Lifestyle and socio-economic inequalities in diabetes prevalence in South Africa: A decomposition analysis.

Background: Inequalities in diabetes are widespread and are exacerbated by differences in lifestyle. Many studies that have estimated inequalities in diabetes make use of self-reported diabetes which is often biased by differences in access to health care and diabetes awareness. This study adds to this literature by making use of a more objective standardised measure of diabetes in South Africa.

Association of Obesity With Mortality Over 24 Years of Weight History: Findings From the Framingham Heart Study.

Importance: Many studies of the association between obesity and mortality rely on weight status at a single point in time, making it difficult to adequately address bias associated with reverse causality.

Objective: To investigate the association between maximum body mass index (BMI) and all-cause mortality without the consequences of reverse causality.

Design, Setting, And Participants: Prospective cohort studies for the original and offspring cohorts of the Framingham Heart Study.

Linbots: Soft Modular Robots Utilizing Voice Coils.

Robots performing automated tasks in uncontrolled environments need to adapt to environmental changes. Through building large collectives of robots, this robust and adaptive behavior can emerge from simple individual rules. These collectives can also be reconfigured, allowing for adaption to new tasks.

sPyNNaker: A Software Package for Running PyNN Simulations on SpiNNaker.

This work presents sPyNNaker 4.0.0, the latest version of the software package for simulating PyNN-defined spiking neural networks (SNNs) on the SpiNNaker neuromorphic platform.

Patterns of weight change associated with disease diagnosis in a national sample.

Background: The incidence and/or diagnosis of a major disease may activate weight change. Patterns of weight change associated with diagnoses have not been systematically documented.

Methods: We use data on adults ages 30+ in the National Health and Nutrition Examination Survey (NHANES) from 1999-2014.

Code Generation in Computational Neuroscience: A Review of Tools and Techniques.

Advances in experimental techniques and computational power allowing researchers to gather anatomical and electrophysiological data at unprecedented levels of detail have fostered the development of increasingly complex models in computational neuroscience. Large-scale, biophysically detailed cell models pose a particular set of computational challenges, and this has led to the development of a number of domain-specific simulators. At the other level of detail, the ever growing variety of point neuron models increases the implementation barrier even for those based on the relatively simple integrate-and-fire neuron model.

"TRPV1 is a component of the atrial natriuretic signaling complex, and using orally delivered antagonists, presents a valid therapeutic target in the longitudinal reversal and treatment of cardiac hypertrophy and heart failure".

Activation of the atrial natriuretic signaling pathway is intrinsic to the pathological responses associated with a range of cardiovascular diseases that stress the heart, especially those involved in sustained cardiac pressure overload which induces hypertrophy and the pathological remodeling that frequently leads to heart failure. We identify transient receptor potential cation channel, subfamily V, member 1, as a regulated molecular component, and therapeutic target of this signaling system. Data show that TRPV1 is a physical component of the natriuretic peptide A, cGMP, PKG signaling complex, interacting with the Natriuretic Peptide Receptor 1 (NPR1), and upon binding its ligand, Natriuretic Peptide A (NPPA, ANP) TRPV1 activation is subsequently suppressed through production of cGMP and PKG mediated phosphorylation of the TRPV1 channel.

Soft Radio-Frequency Identification Sensors: Wireless Long-Range Strain Sensors Using Radio-Frequency Identification.

Increasing amounts of attention are being paid to the study of Soft Sensors and Soft Systems. Soft Robotic Systems require input from advances in the field of Soft Sensors. Soft sensors can help a soft robot to perceive and to act upon its immediate environment.

Soil and water bioengineering: Practice and research needs for reconciling natural hazard control and ecological restoration.

Soil and water bioengineering is a technology that encourages scientists and practitioners to combine their knowledge and skills in the management of ecosystems with a common goal to maximize benefits to both man and the natural environment. It involves techniques that use plants as living building materials, for: (i) natural hazard control (e.g.

The Limpet: A ROS-Enabled Multi-Sensing Platform for the ORCA Hub.

The oil and gas industry faces increasing pressure to remove people from dangerous offshore environments. Robots present a cost-effective and safe method for inspection, repair, and maintenance of topside and marine offshore infrastructure. In this work, we introduce a new multi-sensing platform, the Limpet, which is designed to be low-cost and highly manufacturable, and thus can be deployed in huge collectives for monitoring offshore platforms.

Optimization of Acquisition and Analysis Methods for Clinical Dynamic Susceptibility Contrast MRI Using a Population-Based Digital Reference Object.

Background And Purpose: The accuracy of DSC-MR imaging CBV maps in glioblastoma depends on acquisition and analysis protocols. Multisite protocol heterogeneity has challenged standardization initiatives due to the difficulties of in vivo validation. This study sought to compare the accuracy of routinely used protocols using a digital reference object.

Prevalence, incidence, predictors, treatment, and control of hypertension among HIV-positive adults on antiretroviral treatment in public sector treatment programs in South Africa.

Background: One of the key risk factors for cardiovascular disease is hypertension. Hypertension, which leads to heart attacks and strokes, already affects one billion people worldwide, making it a global public health issue. Incidence and prevalence of the condition is on the rise in low- and middle-income countries, with the biggest increase in sub-Saharan Africa and South Africa at the forefront.

An Investigation into Tetrodotoxin (TTX) Levels Associated with the Red Dorsal Spots in Eastern Newt () Efts and Adults.

