lockdown policies on COVID-19 pandemic in Bangladesh. C_LIO_LIAppearance of second infection peak in 6-7 months after the withdrawal of current lockdown. C_LI

Integration of Kalman filter in the epidemiological model: a robust approach to predict COVID-19 outbreak in Bangladesh

As one of the most densely populated countries in the world, Bangladesh have been trying to contain the impact of a pandemic like COVID-19 since March, 2020. Although government announced an array of restricted measures to slow down the diffusion in the beginning of the pandemic, the lockdown has been lifted gradually by reopening all the industries, markets and offices with a notable exception of educational institutes. As the physical geography of Bangladesh is highly variable across the largest delta, the population of different regions and their lifestyle also differ in the country. Thus, to get the real scenario of the current pandemic across Bangladesh, it is essential to analyze the transmission dynamics over the individual districts. In this article, we propose to integrate the Unscented Kalman Filter (UKF) with classic SIRD model to explain the epidemic evolution of individual districts in the country. We show that UKF-SIRD model results in a robust prediction of the transmission dynamics for 1-4 months. Then we apply the robust UKF-SIRD model over different regions in Bangladesh to estimates the course of the epidemic. Our analysis demonstrate that in addition to the densely populated areas, industrial areas and popular tourist spots are in the risk of higher COVID-19 transmission. In the light of these outcomes, we provide a set of suggestions to contain the pandemic in Bangladesh. All the data and relevant codebase is available at https://mjonyh.github.io. HighlightsO_LIWe integrate the UKF with classic SIRD model for the better estimation of the COVID-19 diffusion of 64 districts in Bangladesh. C_LIO_LINationwide analysis show the strong correlation between population density and the number of COVID-19 positive cases in the country. C_LIO_LIIndustrial zones and popular tourists spots are at greater risk of spreading the Coronavirus. C_LIO_LIWith the better assessment of the COVID-19 cases dynamics, the Government will find effective policies to contain the current pandemic. C_LI

Adjusted Dynamics of COVID-19 Pandemic due to Herd Immunity in Bangladesh

Amid growing debate between scientists and policymakers on the trade-off between public safety and reviving economy during the COVID-19 pandemic, the government of Bangladesh decided to relax the countrywide lockdown restrictions from the beginning of June 2020. Instead, the Ministry of Public Affairs officials have declared some parts of the capital city and a few other districts as red zones or high-risk areas based on the number of people infected in the late June 2020. Nonetheless, the COVID-19 infection rate had been increasing in almost every other part of the country. Ironically, rather than ensuring rapid tests and isolation of COVID-19 patients, from the beginning of July 2020, the Directorate General of Health Services restrained the maximum number of tests per laboratory. Thus, the health experts have raised the question of whether the government is heading toward achieving herd immunity instead of containing the COVID-19 pandemic. In this article, the dynamics of the pandemic due to SARS-CoV-2 in Bangladesh are analyzed with the SIRD model. We demonstrate that the herd immunity threshold can be reduced to 31% than that of 60% by considering age group cluster analysis resulting in a total of 53.0 million susceptible populations. With the data of Covid-19 cases till July 22, 2020, the time-varying reproduction numbers are used to explain the nature of the pandemic. Based on the estimations of active, severe, and critical cases, we discuss a set of policy recommendations to improve the current pandemic control methods in Bangladesh.

Molecular characterization and functional annotation of a hypothetical protein (SCO0618) of Streptomyces coelicolor A3(2)

Streptomyces coelicolor is a gram-positive soil bacterium which is well known for the production of several antibiotics used in various biotechnological applications. But numerous proteins from its genome are considered hypothetical proteins. Therefore, the present study aimed to reveal the functions of a hypothetical protein from the genome of S. coelicolor. Several bioinformatics tools were employed to predict the structure and function of this protein. Sequence similarity was searched through the available bioinformatics databases to find out the homologous protein. The secondary and tertiary structure were predicted and further validated with quality assessment tools. Furthermore, the active site and the interacting proteins were also explored with the utilization of CASTp and STRING server. The hypothetical protein showed the important biological activity having with two functional domain including POD-like_MBL-fold and rhodanese homology domain. The functional annotation exposed that the selected hypothetical protein could show the hydrolase activity. Furthermore, protein-protein interactions of selected hypothetical protein revealed several functional partners those have the significant role for the bacterial survival. At last, the current study depicts that the annotated hypothetical protein is linked with hydrolase activity which might be of great interest to the further research in bacterial genetics.

