Viral quasispecies refers to the complex and dynamic mutant distributions (also termed mutant spectra, clouds or swarms) that arise as a result of high error rates during RNA genome replication. The mutant spectrum of individual RNA virus populations is modified by continuous generation of variant genomes, competition and interactions among them, environmental influences, bottleneck events, and bloc transmission of viral particles. Quasispecies dynamics provides a new perspective on how viruses adapt, evolve and cause disease, and sheds light on strategies to combat them.
View Article and Find Full Text PDFBackground: Umbilical cord blood (CB) units stored in banks are an important source of hematopoietic stem cells for transplantation and other cell therapies. New applications, such as their use in transfusions, require rapid quality release as cord blood red blood cells (CB-RBC) have a shorter shelf life.
Study Design And Methods: This project aims to investigate the most prevalent microbial contaminants in CB preparations and validate a rapid sterility testing strategy for CB-RBC based on an automated system (BACT/ALERT®) in tandem with a molecular assay (real-time PCR) capable of detecting at least 100 CFU/mL of Cutibacterium acnes in CB-RBC to accelerate the detection of the most common slow-growing bacteria.
Mitochondria are central to cellular function, particularly in metabolically active tissues such as skeletal muscle. Nuclear-encoded RNAs typically localize within the nucleus and cytosol but a small population may also translocate to subcellular compartments such as mitochondria. We aimed to investigate the nuclear-encoded RNAs that localize within the mitochondria of skeletal muscle cells and tissue.
View Article and Find Full Text PDFAnimal movements are typically influenced by multiple environmental factors simultaneously, and individuals vary in their response to this environmental heterogeneity. Therefore, understanding how environmental aspects, including biotic, abiotic, and anthropogenic factors, influence the movements of wild animals is an important focus of wildlife research and conservation. We apply Exponential Random Graph Models (ERGMs) to analyze movement networks of a bull shark population in a network of acoustic receivers and identify the effects of environmental, social, or other types of covariates on their movements.
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