We investigated the concentration of tetrodotoxin (TTX) in sections of skin containing and lacking red dorsal spots in both Eastern newt () efts and adults. Several other species, such as and have granular glands concentrated in brightly pigmented regions on the dorsum, and thus we hypothesized that the red dorsal spots of Eastern newts may also possess higher levels of TTX than the surrounding skin. We found no difference between the concentrations of TTX in the red spots as compared to neighboring skin lacking these spots in either efts or adults.

Electronic Cigarette Use Prevalence, Associated Factors, and Pattern by Cigarette Smoking Status in the United States From NHANES (National Health and Nutrition Examination Survey) 2013-2014.

Background: To examine the prevalence and patterns of recent electronic cigarette (e-cigarette) use in a nationally representative sample of US adults and adolescents.

Methods And Results: Using tobacco information from NHANES (National Health and Nutrition Examination Survey) 2013-2014, 5423 adults and 895 adolescents (aged 13-17 years) were included in this analysis. Demographic, tobacco use, and drug use information were self-reported.

Behavioral Learning in a Cognitive Neuromorphic Robot: An Integrative Approach.

We present here a learning system using the iCub humanoid robot and the SpiNNaker neuromorphic chip to solve the real-world task of object-specific attention. Integrating spiking neural networks with robots introduces considerable complexity for questionable benefit if the objective is simply task performance. But, we suggest, in a cognitive robotics context, where the goal is understanding how to compute, such an approach may yield useful insights to neural architecture as well as learned behavior, especially if dedicated neural hardware is available.

Socioeconomic and Racial/Ethnic Differences in E-Cigarette Uptake Among Cigarette Smokers: Longitudinal Analysis of the Population Assessment of Tobacco and Health (PATH) Study.

Introduction: Sociodemographic differences in electronic cigarette use among cigarette smokers have not been previously characterized in the US adult population.

Methods: We analyzed longitudinal data from Waves 1 and 2 of the nationally representative Population Assessment of Tobacco and Health (PATH) study. Differences by income (based on federal poverty level (FPL)) and race/ethnicity in e-cigarette uptake at Wave 2 among cigarette smokers who were e-cigarette nonusers at Wave 1 were assessed using binomial and multinomial logistic regression.

Representation of obese participants in obesity-related cancer randomized trials.

Background: Obesity is a risk factor for numerous cancer types, and may influence cancer treatment outcomes. Underrepresentation of obese patients in obesity-related cancer randomized controlled trials (RCTs) may affect generalizability of results. We aimed to assess the reporting of information about eligibility and enrollment of obese participants in obesity-related cancer RCTs.

Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model.

The digital neuromorphic hardware SpiNNaker has been developed with the aim of enabling large-scale neural network simulations in real time and with low power consumption. Real-time performance is achieved with 1 ms integration time steps, and thus applies to neural networks for which faster time scales of the dynamics can be neglected. By slowing down the simulation, shorter integration time steps and hence faster time scales, which are often biologically relevant, can be incorporated.

Stratified Probabilistic Bias Analysis for Body Mass Index-related Exposure Misclassification in Postmenopausal Women.

Background: There is widespread concern about the use of body mass index (BMI) to define obesity status in postmenopausal women because it may not accurately represent an individual's true obesity status. The objective of the present study is to examine and adjust for exposure misclassification bias from using an indirect measure of obesity (BMI) compared with a direct measure of obesity (percent body fat).

Methods: We used data from postmenopausal non-Hispanic black and non-Hispanic white women in the Women's Health Initiative (n=126,459).

Mechanical traits of fine roots as a function of topology and anatomy.

Background And Aims: Root mechanical traits, including tensile strength (Tr), tensile strain (εr) and modulus of elasticity (Er), are key functional traits that help characterize plant anchorage and the physical contribution of vegetation to landslides and erosion. The variability in these traits is high among tree fine roots and is poorly understood. Here, we explore the variation in root mechanical traits as well as their underlying links with morphological (diameter), architectural (topological order) and anatomical (stele and cortex sizes) traits.

Multi-Functional Sensing for Swarm Robots Using Time Sequence Classification: HoverBot, an Example.

Scaling up robot swarms to collectives of hundreds or even thousands without sacrificing sensing, processing, and locomotion capabilities is a challenging problem. Low-cost robots are potentially scalable, but the majority of existing systems have limited capabilities, and these limitations substantially constrain the type of experiments that could be performed by robotics researchers. Instead of adding functionality by adding more components and therefore increasing the cost, we demonstrate how low-cost hardware can be used beyond its standard functionality.

Imaging vascular and hemodynamic features of the brain using dynamic susceptibility contrast and dynamic contrast enhanced MRI.

In the context of neurologic disorders, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MRI provide valuable insights into cerebral vascular function, integrity, and architecture. Even after two decades of use, these modalities continue to evolve as their biophysical and kinetic basis is better understood, with improvements in pulse sequences and accelerated imaging techniques and through application of more robust and automated data analysis strategies. Here, we systematically review each of these elements, with a focus on how their integration improves kinetic parameter accuracy and the development of new hemodynamic biomarkers that provide sub-voxel sensitivity (e.

Electronic Cigarette Prevalence and Patterns of Use in Adults with a History of Cardiovascular Disease in the United States.

Background: Characterizing electronic cigarette (e-cigarette) use patterns is important for guiding tobacco regulatory policy and projecting the future burden of tobacco-related diseases. Few studies have examined patterns of e-cigarette use in individuals with cardiovascular disease (CVD).

Methods And Results: We examined e-cigarette use in adults aged 18 to 89 years with a history of CVD, using data from the 2014 National Health Interview Survey.