Impact of visceral fat on skeletal muscle mass and vice versa in a prospective cohort study: The Korean Sarcopenic Obesity Study (KSOS)

Objectives: Sarcopenia and visceral obesity have been suggested to aggravate each other, resulting in a vicious cycle. However, evidence based on prospective study is very limited. Our purpose was to investigate whether visceral fat promotes a decrease in skeletal muscle mass and vice versa. Methods: We observed changes in anthropometric and body composition data during a follow-up period of 27.6±2.8 months in 379 Korean men and women (mean age 51.9±14.6 years) from the Korean Sarcopenic Obesity Study (KSOS). Appendicular lean soft tissue (ALST) mass was calculated using dual-energy X-ray absorptiometry, and visceral fat area (VFA) was measured using computed tomography at baseline and follow-up examination. Results: ALST mass significantly decreased, whereas trunk and total fat mass increased in both men and women despite no significant change in weight and body mass index. In particular, women with visceral obesity at baseline had a greater decrease in ALST mass than those without visceral obesity (P=0.001). In multiple linear regression analysis, baseline VFA was an independent negative predictor of the changes in ALST after adjusting for confounding factors including age, gender, life style and body composition parameters, insulin resistance, high sensitivity C-reactive protein and vitamin D levels (P=0.001), whereas the association between baseline ALST mass and changes in VFA was not statistically significant (P=0.555). Conclusions: This longitudinal study showed that visceral obesity was associated with future loss of skeletal muscle mass in Korean adults. These results may provide novel insight into sarcopenic obesity in an aging society

Long-term follow-up of beryllium sensitized workers from a single employer

<p>Abstract</p> <p>Background</p> <p>Up to 12% of beryllium-exposed American workers would test positive on beryllium lymphocyte proliferation test (BeLPT) screening, but the implications of sensitization remain uncertain.</p> <p>Methods</p> <p>Seventy two current and former employees of a beryllium manufacturer, including 22 with pathologic changes of chronic beryllium disease (CBD), and 50 without, with a confirmed positive test were followed-up for 7.4 +/-3.1 years.</p> <p>Results</p> <p>Beyond predicted effects of aging, flow rates and lung volumes changed little from baseline, while D_LCO dropped 17.4% of predicted on average. Despite this group decline, only 8 subjects (11.1%) demonstrated physiologic or radiologic abnormalities typical of CBD. Other than baseline status, no clinical or laboratory feature distinguished those who clinically manifested CBD at follow-up from those who did not.</p> <p>Conclusions</p> <p>The clinical outlook remains favorable for beryllium-sensitized individuals over the first 5-12 years. However, declines in D_LCO may presage further and more serious clinical manifestations in the future. These conclusions are tempered by the possibility of selection bias and other study limitations.</p

Seasonal and decadal forecasts of Atlantic Sea surface temperatures using a linear inverse model

Predictability of Atlantic Ocean sea surface temperatures (SST) on seasonal and decadal timescales is investigated using a suite of statistical linear inverse models (LIM). Observed monthly SST anomalies in the Atlantic sector (between 22(Formula presented.)S and 66(Formula presented.)N) are used to construct the LIMs for seasonal and decadal prediction. The forecast skills of the LIMs are then compared to that from two current operational forecast systems. Results indicate that the LIM has good forecast skill for time periods of 3–4 months on the seasonal timescale with enhanced predictability in the spring season. On decadal timescales, the impact of inter-annual and intra-annual variability on the predictability is also investigated. The results show that the suite of LIMs have forecast skill for about 3–4 years over most of the domain when we use only the decadal variability for the construction of the LIM. Including higher frequency variability helps improve the forecast skill and maintains the correlation of LIM predictions with the observed SST anomalies for longer periods. These results indicate the importance of temporal scale interactions in improving predictability on decadal timescales. Hence, LIMs can not only be used as benchmarks for estimates of statistical skill but also to isolate contributions to the forecast skills from different timescales, spatial scales or even model components

Body image, body dissatisfaction and weight status in south asian children: a cross-sectional study

