Prediction of phenotype and gene expression for combinations of mutations

Molecular interactions provide paths for information flows. Genetic interactions reveal active information flows and reflect their functional consequences. We integrated these complementary data types to model the transcription network controlling cell differentiation in yeast. Genetic interactions were inferred from linear decomposition of gene expression data and were used to direct the construction of a molecular interaction network mediating these genetic effects. This network included both known and novel regulatory influences, and predicted genetic interactions. For corresponding combinations of mutations, the network model predicted quantitative gene expression profiles and precise phenotypic effects. Multiple predictions were tested and verified

Low fitness partially explains resting metabolic rate differences between African American and white women

Background High levels of obesity among African American women have been hypothesized to be partially resultant from a lower resting metabolic rate compared with white women. The aim of the current study was to determine if differences in cardiorespiratory fitness and moderate-to-vigorous physical activity are associated with differences in resting metabolic rate among free-living young adult African American women and white women. Methods Participants were 179 women (white women n = 141, African American women n = 38, mean age = 27.7 years). Resting metabolic rate was measured using indirect calorimetry, body composition using dual energy x-ray absorptiometry, cardiorespiratory fitness via maximal treadmill test, and moderate-to-vigorous physical activity using an activity monitor. Results African American women had higher body mass index, fat mass, and fat-free mass compared with white women but lower levels of cardiorespiratory fitness. No differences were observed between African American and white women in resting metabolic rate when expressed as kcal/day (1390.8 ± 197.5 vs 1375.7 ± 173.6 kcal/day, P =.64), but African American women had a lower resting metabolic rate when expressed relative to body weight (2.56 ± 0.30 vs 2.95 ± 0.33 mL/kg/min,

Biofuel Blending Reduces Aircraft Engine Particle Emissions at Cruise Conditions

Aviation aerosol emissions have a disproportionately large climatic impact because they are emitted high in the relatively pristine upper troposphere where they can form linear contrails and influence cirrus clouds. Research aircraft from NASA, DLR, and NRC Canada made airborne measurements of gaseous and aerosol composition and contrail microphysical properties behind the NASA DC-8 aircraft at cruise altitudes. The DC-8 CFM-56-2C engines burned traditional medium-sulfur Jet A fuel as well as a low-sulfur Jet A fuel and a 50:50 biofuel blend. Substantial, two-to-three-fold emissions reductions are found for both particle number and mass emissions across the range of cruise thrust operating conditions. These observations provide direct and compelling evidence for the beneficial impacts of biojet fuel blending under real-world conditions

Maximal Extraction of Biological Information from Genetic Interaction Data

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

Effect of concurrent mitral valve surgery for secondary mitral regurgitation upon mortality after aortic valve replacement or coronary artery bypass surgery

ObjectivesIt is uncertain whether concurrent mitral valve repair or replacement for moderate or greater secondary mitral regurgitation at the time of coronary artery bypass graft or aortic valve replacement surgery improves long-term survival.MethodsPatients undergoing coronary artery bypass graft and/or aortic valve replacement surgery with moderate or greater secondary mitral regurgitation were reviewed. The effect of concurrent mitral valve repair or replacement upon long-term mortality was assessed while accounting for patient and operative characteristics and mitral regurgitation severity.ResultsOf 1,515 patients, 938 underwent coronary artery bypass graft or aortic valve replacement surgery alone and 577 underwent concurrent mitral valve repair or replacement. Concurrent mitral valve repair or replacement did not alter the risk of postoperative mortality for patients with moderate mitral regurgitation (hazard ratio = 0.93; 0.75–1.17) or more-than-moderate mitral regurgitation (hazard ratio = 1.09; 0.74–1.60) in multivariable regression. Patients with more-than-moderate mitral regurgitation undergoing coronary artery bypass graft-only surgery had a survival advantage from concurrent mitral valve repair or replacement in the first two postoperative years (P = 0.028) that did not persist beyond that time. Patients who underwent concurrent mitral valve repair or replacement had a higher rate of later mitral valve operation or reoperation over the five subsequent years (1.9% vs. 0.2%; P = 0.0014) than those who did not.ConclusionsThese observations suggest that mitral valve repair or replacement for more-than-moderate mitral regurgitation at the time of coronary artery bypass grafting may be reasonable in a suitably selected coronary artery bypass graft population but not for aortic valve replacement, with or without coronary artery bypass grafting. Our findings are supportive of 2021 European guidelines that severe secondary mitral regurgitation “should” or be “reasonabl[y]” intervened upon at the time of coronary artery bypass grafting but do not support 2020 American guidelines for performing mitral valve repair or replacement concurrent with aortic valve replacement, with or without coronary artery bypass grafting

