BACKGROUND:

Pediatric subspecialists routinely provide procedural sedation outside the operating room. No large study has reported trends in outpatient pediatric procedural sedation. Our purpose in this study was to identify significant trends in outpatient procedural sedation using the Pediatric Sedation Research Consortium.

BACKGROUND:

More than 80% of children with cancer become long-term survivors, yet most survivors experience late effects of treatment. Little is known about how parents and physicians consider late-effects risks against a potential survival benefit when making treatment decisions.

Electronic cigarette or vaping product use–associated lung injury (EVALI) is a newly emerging diagnosis in the United States, yet the incidence has surged greatly in the past year. With the trend of using electronic cigarettes (e-cigarettes) and vaping rising at an alarming rate among teenagers, many are resorting to friends, illicit drug dealers, and other informal sources to obtain their e-cigarettes, which is greatly contributing to the national outbreak of EVALI. The incidence of adolescents presenting with the constellation of respiratory, gastrointestinal, and constitutional symptoms characteristic of EVALI has been widely reported within the nation. We present one such case of an adolescent boy with a 2-year history of daily vaping who presented with nausea, vomiting, weight loss, and fever but lacked the respiratory symptoms that have been reported in the majority of EVALI cases reported thus far. Computed tomography scan of the abdomen and pelvis revealed an incidental finding of lung pathology characteristic of EVALI, prompting further workup and diagnosis of EVALI. In this case, it is demonstrated that the presentation of EVALI can be variable and is still poorly defined. The rising morbidity and mortality from EVALI reveal the importance of considering EVALI in all patients with a history of vaping or e-cigarette use, regardless of the presence or absence of respiratory symptoms.

BACKGROUND AND OBJECTIVES:

A previous single-county study found that retail stores usually asked young-looking tobacco customers to show proof-of-age identification, but a large proportion of illegal tobacco sales to minors occurred after the customers had shown identification proving they were too young to purchase tobacco. We sought to investigate these findings on a larger scale.

BACKGROUND AND OBJECTIVES:

High-quality cardiopulmonary resuscitation (CPR) increases the likelihood of survival of pediatric out-of-hospital cardiac arrest (OHCA). Maintenance of high-quality CPR during transition of care between prehospital and pediatric emergency department (PED) providers is challenging. Our objective for this initiative was to minimize pauses in compressions, in alignment with American Heart Association recommendations, for patients with OHCA during the handoffs from prehospital to PED providers. We aimed to decrease interruptions in compressions during the first 2 minutes of PED care from 17 seconds (baseline data) to 10 seconds over 12 months. Our secondary aims were to decrease the length of the longest pause in compressions to <10 seconds and eliminate encounters in which time to defibrillator pad placement was >120 seconds.

OBJECTIVES:

Children born very preterm (VPT) are at an increased risk of developing mental health (MH) disorders. Our aim for this study was to assess rates of MH disorders in children born VPT and term at 13 years of age and stability of MH disorders between ages 7 and 13 years by using a diagnostic measure.

BACKGROUND:

Although autodialer centralized reminder and recall (C-R/R) from state immunization information systems (IISs) has been shown to raise childhood vaccination rates, its impact on human papillomavirus (HPV) vaccination rates is unclear.

OBJECTIVES:

To describe (1) the developmental trajectories of peer victimization from 6 to 17 years of age and (2) the early childhood behaviors and family characteristics associated with the trajectories.

BACKGROUND AND OBJECTIVES:

Early diagnosis of cerebral palsy (CP) is critical in obtaining evidence-based interventions when plasticity is greatest. In 2017, international guidelines for early detection of CP were published on the basis of a systematic review of evidence. Our study aim was to reduce the age at CP diagnosis throughout a network of 5 diverse US high-risk infant follow-up programs through consistent implementation of these guidelines.

OBJECTIVES:

Standing orders are an effective way to increase vaccination rates, yet little is known about how pediatricians use this strategy for childhood immunizations. We assessed current use of, barriers to using, and factors associated with use of standing orders for vaccination among pediatricians.