Background Childhood obesity is a continuing problem in the UK and South Asian children represent a group that are particularly vulnerable to its health consequences. The relationship between body dissatisfaction and obesity is well documented in older children and adults, but is less clear in young children, particularly South Asians. A better understanding of this relationship in young South Asian children will inform the design and delivery of obesity intervention programmes. The aim of this study is to describe body image size perception and dissatisfaction, and their relationship to weight status in primary school aged UK South Asian children. Methods Objective measures of height and weight were undertaken on 574 predominantly South Asian children aged 5-7 (296 boys and 278 girls). BMI z-scores, and weight status (underweight, healthy weight, overweight or obese) were calculated based on the UK 1990 BMI reference charts. Figure rating scales were used to assess perceived body image size (asking children to identify their perceived body size) and dissatisfaction (difference between perceived current and ideal body size). The relationship between these and weight status were examined using multivariate analyses. Results Perceived body image size was positively associated with weight status (partial regression coefficient for overweight/obese vs. non-overweight/obese was 0.63 (95% CI 0.26-0.99) and for BMI z-score was 0.21 (95% CI 0.10-0.31), adjusted for sex, age and ethnicity). Body dissatisfaction was also associated with weight status, with overweight and obese children more likely to select thinner ideal body size than healthy weight children (adjusted partial regression coefficient for overweight/obese vs. non-overweight/obese was 1.47 (95% CI 0.99-1.96) and for BMI z-score was 0.54 (95% CI 0.40-0.67)). Conclusions Awareness of body image size and increasing body dissatisfaction with higher weight status is established at a young age in this population. This needs to be considered when designing interventions to reduce obesity in young children, in terms of both benefits and harms

Altered thymic differentiation and modulation of arthritis by invariant NKT cells expressing mutant ZAP70

Various subsets of invariant natural killer T (iNKT) cells with different cytokine productions develop in the mouse thymus, but the factors driving their differentiation remain unclear. Here we show that hypomorphic alleles of Zap70 or chemical inhibition of Zap70 catalysis leads to an increase of IFN-gamma-producing iNKT cells (NKT1 cells), suggesting that NKT1 cells may require a lower TCR signal threshold. Zap70 mutant mice develop IL-17-dependent arthritis. In a mouse experimental arthritis model, NKT17 cells are increased as the disease progresses, while NKT1 numbers negatively correlates with disease severity, with this protective effect of NKT1 linked to their IFN-gamma expression. NKT1 cells are also present in the synovial fluid of arthritis patients. Our data therefore suggest that TCR signal strength during thymic differentiation may influence not only IFN-gamma production, but also the protective function of iNKT cells in arthritis

Scattering Amplitudes and BCFW Recursion in Twistor Space

Twistor ideas have led to a number of recent advances in our understanding of scattering amplitudes. Much of this work has been indirect, determining the twistor space support of scattering amplitudes by examining the amplitudes in momentum space. In this paper, we construct the actual twistor scattering amplitudes themselves. We show that the recursion relations of Britto, Cachazo, Feng and Witten have a natural twistor formulation that, together with the three-point seed amplitudes, allows us to recursively construct general tree amplitudes in twistor space. We obtain explicit formulae for $n$-particle MHV and NMHV super-amplitudes, their CPT conjugates (whose representations are distinct in our chiral framework), and the eight particle N^2MHV super-amplitude. We also give simple closed form formulae for the N=8 supergravity recursion and the MHV and conjugate MHV amplitudes. This gives a formulation of scattering amplitudes in maximally supersymmetric theories in which superconformal symmetry and its breaking is manifest. For N^kMHV, the amplitudes are given by 2n-4 integrals in the form of Hilbert transforms of a product of $n-k-2$ purely geometric, superconformally invariant twistor delta functions, dressed by certain sign operators. These sign operators subtly violate conformal invariance, even for tree-level amplitudes in N=4 super Yang-Mills, and we trace their origin to a topological property of split signature space-time. We develop the twistor transform to relate our work to the ambidextrous twistor diagram approach of Hodges and of Arkani-Hamed, Cachazo, Cheung and Kaplan.Comment: v2: minor corrections + extra refs. v3: further minor corrections, extra discussion of signature issues + more ref