Molecular characterization and functional annotation of a hypothetical protein (SCO0618) of Streptomyces coelicolor A3(2)

Streptomyces coelicolor is a gram-positive soil bacterium which is well known for the production of several antibiotics used in various biotechnological applications. But numerous proteins from its genome are considered hypothetical proteins. Therefore, the present study aimed to reveal the functions of a hypothetical protein from the genome of S. coelicolor. Several bioinformatics tools were employed to predict the structure and function of this protein. Sequence similarity was searched through the available bioinformatics databases to find out the homologous protein. The secondary and tertiary structure were predicted and further validated with quality assessment tools. Furthermore, the active site and the interacting proteins were also explored with the utilization of CASTp and STRING server. The hypothetical protein showed the important biological activity having with two functional domain including POD-like_MBL-fold and rhodanese homology domain. The functional annotation exposed that the selected hypothetical protein could show the hydrolase activity. Furthermore, protein-protein interactions of selected hypothetical protein revealed several functional partners those have the significant role for the bacterial survival. At last, the current study depicts that the annotated hypothetical protein is linked with hydrolase activity which might be of great interest to the further research in bacterial genetics.

Prevalence and factors associated with tobacco use among men in India: findings from a nationally representative data

BACKGROUND@#Tobacco consumption causes almost 638,000 premature deaths per year in India. This study sought to examine the prevalence and determinants of tobacco use among men in India.@*METHODS@#We analyzed data from the fourth round of the National Family Health Survey in India. These nationally representative cross-sectional sample data were collected from January 20, 2015, to December 4, 2016. A total of 112,122 men aged 15-54 years were included in this study. Primary outcomes were tobacco use categorized into smoking, smokeless, any tobacco, and both smoked and smokeless tobacco use. Complex survey design and sampling weights were applied in both the descriptive analyses and logistic regression models. We present the findings using odds ratios.@*RESULTS@#The prevalence of tobacco use among men in India for the studied period was 45.5% (95% CI 44.9-46.1), smoking was 24.6% (95% CI 24.1-25.1), smokeless tobacco use was 29.1% (95% CI 28.6-29.6), and both smoked and smokeless tobacco use was 8.4% (95% CI 8.1-8.7). The prevalence of tobacco use among men was higher among the elderly, separated/divorced/widowed individuals, those with lower education and wealth status, alcohol consumers, manual workers, and residents of the northeast region. Multivariate analysis showed that age, lower education, occupation, region, alcohol consumption, separated/divorced/widowed status, and economic status were substantially associated with tobacco use among Indian men.@*CONCLUSIONS@#Innovative and cost-effective strategies targeting high-risk groups are crucial to curbing the tobacco epidemic in India. Anti-smoking campaigns should also focus on mitigating alcohol abuse. Reducing tobacco marketing and implementing formal education about the dangers of tobacco use, progressive taxing, packaging, and labeling of tobacco products and price strategies should be harmonized in legal provisions.

Leonurus sibiricus L. (honeyweed): A review of its phytochemistry and pharmacology

Leonurus sibiricus is a herbaceous plant found in many countries in Asia and America. This plant is widely practiced as a remedy for the treatment of diabetes, menstrual irregularities, and bronchitis. The approval of therapeutic implications of any drugs depends on the well characterized mode of actions of the compounds. The bioactive compounds like diterpenes, triterpenes, flavonoids and phenolic acids in Leonurus sibiricus show analgesic, anti-inflammatory, anti-oxidant, anti-atherogenic and anti-hemorrhagic, anti-diabetic, anti-bacterial and allelopathic potency. Interestingly, the expression level of some genes is altered by the crude extract treatments, which are effective against cancers, diabetes and cardiovascular diseases where the molecular mechanisms are yet to be explored. Intriguingly, the extracts significantly induce nitric oxide production by endothelial nitric oxide synthase, a signaling molecule of vasodilation in combination with interferon-γ indicating positive effect on atherosclerosis. Further investigations are required to unlock the effects of bioactive compounds found in extracts at clinical settings.

A protein-dependent side-chain rotamer library.

BACKGROUND: Protein side-chain packing problem has remained one of the key open problems in bioinformatics. The three main components of protein side-chain prediction methods are a rotamer library, an energy function and a search algorithm. Rotamer libraries summarize the existing knowledge of the experimentally determined structures quantitatively. Depending on how much contextual information is encoded, there are backbone-independent rotamer libraries and backbone-dependent rotamer libraries. Backbone-independent libraries only encode sequential information, whereas backbone-dependent libraries encode both sequential and locally structural information. However, side-chain conformations are determined by spatially local information, rather than sequentially local information. Since in the side-chain prediction problem, the backbone structure is given, spatially local information should ideally be encoded into the rotamer libraries. METHODS: In this paper, we propose a new type of backbone-dependent rotamer library, which encodes structural information of all the spatially neighboring residues. We call it protein-dependent rotamer libraries. Given any rotamer library and a protein backbone structure, we first model the protein structure as a Markov random field. Then the marginal distributions are estimated by the inference algorithms, without doing global optimization or search. The rotamers from the given library are then re-ranked and associated with the updated probabilities. RESULTS: Experimental results demonstrate that the proposed protein-dependent libraries significantly outperform the widely used backbone-dependent libraries in terms of the side-chain prediction accuracy and the rotamer ranking ability. Furthermore, without global optimization/search, the side-chain prediction power of the protein-dependent library is still comparable to the global-search-based side-chain prediction methods.