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Objective: Coronavirus-19 (COVID-19) outbreaks have been reported in a range of climates worldwide, including Bangladesh. There is less evidence of a link between the COVID-19 pandemic and climatic variables. This research article’s purpose is to examine the relationship between COVID-19 outbreaks and climatic factors in Dhaka, Bangladesh. Methods: The daily time series COVID-19 data used in this study span from May 1, 2020, to April 14, 2021, for the study area, Dhaka, Bangladesh. The Climatic factors included in this study were average temperature, particulate matter ( P M 2 . 5 ), humidity, carbon emissions, and wind speed within the same timeframe and location. The strength and direction of the relationship between meteorological factors and COVID-19 positive cases are examined using the Spearman correlation. This study examines the asymmetric effect of climatic factors on the COVID-19 pandemic in Dhaka, Bangladesh, using the Nonlinear Autoregressive Distributed Lag (NARDL) model. Results: COVID-19 widespread has a substantial positive association with wind speed (r = .781), temperature (r = .599), and carbon emissions (r = .309), whereas P M 2 . 5 (r = −.178) has a negative relationship at the 1% level of significance. Furthermore, with a 1% change in temperature, the incidence of COVID-19 increased by 1.23% in the short run and 1.53% in the long run, with the remaining variables remaining constant. Similarly, in the short-term, humidity was not significantly related to the COVID-19 pandemic. However, in the long term, it increased 1.13% because of a 1% change in humidity. The changes in PM2.5 level and wind speed are significantly associated with COVID-19 new cases after adjusting population density and the human development index.

Background and Objective: There have been significant effects of the current coronavirus-19 (COVID-19) infection outbreak on many facets of everyday life, particularly the environment. Despite the fact that a number of studies have already been published on the topic, an analysis of those studies’ findings on COVID-19’s effects on environmental pollution is still lacking. The goal of the research is to look into greenhouse gas emissions and air pollution in Bangladesh when COVID-19 is under rigorous lockdown. The specific drivers of the asymmetric relationship between air pollution and COVID-19 are being investigated. Methods: The nonlinear relationship between carbon dioxide ( C O 2 ) emissions, fine particulate matter ( P M 2 . 5 ) , and COVID-19, as well as its precise components, are also being investigated. To examine the asymmetric link between COVID-19 factors on C O 2 emissions and P M 2 . 5 , we employed the nonlinear autoregressive distributed lag (NARDL) model. Daily positive cases and daily confirmed death by COVID-19 are considered the factors of COVID-19, with lockdown as a dummy variable. Results: The bound test confirmed the existence of long-run and short-run relationships between variables. Bangladesh’s strict lockdown, enforced in reaction to a surge of COVID-19 cases, reduced air pollution and dangerous gas emissions, mainly C O 2 , according to the dynamic multipliers graph.

Human papillomavirus 16 and human papillomavirus 18 have been associated with different life-threatening cancers, including cervical, lung, penal, vulval, vaginal, anal, and oropharyngeal cancers, while cervical cancer is the most prominent one. Several research studies have suggested that the oncoproteins E6 and E7 are the leading cause of cancers associated with the human papillomavirus infection. Therefore, we developed two mRNA vaccines (V1 and V2) targeting these oncoproteins. We used several bioinformatics tools to predict helper T lymphocyte, cytotoxic T lymphocyte, and B-cell epitopes derived from the proteins and assessed their antigenicity, allergenicity, and toxicity. Both vaccines were constructed using selected epitopes, linkers, and adjuvants. After that, the vaccines were applied for physicochemical properties, secondary and tertiary structure predictions, and subsequent docking and simulation analyses. Accordingly, vaccine 1 (V1) and vaccine 2 (V2) showed better hydrophilicity with the grand average hydropathicity score of -0.811 and -0.648, respectively. The secondary and tertiary structures of the vaccines were also deemed satisfactory, with high stability indicated by the Ramachandran plot (V1:94.5% and V2:87.1%) and Z scores (V1: -5.15 and V2: -4.1). Docking analysis revealed substantial affinity of the vaccines towards the toll-like receptor-2 (V1: -1159.3, V2: -1246.3) and toll-like receptor-4 (V1: -1109.3, V2: -1244.8) receptors. Molecular dynamic simulation validated structural integrity and indicated varying stability throughout the simulation. Codon optimization showed significant expression of the vaccines (V1:51.88% and V2:51.63%) in E . coli vectors. Furthermore, regarding immune stimulation, the vaccines elicited significant B-cell and T-cell responses, including sustained adaptive and innate immune responses. Finally, thermodynamic predictions indicated stable mRNA structures of the vaccines (V1: -502.60 kcal/mol and V2: -450.90 kcal/mol). The proposed vaccines designed effectively targeting human papillomavirus oncoproteins have demonstrated promising results via robust immune responses, suggesting their suitability for further clinical advancement, including in vitro and in vivo experiments.