We describe an atypical pediatric case of immunoglobulin A vasculitis (IgAV), also referred to as Henoch-Schönlein purpura, in which formation of spontaneous hematoma of the paraspinal muscles developed. Spontaneous or unprovoked hematomas rarely occur in IgAV. These manifestations have not been described specifically in the pediatric literature as coinciding with IgAV. These findings are alarming for nonaccidental trauma, particularly in a patient without underlying blood dyscrasia. Our objective for this report is to highlight the possible association of muscular hematoma formation with IgAV and to help providers consider this association when trauma and hemophilia has been ruled out.

Multienvironment trials (METs) are widely used to assess the performance of promising crop germplasm. Though seldom designed to elucidate genetic mechanisms, MET data sets are often much larger than could be duplicated for genetic research and, given proper interpretation, may offer valuable insights into the genetics of adaptation across time and space. The Cooperative Dry Bean Nursery (CDBN) is a MET for common bean (Phaseolus vulgaris) grown for > 70 years in the United States and Canada, consisting of 20–50 entries each year at 10–20 locations. The CDBN provides a rich source of phenotypic data across entries, years, and locations that is amenable to genetic analysis. To study stable genetic effects segregating in this MET, we conducted genome-wide association studies (GWAS) using best linear unbiased predictions derived across years and locations for 21 CDBN phenotypes and genotypic data (1.2 million SNPs) for 327 CDBN genotypes. The value of this approach was confirmed by the discovery of three candidate genes and genomic regions previously identified in balanced GWAS. Multivariate adaptive shrinkage (mash) analysis, which increased our power to detect significant correlated effects, found significant effects for all phenotypes. Mash found two large genomic regions with effects on multiple phenotypes, supporting a hypothesis of pleiotropic or linked effects that were likely selected on in pursuit of a crop ideotype. Overall, our results demonstrate that statistical genomics approaches can be used on MET phenotypic data to discover significant genetic effects and to define genomic regions associated with crop improvement.

In plant–pathogen relations, disease symptoms arise from the interaction of the host and pathogen genomes. Host–pathogen functional gene interactions are well described, whereas little is known about how the pathogen genetic variation modulates both organisms’ transcriptomes. To model and generate hypotheses on a generalist pathogen control of gene expression regulation, we used the Arabidopsis thaliana–Botrytis cinerea pathosystem and the genetic diversity of a collection of 96 B. cinerea isolates. We performed expression-based genome-wide association (eGWA) for each of 23,947 measurable transcripts in Arabidopsis (host), and 9267 measurable transcripts in B. cinerea (pathogen). Unlike other eGWA studies, we detected a relative absence of locally acting expression quantitative trait loci (cis-eQTL), partly caused by structural variants and allelic heterogeneity hindering their identification. This study identified several distantly acting trans-eQTL linked to eQTL hotspots dispersed across Botrytis genome that altered only Botrytis transcripts, only Arabidopsis transcripts, or transcripts from both species. Gene membership in the trans-eQTL hotspots suggests links between gene expression regulation and both known and novel virulence mechanisms in this pathosystem. Genes annotated to these hotspots provide potential targets for blocking manipulation of the host response by this ubiquitous generalist necrotrophic pathogen.

Secondary branch number per panicle plays a crucial role in regulating grain number and yield in rice. Here, we report the positional cloning and functional characterization for SECONDARY BRANCH NUMBER7 (qSBN7), a quantitative trait locus affecting secondary branch per panicle and grain number. Our research revealed that the causative variants of qSBN7 are located in the distal promoter region of FRIZZLE PANICLE (FZP), a gene previously associated with the repression of axillary meristem development in rice spikelets. qSBN7 is a novel allele of FZP that causes an ~56% decrease in its transcriptional level, leading to increased secondary branch and grain number, and reduced grain length. Field evaluations showed that qSBN7 increased grain yield by 10.9% in a temperate japonica variety, TN13, likely due to its positive effect on sink capacity. Our findings suggest that incorporation of qSBN7 can increase yield potential and improve the breeding of elite rice varieties.

