Ethnic differences in adiposity and diabetes risk – insights from genetic studies

Type 2 diabetes is more common in non-Europeans and starts at a younger age and at lower BMI cut-offs. This review discusses the insights from genetic studies about pathophysiological mechanisms which determine risk of disease with a focus on the role of adiposity and body fat distribution in ethnic disparity in risk of type 2 diabetes. During the past decade, genome-wide association studies (GWAS) have identified more than 400 genetic variants associated with the risk of type 2 diabetes. The Eurocentric nature of these genetic studies have made them less effective in identifying mechanisms that make non-Europeans more susceptible to higher risk of disease. One possible mechanism suggested by epidemiological studies is the role of ethnic difference in body fat distribution. Using genetic variants associated with an ability to store extra fat in a safe place, which is subcutaneous adipose tissue, we discuss how different ethnic groups could be genetically less susceptible to type 2 diabetes by developing a more favourable fat distribution

New periodic orbits in the solar sail restricted three body problem

In this paper we consider periodic orbits of a solar sail in the Earth-Sun restricted three-body problem. In particular, we consider orbits which are high above the ecliptic plane, in contrast to the classical Halo orbits about the collinear equilibria. We begin with the Circular Restricted Three-Body Problem (CRTBP) where periodic orbits about equilibria are naturally present at linear order. Using the method of Lindstedt-Poincaré, we construct nth order approximations to periodic solutions of the nonlinear equations of motion. In the second part of the paper we generalize to the Elliptic Restricted Three Body Problem (ERTBP). A numerical continuation, with the eccentricity, e, as the varying parameter, is used to find periodic orbits above the ecliptic, starting from a known orbit at e = 0 and continuing to the required eccentricity of e = 0:0167. The stability of these periodic orbits is investigated

Preterm nutritional intake and MRI phenotype at term age: a prospective observational study

Objective: To describe (1) the relationship between nutrition and the preterm-at-term infant phenotype, (2) phenotypic differences between preterm-at-term infants and healthy term born infants and (3) relationships between somatic and brain MRI outcomes. Design: Prospective observational study. Setting: UK tertiary neonatal unit. Participants: Preterm infants (<32 weeks gestation) (n=22) and healthy term infants (n=39) Main outcome measures: Preterm nutrient intake; total and regional adipose tissue (AT) depot volumes; brain volume and proximal cerebral arterial vessel tortuosity (CAVT) in preterm infants and in term infants. Results: Preterm nutrition was deficient in protein and high in carbohydrate and fat. Preterm nutrition was not related to AT volumes, brain volume or proximal CAVT score; a positive association was noted between human milk intake and proximal CAVT score (r=0.44, p=0.05). In comparison to term infants, preterm infants had increased total adiposity, comparable brain volumes and reduced proximal CAVT scores. There was a significant negative correlation between deep subcutaneous abdominal AT volume and brain volume in preterm infants (r=−0.58, p=0.01). Conclusions: Though there are significant phenotypic differences between preterm infants at term and term infants, preterm macronutrient intake does not appear to be a determinant. Our preliminary data suggest that (1) human milk may exert a beneficial effect on cerebral arterial vessel tortuosity and (2) there is a negative correlation between adiposity and brain volume in preterm infants at term. Further work is warranted to see if our findings can be replicated and to understand the causal mechanisms

Theory of necking localization in unconstrained electromagnetic expansion of thin sheets

AbstractCertain sheet metal alloys of industrial interest show a significant increase in ductility, over conventional forming methods, when high speed electromagnetic processes are used. The present work models the necking localization of a metal sheet during an electromagnetic process and examines the factors that influence this process. A Marciniak–Kuczynski “weak band” model is used to predict the onset of necking of a thin sheet under plane stress, an idealization of the local conditions in a thin sheet subjected to unconstrained electromagnetic loading. It is found that electromagnetic forming (EMF) increases ductility over quasistatic techniques due to the material’s strain-rate sensitivity, with ductility increasing monotonically with applied strain rates. The electric current also increases onset of necking strains, but the details depend on thermal sensitivity and temperature-dependence of the strain-rate sensitivity exponent. Given the insensitivity of the results to actual strain profiles, this local type analysis provides a useful tool that can be used for ductility predictions involving EMF processes

A Framework for Automatic Morphological Feature Extraction and Analysis of Abdominal Organs in MRI Volumes

The accurate 3D reconstruction of organs from radiological scans is an essential tool in computer-aided diagnosis (CADx) and plays a critical role in clinical, biomedical and forensic science research. The structure and shape of the organ, combined with morphological measurements such as volume and curvature, can provide significant guidance towards establishing progression or severity of a condition, and thus support improved diagnosis and therapy planning. Furthermore, the classification and stratification of organ abnormalities aim to explore and investigate organ deformations following injury, trauma and illness. This paper presents a framework for automatic morphological feature extraction in computer-aided 3D organ reconstructions following organ segmentation in 3D radiological scans. Two different magnetic resonance imaging (MRI) datasets are evaluated. Using the MRI scans of 85 adult volunteers, the overall mean volume for the pancreas organ is 69.30 ± 32.50cm3, and the 3D global curvature is (35.23 ± 6.83) × 10−3. Another experiment evaluates the MRI scans of 30 volunteers, and achieves mean liver volume of 1547.48 ± 204.19cm3 and 3D global curvature (19.87 ± 3.62) × 10− 3. Both experiments highlight a negative correlation between 3D curvature and volume with a statistical difference (p < 0.0001). Such a tool can support the investigation into organ related conditions such as obesity, type 2 diabetes mellitus and liver disease

A Framework for Morphological Feature Extraction of Organs from MR Images for Detection and Classification of Abnormalities

In clinical practice, a misdiagnosis can lead to incorrect or delayed treatment, and in some cases, no treatment at all; consequently, the condition of a patient may worsen to varying degrees, in some cases proving fatal. The accurate 3D reconstruction of organs, which is a pioneering tool of medical image computing (MIC) technology, plays a key role in computer aided diagnosis (CADx), thereby enabling medical professionals to perform enhanced analysis on a region of interest. From here, the shape and structure of the organ coupled with measurements of its volume and curvature can provide significant guidance towards establishing the severity of a disorder or abnormality, consequently supporting improved diagnosis and treatment planning. Moreover, the classification and stratification of organ abnormalities is widely utilised within biomedical, forensic and MIC research for exploring and investigating organ deformations following injury, illness or trauma. This paper presents a tool that calculates, classifies and analyses pancreatic volume and curvature following their 3D reconstruction. Magnetic resonance imaging (MRI) volumes of 115 adult patients are evaluated in order to examine a correlation between these two variables. Such a tool can be utilised in the scope of much greater research and investigation. It can also be incorporated into the development of effective medical image analysis software application in the stratification of subjects and targeting of therapies