Cardiovascular informatics: building a bridge to data harmony.

The search for new strategies for better understanding cardiovascular (CV) disease is a constant one, spanning multitudinous types of observations and studies. A comprehensive characterization of each disease state and its biomolecular underpinnings relies upon insights gleaned from extensive information collection of various types of data. Researchers and clinicians in CV biomedicine repeatedly face questions regarding which types of data may best answer their questions, how to integrate information from multiple datasets of various types, and how to adapt emerging advances in machine learning and/or artificial intelligence to their needs in data processing. Frequently lauded as a field with great practical and translational potential, the interface between biomedical informatics and CV medicine is challenged with staggeringly massive datasets. Successful application of computational approaches to decode these complex and gigantic amounts of information becomes an essential step toward realizing the desired benefits. In this review, we examine recent efforts to adapt informatics strategies to CV biomedical research: automated information extraction and unification of multifaceted -omics data. We discuss how and why this interdisciplinary space of CV Informatics is particularly relevant to and supportive of current experimental and clinical research. We describe in detail how open data sources and methods can drive discovery while demanding few initial resources, an advantage afforded by widespread availability of cloud computing-driven platforms. Subsequently, we provide examples of how interoperable computational systems facilitate exploration of data from multiple sources, including both consistently formatted structured data and unstructured data. Taken together, these approaches for achieving data harmony enable molecular phenotyping of CV diseases and unification of CV knowledge.

Adverse childhood experiences and obesity over time.

OBJECTIVE: The effects of adverse childhood experiences (ACE) on children and adolescents' health status such as obesity are understudied. The current study addressed the effect of ACE on obesity status during childhood utilising multiple waves of national panel data. DESIGN: Longitudinal survey. SETTING: Data were drawn from three waves of the second cohort of the National Survey of Child and Adolescent Well-Being (NSCAW II). NSCAW II study sampled cases from Child Protective Services investigations that were closed between February 2008 and April 2009 nationwide. We measured ACE cumulatively and as separate events and stratified by gender. PARTICIPANTS: Totally, 3170 youth births to 14 years of age at baseline. RESULTS: A count measure of ACE is indeed associated with greater odds of obesity during childhood. Differential effects for different types of ACE were also found, most notably neglect. For girls, physical and psychological neglect increased odds of obesity. CONCLUSIONS: Findings support evidence for the importance of using both a count measure of ACE as well as separating out single events by gender.

A Second Look at FAIR in Proteomic Investigations.

Proteomics is, by definition, comprehensive and large-scale, seeking to unravel ome-level protein features with phenotypic information on an entire system, an organ, cells, or organisms. This scope consistently involves and extends beyond single experiments. Multitudinous resources now exist to assist in making the results of proteomics experiments more findable, accessible, interoperable, and reusable (FAIR), yet many tools are awaiting to be adopted by our community. Here we highlight strategies for expanding the impact of proteomics data beyond single studies. We show how linking specific terminologies, identifiers, and text (words) can unify individual data points across a wide spectrum of studies and, more importantly, how this approach may potentially reveal novel relationships. In this effort, we explain how data sets and methods can be rendered more linkable and how this maximizes their value. We also include a discussion on how data linking strategies benefit stakeholders across the proteomics community and beyond.

Effective piezoelectric response of substrate-integrated ZnO nanowire array devices on galvanized steel.

Harvesting waste energy through electromechanical coupling in practical devices requires combining device design with the development of synthetic strategies for large-area controlled fabrication of active piezoelectric materials. Here, we show a facile route to the large-area fabrication of ZnO nanostructured arrays using commodity galvanized steel as the Zn precursor as well as the substrate. The ZnO nanowires are further integrated within a device construct and the effective piezoelectric response is deduced based on a novel experimental approach involving induction of stress in the nanowires through pressure wave propagation along with phase-selective lock-in detection of the induced current. The robust methodology for measurement of the effective piezoelectric coefficient developed here allows for interrogation of piezoelectric functionality for the entire substrate under bending-type deformation of the ZnO nanowires.

Breastfeeding as a modifier of the respiratory effects of air pollution in children.

BACKGROUND: Breastfeeding and air pollution are both important factors for respiratory symptoms and asthma in children. Few studies have examined possible interaction between them on respiratory outcomes. METHODS: We studied 31,049 Chinese children, ages 2-14 years old, from 25 elementary schools and 50 kindergartens in the Seven Northeastern Cities during 2008-2009. Parents or guardians completed questionnaires about the children's histories of respiratory conditions, risk factors, and feeding methods. Three-year average concentrations of particles with an aerodynamic diameter ≤ 10 µm, sulfur dioxide, nitrogen dioxides, and ozone were calculated from monitoring stations in 25 study districts. We used two-level logistic regressions to examine the effects of exposure, controlling for covariates. RESULTS: Association of air pollution with childhood respiratory conditions was modified by breastfeeding. Compared with children who had been breastfed, those who were not exhibited consistently stronger effects of air pollution. Among non-breastfed children, odds ratios (ORs) per 10 µg/m increase in nitrogen dioxide were 1.40 (95% confidence interval = 1.19-1.64) for cough, 1.41 (1.16-1.71) for phlegm, 1.17 (1.00-1.36) for current wheeze, and 1.25 (1.07-1.46) for doctor-diagnosed asthma. For breastfed children, the ORs were 1.25 (1.09-1.43) for cough, 1.15 (0.99-1.34) for phlegm, 0.97 (0.87-1.08) for current wheeze, and 1.17 (1.05-1.32) for doctor-diagnosed asthma. Breastfeeding was more protective among younger children. Breastfeeding was also associated with reduced effects of passive smoke exposure in children. CONCLUSION: Breastfeeding is associated with smaller associations between air pollution and respiratory conditions in children, suggesting that breastfeeding reduces susceptibility to the respiratory effects of pollutants.

On the Landau theory of phase transitions: a hierarchical dynamic model.

The Landau theory of phase transitions has been re-examined under the framework of a modified mean field theory in ferroelectrics. By doing so, one can see that there are two atomic movements involved in the ferroelectric phase transition; the first corresponds to the vibration of the crystalline lattice, which will render phonon mode softening at the critical point, and the second represents the slow evolution of a partially ordered nematic phase formed by the cooperative behavior of high-temperature structure precursors. In this hierarchical dynamic structure, the former fast dynamics could be significantly modulated by the latter slow dynamics in the vicinity of the Curie temperature; it then turns out that it is the behavior of the nematic phase on approaching the critical point that makes the Landau theory deviate from experimental observations.

Rate of kidney function decline associates with mortality.

The effect of rate of decline of kidney function on risk for death is not well understood. Using the Department of Veterans Affairs national databases, we retrospectively studied a cohort of 4171 patients who had rheumatoid arthritis and early stage 3 chronic kidney disease (CKD; estimated GFR 45 to 60 ml/min) and followed them longitudinally to characterize predictors of disease progression and the effect of rate of kidney function decline on mortality. After a median of 2.6 years, 1604 (38%) maintained stable kidney function; 426 (10%), 1147 (28%), and 994 (24%) experienced mild, moderate, and severe progression of CKD, respectively (defined as estimated GFR decline of 0 to 1, 1 to 4, and >4 ml/min per yr). Peripheral artery disease predicted moderate progression of CKD progression. Black race, hypertension, diabetes, cardiovascular disease, and peripheral artery disease predicted severe progression of CKD. After a median of 5.7 years, patients with severe progression had a significantly increased risk for mortality (hazard ratio 1.54; 95% confidence interval 1.30 to 1.82) compared with those with mild progression; patients with moderate progression exhibited a similar trend (hazard ratio 1.10; 95% confidence interval 0.98 to 1.30). Our results demonstrate an independent and graded association between the rate of kidney function decline and mortality. Incorporating the rate of decline into the definition of CKD may transform a static definition into a dynamic one that more accurately describes the potential consequences of the disease for an individual.