Real geography is continuous, but standard models in population genetics are based on discrete, well-mixed populations. As a result, many methods of analyzing genetic data assume that samples are a random draw from a well-mixed population, but are applied to clustered samples from populations that are structured clinally over space. Here, we use simulations of populations living in continuous geography to study the impacts of dispersal and sampling strategy on population genetic summary statistics, demographic inference, and genome-wide association studies (GWAS). We find that most common summary statistics have distributions that differ substantially from those seen in well-mixed populations, especially when Wright’s neighborhood size is < 100 and sampling is spatially clustered. "Stepping-stone" models reproduce some of these effects, but discretizing the landscape introduces artifacts that in some cases are exacerbated at higher resolutions. The combination of low dispersal and clustered sampling causes demographic inference from the site frequency spectrum to infer more turbulent demographic histories, but averaged results across multiple simulations revealed surprisingly little systematic bias. We also show that the combination of spatially autocorrelated environments and limited dispersal causes GWAS to identify spurious signals of genetic association with purely environmentally determined phenotypes, and that this bias is only partially corrected by regressing out principal components of ancestry. Last, we discuss the relevance of our simulation results for inference from genetic variation in real organisms.

The question of the relative evolutionary roles of adaptive and nonadaptive processes has been a central debate in population genetics for nearly a century. While advances have been made in the theoretical development of the underlying models, and statistical methods for estimating their parameters from large-scale genomic data, a framework for an appropriate null model remains elusive. A model incorporating evolutionary processes known to be in constant operation, genetic drift (as modulated by the demographic history of the population) and purifying selection, is lacking. Without such a null model, the role of adaptive processes in shaping within- and between-population variation may not be accurately assessed. Here, we investigate how population size changes and the strength of purifying selection affect patterns of variation at "neutral" sites near functional genomic components. We propose a novel statistical framework for jointly inferring the contribution of the relevant selective and demographic parameters. By means of extensive performance analyses, we quantify the utility of the approach, identify the most important statistics for parameter estimation, and compare the results with existing methods. Finally, we reanalyze genome-wide population-level data from a Zambian population of Drosophila melanogaster, and find that it has experienced a much slower rate of population growth than was inferred when the effects of purifying selection were neglected. Our approach represents an appropriate null model, against which the effects of positive selection can be assessed.

Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying signatures of selection in the ancestor that are shared among its descendants is important to contextualize the timing of a sweep, but few methods exist for this purpose. We introduce the statistic SS-H12, which can identify genomic regions under shared positive selection across populations and is based on the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. SS-H12 is distinct from comparable statistics because it requires a minimum of only two populations, and properly identifies and differentiates between independent convergent sweeps and true ancestral sweeps, with high power and robustness to a variety of demographic models. Furthermore, we can apply SS-H12 in conjunction with the ratio of statistics we term and to further classify identified shared sweeps as hard or soft. Finally, we identified both previously reported and novel shared sweep candidates from human whole-genome sequences. Previously reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-Europeans, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan Africans involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.

The vertebrate limb serves as an experimental paradigm to study mechanisms that regulate development of the stereotypical skeletal elements. In this study, we simultaneously inactivated Sall4 using Hoxb6Cre and Plzf in mouse embryos, and found that their combined function regulates development of the proximal-anterior skeletal elements in hindlimbs. The Sall4; Plzf double knockout exhibits severe defects in the femur, tibia, and anterior digits, distinct defects compared to other allelic series of Sall4; Plzf. We found that Sall4 regulates Plzf expression prior to hindlimb outgrowth. Further expression analysis indicated that Hox10 genes and GLI3 are severely downregulated in the Sall4; Plzf double knockout hindlimb bud. In contrast, PLZF expression is reduced but detectable in Sall4; Gli3 double knockout limb buds, and SALL4 is expressed in the Plzf; Gli3 double knockout limb buds. These results indicate that Plzf, Gli3, and Hox10 genes downstream of Sall4, regulate femur and tibia development. In the autopod, we show that Sall4 negatively regulates Hedgehog signaling, which allows for development of the most anterior digit. Collectively, our study illustrates genetic systems that regulate development of the proximal-anterior skeletal elements in hindlimbs.

