The precise and unambiguous detection and quantification of internal RNA modifications represents a critical step for understanding their physiological functions. The methods of direct RNA sequencing are quickly developing allowing for the precise location of internal RNA marks. This detection is however not quantitative and still presents detection limits.
View Article and Find Full Text PDFAdenosine deaminase acting on RNA 1 (ADAR1) is the principal enzyme for the adenosine-to-inosine RNA editing that prevents the aberrant activation of cytosolic nucleic acid sensors by endogenous double stranded RNAs and the activation of interferon-stimulated genes. In mice, the conditional neural crest deletion of reduces the survival of melanocytes and alters the differentiation of Schwann cells that fail to myelinate nerve fibers in the peripheral nervous system. These myelination defects are partially rescued upon the concomitant removal of the Mda5 antiviral dsRNA sensor in vitro, suggesting implication of the Mda5/Mavs pathway and downstream effectors in the genesis of mutant phenotypes.
View Article and Find Full Text PDFThe RNA editing enzyme adenosine deaminase acting on RNA 1 (ADAR1) is essential for correct functioning of innate immune responses. The ADAR1p110 isoform is mainly nuclear and ADAR1p150, which is interferon (IFN) inducible, is predominately cytoplasmic. Using three different methods - co-immunoprecipitation (co-IP) of endogenous ADAR1, Strep-tag co-IP and BioID with individual ADAR1 isoforms - a comprehensive interactome was generated during both homeostasis and the IFN response.
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October 2024
Objective: Throughout the COVID-19 pandemic, the effectiveness of face mask mandates was intensely debated. The objective of this study was to describe how face mask mandates at the state, county, and local levels differed in their effectiveness in reducing the number of COVID-19 cases in the jurisdiction where the mandate was implemented and throughout Utah.
Methods: We used publicly available data from the Utah Department of Health and Human Services.
Background: Understanding how infectious disease transmission varies from person to person, including associations with age and contact behavior, can help design effective control strategies. Within households, transmission may be highly variable because of differing transmission risks by age, household size, and individual contagiousness. Our aim was to disentangle those factors by fitting mathematical models to SARS-CoV-2 household survey and serologic data.
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