Associations between insulin and glucose concentrations and anthropometric measures of fat mass in Australian adolescents

Background One of the most serious, yet common co-morbidities of obesity is insulin resistance, which if untreated may progress to type 2 diabetes. This paper describes the insulin and glucose concentration distributions, the prevalence of elevated insulin, the associations between insulin and body mass index (BMI), waist circumference, waist-to-height ratio (WHtR) and fat mass index in a representative sample of Australian adolescents. Methods Cross-sectional population-based study of adolescent boys and girls (N = 496, mean age 15.3 years) attending schools in metropolitan Sydney, Australia. Fasting venous blood collected and analysed for insulin and glucose concentrations. Height, weight, waist circumference measured, BMI and waist-to-height ratio calculated. Pubertal status self-reported. Results Glucose concentrations were normally distributed and were not associated with adiposity. Insulin concentrations were distributed logarithmically, were higher among girls than boys overall and within the same ranges of BMI and waist circumference, but were lower among girls than boys within the same ranges of fat mass adjusted for height. The prevalence of elevated insulin concentration (defined as \u3e 100 pmol/L) was 15.9% and 17.1% among boys and girls, respectively. Correlations between insulin concentration and BMI, waist circumference, WHtR and fat mass adjusted for height were 0.53, 0.49, 0.51 and 0.55, among boys, respectively, and 0.35, 0.40, 0.42 and 0.34, among girls, respectively. Conclusions Elevated insulin is highly correlated with adiposity in adolescents. BMI and WHtR are simple measures that can be used to identify young people who should be screened for insulin resistance and other co-morbidities

Design and Characterization of an Aerosol Test Chamber for Emergency Response Patient Contamination Control Simulation and Research

Contaminated or infected patients present a risk of cross-contamination for emergency responders, attending medical personnel and medical facilities as they enter a treatment facility. The controlled conditions of an aerosol test chamber are required to examine factors of contamination, decontamination, and cross-contamination. This study presents the design, construction, and a method for characterizing an aerosol test chamber for a full-sized manikin on a standard North Atlantic Treaty Organization litter. The methodology combined air velocity measurements, aerosol particle counts and size distributions, and computational fluid dynamics modeling to describe the chamber’s performance in three dimensions. This detailed characterization facilitates future experimental design by predicting chamber performance for a variety of patient-focused research

Simulations of the OzDES AGN reverberation mapping project

As part of the Australian spectroscopic dark energy survey (OzDES) we are carrying out a large-scale reverberation mapping study of ≥500 quasars over five years in the 30 deg2 area of the Dark Energy Survey (DES) supernova fields. These quasars have redshifts ranging up to 4 and have apparent AB magnitudes between 16.8 mag < r < 22.5 mag. The aim of the survey is to measure time lags between fluctuations in the quasar continuum and broad emission-line fluxes of individual objects in order to measure black hole masses for a broad range of active galactic nuclei (AGN) and constrain the radius-luminosity (R-L) relationship. Here we investigate the expected efficiency of the OzDES reverberation mapping campaign and its possible extensions. We expect to recover lags for-35-45 per cent of the quasars. AGN with shorter lags and greater variability aremore likely to yield a lag measurement, and objects with lags ≲6 months or-1 yr are expected to be recovered the most accurately. The baseline OzDES reverberation mapping campaign is predicted to produce an unbiased measurement of the R-L relationship parameters for H β, MgII λ2798, and CIV λ1549. Extending the baseline survey by either increasing the spectroscopic cadence, extending the survey season, or improving the emission-line flux measurement accuracy will significantly improve the R-L parameter constraints for all broad emission lines

Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients.

In December 2017, the National Academy of Neuropsychology convened an interorganizational Summit on Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients in Denver, Colorado. The Summit brought together representatives of a broad range of stakeholders invested in the care of older adults to focus on the topic of cognitive health and aging. Summit participants specifically examined questions of who should be screened for cognitive impairment and how they should be screened in medical settings. This is important in the context of an acute illness given that the presence of cognitive impairment can have significant implications for care and for the management of concomitant diseases as well as pose a major risk factor for dementia. Participants arrived at general principles to guide future screening approaches in medical populations and identified knowledge gaps to direct future research. Key learning points of the summit included: recognizing the importance of educating patients and healthcare providers about the value of assessing current and baseline cognition;emphasizing that any screening tool must be appropriately normalized and validated in the population in which it is used to obtain accurate information, including considerations of language, cultural factors, and education; andrecognizing the great potential, with appropriate caveats, of electronic health records to augment cognitive screening and tracking of changes in cognitive health over time

Associations between insulin and glucose concentrations and anthropometric measures of fat mass in Australian adolescents

