Background: Having inadequate health care systems and poor socio-economic infrastructure, Bangladesh has been braving to contain the impact of current COVID-19 pandemic since March, 2020. To curb the diffusion of COVID-19, the local government has responded to the outbreak by enforcing a set of restricted measures on economic and social activities across the country. Objectives: Here, we aim to assess the propagation of COVID-19 by estimating the coronavirus active cases and mortality rate in two major business hubs of Bangladesh, namely Dhaka and Chittagong city under flexible lockdown conditions. Methods: We apply a data-driven forecasting model using Susceptible, Exposed, Infected, Recovered and Deaths status through time to deal with coronavirus outbreak. Results: The epidemiological model forecasts the dire consequences for Dhaka city with 2400 death cases at the end of December, 2020, whereas Chittagong city might experience 14% more deaths than Dhaka if the severe restrictions are not implemented to control the pandemic. Conclusion: Although lockdown has a positive impact in reducing the diffusion of COVID-19, it is disastrous for human welfare and national economies. Therefore, a unidirectional decision by the policymakers might cost a very high price on either way for a lower-middle-income country, Bangladesh. In this study, we suggest a fair trade-off between public health and the economy to avoid enormous death tolls and economic havoc 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.

The ability of an organism to respond to environmental changes is paramount to survival across a range of conditions. The bacterial heme nitric oxide/oxygen binding proteins (H-NOX) are a family of biofilm-regulating gas sensors that enable bacteria to respond accordingly to the cytotoxic molecule nitric oxide. By interacting with downstream signaling partners, H-NOX regulates the production of the bacterial secondary messenger cyclic diguanylate monophosphate (c-di-GMP) to influence biofilm formation. The aquatic organism Caulobacter crescentus has the propensity to attach to surfaces as part of its transition into the stalked S-phase of its life cycle. This behavior is heavily influenced by intracellular c-di-GMP and thus poses H-NOX as a potential influencer of C. crescentus surface attachment and cell cycle. By generating a strain of C. crescentus lacking hnox, our laboratory has demonstrated that this strain exhibits a considerable growth deficit, an increase in biofilm formation, and an elevation in c-di-GMP. Furthermore, in our comprehensive proteome study of 2779 proteins, 236 proteins were identified that exhibited differential expression in Δhnox C. crescentus, with 132 being downregulated and 104 being upregulated, as determined by a fold change of ≥1.5 or ≤0.66 and a p value ≤0.05. Our systematic analysis unveiled several regulated candidates including GcrA, PopA, RsaA, FtsL, DipM, FlgC, and CpaE that are associated with the regulation of the cellular division process, surface proteins, flagellum, and pili assembly. Further examination of Gene Ontology and pathways indicated that the key differences could be attributed to several metabolic processes. Taken together, our data indicate a role for the HNOX protein in C. crescentus cell cycle progression.

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder worldwide. Despite extensive research, the etiology of both familial and sporadic PD remains unclear. While most PD cases are sporadic, a significant minority are linked to genetic mutations, notably in the synuclein‐alpha (SNCA) and leucine‐rich repeat kinase 2 (LRRK2) genes. Animal models, such as Drosophila melanogaster (D. melanogaster), enable detailed study of these genetic mutations and their neurotoxic effects. Recent advancements in mass spectrometry‐based proteomics have enhanced our understanding of PD by facilitating comprehensive analysis of protein expression and interactions in mutant and wild‐type organisms, potentially revealing novel therapeutic targets. This review highlights the pivotal role of mass spectrometry‐based proteomics in advancing PD research, emphasizing the contributions of D. melanogaster models in identifying potential biomarkers.

Bangladesh registered 20,117,32 confirmed cases of COVID-19 and the death toll crossed the grim milestone of 29,323 across the country as of August 31st, 2022. Despite the enforcement of stringent COVID-19 measures, the country witnessed an accelerated diffusion of coronavirus cases during the national events, inclusive of short festivals, in 2020. The present study aims to examine the association between these national holidays and the COVID-19 trasmission rate in Bangladesh. We employed a mathematical model and calculated the instantaneous reproduction number, Rt, of the 64 districts in Bangladesh to check the dynamics of COVID-19 diffusion. The comprehensive analysis shows a notable escalation of Rt value and thus the enhanced transmission rate in Dhaka and in all industrialized cities during the major events such as, garments reopening and religious holidays in Bangladesh. We further showcase the COVID-19 diffusion explicitly in Dhaka Division at the first phase of the pandemic in Bangladesh. Based on our analysis, a set of measures, including restricted public mobility and the celebration of festivals, alongside improving the public’s awareness of the situation, has been recommended to evade the future pandemic risks while running the national festival activities 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 . Highlights: We integrate the UKF with classic SIRD model for the better estimation of the COVID-19 diffusion of 64 districts in Bangladesh. Nationwide analysis show the strong correlation between population density and the number of COVID-19 positive cases in the country. Industrial zones and popular tourists spots are at greater risk of spreading the Coronavirus. With the better assessment of the COVID-19 cases dynamics, the Government will find effective policies to contain the current pandemic.