Enclaves in the Cadillac Mountain Granite (Coastal Maine): Samples of Hybrid Magma from the Base of the Chamber

The Cadillac Mountain intrusive complex is dominated by the Cadillac Mountain granite and a 2–3 km thick section of interlayered gabbroic, dioritic and granitic rocks which occurs near the base of the granite. The layered rocks record hundreds of injections of basaltic magma that ponded on the chamber floor and variably interacted with the overlying silicic magma. Magmatic enclaves, ranging in composition from 55 to 78 wt % SiO2, are abundant in granite above the layered mafic rocks. The most mafic enclaves are highly enriched in incompatible elements and depleted in compatible elements. Their compositions can be best explained by periodic replenishment, mixing and fractional crystallization of basaltic magma at the base of the chamber. The intermediate to silicic enclaves formed by hybridization between the evolved basaltic magma and resident silicic magma. There is little evidence for significant exchange between enclaves and the enclosing granite. Instead, hybridization apparently occurred between stratified mafic and silicic magmas at the base of the chamber. Enclaves in a restricted area commonly show distinctive compositional characteristics, suggesting they were derived from a discrete batch of hybrid magma. Enclaves were probably dispersed into a localized portion of the granitic magma when replenishment or eruption disrupted the intermediate layer

State-based policies on alcohol use during pregnancy

Alcohol use is common in the United States. In 2020, 54.2% of adults age 18 and older reported drinking in the last month.1 Among female adults age 18 and older, 66.9% reported consuming alcohol in the last year and 51.2% reported any alcohol use in the past month.1 An estimated 9% of women have an alcohol use disorder.1 Approximately 18% of reproductive-age women (18–44 years) binge drink (defined as consuming four or more standard drinks in about 2 hours for women).2,3 Concerningly, analysis of data from the Behavioral Risk Factor Surveillance System (BRFSS) collected between 2011 and 2018 suggests that alcohol consumption during pregnancy is increasing.4 Recent analysis of 2018–2020 BRFSS data indicates that 13.5% of pregnant adults reported current drinking and 5.2% reported binge drinking, and these numbers are likely an underestimation.4,5 Fetal alcohol spectrum disorders (FASDs) are a range of life-long developmental conditions associated with exposure to alcohol during pregnancy.6 These conditions include fetal alcohol syndrome, partial fetal alcohol syndrome, alcohol-related neurodevelopmental disorder, alcohol-related birth defects, and neurobehavioral disorder associated with prenatal alcohol exposure.7,8 According to recent estimates, up to 1 in 20 schoolchildren in the US may have FASDs.9 The impact of such alcohol exposure can result in changes in brain development, manifesting as impaired neurocognitive function, poor executive functioning, attention deficits, and memory impairment, among other outcomes.7,9 Additionally, prenatal alcohol exposure can result in adverse birth outcomes such as premature birth and low birth weight.10 In an effort to reduce the number of alcohol-exposed pregnancies, 43 states have implemented legislation targeting alcohol use among pregnant people. This brief report summarizes the current status of these policies.Ye

Mining gene expression data by interpreting principal components

BACKGROUND: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many instances the biologically important goal is to identify relatively small sets of genes that share coherent expression across only some conditions, rather than all or most conditions as required in traditional clustering; e.g. genes that are highly up-regulated and/or down-regulated similarly across only a subset of conditions. Equally important is the need to learn which conditions are the decisive ones in forming such gene sets of interest, and how they relate to diverse conditional covariates, such as disease diagnosis or prognosis. RESULTS: We present a method for automatically identifying such candidate sets of biologically relevant genes using a combination of principal components analysis and information theoretic metrics. To enable easy use of our methods, we have developed a data analysis package that facilitates visualization and subsequent data mining of the independent sources of significant variation present in gene microarray expression datasets (or in any other similarly structured high-dimensional dataset). We applied these tools to two public datasets, and highlight sets of genes most affected by specific subsets of conditions (e.g. tissues, treatments, samples, etc.). Statistically significant associations for highlighted gene sets were shown via global analysis for Gene Ontology term enrichment. Together with covariate associations, the tool provides a basis for building testable hypotheses about the biological or experimental causes of observed variation. CONCLUSION: We provide an unsupervised data mining technique for diverse microarray expression datasets that is distinct from major methods now in routine use. In test uses, this method, based on publicly available gene annotations, appears to identify numerous sets of biologically relevant genes. It has proven especially valuable in instances where there are many diverse conditions (10's to hundreds of different tissues or cell types), a situation in which many clustering and ordering algorithms become problematic. This approach also shows promise in other topic domains such as multi-spectral imaging datasets

A mathematical and computational framework for quantitative comparison and integration of large-scale gene expression data

