The role of an addictive tendency towards food and patterns of body fat distribution in obesity and metabolic health

Food addiction (FA) is a contributing factor to obesity. Individuals with similar total body fat (BF) %, exhibit a large amount of heterogeneity in how BF is distributed. Certain BF distribution (BFD) patterns produce different outcomes regarding metabolic health. Little is known about how FA influences BFD and metabolic profiles. The study was designed to evaluate the correlation between FA symptom counts and metabolic characteristics, the correlation between FA symptoms and BFD patterns with emphasis on central obesity and Visceral fat (VF), and the role of android fat (AF) in women’s metabolic health. Data from the CODING study was used for analysis. FA symptoms are correlated with HOMA-β, triglycerides (TG), inversely correlated with high-density lipoprotein (HDL) in men and are correlated with TG in post-menopausal women. FA symptom counts were also associated with central obesity markers in men and women, including trunk fat (TF) and VF. Women exhibited slightly stronger correlations for all BFD measures except for VF and AF than in men. AF to GF ratio (AGR) affected metabolic characteristics and metabolic syndrome (MetS) risk in women. When separated into AGR tertiles, women in each tertile differed significantly in levels of insulin, glucose, TG, HDL, low-density lipoprotein (LDL), total cholesterol (TC), blood pressure (BP), and waist circumference (WC). Women in the top tertile exhibited higher levels of HOMA-IR and HOMA-β. When women in the top AGR quartile, matched by age and body mass index (BMI) with a control group while controlling for VF, were 2.4x more likely to have MetS. In conclusion, FA symptoms exhibit correlations with markers of metabolic disturbance in men and to a smaller degree in women. FA symptoms are also correlated with central obesity in men and women. Women with high levels of AF are at increased risk of developing MetS when compared to women of similar age and BMI

The Association of Upper Body Obesity with Insulin Resistance in the Newfoundland Population

Body-fat distribution is a primary risk factor for insulin resistance and cardiovascular disease. Visceral fat explains only a portion of this risk. The link between upper-body fat and insulin resistance is uncertain. Furthermore, upper-body fat is not clearly defined. Dual-energy X-ray absorptiometry (DXA) can accurately quantify body fat. In this study, we explored the relationship between non-visceral upper-body adiposity and insulin resistance and other markers of metabolic syndrome. Fat proportions in the upper body, leg, and visceral regions were quantified by using DXA in 2547 adult Newfoundlanders aged 19 and older. Adjusting for remaining fat regions, we performed partial correlation analysis for each body region and insulin resistance defined by the Homeostatic Model of Assessment (HOMA). Similarly, partial correlation analysis was also performed between each fat region and other markers of metabolic syndrome, including high-density lipoprotein cholesterol (HDL), triglycerides (TG), body mass index (BMI), and blood pressure. Major confounding factors, including age, caloric intake, and physical activity, were statistically controlled by using partial correlation analysis. Interactions between sex, menopausal status, and medication status were also tested. Arm adiposity was correlated with HOMA-IR (R = 0.132, p < 0.001) and HOMA-β (R = 0.134, p < 0.001). Visceral adiposity was correlated with HOMA-IR (R = 0.230, p < 0.001) and HOMA-β (R = 0.160, p < 0.001). No significant correlation between non-visceral trunk adiposity and insulin resistance was found. Non-visceral trunk adiposity was negatively correlated with HDL in men (R = −0.110, p < 0.001) and women (R = −0.117, p < 0.001). Non-visceral trunk adiposity was correlated with TG (total: R = 0.079, p < 0.001; men: R = 0.105, p = 0.012; women: R = 0.078, p = 0.001). In menopausal women, leg adiposity was negatively correlated with HOMA-IR (R = −0.196, p < 0.001) and HOMA-β (R = −0.101, p = 0.012). Upper-body adiposity in the arms is an independent contributor to insulin resistance. Upper-body adiposity in the non-visceral trunk region is an independent contributor to metabolic syndrome. Leg adiposity is protective against metabolic syndrome in women

A comparison of trackbed design methodologies: a case study from a heavy haul freight railway

