Contrasting impacts of heat stress on violent and nonviolent robbery in Beijing, China

Previous studies investigating the relation between heat stress and crime incidents often focus on violent crimes. In this study, the impacts of heat stress on two types of robbery (violent and nonviolent) in China are compared using crime statistics collected in Beijing and heat stress indices that consider the combined effects of temperature and humidity. The results indicate that the abrupt change in the trend of robbery rates is affected by the 2008 Beijing Olympic Games. The nonviolent robbery rates have a more pronounced seasonality and are better correlated with heat stress at daily scales, especially during the period from 2009 to 2014 when no trend exists. The results also demonstrate that both violent and nonviolent robbery rates significantly increase with heat stress in spring. The nonviolent robbery rates also significantly increase with heat stress in summer. The influence of heat stress on violent robbery rate is more complicated and nonlinear

Multi-site and multi-depth near-infrared spectroscopy in a model of simulated (central) hypovolemia: lower body negative pressure

Purpose: To test the hypothesis that the sensitivity of near-infrared spectroscopy (NIRS) in reflecting the degree of (compensated) hypovolemia would be affected by the application site and probing depth. We simultaneously applied multi-site (thenar and forearm) and multi-depth (15-2.5 and 25-2.5 mm probe distance) NIRS in a model of simulated hypovolemia: lower body negative pressure (LBNP). Methods: The study group comprised 24 healthy male volunteers who were subjected to an LBNP protocol in which a baseline period of 30 min was followed by a step-wise manipulation of negative pressure in the following steps: 0, -20, -40, -60, -80 and -100 mmHg. Stroke volume and heart rate were measured using volume-clamp finger plethysmography. Two multi-depth NIRS devices were used to measure tissue oxygen saturation (StO2) and tissue hemoglobin index (THI) continuously in the thenar and the forearm. To monitor the shift of blood volume towards the lower extremities, calf THI was measured by single-depth NIRS. Results: The main findings were that the application of LBNP resulted in a significant reduction in stroke volume which was accompanied by a reduction in forearm StO2 and THI. Conclusions: NIRS can be used to detect changes in StO2 and THI consequent upon central hypovolemia. Forearm NIRS measurements reflect hypovolemia more sensitively than thenar NIRS measurements. The sensitivity of these NIRS measurements does not depend on NIRS probing depth. The LBNP-induced shift in blood volume is reflected by a decreased THI in the forearm and an increased THI in the calf

The Effect of Human Factor H on Immunogenicity of Meningococcal Native Outer Membrane Vesicle Vaccines with Over-Expressed Factor H Binding Protein

The binding of human complement inhibitors to vaccine antigens in vivo could diminish their immunogenicity. A meningococcal ligand for the complement down-regulator, factor H (fH), is fH-binding protein (fHbp), which is specific for human fH. Vaccines containing recombinant fHbp or native outer membrane vesicles (NOMV) from mutant strains with over-expressed fHbp are in clinical development. In a previous study in transgenic mice, the presence of human fH impaired the immunogenicity of a recombinant fHbp vaccine. In the present study, we prepared two NOMV vaccines from mutant group B strains with over-expressed wild-type fHbp or an R41S mutant fHbp with no detectable fH binding. In wild-type mice in which mouse fH did not bind to fHbp in either vaccine, the NOMV vaccine with wild-type fHbp elicited 2-fold higher serum IgG anti-fHbp titers (P = 0.001) and 4-fold higher complement-mediated bactericidal titers against a PorA-heterologous strain than the NOMV with the mutant fHbp (P = 0.003). By adsorption, the bactericidal antibodies were shown to be directed at fHbp. In transgenic mice in which human fH bound to the wild-type fHbp but not to the R41S fHbp, the NOMV vaccine with the mutant fHbp elicited 5-fold higher serum IgG anti-fHbp titers (P = 0.002), and 19-fold higher bactericidal titers than the NOMV vaccine with wild-type fHbp (P = 0.001). Thus, in mice that differed only by the presence of human fH, the respective results with the two vaccines were opposite. The enhanced bactericidal activity elicited by the mutant fHbp vaccine in the presence of human fH far outweighed the loss of immunogenicity of the mutant protein in wild-type animals. Engineering fHbp not to bind to its cognate complement inhibitor, therefore, may increase vaccine immunogenicity in humans

An illustrated anatomical ontology of the developing mouse lower urogenital tract

Malformation of the urogenital tract represents a considerable paediatric burden, with many defects affecting the lower urinary tract (LUT), genital tubercle and associated structures. Understanding the molecular basis of such defects frequently draws on murine models. However, human anatomical terms do not always superimpose on the mouse, and the lack of accurate and standardised nomenclature is hampering the utility of such animal models. We previously developed an anatomical ontology for the murine urogenital system. Here, we present a comprehensive update of this ontology pertaining to mouse LUT, genital tubercle and associated reproductive structures (E10.5 to adult). Ontology changes were based on recently published insights into the cellular and gross anatomy of these structures, and on new analyses of epithelial cell types present in the pelvic urethra and regions of the bladder. Ontology changes include new structures, tissue layers and cell types within the LUT, external genitalia and lower reproductive structures. Representative illustrations, detailed text descriptions and molecular markers that selectively label muscle, nerves/ganglia and epithelia of the lower urogenital system are also presented. The revised ontology will be an important tool for researchers studying urogenital development/malformation in mouse models and will improve our capacity to appropriately interpret these with respect to the human situation

Disease Gene Characterization through Large-Scale Co-Expression Analysis

In the post genome era, a major goal of biology is the identification of specific roles for individual genes. We report a new genomic tool for gene characterization, the UCLA Gene Expression Tool (UGET).Celsius, the largest co-normalized microarray dataset of Affymetrix based gene expression, was used to calculate the correlation between all possible gene pairs on all platforms, and generate stored indexes in a web searchable format. The size of Celsius makes UGET a powerful gene characterization tool. Using a small seed list of known cartilage-selective genes, UGET extended the list of known genes by identifying 32 new highly cartilage-selective genes. Of these, 7 of 10 tested were validated by qPCR including the novel cartilage-specific genes SDK2 and FLJ41170. In addition, we retrospectively tested UGET and other gene expression based prioritization tools to identify disease-causing genes within known linkage intervals. We first demonstrated this utility with UGET using genetically heterogeneous disorders such as Joubert syndrome, microcephaly, neuropsychiatric disorders and type 2 limb girdle muscular dystrophy (LGMD2) and then compared UGET to other gene expression based prioritization programs which use small but discrete and well annotated datasets. Finally, we observed a significantly higher gene correlation shared between genes in disease networks associated with similar complex or Mendelian disorders.UGET is an invaluable resource for a geneticist that permits the rapid inclusion of expression criteria from one to hundreds of genes in genomic intervals linked to disease. By using thousands of arrays UGET annotates and prioritizes genes better than other tools especially with rare tissue disorders or complex multi-tissue biological processes. This information can be critical in prioritization of candidate genes for sequence analysis

Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10-8, HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10-8, HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4×10-8, HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific associat

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017

Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. METHODS: The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised