A new method for spatially resolving the turbulence driving mixture in the ISM with application to the Small Magellanic Cloud

Turbulence plays a crucial role in shaping the structure of the interstellar medium. The ratio of the three-dimensional density contrast ($\sigma_{\rho/\rho_0}$) to the turbulent sonic Mach number ($\mathcal{M}$) of an isothermal, compressible gas describes the ratio of solenoidal to compressive modes in the turbulent acceleration field of the gas, and is parameterised by the turbulence driving parameter: $b=\sigma_{\rho/\rho_0}/\mathcal{M}$. The turbulence driving parameter ranges from $b=1/3$ (purely solenoidal) to $b=1$ (purely compressive), with $b=0.38$ characterising the natural mixture (1/3~compressive, 2/3~solenoidal) of the two driving modes. Here we present a new method for recovering $\sigma_{\rho/\rho_0}$, $\mathcal{M}$, and $b$, from observations on galactic scales, using a roving kernel to produce maps of these quantities from column density and centroid velocity maps. We apply our method to high-resolution HI emission observations of the Small Magellanic Cloud (SMC) from the GASKAP-HI survey. We find that the turbulence driving parameter varies between $b\sim 0.3$ and $b\sim 1.0$ within the main body of the SMC, but the median value converges to $b\sim0.51$, suggesting that the turbulence is overall driven more compressively ($b>0.38$). We observe no correlation between the $b$ parameter and HI or H$\alpha$ intensity, indicating that compressive driving of HI turbulence cannot be determined solely by observing HI or H$\alpha$ emission density, and that velocity information must also be considered. Further investigation is required to link our findings to potential driving mechanisms such as star-formation feedback, gravitational collapse, or cloud-cloud collisions.Comment: 20 pages, 16 figures, accepted to MNRA

Psychiatric disorders, myoclonus dystonia and SGCE:An international study

OBJECTIVE: Myoclonus-dystonia (M-D) is a hyperkinetic movement disorder, typically alcohol-responsive upper body myoclonus and dystonia. The majority of autosomal dominant familial cases are caused by epsilon-sarcoglycan gene (SGCE) mutations. Previous publications have observed increased rates of psychiatric disorders amongst SGCE mutation-positive populations. We analyzed the psychiatric data from four international centers, forming the largest cohort to date, to further determine the extent and type of psychiatric disorders in M-D.METHODS: Psychiatric data from SGCE mutation-positive M-D cohorts, collected by movement disorder specialists in the Netherlands, United Kingdom, United States, and Germany, were analyzed. These data were collected using standardized, systematic questionnaires allowing classification of symptoms according to Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) criteria. Based on motor findings and SGCE mutation analysis, participants were classified into one of three groups: manifesting carriers, nonmanifesting carriers and noncarriers.RESULTS: Data from 307 participants were evaluated (140 males, 167 females, mean age at examination: 42.5 years). Two-thirds of motor affected mutation carriers (n = 132) had ≥1 psychiatric diagnosis, specific, and social phobias being most common followed by alcohol dependence and obsessive-compulsive disorder (OCD). Compared to familial controls, affected mutation carriers had significantly elevated overall rates of psychiatric disorders (P &lt; 0.001). The most significant differences were observed with alcohol dependence (P &lt; 0.001), OCD (P &lt; 0.001), social and specific phobias (P &lt; 0.001).INTERPRETATION: M-D due to SGCE mutations is associated with specific psychiatric disorders, most commonly OCD, anxiety-related disorders, and alcohol dependence. These suggest either a potential pleiotropic function for SGCE within the central nervous system or a secondary effect of the motor disorder.</p

Multiple QTLs linked to agro-morphological and physiological traits related to drought tolerance in potato.

Dissection of the genetic architecture of adaptation and abiotic stress-related traits is highly desirable for developing drought-tolerant potatoes and enhancing the resilience of existing cultivars, particularly as agricultural production in rain-fed areas may be reduced by up to 50 % by 2020. The “DMDD” potato progeny was developed at International Potato Center (CIP) by crossing the sequenced double monoploid line DM and a diploid cultivar of the Solanum tuberosum diploid Andigenum Goniocalyx group. Recently, a high-density integrated genetic map based on single nucleotide polymorphism (SNP), diversity array technology (DArT), simple sequence repeats (SSRs), and amplified fragment length polymorphism (AFLP) markers was also made available for this population. Two trials were conducted, in greenhouse and field, for drought tolerance with two treatments each, well-watered and terminal drought, in which watering was suspended 60 days after planting. The DMDD population was evaluated for agro-morphological and physiological traits before and after initiation of stress, at multiple time points. Two dense parental genetic maps were constructed using published genotypic data, and quantitative trait locus (QTL) analysis identified 45 genomic regions associated with nine traits in well-watered and terminal drought treatments and 26 potentially associated with drought stress. In this study, the strong influence of environmental factors besides water shortage on the expression of traits and QTLs reflects the multigenic control of traits related to drought tolerance. This is the first study to our knowledge in potato identifying QTLs for drought-related traits in field and greenhouse trials, giving new insights into genetic architecture of drought-related traits. Many of the QTLs identified have the potential to be used in potato breeding programs for enhanced drought tolerance