An empirical model for probabilistic decadal prediction: global attribution and regional hindcasts

Empirical models, designed to predict surface variables over seasons to decades ahead, provide useful benchmarks for comparison against the performance of dynamical forecast systems; they may also be employable as predictive tools for use by climate services in their own right. A new global empirical decadal prediction system is presented, based on a multiple linear regression approach designed to produce probabilistic output for comparison against dynamical models. A global attribution is performed initially to identify the important forcing and predictor components of the model . Ensemble hindcasts of surface air temperature anomaly fields are then generated, based on the forcings and predictors identified as important, under a series of different prediction ‘modes’ and their performance is evaluated. The modes include a real-time setting, a scenario in which future volcanic forcings are prescribed during the hindcasts, and an approach which exploits knowledge of the forced trend. A two-tier prediction system, which uses knowledge of future sea surface temperatures in the Pacific and Atlantic Oceans, is also tested, but within a perfect knowledge framework. Each mode is designed to identify sources of predictability and uncertainty, as well as investigate different approaches to the design of decadal prediction systems for operational use. It is found that the empirical model shows skill above that of persistence hindcasts for annual means at lead times of up to 10 years ahead in all of the prediction modes investigated. It is suggested that hindcasts which exploit full knowledge of the forced trend due to increasing greenhouse gases throughout the hindcast period can provide more robust estimates of model bias for the calibration of the empirical model in an operational setting. The two-tier system shows potential for improved real-time prediction, given the assumption that skilful predictions of large-scale modes of variability are available. The empirical model framework has been designed with enough flexibility to facilitate further developments, including the prediction of other surface variables and the ability to incorporate additional predictors within the model that are shown to contribute significantly to variability at the local scale. It is also semi-operational in the sense that forecasts have been produced for the coming decade and can be updated when additional data becomes available

An Analytically Solvable Model for Rapid Evolution of Modular Structure

Biological systems often display modularity, in the sense that they can be decomposed into nearly independent subsystems. Recent studies have suggested that modular structure can spontaneously emerge if goals (environments) change over time, such that each new goal shares the same set of sub-problems with previous goals. Such modularly varying goals can also dramatically speed up evolution, relative to evolution under a constant goal. These studies were based on simulations of model systems, such as logic circuits and RNA structure, which are generally not easy to treat analytically. We present, here, a simple model for evolution under modularly varying goals that can be solved analytically. This model helps to understand some of the fundamental mechanisms that lead to rapid emergence of modular structure under modularly varying goals. In particular, the model suggests a mechanism for the dramatic speedup in evolution observed under such temporally varying goals

A call for using natural compounds in the development of new antimalarial treatments – an introduction

Natural compounds, mostly from plants, have been the mainstay of traditional medicine for thousands of years. They have also been the source of lead compounds for modern medicine, but the extent of mining of natural compounds for such leads decreased during the second half of the 20th century. The advantage of natural compounds for the development of drugs derives from their innate affinity for biological receptors. Natural compounds have provided the best anti-malarials known to date. Recent surveys have identified many extracts of various organisms (mostly plants) as having antiplasmodial activity. Huge libraries of fractionated natural compounds have been screened with impressive hit rates. Importantly, many cases are known where the crude biological extract is more efficient pharmacologically than the most active purified compound from this extract. This could be due to synergism with other compounds present in the extract, that as such have no pharmacological activity. Indeed, such compounds are best screened by cell-based assay where all potential targets in the cell are probed and possible synergies identified. Traditional medicine uses crude extracts. These have often been shown to provide many concoctions that deal better with the overall disease condition than with the causative agent itself. Traditional medicines are used by ~80 % of Africans as a first response to ailment. Many of the traditional medicines have demonstrable anti-plasmodial activities. It is suggested that rigorous evaluation of traditional medicines involving controlled clinical trials in parallel with agronomical development for more reproducible levels of active compounds could improve the availability of drugs at an acceptable cost and a source of income in malaria endemic countries