<p>Abstract</p> <p>Background</p> <p>One of the most serious, yet common co-morbidities of obesity is insulin resistance, which if untreated may progress to type 2 diabetes. This paper describes the insulin and glucose concentration distributions, the prevalence of elevated insulin, the associations between insulin and body mass index (BMI), waist circumference, waist-to-height ratio (WHtR) and fat mass index in a representative sample of Australian adolescents.</p> <p>Methods</p> <p>Cross-sectional population-based study of adolescent boys and girls (N = 496, mean age 15.3 years) attending schools in metropolitan Sydney, Australia. Fasting venous blood collected and analysed for insulin and glucose concentrations. Height, weight, waist circumference measured, BMI and waist-to-height ratio calculated. Pubertal status self-reported.</p> <p>Results</p> <p>Glucose concentrations were normally distributed and were not associated with adiposity. Insulin concentrations were distributed logarithmically, were higher among girls than boys overall and within the same ranges of BMI and waist circumference, but were lower among girls than boys within the same ranges of fat mass adjusted for height. The prevalence of elevated insulin concentration (defined as > 100 pmol/L) was 15.9% and 17.1% among boys and girls, respectively. Correlations between insulin concentration and BMI, waist circumference, WHtR and fat mass adjusted for height were 0.53, 0.49, 0.51 and 0.55, among boys, respectively, and 0.35, 0.40, 0.42 and 0.34, among girls, respectively.</p> <p>Conclusions</p> <p>Elevated insulin is highly correlated with adiposity in adolescents. BMI and WHtR are simple measures that can be used to identify young people who should be screened for insulin resistance and other co-morbidities.</p

The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside

Background: Translational medicine requires the integration of knowledge using heterogeneous data from health care to the life sciences. Here, we describe a collaborative effort to produce a prototype Translational Medicine Knowledge Base (TMKB) capable of answering questions relating to clinical practice and pharmaceutical drug discovery. Results: We developed the Translational Medicine Ontology (TMO) as a unifying ontology to integrate chemical, genomic and proteomic data with disease, treatment, and electronic health records. We demonstrate the use of Semantic Web technologies in the integration of patient and biomedical data, and reveal how such a knowledge base can aid physicians in providing tailored patient care and facilitate the recruitment of patients into active clinical trials. Thus, patients, physicians and researchers may explore the knowledge base to better understand therapeutic options, efficacy, and mechanisms of action. Conclusions: This work takes an important step in using Semantic Web technologies to facilitate integration of relevant, distributed, external sources and progress towards a computational platform to support personalized medicine. Availability: TMO can be downloaded from http://code.google.com/p/translationalmedicineontology and TMKB can be accessed at http://tm.semanticscience.org/sparql

Explaining Gender-Specific Racial Differences in Obesity Using Biased Self-Reports of Food Intake

Policymakers have an interest in identifying the differences in behavior patterns - namely, habitual caloric intake and physical activity levels - that contribute to demographic variation in body mass index (BMI) and obesity risk. While disparities in mean BMI and obesity rates between whites (non-Hispanic) and African-Americans (non-Hispanic) are well-documented, the behavioral differences that underlie these gaps have not been carefully identified. Moreover, the female-specificity of the black-white obesity gap has received relatively little attention. In the National Health and Nutrition Examination Surveys (NHANES) data, we initially observe a very weak relationship between self-reported measures of caloric intake and physical activity and either BMI or obesity risk, and these behaviors appear to explain only a small fraction of the black-white BMI gap (or obesity gap) among women. These unadjusted estimates echo previous findings from large survey datasets such as the NHANES. Using an innovative method to mitigate the widely recognized problem of measurement error in self-reported behaviors' proxying for measurement errors using the ratio of reported caloric intake to estimated true caloric needs' we obtain much stronger relationships between behaviors and BMI (or obesity risk). Behaviors can in fact account for a significant share of the BMI gap (and the obesity gap) between black women and white women and are consistent with the presence of much smaller gaps between black men and white men. The analysis also shows that the effects smoking has on BMI and obesity risk are small-to-negligible when measurement error is properly controlled

Myocardial tagging by Cardiovascular Magnetic Resonance: evolution of techniques--pulse sequences, analysis algorithms, and applications

Cardiovascular magnetic resonance (CMR) tagging has been established as an essential technique for measuring regional myocardial function. It allows quantification of local intramyocardial motion measures, e.g. strain and strain rate. The invention of CMR tagging came in the late eighties, where the technique allowed for the first time for visualizing transmural myocardial movement without having to implant physical markers. This new idea opened the door for a series of developments and improvements that continue up to the present time. Different tagging techniques are currently available that are more extensive, improved, and sophisticated than they were twenty years ago. Each of these techniques has different versions for improved resolution, signal-to-noise ratio (SNR), scan time, anatomical coverage, three-dimensional capability, and image quality. The tagging techniques covered in this article can be broadly divided into two main categories: 1) Basic techniques, which include magnetization saturation, spatial modulation of magnetization (SPAMM), delay alternating with nutations for tailored excitation (DANTE), and complementary SPAMM (CSPAMM); and 2) Advanced techniques, which include harmonic phase (HARP), displacement encoding with stimulated echoes (DENSE), and strain encoding (SENC). Although most of these techniques were developed by separate groups and evolved from different backgrounds, they are in fact closely related to each other, and they can be interpreted from more than one perspective. Some of these techniques even followed parallel paths of developments, as illustrated in the article. As each technique has its own advantages, some efforts have been made to combine different techniques together for improved image quality or composite information acquisition. In this review, different developments in pulse sequences and related image processing techniques are described along with the necessities that led to their invention, which makes this article easy to read and the covered techniques easy to follow. Major studies that applied CMR tagging for studying myocardial mechanics are also summarized. Finally, the current article includes a plethora of ideas and techniques with over 300 references that motivate the reader to think about the future of CMR tagging

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution