Do socioeconomic factors shape weight and obesity trajectories over the transition from midlife to old age? Results from the French GAZEL cohort study

BACKGROUND: Obesity is a contemporary epidemic that does not affect all age groups and sections of society equally. OBJECTIVE: The objective was to examine socioeconomic differences in trajectories of body mass index (BMI; in kg/m(2)) and obesity between the ages of 45 and 65 y. DESIGN: A total of 13,297 men and 4532 women from the French GAZEL (Gaz de France Electricité de France) cohort study reported their height in 1990 and their weight annually over the subsequent 18 y. Changes in BMI and obesity between ages 45 and 49 y, 50 and 54 y, 55 and 59 y, and 60 and 65 y as a function of education and occupational position (at age 35 y) were modeled by using linear mixed models and generalized estimating equations. RESULTS: BMI and obesity rates increased between the ages of 45 and 65 y. In men, BMI was higher in unskilled workers than in managers at age 45 y; this difference in BMI increased from 0.82 (95% CI: 0.66, 0.99) at 45 y to 1.06 (95% CI: 0.85, 1.27) at 65 y. Men with a primary school education compared with those with a high school degree at age 45 y had a 0.75 (95% CI: 0.51, 1.00) higher BMI, and this difference increased to 1.32 (95% CI: 1.03,1.62) at age 65 y. Obesity rates were 3.35% and 7.68% at age 45 y and 9.52% and 18.10% at age 65 y in managers and unskilled workers, respectively; the difference in obesity increased by 4.25% (95% CI: 1.87, 6.52). A similar trend was observed in women. Conclusions: Weight continues to increase in the transition between midlife and old age; this increase is greater in lower socioeconomic groups.

Gender and weight shape brain dynamics during food viewing.

Hemodynamic imaging results have associated both gender and body weight to variation in brain responses to food-related information. However, the spatio-temporal brain dynamics of gender-related and weight-wise modulations in food discrimination still remain to be elucidated. We analyzed visual evoked potentials (VEPs) while normal-weighted men (n = 12) and women (n = 12) categorized photographs of energy-dense foods and non-food kitchen utensils. VEP analyses showed that food categorization is influenced by gender as early as 170 ms after image onset. Moreover, the female VEP pattern to food categorization co-varied with participants' body weight. Estimations of the neural generator activity over the time interval of VEP modulations (i.e. by means of a distributed linear inverse solution [LAURA]) revealed alterations in prefrontal and temporo-parietal source activity as a function of image category and participants' gender. However, only neural source activity for female responses during food viewing was negatively correlated with body-mass index (BMI) over the respective time interval. Women showed decreased neural source activity particularly in ventral prefrontal brain regions when viewing food, but not non-food objects, while no such associations were apparent in male responses to food and non-food viewing. Our study thus indicates that gender influences are already apparent during initial stages of food-related object categorization, with small variations in body weight modulating electrophysiological responses especially in women and in brain areas implicated in food reward valuation and intake control. These findings extend recent reports on prefrontal reward and control circuit responsiveness to food cues and the potential role of this reactivity pattern in the susceptibility to weight gain.

Off-axis low coherence interferometry contouring

In this article we present a method to achieve tri-dimensional contouring of macroscopic objects. A modified reference wave speckle interferometer is used in conjunction with a source of reduced coherence. The depth signal is given by the envelope of the interference signal, directly determined by the coherence length of the source. Fringes are detected in the interferogram obtained by a single shot and are detected by means of adequate filtering. With the approach based on off-axis configuration, a contour line can be extracted from a single acquisition, thus allowing to use the system in harsh environment. (C) 2009 Elsevier B.V. All rights reserved.

Mass detection on mammograms: influence of signal shape uncertainty on human and model observers.

We studied the influence of signal variability on human and model observers for detection tasks with realistic simulated masses superimposed on real patient mammographic backgrounds and synthesized mammographic backgrounds (clustered lumpy backgrounds, CLB). Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) tasks for which the observers did not have prior knowledge of the shape or size of the signal. Human observers' performance did not vary significantly when benign masses were superimposed on real images or on CLB. Uncertainty and variability in signal shape did not degrade human performance significantly compared with the SKE task, while variability in signal size did. Implementation of appropriate internal noise components allowed the fit of model observers to human performance.

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

Unilateral cricothyroid contraction and glottic configuration.