Structural and Functional Similarities between Osmotin from Nicotiana Tabacum Seeds and Human Adiponectin

Osmotin, a plant protein, specifically binds a seven transmembrane domain receptor-like protein to exert its biological activity via a RAS2/cAMP signaling pathway. The receptor protein is encoded in the gene ORE20/PHO36 and the mammalian homolog of PHO36 is a receptor for the human hormone adiponectin (ADIPOR1). Moreover it is known that the osmotin domain I can be overlapped to the β-barrel domain of adiponectin. Therefore, these observations and some already existing structural and biological data open a window on a possible use of the osmotin or of its derivative as adiponectin agonist. We have modelled the three-dimensional structure of the adiponectin trimer (ADIPOQ), and two ADIPOR1 and PHO36 receptors. Moreover, we have also modelled the following complexes: ADIPOQ/ADIPOR1, osmotin/PHO36 and osmotin/ADIPOR1. We have then shown the structural determinants of these interactions and their physico-chemical features and analyzed the related interaction residues involved in the formation of the complexes. The stability of the modelled structures and their complexes was always evaluated and controlled by molecular dynamics. On the basis of these results a 9 residues osmotin peptide was selected and its interaction with ADIPOR1 and PHO36 was modelled and analysed in term of energetic stability by molecular dynamics. To confirm in vivo the molecular modelling data, osmotin has been purified from nicotiana tabacum seeds and its nine residues peptide synthesized. We have used cultured human synovial fibroblasts that respond to adiponectin by increasing the expression of IL-6, TNF-alpha and IL-1beta via ADIPOR1. The biological effect on fibroblasts of osmotin and its peptide derivative has been found similar to that of adiponectin confirming the results found in silico

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe

Measuring the health-related Sustainable Development Goals in 188 countries : a baseline analysis from the Global Burden of Disease Study 2015

Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59.3 (95% uncertainty interval 56.8-61.8) and varied widely by country, ranging from 85.5 (84.2-86.5) in Iceland to 20.4 (15.4-24.9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2) = 0.88) and the MDG index (r(2) = 0.2), whereas the non-MDG index had a weaker relation with SDI (r(2) = 0.79). Between 2000 and 2015, the health-related SDG index improved by a median of 7.9 (IQR 5.0-10.4), and gains on the MDG index (a median change of 10.0 [6.7-13.1]) exceeded that of the non-MDG index (a median change of 5.5 [2.1-8.9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Peer reviewe

Comparison of SUVmax and SUVpeak based segmentation to determine primary lung tumour volume on FDG PET-CT correlated with pathology data

PURPOSE: The aim of the study was to compare simple SUVmax and SUVpeak based segmentation methods for calculating the lung tumour volume, compared to a pathology ground truth. METHODS: Thirty patients diagnosed with early stage Non-Small Cell lung cancer (NSCLC) underwent surgical resection in the Netherlands between 2006 and 2008. FDG PET-CT scans for these patients were acquired within a median of 20 days before surgery. The tumour volume for each percentage SUVmax and SUVpeak threshold, with and without background correction, was calculated for each patient. The percentage threshold that provided the tumour volume that corresponded best with the pathology volume was considered to be the optimal threshold. The optimal thresholds were plotted as a function of tumour volume using a power law function and cross validated using the leave-one-out technique. RESULTS: The mean optimal percentage threshold was 50% ± 10% and 62% ± 15% for the SUVmax and SUVpeak without background correction respectively and 47% ± 10% and 60 ± 15% for the SUVmax and SUVpeak with background correction respectively. The optimal threshold curves could be fitted well with power law function. After cross validation the correlation between the effective tumour diameter in pathology and autosegmentation was 0.900 and 0.905 for the SUVmax and SUVpeak without background correction respectively and 0.913 and 0.908 for the SUVmax and SUVpeak with background correction respectively. CONCLUSION: No benefit was shown on clinical data for the SUVpeak based segmentation method over a SUVmax based one. Both methods can be used to determine the tumour volumes in resected NSCLC tumours