Cardiac rehabilitation (CR) is an evidence-based intervention that uses patient education, health behavior modification, and exercise training to improve secondary prevention outcomes in patients ...with cardiovascular disease. CR programs reduce morbidity and mortality rates in adults with ischemic heart disease, heart failure, or cardiac surgery but are significantly underused, with only a minority of eligible patients participating in CR in the United States. New delivery strategies are urgently needed to improve participation. One potential strategy is home-based CR (HBCR). In contrast to center-based CR services, which are provided in a medically supervised facility, HBCR relies on remote coaching with indirect exercise supervision and is provided mostly or entirely outside of the traditional center-based setting. Although HBCR has been successfully deployed in the United Kingdom, Canada, and other countries, most US healthcare organizations have little to no experience with such programs. The purpose of this scientific statement is to identify the core components, efficacy, strengths, limitations, evidence gaps, and research necessary to guide the future delivery of HBCR in the United States. Previous randomized trials have generated low- to moderate-strength evidence that HBCR and center-based CR can achieve similar improvements in 3- to 12-month clinical outcomes. Although HBCR appears to hold promise in expanding the use of CR to eligible patients, additional research and demonstration projects are needed to clarify, strengthen, and extend the HBCR evidence base for key subgroups, including older adults, women, underrepresented minority groups, and other higher-risk and understudied groups. In the interim, we conclude that HBCR may be a reasonable option for selected clinically stable low- to moderate-risk patients who are eligible for CR but cannot attend a traditional center-based CR program.
In 2010, the American Heart Association defined a novel construct of cardiovascular health to promote a paradigm shift from a focus solely on disease treatment to one inclusive of positive health ...promotion and preservation across the life course in populations and individuals. Extensive subsequent evidence has provided insights into strengths and limitations of the original approach to defining and quantifying cardiovascular health. In response, the American Heart Association convened a writing group to recommend enhancements and updates. The definition and quantification of each of the original metrics (Life's Simple 7) were evaluated for responsiveness to interindividual variation and intraindividual change. New metrics were considered, and the age spectrum was expanded to include the entire life course. The foundational contexts of social determinants of health and psychological health were addressed as crucial factors in optimizing and preserving cardiovascular health. This presidential advisory introduces an enhanced approach to assessing cardiovascular health: Life's Essential 8. The components of Life's Essential 8 include diet (updated), physical activity, nicotine exposure (updated), sleep health (new), body mass index, blood lipids (updated), blood glucose (updated), and blood pressure. Each metric has a new scoring algorithm ranging from 0 to 100 points, allowing generation of a new composite cardiovascular health score (the unweighted average of all components) that also varies from 0 to 100 points. Methods for implementing cardiovascular health assessment and longitudinal monitoring are discussed, as are potential data sources and tools to promote widespread adoption in policy, public health, clinical, institutional, and community settings.
The innate immune response of multicellular organisms is initiated by the binding of soluble and membrane-bound host molecules including lectins to the surface of pathogenic organisms. Until ...recently, it was believed that the epitopes recognized by host molecules were uniquely associated with the pathogenic organisms. Hence, the term pattern recognition receptors (PRRs) was used to describe their binding specificities. However, with an expanding number of lectin classes including C-type lectins, siglecs, and galectins recognized as PRRs, it is apparent that many of the glycan epitopes recognized on foreign pathogens are present in the host and involved in cellular functions. Hence, the molecular basis for pattern recognition by lectins of carbohydrate epitopes on pathogens is in question. A number of studies indicate that the density and number of glycan epitopes in multivalent carbohydrates and glycoprotein receptors determine the affinity of lectins and their effector functions. This paper reviews lectins that are involved in innate immunity, mechanisms of enhanced affinity and cross-linking of lectins with density-dependent glycan epitopes, density-dependent recognition of glycan receptors by lectins in host systems and lectin-glycan interactions in foreign pathogens. Evidence indicates that lectin pattern recognition in innate immunity is part of a general mechanism of density-dependent glycan recognition. This leads to a new definition of lectin receptor in biological systems, which considers the density and number of glycan epitopes on the surface of cells and not just the affinity of single epitopes.
The ever-increasing volume and accessibility of remote sensing data has spawned many alternative approaches for mapping important environmental features and processes. For example, there are several ...viable but highly varied strategies for using time series of Landsat imagery to detect changes in forest cover. Performance among algorithms varies across complex natural systems, and it is reasonable to ask if aggregating the strengths of an ensemble of classifiers might result in increased overall accuracy. Relatively simple rules have been used in the past to aggregate classifications among remotely sensed maps (e.g. using majority predictions), and in other fields, empirical models have been used to create situationally specific algorithm weights. The latter process, called “stacked generalization” (or “stacking”), typically uses a parametric model for the fusion of algorithm outputs. We tested the performance of several leading forest disturbance detection algorithms against ensembles of the outputs of those same algorithms based upon stacking using both parametric and Random Forests-based fusion rules. Stacking using a Random Forests model cut omission and commission error rates in half in many cases in relation to individual change detection algorithms, and cut error rates by one quarter compared to more conventional parametric stacking. Stacking also offers two auxiliary benefits: alignment of outputs to the precise definitions built into a particular set of empirical calibration data; and, outputs which may be adjusted such that map class totals match independent estimates of change in each year. In general, ensemble predictions improve when new inputs are added that are both informative and uncorrelated with existing ensemble components. As increased use of cloud-based computing makes ensemble mapping methods more accessible, the most useful new algorithms may be those that specialize in providing spectral, temporal, or thematic information not already available through members of existing ensembles.