One of the major roles of railway trackbed layers is to reduce vehicle induced stresses applied to the underlying subgrade to a level that limits the progressive build up of permanent deformation. The ability of trackbed layers to satisfy this requirement is dependent upon the materials used for construction and their thickness. Numerous design methods, (both empirical and analytical), have been developed across the World to evaluate trackbed design thickness. However, where there is limited information or experience of previous trackbed design with the specific materials or site conditions under consideration, the choice of methodology becomes one of engineering judgment, in assessing the significance and reliability of the design input parame-ters. This paper describes a number of design methods which were assessed in a recent project to design a new heavy haul freight railway trackbed, founded on moisture sensitive subgrades, using locally available materials for the track support layers. The produced design thicknesses for each of the methods are compared for differing subgrade conditions. The results show considerable variation of thicknesses from each method with little consistent pattern to the variation. Reasons for these variations are suggested and the choice of the final design used for specific subgrade conditions are presented together with appropriate justification. Concluding on these issues, recommendations are made for a more considered approach to trackbed design

The Association Between an Addictive Tendency Toward Food and Metabolic Characteristics in the General Newfoundland Population

Background: Our previous study of 29 obese food addiction (FA) patients found that FA is associated with lipid profiles and hormones which may be a factor in cardiovascular disease (CVD) and insulin resistance (IR). However, there is currently no data available regarding the relationship between FA symptoms and metabolic characteristics of CVD and IR in the general population. We designed this study to investigate the correlation between FA symptoms with lipid profiles and IR in men and women of the general Newfoundland population. Methods: 710 individuals (435 women and 275 men) recruited from the general Newfoundland population were used in analysis. FA symptoms were evaluated using the Yale Food Addiction Scale (YFAS). Glucose, insulin, HDL, LDL, total cholesterol and triglycerides levels were measured. IR was evaluated using the homeostatic model of assessment (HOMA). Participants were grouped by sex and menopausal status. Age, physical activity, calories and total % body fat were controlled. Results: Partial correlation analysis revealed that in men, YFAS symptom counts were significantly correlated with HOMA-b (r = 0.196, p = 0.021), triglycerides (r = 0.140, p = 0.025) and inversely correlated with HDL (r = −0.133, p = 0.033). After separating by menopausal status, pre-menopausal women exhibited no correlations and post-menopausal women had a significantcorrelation with triglycerides (r = 0.198, p = 0.016). Conclusion: FA is significantly correlated with several markers of metabolic disturbance in men and to a lesser extent, post-menopausal women, in the general population. Further research is required to explain sex specific associations and elucidate any potentially causal mechanisms behind this correlation

The SEGUE Stellar Parameter Pipeline. III. Comparison with High-Resolution Spectroscopy of SDSS/SEGUE Field Stars

We report high-resolution spectroscopy of 125 field stars previously observed as part of the Sloan Digital Sky Survey and its program for Galactic studies, the Sloan Extension for Galactic Understanding and Exploration (SEGUE). These spectra are used to measure radial velocities and to derive atmospheric parameters, which we compare with those reported by the SEGUE Stellar Parameter Pipeline (SSPP). The SSPP obtains estimates of these quantities based on SDSS ugriz photometry and low-resolution (R = 2000) spectroscopy. For F- and G-type stars observed with high signal-to-noise ratios (S/N), we empirically determine the typical random uncertainties in the radial velocities, effective temperatures, surface gravities, and metallicities delivered by the SSPP to be 2.4 km/s, 130 K (2.2%), 0.21 dex, and 0.11 dex, respectively, with systematic uncertainties of a similar magnitude in the effective temperatures and metallicities. We estimate random errors for lower S/N spectra based on numerical simulations.Comment: 37 pages, 6 tables, 6 figures, submitted to the Astronomical Journa

Shortened Modified Look-Locker Inversion recovery (ShMOLLI) for clinical myocardial T1-mapping at 1.5 and 3 T within a 9 heartbeat breathhold