Epithelial-Mesenchymal Transition in Cancer: Parallels Between Normal Development and Tumor Progression

From the earliest stages of embryonic development, cells of epithelial and mesenchymal origin contribute to the structure and function of developing organs. However, these phenotypes are not always permanent, and instead, under the appropriate conditions, epithelial and mesenchymal cells convert between these two phenotypes. These processes, termed Epithelial-Mesenchymal Transition (EMT), or the reverse Mesenchymal-Epithelial Transition (MET), are required for complex body patterning and morphogenesis. In addition, epithelial plasticity and the acquisition of invasive properties without the full commitment to a mesenchymal phenotype are critical in development, particularly during branching morphogenesis in the mammary gland. Recent work in cancer has identified an analogous plasticity of cellular phenotypes whereby epithelial cancer cells acquire mesenchymal features that permit escape from the primary tumor. Because local invasion is thought to be a necessary first step in metastatic dissemination, EMT and epithelial plasticity are hypothesized to contribute to tumor progression. Similarities between developmental and oncogenic EMT have led to the identification of common contributing pathways, suggesting that the reactivation of developmental pathways in breast and other cancers contributes to tumor progression. For example, developmental EMT regulators including Snail/Slug, Twist, Six1, and Cripto, along with developmental signaling pathways including TGF-β and Wnt/β-catenin, are misexpressed in breast cancer and correlate with poor clinical outcomes. This review focuses on the parallels between epithelial plasticity/EMT in the mammary gland and other organs during development, and on a selection of developmental EMT regulators that are misexpressed specifically during breast cancer

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

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

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

Criterion validity of wrist accelerometry for assessing energy intake via the intake-balance technique

Abstract Background Intake-balance assessments measure energy intake (EI) by summing energy expenditure (EE) with concurrent change in energy storage (ΔES). Prior work has not examined the validity of such calculations when EE is estimated via open-source techniques for research-grade accelerometry devices. The purpose of this study was to test the criterion validity of accelerometry-based intake-balance methods for a wrist-worn ActiGraph device. Methods Healthy adults (n = 24) completed two 14-day measurement periods while wearing an ActiGraph accelerometer on the non-dominant wrist. During each period, criterion values of EI were determined based on ΔES measured by dual X-ray absorptiometry and EE measured by doubly labeled water. A total of 11 prediction methods were tested, 8 derived from the accelerometer and 3 from non-accelerometry methods (e.g., diet recall; included for comparison). Group-level validity was assessed through mean bias, while individual-level validity was assessed through mean absolute error, mean absolute percentage error, and Bland–Altman analysis. Results Mean bias for the three best accelerometry-based methods ranged from -167 to 124 kcal/day, versus -104 to 134 kcal/day for the non-accelerometry-based methods. The same three accelerometry-based methods had mean absolute error of 323–362 kcal/day and mean absolute percentage error of 18.1-19.3%, versus 353–464 kcal/day and 19.5-24.4% for the non-accelerometry-based methods. All 11 methods demonstrated systematic bias in the Bland–Altman analysis. Conclusions Accelerometry-based intake-balance methods have promise for advancing EI assessment, but ongoing refinement is necessary. We provide an R package to facilitate implementation and refinement of accelerometry-based methods in future research (see paulhibbing.com/IntakeBalance)

Extremes of weight gain and weight loss with detailed assessments of energy balance: illustrative case studies and clinical recommendations

Extreme weight changes, or changes in weight greater than 10 kg within a 2-year period, can be caused by numerous factors that are much different than typical weight fluctuations. This paper uses two interesting cases of extreme weight change (a female who experienced extreme weight gain and a male who experienced extreme weight loss) from participants in the Energy Balance Study to illustrate the physiological and psychosocial variables associated with the weight change over a 15-month period, including rigorous assessments of energy intake, physical activity (PA) and energy expenditure, and body composition. In addition, we provide a brief review of the literature regarding the relationship between energy balance (EB) and weight change, as well as insight into proper weight management strategies. The case studies presented here are then placed in the context of the literature regarding EB and weight change. This report further supports previous research on the importance of regular doses of PA for weight maintenance, and that even higher volumes of PA are necessary for weight loss. Practitioners should emphasize the importance of PA to their patients and take steps to monitor their patients’ involvement in PA