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•Stacking can be used to leverage an ensemble of maps to improve accuracy.•Stacking can align a mapping process with project-specific class definitions.•Random Forests was better than logistic regression as an ensemble fusion rule.•Cloud computing lowers barriers to stacking.•Future algorithm development may focus on specialization to fill ensemble gaps.
Education Abroad and the Undergraduate Experience Elizabeth Brewer, Anthony C. Ogden / Elizabeth Brewer, Anthony C. Ogden
Stylus Publishing LLC,
2019, 2019-05-10, 2023-07-03, 2019-05-13
eBook, Book
How can education abroad be embedded into undergraduate education so that students experience it as an integral component and something they help shape, rather than as time away from their education ...and a commodity to be consumed? How can colleges and universities maximize the educational value of education abroad by forging stronger connections between it and other undergraduate experiences, including other high-impact educational practices?
The COVID-19 health crisis has disproportionately impacted populations who have been historically marginalized in health care and public health, including low-income and racial and ethnic minority ...groups. Members of marginalized communities experience undue barriers to accessing health care through virtual care technologies, which have become the primary mode of ambulatory health care delivery during the COVID-19 pandemic. Insights generated during the COVID-19 pandemic can inform strategies to promote health equity in virtual care now and in the future.
The aim of this study is to generate insights arising from literature that was published in direct response to the widespread use of virtual care during the COVID-19 pandemic, and had a primary focus on providing recommendations for promoting health equity in the delivery of virtual care.
We conducted a narrative review of literature on health equity and virtual care during the COVID-19 pandemic published in 2020, describing strategies that have been proposed in the literature at three levels: (1) policy and government, (2) organizations and health systems, and (3) communities and patients.
We highlight three strategies for promoting health equity through virtual care that have been underaddressed in this literature: (1) simplifying complex interfaces and workflows, (2) using supportive intermediaries, and (3) creating mechanisms through which marginalized community members can provide immediate input into the planning and delivery of virtual care.
We conclude by outlining three areas of work that are required to ensure that virtual care is employed in ways that are equity enhancing in a post-COVID-19 reality.
Predictive models are central to both archaeological research and cultural resource management. Yet, archaeological applications of predictive models are often insufficient due to small training data ...sets, inadequate statistical techniques, and a lack of theoretical insight to explain the responses of past land use to predictor variables. Here we address these critiques and evaluate the predictive power of four statistical approaches widely used in ecological modeling-generalized linear models, generalized additive models, maximum entropy, and random forests-to predict the locations of Formative Period (2100-650 BP) archaeological sites in the Grand Staircase-Escalante National Monument. We assess each modeling approach using a threshold-independent measure, the area under the curve (AUC), and threshold-dependent measures, like the true skill statistic. We find that the majority of the modeling approaches struggle with archaeological datasets due to the frequent lack of true-absence locations, which violates model assumptions of generalized linear models, generalized additive models, and random forests, as well as measures of their predictive power (AUC). Maximum entropy is the only method tested here which is capable of utilizing pseudo-absence points (inferred absence data based on known presence data) and controlling for a non-representative sampling of the landscape, thus making maximum entropy the best modeling approach for common archaeological data when the goal is prediction. Regression-based approaches may be more applicable when prediction is not the goal, given their grounding in well-established statistical theory. Random forests, while the most powerful, is not applicable to archaeological data except in the rare case where true-absence data exist. Our results have significant implications for the application of predictive models by archaeologists for research and conservation purposes and highlight the importance of understanding model assumptions.
Objectives This study sought to investigate the effect of endothelial dysfunction on the development of cardiac hypertrophy and fibrosis. Background Endothelial dysfunction accompanies cardiac ...hypertrophy and fibrosis, but its contribution to these conditions is unclear. Increased nicotinamide adenine dinucleotide phosphate oxidase-2 (NOX2) activation causes endothelial dysfunction. Methods Transgenic mice with endothelial-specific NOX2 overexpression (TG mice) and wild-type littermates received long-term angiotensin II (AngII) infusion (1.1 mg/kg/day, 2 weeks) to induce hypertrophy and fibrosis. Results TG mice had systolic hypertension and hypertrophy similar to those seen in wild-type mice but developed greater cardiac fibrosis and evidence of isolated left ventricular diastolic dysfunction (p < 0.05). TG myocardium had more inflammatory cells and VCAM-1–positive vessels than did wild-type myocardium after AngII treatment (both p < 0.05). TG microvascular endothelial cells (ECs) treated with AngII recruited 2-fold more leukocytes than did wild-type ECs in an in vitro adhesion assay (p < 0.05). However, inflammatory cell NOX2 per se was not essential for the profibrotic effects of AngII. TG showed a higher level of endothelial-mesenchymal transition (EMT) than did wild-type mice after AngII infusion. In cultured ECs treated with AngII, NOX2 enhanced EMT as assessed by the relative expression of fibroblast versus endothelial-specific markers. Conclusions AngII-induced endothelial NOX2 activation has profound profibrotic effects in the heart in vivo that lead to a diastolic dysfunction phenotype. Endothelial NOX2 enhances EMT and has proinflammatory effects. This may be an important mechanism underlying cardiac fibrosis and diastolic dysfunction during increased renin-angiotensin activation.
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