<p>Abstract</p> <p>Background</p> <p>T1 mapping allows direct <it>in-vivo </it>quantitation of microscopic changes in the myocardium, providing new diagnostic insights into cardiac disease. Existing methods require long breath holds that are demanding for many cardiac patients. In this work we propose and validate a novel, clinically applicable, pulse sequence for myocardial T1-mapping that is compatible with typical limits for end-expiration breath-holding in patients.</p> <p>Materials and methods</p> <p>The Shortened MOdified Look-Locker Inversion recovery (ShMOLLI) method uses sequential inversion recovery measurements within a single short breath-hold. Full recovery of the longitudinal magnetisation between sequential inversion pulses is not achieved, but conditional interpretation of samples for reconstruction of T1-maps is used to yield accurate measurements, and this algorithm is implemented directly on the scanner. We performed computer simulations for 100 ms<T1 < 2.7 s and heart rates 40-100 bpm followed by phantom validation at 1.5T and 3T. <it>In-vivo </it>myocardial T1-mapping using this method and the previous gold-standard (MOLLI) was performed in 10 healthy volunteers at 1.5T and 3T, 4 volunteers with contrast injection at 1.5T, and 4 patients with recent myocardial infarction (MI) at 3T.</p> <p>Results</p> <p>We found good agreement between the average ShMOLLI and MOLLI estimates for T1 < 1200 ms. In contrast to the original method, ShMOLLI showed no dependence on heart rates for long T1 values, with estimates characterized by a constant 4% underestimation for T1 = 800-2700 ms. <it>In-vivo</it>, ShMOLLI measurements required 9.0 ± 1.1 s (MOLLI = 17.6 ± 2.9 s). Average healthy myocardial T1 s by ShMOLLI at 1.5T were 966 ± 48 ms (mean ± SD) and 1166 ± 60 ms at 3T. In MI patients, the T1 in unaffected myocardium (1216 ± 42 ms) was similar to controls at 3T. Ischemically injured myocardium showed increased T1 = 1432 ± 33 ms (p < 0.001). The difference between MI and remote myocardium was estimated 15% larger by ShMOLLI than MOLLI (p < 0.04) which suffers from heart rate dependencies for long T1. The <it>in-vivo </it>variability within ShMOLLI T1-maps was only 14% (1.5T) or 18% (3T) higher than the MOLLI maps, but the MOLLI acquisitions were twice longer than ShMOLLI acquisitions.</p> <p>Conclusion</p> <p>ShMOLLI is an efficient method that generates immediate, high-resolution myocardial T1-maps in a short breath-hold with high precision. This technique provides a valuable clinically applicable tool for myocardial tissue characterisation.</p

A Search for Additional Planets in the NASA EPOXI Observations of the Exoplanet System GJ 436

We present time series photometry of the M dwarf transiting exoplanet system GJ 436 obtained with the the EPOCh (Extrasolar Planet Observation and Characterization) component of the NASA EPOXI mission. We conduct a search of the high-precision time series for additional planets around GJ 436, which could be revealed either directly through their photometric transits, or indirectly through the variations these second planets induce on the transits of the previously known planet. In the case of GJ 436, the presence of a second planet is perhaps indicated by the residual orbital eccentricity of the known hot Neptune companion. We find no candidate transits with significance higher than our detection limit. From Monte Carlo tests of the time series, we rule out transiting planets larger than 1.5 R_Earth interior to GJ 436b with 95% confidence, and larger than 1.25 R_Earth with 80% confidence. Assuming coplanarity of additional planets with the orbit of GJ 436b, we cannot expect that putative planets with orbital periods longer than about 3.4 days will transit. However, if such a planet were to transit, we rule out planets larger than 2.0 R_Earth with orbital periods less than 8.5 days with 95% confidence. We also place dynamical constraints on additional bodies in the GJ 436 system. Our analysis should serve as a useful guide for similar analyses for which radial velocity measurements are not available, such as those discovered by the Kepler mission. These dynamical constraints on additional planets with periods from 0.5 to 9 days rule out coplanar secular perturbers as small as 10 M_Earth and non-coplanar secular perturbers as small as 1 M_Earth in orbits close in to GJ 436b. We present refined estimates of the system parameters for GJ 436. We also report a sinusoidal modulation in the GJ 436 light curve that we attribute to star spots. [Abridged]Comment: 29 pages, 8 figures, 3 tables, accepted for publication in Ap