Circular RNAs (circRNAs) are closed-loop RNAs forming a covalent bond between their 3' and 5' ends, the back splice junction (BSJ), rendering them resistant to exonucleases and thus more stable compared to linear RNAs. Identification of circRNAs and distinction from their cognate linear RNA is only possible by sequencing the BSJ that is unique to the circRNA. CircRNAs are involved in the regulation of their cognate RNAs by increasing transcription rates, RNA stability, and alternative splicing.
View Article and Find Full Text PDFBackground: In the United States, e-cigarettes, or vapes, are the second most commonly used tobacco product. Despite abundant smartphone app-based cigarette cessation programs, there are few such programs for vaping and even fewer supporting data.
Objective: This exploratory, prospective, single-arm, remote cohort study of the Pivot vaping cessation program assessed enrollment and questionnaire completion rates, participant engagement and retention, changes in attitudes toward quitting vaping, changes in vaping behavior, and participant feedback.
Circular RNAs (circRNAs) are covalently closed single-stranded RNAs, generated through a back-splicing process that links a downstream 5' site to an upstream 3' end. The only distinction in the sequence between circRNA and their linear cognate RNA is the back splice junction. Their low abundance and sequence similarity with their linear origin RNA have made the discovery and identification of circRNA challenging.
View Article and Find Full Text PDFAnalysis of intact proteins by mass spectrometry enables direct quantitation of the specific proteoforms present in a sample and is an increasingly important tool for biopharmaceutical and academic research. Interpreting and quantifying intact protein species from mass spectra typically involves many challenges including mass deconvolution and peak processing as well as determining optimal spectral averaging parameters and matching masses to theoretical proteoforms. Each of these steps can present informatic hurdles, as parameters often need to be tailored specifically to the data sets.
View Article and Find Full Text PDFBackground: Increased smartphone ownership has led to the development of mobile smoking cessation programs. Although the related body of evidence, gathered through the conduct of randomized controlled trials (RCTs), has grown in quality and rigor, there is a need for longer-term data to assess associated smoking cessation durability.
Objective: The primary aim was to compare smoking cessation outcomes at 52 weeks in adult smokers randomized to a mobile smoking cessation program, Pivot (intervention), versus QuitGuide (control).