The Hippo pathway is an evolutionarily conserved signaling network that regulates organ size, cell fate, and tumorigenesis. In the context of organ size control, the pathway incorporates a large variety of cellular cues, such as cell polarity and adhesion, into an integrated transcriptional response. The central Hippo signaling effector is the transcriptional coactivator Yorkie, which controls gene expression in partnership with different transcription factors, most notably Scalloped. When it is not activated by Yorkie, Scalloped can act as a repressor of transcription, at least in part due to its interaction with the corepressor protein Tgi. The mechanism by which Tgi represses transcription is incompletely understood, and therefore we sought to identify proteins that potentially operate together with Tgi. Using an affinity purification and mass-spectrometry approach we identified Pits and CtBP as Tgi-interacting proteins, both of which have been linked to transcriptional repression. Both Pits and CtBP were required for Tgi to suppress the growth of the Drosophila melanogaster eye and CtBP loss suppressed the undergrowth of yorkie mutant eye tissue. Furthermore, as reported previously for Tgi, overexpression of Pits repressed transcription of Hippo pathway target genes. These findings suggest that Tgi might operate together with Pits and CtBP to repress transcription of genes that normally promote tissue growth. The human orthologs of Tgi, CtBP, and Pits (VGLL4, CTBP2, and IRF2BP2) have previously been shown to physically and functionally interact to control transcription, implying that the mechanism by which these proteins control transcriptional repression is conserved throughout evolution.

BEAF (Boundary Element-Associated Factor) was originally identified as a Drosophila melanogaster chromatin domain insulator-binding protein, suggesting a role in gene regulation through chromatin organization and dynamics. Genome-wide mapping found that BEAF usually binds near transcription start sites, often of housekeeping genes, suggesting a role in promoter function. This would be a nontraditional role for an insulator-binding protein. To gain insight into molecular mechanisms of BEAF function, we identified interacting proteins using yeast two-hybrid assays. Here, we focus on the transcription factor Serendipity (Sry-). Interactions were confirmed in pull-down experiments using bacterially expressed proteins, by bimolecular fluorescence complementation, and in a genetic assay in transgenic flies. Sry- interacted with promoter-proximal BEAF both when bound to DNA adjacent to BEAF or > 2-kb upstream to activate a reporter gene in transient transfection experiments. The interaction between BEAF and Sry- was detected using both a minimal developmental promoter (y) and a housekeeping promoter (RpS12), while BEAF alone strongly activated the housekeeping promoter. These two functions for BEAF implicate it in playing a direct role in gene regulation at hundreds of BEAF-associated promoters.

Replication initiation in eukaryotic cells occurs asynchronously throughout S phase, yielding early- and late-replicating regions of the genome, a process known as replication timing (RT). RT changes during development to ensure accurate genome duplication and maintain genome stability. To understand the relative contributions that cell lineage, cell cycle, and replication initiation regulators have on RT, we utilized the powerful developmental systems available in Drosophila melanogaster. We generated and compared RT profiles from mitotic cells of different tissues and from mitotic and endocycling cells of the same tissue. Our results demonstrate that cell lineage has the largest effect on RT, whereas switching from a mitotic to an endoreplicative cell cycle has little to no effect on RT. Additionally, we demonstrate that the RT differences we observed in all cases are largely independent of transcriptional differences. We also employed a genetic approach in these same cell types to understand the relative contribution the eukaryotic RT control factor, Rif1, has on RT control. Our results demonstrate that Rif1 can function in a tissue-specific manner to control RT. Importantly, the Protein Phosphatase 1 (PP1) binding motif of Rif1 is essential for Rif1 to regulate RT. Together, our data support a model in which the RT program is primarily driven by cell lineage and is further refined by Rif1/PP1 to ultimately generate tissue-specific RT programs.

During meiotic prophase, concurrent transcription, recombination, and chromosome synapsis place substantial topological strain on chromosomal DNA, but the role of topoisomerases in this context remains poorly defined. Here, we analyzed the roles of topoisomerases I and II (Top1 and Top2) during meiotic prophase in Saccharomyces cerevisiae. We show that both topoisomerases accumulate primarily in promoter-containing intergenic regions of actively transcribing genes, including many meiotic double-strand break (DSB) hotspots. Despite the comparable binding patterns, top1 and top2 mutations have different effects on meiotic recombination. TOP1 disruption delays DSB induction and shortens the window of DSB accumulation by an unknown mechanism. By contrast, temperature-sensitive top2-1 mutants exhibit a marked delay in meiotic chromosome remodeling and elevated DSB signals on synapsed chromosomes. The problems in chromosome remodeling were linked to altered Top2 binding patterns rather than a loss of Top2 catalytic activity, and stemmed from a defect in recruiting the chromosome remodeler Pch2/TRIP13 to synapsed chromosomes. No chromosomal defects were observed in the absence of TOP1. Our results imply independent roles for Top1 and Top2 in modulating meiotic chromosome structure and recombination.