Analysis of large-scale gene expression studies usually begins with gene clustering. A ubiquitous problem is that different algorithms applied to the same data inevitably give different results, and the differences are often substantial, involving a quarter or more of the genes analyzed. This raises a series of important but nettlesome questions: How are different clustering results related to each other and to the underlying data structure? Is one clustering objectively superior to another? Which differences, if any, are likely candidates to be biologically important? A systematic and quantitative way to address these questions is needed, together with an effective way to integrate and leverage expression results with other kinds of large-scale data and annotations. We developed a mathematical and computational framework to help quantify, compare, visualize and interactively mine clusterings. We show that by coupling confusion matrices with appropriate metrics (linear assignment and normalized mutual information scores), one can quantify and map differences between clusterings. A version of receiver operator characteristic analysis proved effective for quantifying and visualizing cluster quality and overlap. These methods, plus a flexible library of clustering algorithms, can be called from a new expandable set of software tools called CompClust 1.0 (). CompClust also makes it possible to relate expression clustering patterns to DNA sequence motif occurrences, protein–DNA interaction measurements and various kinds of functional annotations. Test analyses used yeast cell cycle data and revealed data structure not obvious under all algorithms. These results were then integrated with transcription motif and global protein–DNA interaction data to identify G(1) regulatory modules

The Landscape of Extreme Genomic Variation in the Highly Adaptable Atlantic Killifish

Understanding and predicting the fate of populations in changing environments require knowledge about the mechanisms that support phenotypic plasticity and the adaptive value and evolutionary fate of genetic variation within populations. Atlantic killifish (Fundulus heteroclitus) exhibit extensive phenotypic plasticity that supports large population sizes in highly fluctuating estuarine environments. Populations have also evolved diverse local adaptations. To yield insights into the genomic variation that supports their adaptability, we sequenced a reference genome and 48 additional whole genomes from a wild population. Evolution of genes associated with cell cycle regulation and apoptosis is accelerated along the killifish lineage, which is likely tied to adaptations for life in highly variable estuarine environments. Genome-wide standing genetic variation, including nucleotide diversity and copy number variation, is extremely high. The highest diversity genes are those associated with immune function and olfaction, whereas genes under greatest evolutionary constraint are those associated with neurological, developmental, and cytoskeletal functions. Reduced genetic variation is detected for tight junction proteins, which in killifish regulate paracellular permeability that supports their extreme physiological flexibility. Low-diversity genes engage in more regulatory interactions than high-diversity genes, consistent with the influence of pleiotropic constraint on molecular evolution. High genetic variation is crucial for continued persistence of species given the pace of contemporary environmental change. Killifish populations harbor among the highest levels of nucleotide diversity yet reported for a vertebrate species, and thus may serve as a useful model system for studying evolutionary potential in variable and changing environments

Adapting and RE-AIMing a heart disease prevention program for older women with diabetes

Coronary heart disease is a pervasive public health problem with a heavy burden among older women. There is a need for developing effective interventions for addressing this problem and for evaluating the dissemination potential of such interventions. A multiple-behavior-change program originally designed for men with heart disease was adapted for women at high risk of heart disease in two randomized clinical trials—the Mediterranean Lifestyle Program and ¡Viva Bien!. Results from these two trials, including readiness for dissemination, are evaluated using the RE-AIM framework in terms of Reach, Effectiveness, Adoption, Implementation, and Maintenance. Program adaptations produced relative high reach as well as consistent and replicated effectiveness and maintenance, and were adopted by a high percentage of primary care offices and clinicians approached. We discuss key findings, lessons learned, future directions for related research, and use of RE-AIM for program development, adaptation, scale-up, and evaluation.Ye

The landscape of extreme genomic variation in the highly adaptable Atlantic killifish

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Genome Biology and Evolution 9 (2017): 659-676, doi:10.1093/gbe/evx023.Understanding and predicting the fate of populations in changing environments require knowledge about the mechanisms that support phenotypic plasticity and the adaptive value and evolutionary fate of genetic variation within populations. Atlantic killifish (Fundulus heteroclitus) exhibit extensive phenotypic plasticity that supports large population sizes in highly fluctuating estuarine environments. Populations have also evolved diverse local adaptations. To yield insights into the genomic variation that supports their adaptability, we sequenced a reference genome and 48 additional whole genomes from a wild population. Evolution of genes associated with cell cycle regulation and apoptosis is accelerated along the killifish lineage, which is likely tied to adaptations for life in highly variable estuarine environments. Genome-wide standing genetic variation, including nucleotide diversity and copy number variation, is extremely high. The highest diversity genes are those associated with immune function and olfaction, whereas genes under greatest evolutionary constraint are those associated with neurological, developmental, and cytoskeletal functions. Reduced genetic variation is detected for tight junction proteins, which in killifish regulate paracellular permeability that supports their extreme physiological flexibility. Low-diversity genes engage in more regulatory interactions than high-diversity genes, consistent with the influence of pleiotropic constraint on molecular evolution. High genetic variation is crucial for continued persistence of species given the pace of contemporary environmental change. Killifish populations harbor among the highest levels of nucleotide diversity yet reported for a vertebrate species, and thus may serve as a useful model system for studying evolutionary potential in variable and changing environments.This work was primarily supported by a grant from the National Science Foundation (collaborative research grants DEB-1265282, DEB-1120512, DEB-1120013, DEB-1120263, DEB-1120333, DEB-1120398 to J.K.C., D.L.C., M.E.H., S.I.K., M.F.O., J.R.S., W.W., and A.W.). Further support was provided by the National Institute of Environmental Health Sciences (1R01ES021934-01 to A.W., P42ES7373 to T.H.H., P42ES007381 to M.E.H., and R01ES019324 to J.R.S.), the National Institute of General Medical Sciences (P20GM103423 and P20GM104318 to B.L.K.), and the National Science Foundation (DBI-0640462 and XSEDE-MCB100147 to D.G.)