Human papillomavirus 16 and human papillomavirus 18 have been associated with different life-threatening cancers, including cervical, lung, penal, vulval, vaginal, anal, and oropharyngeal cancers, while cervical cancer is the most prominent one. Several research studies have suggested that the oncoproteins E6 and E7 are the leading cause of cancers associated with the human papillomavirus infection. Therefore, we developed two mRNA vaccines (V1 and V2) targeting these oncoproteins. We used several bioinformatics tools to predict helper T lymphocyte, cytotoxic T lymphocyte, and B-cell epitopes derived from the proteins and assessed their antigenicity, allergenicity, and toxicity. Both vaccines were constructed using selected epitopes, linkers, and adjuvants. After that, the vaccines were applied for physicochemical properties, secondary and tertiary structure predictions, and subsequent docking and simulation analyses. Accordingly, vaccine 1 (V1) and vaccine 2 (V2) showed better hydrophilicity with the grand average hydropathicity score of -0.811 and -0.648, respectively. The secondary and tertiary structures of the vaccines were also deemed satisfactory, with high stability indicated by the Ramachandran plot (V1:94.5% and V2:87.1%) and Z scores (V1: -5.15 and V2: -4.1). Docking analysis revealed substantial affinity of the vaccines towards the toll-like receptor-2 (V1: -1159.3, V2: -1246.3) and toll-like receptor-4 (V1: -1109.3, V2: -1244.8) receptors. Molecular dynamic simulation validated structural integrity and indicated varying stability throughout the simulation. Codon optimization showed significant expression of the vaccines (V1:51.88% and V2:51.63%) in E. coli vectors. Furthermore, regarding immune stimulation, the vaccines elicited significant B-cell and T-cell responses, including sustained adaptive and innate immune responses. Finally, thermodynamic predictions indicated stable mRNA structures of the vaccines (V1: -502.60 kcal/mol and V2: -450.90 kcal/mol). The proposed vaccines designed effectively targeting human papillomavirus oncoproteins have demonstrated promising results via robust immune responses, suggesting their suitability for further clinical advancement, including in vitro and in vivo experiments.

One of the most important public health concerns is the marked rise in the number of caesarean sections. The World Health Organisation advises against CS rates exceeding 10% or falling below 5%, as both extremes can negatively impact the health of expectant mothers and newborns. The aim of this study was to assess the prevalence of CS and NVD delivery among mothers in Rajshahi Division, Bangladesh. This cross-sectional study (July 2024) included 393 postpartum mothers from Rajshahi Division. Data were collected via semi-structured questionnaires and analyzed using descriptive statistics, chi-square tests, and binary logistic regression. The prevalence of NVD and CS delivery among lower-educated mothers was 59% and 41%, respectively. Mothers in Naogaon district were more likely to deliver by CS compared to those in other districts in Bangladesh. Women aged ≥ 30 years (AOR 74.934; 95% CI 12.831–437.613) were more likely to prefer CS delivery compared to younger women, with this association being statistically significant ( p  < 0.01). Educated women (AOR 83.469; 95% CI 2.554–2727.394) were more likely to prefer CS delivery compared to their lower-educated counterparts, and it was statistically significant ( p  < 0.05). This study found a high prevalence of caesarean section (CS) deliveries in the Rajshahi Division of Bangladesh, with particularly increasing trends observed in Naogaon. Factors such as older maternal age, higher maternal education, lower paternal education, employment in the service sector, non-Muslim religion, and lower family income were associated with higher CS rates. Further research is needed to understand these trends and to promote informed decision-making for the safe and appropriate use of CS in Bangladesh.

Echinococcosis is a significant parasitic zoonotic disease with severe implications for human and animal health. To date, there has been no effective vaccine candidate available for echinococcosis. Therefore, we employed computational approaches to develop a multiepitope-based vaccine using the most potent epitopes of MHC-I, MHC-II, and B-cell derived from the Ag5 protein of Echinococcus spp. The final vaccine construct containing the epitopes, linkers, and adjuvant exhibited potent antigenicity (score > 0.1) with no evidence of allergenicity (score < 0) and toxicity (score < 0) in several computational platforms. The vaccine also exhibited favorable physicochemical characteristics such as being highly soluble (SOLpro score of 0.781243) and hydrophilic (Grand average of hydropathy of -0.433). Moreover, the tertiary structure of the vaccine was also found to be structurally stable, with a Z score of -5.71. Further, the molecular docking analysis confirmed the vaccine's significant binding affinity to the RP-105 (docking score of -1252.7) and TLR-9 (docking score of -970.9). The molecular dynamic simulations confirmed the structural stability of the docked complexes under a virtual physiological system. The negative ΔTOTAL values derived from the MM-PBSA and MM-GBSA analyses confirmed a spontaneous and thermodynamically favorable binding process between the vaccine and receptors. Moreover, the vaccine demonstrated high potentiality to elicit both innate (natural killer cell, dendritic and macrophage) and adaptive (B-cell, helper T cell and cytotoxic T cell) immune responses with sustained humoral immune responses evidenced by increased IFN-γ and IL-2 levels. Following codon optimization and in silico cloning, the vaccine was successfully expressed (CAI value of 0.9607 and average GC content of 52.34%) after being inserted into the pET-28a (+) plasmid of E. coli. These findings highlight the potential of the designed vaccine candidate to combat echinococcosis and lay the groundwork for future preclinical and clinical studies.