Age-at-onset is one of the critical traits in cohort studies of age-related diseases. Large-scale genome-wide association studies (GWAS) of age-at-onset traits can provide more insights into genetic effects on disease progression and transitions between stages. Moreover, proportional hazards (or Cox) regression models can achieve higher statistical power in a cohort study than a case-control trait using logistic regression. Although mixed-effects models are widely used in GWAS to correct for sample dependence, application of Cox mixed-effects models (CMEMs) to large-scale GWAS is so far hindered by intractable computational cost. In this work, we propose COXMEG, an efficient R package for conducting GWAS of age-at-onset traits using CMEMs. COXMEG introduces fast estimation algorithms for general sparse relatedness matrices including, but not limited to, block-diagonal pedigree-based matrices. COXMEG also introduces a fast and powerful score test for dense relatedness matrices, accounting for both population stratification and family structure. In addition, COXMEG generalizes existing algorithms to support positive semidefinite relatedness matrices, which are common in twin and family studies. Our simulation studies suggest that COXMEG, depending on the structure of the relatedness matrix, is orders of magnitude computationally more efficient than coxme and coxph with frailty for GWAS. We found that using sparse approximation of relatedness matrices yielded highly comparable results in controlling false-positive rate and retaining statistical power for an ethnically homogeneous family-based sample. By applying COXMEG to a study of Alzheimer’s disease (AD) with a Late-Onset Alzheimer’s Disease Family Study from the National Institute on Aging sample comprising 3456 non-Hispanic whites and 287 African Americans, we identified the APOE 4 variant with strong statistical power (P = 1e–101), far more significant than that reported in a previous study using a transformed variable and a marginal Cox model. Furthermore, we identified novel SNP rs36051450 (P = 2e–9) near GRAMD1B, the minor allele of which significantly reduced the hazards of AD in both genders. These results demonstrated that COXMEG greatly facilitates the application of CMEMs in GWAS of age-at-onset traits.

There is increasing interest in developing diagnostics that discriminate individual mutagenic mechanisms in a range of applications that include identifying population-specific mutagenesis and resolving distinct mutation signatures in cancer samples. Analyses for these applications assume that mutagenic mechanisms have a distinct relationship with neighboring bases that allows them to be distinguished. Direct support for this assumption is limited to a small number of simple cases, e.g., CpG hypermutability. We have evaluated whether the mechanistic origin of a point mutation can be resolved using only sequence context for a more complicated case. We contrasted single nucleotide variants originating from the multitude of mutagenic processes that normally operate in the mouse germline with those induced by the potent mutagen N-ethyl-N-nitrosourea (ENU). The considerable overlap in the mutation spectra of these two samples make this a challenging problem. Employing a new, robust log-linear modeling method, we demonstrate that neighboring bases contain information regarding point mutation direction that differs between the ENU-induced and spontaneous mutation variant classes. A logistic regression classifier exhibited strong performance at discriminating between the different mutation classes. Concordance between the feature set of the best classifier and information content analyses suggest our results can be generalized to other mutation classification problems. We conclude that machine learning can be used to build a practical classification tool to identify the mutation mechanism for individual genetic variants. Software implementing our approach is freely available under an open-source license.

The way genes contribute to behavior is complicated. Although there are some single genes with large contributions, most behavioral differences are due to small effects from many interacting genes. This makes it hard to identify the genes that cause behavioral differences. Mutagenesis screens in model organisms, selective breeding experiments in animals, comparisons between related populations with different behaviors, and genome-wide association studies in humans are promising and complementary approaches to understanding the heritable aspects of complex behaviors. To connect genes to behaviors requires measuring behavioral differences, locating correlated genetic changes, determining when, where, and how these candidate genes act, and designing causative confirmatory experiments. This area of research has implications from basic discovery science to human mental health.

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