Foot-and-mouth disease virus (FMDV), the causative agent of the foot-and-mouth disease of cattle population possesses a rapid evolutionary rate. In Bangladesh, the first circulation of the O/ME-SA/SA-2018 lineage as a novel sublineage, MYMBD21 was reported from our laboratory. The first whole genome sequence of an isolate, BAN/MY/My-466/2021 (shortly named My-466) of the SA-2018 lineage is characterized and represented in this study.
View Article and Find Full Text PDFPLoS One
January 2025
The rare zoonotic Borna disease virus (BDV) causes fatal neurological disease in various animals, with a high mortality rate exceeding 90% in central Europe. However, unlike most viruses, it establishes persistent infections within the host cell nucleus, hindering treatment. As successful BDV treatments remain elusive, the researchers turned to a computational approach, utilizing molecular docking, ADME/T, post-docking MMGBSA, MD simulation, DCCM, and PCA to identify promising phytochemical drug candidates targeting the BDV Nucleoprotein (PDB ID: 1N93).
View Article and Find Full Text PDFJMIR Pediatr Parent
January 2025
Background: Globally, 10% of pregnant women and 13% of postpartum women experience mental disorders. In Bangladesh, nearly 50% of mothers face common mental disorders, but mental health services and trained professionals to serve their needs are scarce. To address this, the government of Bangladesh's Non-Communicable Disease Control program initiated "Wellbeing Centers," telemental health services in selected public hospitals.
View Article and Find Full Text PDFAnisotropic materials with low symmetries hold significant promise for next-generation electronic and quantum devices. 2M-WS, which is a candidate for topological superconductivity, has garnered considerable interest. However, a comprehensive understanding of how its anisotropic features contribute to unconventional superconductivity, along with a simple, reliable method to identify its crystal orientation, remains elusive.
View Article and Find Full Text PDFMagnetic resonance (MR) images are commonly used to diagnose prolapsed lumbar intervertebral disc (PLID). However, for a computer-aided diagnostic (CAD) system, distinguishing between pathological abnormalities of PLID in MR images is a challenging and intricate task. Here, we propose a comprehensive model for the automatic detection and cropping of regions of interest (ROI) from sagittal MR images using the YOLOv8 framework to solve this challenge.
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