Alzheimer’s disease (AD), a progressive neurodegenerative disorder, is a major global health concern, affecting millions worldwide, with its prevalence expected to triple by 2050. Despite the widespread use of traditional drugs like cholinesterase inhibitors and NMDA receptor antagonists, their limited effectiveness requires innovative therapeutic approaches. This work used Computer-Aided Drug Design (CADD) to renovate AD therapies aimed at both acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) using fungal secondary metabolites. Subsequent pharmacokinetic profiles indicated that all metabolites had significant gastrointestinal absorption, blood-brain barrier permeability, and adherence to Lipinski’s Rule of Five, suggesting favourable drug-like properties. Furthermore, these metabolites exhibited little toxicity, except for Lovastatin, which indicated possible carcinogenicity. Molecular docking revealed three main candidates—Fumitremorgin C, Hericenone J, and Lovastatin—with notable binding affinities for AChE and BuChE. Consequently, the Fumitremorgin C showed the highest affinity for AChE (−10.0 kcal/mol), but Hericenone J showed enhanced inhibition of BuChE (−9.2 kcal/mol), suggesting its potential use in advanced stages of AD. Molecular dynamics simulations spanning 100 ns validated the stability of enzyme-ligand complexes, with Hericenone J exhibiting the greatest stability, low RMSD, and strong hydrogen bond interactions. The RMSF analysis further demonstrated that Hericenone J preserved structural integrity, whereas ROG and SASA values validated its compactness and stability. As determined by binding energy calculations, Hericenone J had the most inhibitory potential, followed by Lovastatin. However, Hericenone J’s constant adoption of low-energy conformations, as shown by the principal component and Gibbs free energy analyses, suggested robust and stable interactions with both cholinesterases. With its superior pharmacokinetic profiles, significant binding affinity, and high stability, Hericenone J is the most promising dual cholinesterase inhibitor. These results support the notion that Hericenone J might be an effective treatment for AD if subjected to more preclinical trials.

This study examines the relationship between climatic factors and the prevalence of COVID-19 in Bangladesh. The Pearson correlation coefficient, the Spearman correlation coefficient, and Kendall's correlation coefficient have all been used to assess the intensity and direction of the relationship between climatic factors and COVID-19. The lagged effects of climatic parameters on COVID-19 daily confirmed cases from Bangladesh are being investigated using the Auto Regressive Distributed Lag (ARDL) model. As a result, one non-climatic variable, such as a daily lab test, is considered a control variable. As climatic variables, average temperature (°C), average humidity (percent), average rainfall (mm), and average wind speed (km/h) were well chosen and the same time one environmental variable (a proxy of air quality) like average particulate matter ( PM 2.5 ) is considered into account. The time series data used in this analysis was from May 1, 2020, to April 14, 2021. The findings of correlation analysis indicate that there is an important /strong, significant, and positive relationship between COVID-19 widespread and temperature (°C), humidity (percent), rainfall (mm), and wind speed (km/h), whereas there is a negative, weak, and significant relationship between PM 2.5 and COVID-19 widespread. In addition, the ARDL findings suggest that temperature (°C), PM 2.5 , and wind speed (km/h) have major lag effects on COVID-19 in Bangladesh, while humidity (percent) and rainfall (mm) have negligible lag effects. This study will be helpful to environmental activists and policymakers in creating future sustainable improvement plans for climate and weather conditions in Bangladesh.

The mechanism of the negative regulation of proopiomelanocortin gene (Pomc) by glucocorticoids (Gcs) is still unclear in many points. Here, we demonstrated the involvement of neurogenic differentiation factor 1 (NeuroD1) in the Gc-mediated negative regulation of Pomc. Murine pituitary adrenocorticotropic hormone (ACTH) producing corticotroph tumor-derived AtT20 cells were treated with dexamethasone (DEX) (1-100 nM) and cultured for 24 hrs. Thereafter, Pomc mRNA expression was studied by quantitative real-time PCR and rat Pomc promoter (-703/+58) activity was examined by luciferase assay. Both Pomc mRNA expression and Pomc promoter activity were inhibited by DEX in a dose-dependent manner. Deletion and point mutant analyses of Pomc promoter suggested that the DEX-mediated transcriptional repression was mediated via E-box that exists at -376/-371 in the promoter. Since NeuroD1 is known to bind to and activate E-box of the Pomc promoter, we next examined the effect of DEX on NeuroD1 expression. Interestingly, DEX dose-dependently inhibited NeuroD1 mRNA expression, mouse NeuroD1 promoter (-2.2-kb) activity, and NeuroD1 protein expression in AtT20 cells. In addition, we confirmed the inhibitory effect of DEX on the interaction of NeuroD1 and E-box on Pomc promoter by chromatin immunoprecipitation (ChIP) assay. Finally, overexpression of mouse NeuroD1 could rescue the DEX-mediated inhibition of Pomc mRNA expression and Pomc promoter activity. Taken together, it is suggested that the suppression of NeuroD1 expression and the inhibition of NeuroD1/E-box interaction may play an important role in the Gc-mediated negative regulation of Pomc.