Mall Walking Program Environments, Features, and Participants: A Scoping Review

Introduction Walking is a preferred and recommended physical activity for middle-aged and older adults, but many barriers exist, including concerns about safety (ie, personal security), falling, and inclement weather. Mall walking programs may overcome these barriers. The purpose of this study was to summarize the evidence on the health-related value of mall walking and mall walking programs. Methods We conducted a scoping review of the literature to determine the features, environments, and benefits of mall walking programs using the RE-AIM framework (reach, effectiveness, adoption, implementation, and maintenance). The inclusion criteria were articles that involved adults aged 45 years or older who walked in indoor or outdoor shopping malls. Exclusion criteria were articles that used malls as laboratory settings or focused on the mechanics of walking. We included published research studies, dissertations, theses, conference abstracts, syntheses, non research articles, theoretical papers, editorials, reports, policy briefs, standards and guidelines, and non research conference abstracts and proposals. Websites and articles written in a language other than English were excluded. Results We located 254 articles on mall walking; 32 articles met our inclusion criteria. We found that malls provided safe, accessible, and affordable exercise environments for middle-aged and older adults. Programmatic features such as program leaders, blood pressure checks, and warm-up exercises facilitated participation. Individual benefits of mall walking programs included improvements in physical, social, and emotional well-being. Limited transportation to the mall was a barrier to participation. Conclusion We found the potential for mall walking programs to be implemented in various communities as a health promotion measure. However, the research on mall walking programs is limited and has weak study designs. More rigorous research is needed to define best practices for mall walking programs’ reach, effectiveness, adoption, implementation, and maintenance.Ye

Understanding and applying the RE-AIM framework: Clarifications and resources

Introduction: Understanding, categorizing, and using implementation science theories, models, and frameworks is a complex undertaking. The issues involved are even more challenging given the large number of frameworks and that some of them evolve significantly over time. As a consequence, researchers and practitioners may be unintentionally mischaracterizing frameworks or basing actions and conclusions on outdated versions of a framework. Methods: This paper addresses how the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework has been described, summarizes how the model has evolved over time, and identifies and corrects several misconceptions. Results: We address 13 specific areas where misconceptions have been noted concerning the use of RE-AIM and summarize current guidance on these issues. We also discuss key changes to RE-AIM over the past 20 years, including the evolution to Pragmatic Robust Implementation and Sustainability Model, and provide resources for potential users to guide application of the framework. Conclusions: RE-AIM and many other theories and frameworks have evolved, been misunderstood, and sometimes been misapplied. To some degree, this is inevitable, but we conclude by suggesting some actions that reviewers, framework developers, and those selecting or applying frameworks can do to prevent or alleviate these problems.Ye

Association of Accelerometry-Measured Physical Activity and Cardiovascular Events in Mobility-Limited Older Adults: The LIFE (Lifestyle Interventions and Independence for Elders) Study.

BACKGROUND:Data are sparse regarding the value of physical activity (PA) surveillance among older adults-particularly among those with mobility limitations. The objective of this study was to examine longitudinal associations between objectively measured daily PA and the incidence of cardiovascular events among older adults in the LIFE (Lifestyle Interventions and Independence for Elders) study. METHODS AND RESULTS:Cardiovascular events were adjudicated based on medical records review, and cardiovascular risk factors were controlled for in the analysis. Home-based activity data were collected by hip-worn accelerometers at baseline and at 6, 12, and 24 months postrandomization to either a physical activity or health education intervention. LIFE study participants (n=1590; age 78.9±5.2 [SD] years; 67.2% women) at baseline had an 11% lower incidence of experiencing a subsequent cardiovascular event per 500 steps taken per day based on activity data (hazard ratio, 0.89; 95% confidence interval, 0.84-0.96; P=0.001). At baseline, every 30 minutes spent performing activities ≥500 counts per minute (hazard ratio, 0.75; confidence interval, 0.65-0.89 [P=0.001]) were also associated with a lower incidence of cardiovascular events. Throughout follow-up (6, 12, and 24 months), both the number of steps per day (per 500 steps; hazard ratio, 0.90, confidence interval, 0.85-0.96 [P=0.001]) and duration of activity ≥500 counts per minute (per 30 minutes; hazard ratio, 0.76; confidence interval, 0.63-0.90 [P=0.002]) were significantly associated with lower cardiovascular event rates. CONCLUSIONS:Objective measurements of physical activity via accelerometry were associated with cardiovascular events among older adults with limited mobility (summary score >10 on the Short Physical Performance Battery) both using baseline and longitudinal data. CLINICAL TRIAL REGISTRATION:URL: http://www.clinicaltrials.gov. Unique identifier: NCT01072500