94 research outputs found

    Maximal Extraction of Biological Information from Genetic Interaction Data

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    Targeted genetic perturbation is a powerful tool for inferring gene function in model organisms. Functional relationships between genes can be inferred by observing the effects of multiple genetic perturbations in a single strain. The study of these relationships, generally referred to as genetic interactions, is a classic technique for ordering genes in pathways, thereby revealing genetic organization and gene-to-gene information flow. Genetic interaction screens are now being carried out in high-throughput experiments involving tens or hundreds of genes. These data sets have the potential to reveal genetic organization on a large scale, and require computational techniques that best reveal this organization. In this paper, we use a complexity metric based in information theory to determine the maximally informative network given a set of genetic interaction data. We find that networks with high complexity scores yield the most biological information in terms of (i) specific associations between genes and biological functions, and (ii) mapping modules of co-functional genes. This information-based approach is an automated, unsupervised classification of the biological rules underlying observed genetic interactions. It might have particular potential in genetic studies in which interactions are complex and prior gene annotation data are sparse

    North Carolina public school teachers’ contact patterns and mask use within and outside of school during the pre-vaccine phase of the COVID-19 pandemic

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    Background : Teachers are central to school-associated transmission networks, but little is known about their behavioral patterns during the COVID-19 pandemic. Methods : We conducted a cross-sectional survey of 700 North Carolina public school teachers in four districts open to in-person learning in November-December 2020 (pre-COVID-19 vaccines). We assessed indoor and outdoor time spent, numbers of people encountered at 94%) reported wearing masks inside school, stores, and salons; intermediate percentages (∼50%-85%) inside places of worship, bars/restaurants, and recreational settings; and few (<25%) in their or others’ homes. Approximately half reported daily close contact with students. Conclusions : As schools reopened in the COVID-19 pandemic, potential transmission opportunities arose through close contacts within and outside of school, along with suboptimal mask use by teachers and/or those around them. Our granular estimates underscore the importance of multi-layered mitigation strategies and can inform interventions and mathematical models addressing school-associated transmission

    Airborne formaldehyde and volatile organic compound measurements over the Daesan petrochemical complex on Korea’s northwest coast during the Korea-United States Air Quality study

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    The U.S. National Aeronautics and Space Administration in partnership with Korea’s National Institute of Environmental Research embarked on the Korea-United States Air Quality (KORUS-AQ) study to address air quality issues over the Korean peninsula. Underestimation of volatile organic compound (VOC) emissions from various large facilities on South Korea’s northwest coast may contribute to this problem, and this study focuses on quantifying top-down emissions of formaldehyde (CH₂O) and VOCs from the largest of these facilities, the Daesan petrochemical complex, and comparisons with the latest emission inventories. To accomplish this and additional goals discussed herein, this study employed a number of measurements acquired during KORUS-AQ onboard the NASA DC-8 aircraft during three Daesan overflights on June 2, 3, and 5, 2016, in conjunction with a mass balance approach. The measurements included fast airborne measurements of CH₂O and ethane from an infrared spectrometer, additional fast measurements from other instruments, and a suite of 33 VOC measurements acquired by the whole air sampler. The mass balance approach resulted in consistent top-down yearly Daesan VOC emission flux estimates, which averaged (61 ± 14) × 10³ MT/year for the 33 VOC compounds, a factor of 2.9 ± 0.6 (±1.0) higher than the bottom-up inventory value. The top-down Daesan emission estimate for CH₂O and its four primary precursors averaged a factor of 4.3 ± 1.5 (± 1.9) times higher than the bottom-up inventory value. The uncertainty values in parentheses reflect upper limits for total uncertainty estimates. The resulting averaged top-down Daesan emission estimate for sulfur dioxide (SO₂) yielded a ratio of 0.81–1.0 times the bottom-up SO₂ inventory, and this provides an important cross-check on the accuracy of our mass balance analysis

    Typologies of post-divorce coparenting and parental well-being, parenting quality and children’s psychological adjustment

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    First published online: 30 October 2015The aim of this study was to identify post-divorce coparenting profiles and examine whether these profiles differentiate between levels of parents’ well-being, parenting practices, and children’s psychological problems. Cluster analysis was conducted with Portuguese heterosexual divorced parents (N = 314) to yield distinct postdivorce coparenting patterns. Clusters were based on parents’ self-reported coparenting relationship assessed along four dimensions: agreement, exposure to conflict, undermining/support, and division of labor. A three cluster solution was found and replicated. Parents in the highconflict coparenting group exhibited significantly lower life satisfaction, as well as significantly higher divorce-related negative affect and inconsistent parenting than parents in undermining and cooperative coparenting clusters. The cooperative coparenting group reported higher levels of positive family functioning and lower externalizing and internalizing problems in their children. These results suggested that a positive coparenting alliance may be a protective factor for individual and family outcomes after parental divorce

    Multi-campaign ship and aircraft observations of marine cloud condensation nuclei and droplet concentrations

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    In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP2EX; ORACLES; SOCRATES; MARCUS; and CAPRICORN2. Each campaign involves aircraft measurements, ship-based measurements, or both. Measurements collected over the North and Central Atlantic, Indo-Pacific, and Southern Oceans, represent a range of clean to polluted conditions in various climate regimes. With the extensive range of environmental conditions sampled, this data collection is ideal for testing satellite remote detection methods of CDNC and CCN in marine environments. Remote measurement methods are vital to expanding the available data in these difficult-to-reach regions of the Earth and improving our understanding of aerosol-cloud interactions. The data collection includes particle composition and continental tracers to identify potential contributing CCN sources. Several of these campaigns include High Spectral Resolution Lidar (HSRL) and polarimetric imaging measurements and retrievals that will be the basis for the next generation of space-based remote sensors and, thus, can be utilized as satellite surrogates

    Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: findings from the ENIGMA ADHD, ASD, and OCD Working Groups

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    Objective Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders. Methods Structural T1-weighted whole-brain MRI of controls (n=5,827) and patients with ADHD (n=2,271), ASD (n=1,777), and OCD (n=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. We examined subcortical volume, cortical thickness and surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults using linear mixed-effects models adjusting for age, sex and site (and ICV for subcortical and surface area measures). Results We found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed. Conclusion Our findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippocampal alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders
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