Publications by authors named "S Brumbaugh"

The laboratory mouse is used extensively for human disease modeling and preclinical therapeutic testing for efficacy, biodistribution, and toxicity. The variety of murine models available, and the ability to create new ones, eclipses all other species, but the size of mice and their organs create challenges for many in vivo studies. For pulmonary research, improved methods to access murine airways and lungs, and track substances administered to them, would be desirable.

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Background: Stimulant prescriptions increased by 250% in the United States from 2006-2016 while diagnoses for ADHD minimally increased. There is insufficient data regarding who may be the recipients of these new stimulant prescriptions and safety of stimulants have come under scrutiny in some populations. We aim to describe trends in stimulant prescriptions across biopsychosocial patient level factors between 2010 and 2020.

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Meiosis, although essential for reproduction, is also variable and error-prone: rates of chromosome crossover vary among gametes, between the sexes, and among humans of the same sex, and chromosome missegregation leads to abnormal chromosome numbers (aneuploidy). To study diverse meiotic outcomes and how they covary across chromosomes, gametes and humans, we developed Sperm-seq, a way of simultaneously analysing the genomes of thousands of individual sperm. Here we analyse the genomes of 31,228 human gametes from 20 sperm donors, identifying 813,122 crossovers and 787 aneuploid chromosomes.

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 Recognized variability in fetal heart rate interpretation led the Perinatal Quality Foundation (PQF) to develop a credentialing exam. We report an evaluation of the 1st 4000 plus PQF Fetal Monitoring Credentialing (FMC) exams.  The PQF FMC exam is an online assessment for obstetric providers and nurses.

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The mammalian brain is composed of diverse, specialized cell populations. To systematically ascertain and learn from these cellular specializations, we used Drop-seq to profile RNA expression in 690,000 individual cells sampled from 9 regions of the adult mouse brain. We identified 565 transcriptionally distinct groups of cells using computational approaches developed to distinguish biological from technical signals.

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