It is frequently stated that unilateral cricothyroid muscle (CT) paralysis can be diagnosed by physical examination, noting rotation of the glottis, and shortening and vertical displacement of the ipsilateral vocal fold. These signs, however, are inconsistently observed, and there is considerable controversy regarding the direction of glottic rotation. To determine the effects of CT contraction on three-dimensional glottic configuration, we performed computerized tomography on cadaver larynges before and after simulated CT contraction. Radiopaque makers were used to compute distances. Unilateral CT contraction equally increased the length of both membranous vocal folds, and rotated the posterior glottis less than 1 mm. CT contraction neither adducted the vocal processes, nor significantly their altered vertical level. These results suggest that unilateral CT paralysis cannot be diagnosed on the basis of any clinically apparent change in glottal configuration.

δ 15N measurement of organic and inorganic substances by EA-IRMS: a speciation-dependent procedure

Little attention has been paid so far to the influence of the chemical nature of the substance when measuring δ 15N by elemental analysis (EA)-isotope ratio mass spectrometry (IRMS). Although the bulk nitrogen isotope analysis of organic material is not to be questioned, literature from different disciplines using IRMS provides hints that the quantitative conversion of nitrate into nitrogen presents difficulties. We observed abnormal series of δ 15N values of laboratory standards and nitrates. These unexpected results were shown to be related to the tailing of the nitrogen peak of nitrate-containing compounds. A series of experiments were set up to investigate the cause of this phenomenon, using ammonium nitrate (NH4NO3) and potassium nitrate (KNO3) samples, two organic laboratory standards as well as the international secondary reference materials IAEA-N1, IAEA-N2-two ammonium sulphates [(NH4)2SO4]-and IAEA-NO-3, a potassium nitrate. In experiment 1, we used graphite and vanadium pentoxide (V2O5) as additives to observe if they could enhance the decomposition (combustion) of nitrates. In experiment 2, we tested another elemental analyser configuration including an additional section of reduced copper in order to see whether or not the tailing could originate from an incomplete reduction process. Finally, we modified several parameters of the method and observed their influence on the peak shape, δ 15N value and nitrogen content in weight percent of nitrogen of the target substances. We found the best results using mere thermal decomposition in helium, under exclusion of any oxygen. We show that the analytical procedure used for organic samples should not be used for nitrates because of their different chemical nature. We present the best performance given one set of sample introduction parameters for the analysis of nitrates, as well as for the ammonium sulphate IAEA-N1 and IAEA-N2 reference materials. We discuss these results considering the thermochemistry of the substances and the analytical technique itself. The results emphasise the difference in chemical nature of inorganic and organic samples, which necessarily involves distinct thermochemistry when analysed by EA-IRMS. Therefore, they should not be processed using the same analytical procedure. This clearly impacts on the way international secondary reference materials should be used for the calibration of organic laboratory standards.

Alliance patterns over the course of short-term dynamic psychotherapy: The shape of productive relationships.

The shape of alliance processes over the course of psychotherapy has already been studied in several process-outcome studies on very brief psychotherapy. The present study applies the shape-of-change methodology to short-term dynamic psychotherapies and complements this method with hierarchical linear modeling. A total of 50 psychotherapies of up to 40 sessions were included. Alliance was measured at the end of each session. The results indicate that a linear progression model is most adequate. Three main patterns were found: stable, linear, and quadratic growth. The linear growth pattern, along with the slope parameter, was related to treatment outcome. This study sheds additional light on alliance process research, underscores the importance of linear alliance progression for outcome, and also fosters a better understanding of its limitations.

Genome organization and gene expression shape the transposable element distribution in the Drosophila melanogaster euchromatin.

The distribution of transposable elements (TEs) in a genome reflects a balance between insertion rate and selection against new insertions. Understanding the distribution of TEs therefore provides insights into the forces shaping the organization of genomes. Past research has shown that TEs tend to accumulate in genomic regions with low gene density and low recombination rate. However, little is known about the factors modulating insertion rates across the genome and their evolutionary significance. One candidate factor is gene expression, which has been suggested to increase local insertion rate by rendering DNA more accessible. We test this hypothesis by comparing the TE density around germline- and soma-expressed genes in the euchromatin of Drosophila melanogaster. Because only insertions that occur in the germline are transmitted to the next generation, we predicted a higher density of TEs around germline-expressed genes than soma-expressed genes. We show that the rate of TE insertions is greater near germline- than soma-expressed genes. However, this effect is partly offset by stronger selection for genome compactness (against excess noncoding DNA) on germline-expressed genes. We also demonstrate that the local genome organization in clusters of coexpressed genes plays a fundamental role in the genomic distribution of TEs. Our analysis shows that-in addition to recombination rate-the distribution of TEs is shaped by the interaction of gene expression and genome organization. The important role of selection for compactness sheds a new light on the role of TEs in genome evolution. Instead of making genomes grow passively, TEs are controlled by the forces shaping genome compactness, most likely linked to the efficiency of gene expression or its complexity and possibly their interaction with mechanisms of TE silencing.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.