Modelling eggshell maculation

The eggshells of many avian species are characterised by distinctive patterns of maculation, consisting of speckles, spots, blotches or streaks, the spatial-statistical properties of which vary considerably between (and often within) species. Understanding the mechanisms underlying the production of eggshell maculation would enable us to explore the costs and constraints on the evolution of maculation patterns, but as yet this area is surprisingly understudied. Here I present a simple model of eggshell maculation, which is based on the known biology of pigment deposition, and which can produce a range of realistic maculation patterns. In particular, it provides an explanation for previous observations of maculation heterogeneity and diversity, and allows testable predictions to be made regarding maculation patterns, including a possible signalling role

A monovalent chimpanzee adenovirus Ebola vaccine boosted with MVA

BACKGROUND The West African outbreak of Ebola virus disease that peaked in 2014 has caused more than 11,000 deaths. The development of an effective Ebola vaccine is a priority for control of a future outbreak. METHODS In this phase 1 study, we administered a single dose of the chimpanzee adenovirus 3 (ChAd3) vaccine encoding the surface glycoprotein of Zaire ebolavirus (ZEBOV) to 60 healthy adult volunteers in Oxford, United Kingdom. The vaccine was administered in three dose levels — 1×1010 viral particles, 2.5×1010 viral particles, and 5×1010 viral particles — with 20 participants in each group. We then assessed the effect of adding a booster dose of a modified vaccinia Ankara (MVA) strain, encoding the same Ebola virus glyco- protein, in 30 of the 60 participants and evaluated a reduced prime–boost interval in another 16 participants. We also compared antibody responses to inactivated whole Ebola virus virions and neutralizing antibody activity with those observed in phase 1 studies of a recombinant vesicular stomatitis virus–based vaccine expressing a ZEBOV glycoprotein (rVSV-ZEBOV) to determine relative potency and assess durability. RESULTS No safety concerns were identified at any of the dose levels studied. Four weeks after immunization with the ChAd3 vaccine, ZEBOV-specific antibody responses were similar to those induced by rVSV-ZEBOV vaccination, with a geometric mean titer of 752 and 921, respectively. ZEBOV neutralization activity was also similar with the two vaccines (geo- metric mean titer, 14.9 and 22.2, respectively). Boosting with the MVA vector increased virus-specific antibodies by a factor of 12 (geometric mean titer, 9007) and increased glycoprotein-specific CD8+ T cells by a factor of 5. Significant increases in neutralizing antibodies were seen after boosting in all 30 participants (geometric mean titer, 139; P<0.001). Virus-specific antibody responses in participants primed with ChAd3 remained positive 6 months after vaccination (geometric mean titer, 758) but were significantly higher in those who had received the MVA booster (geometric mean titer, 1750; P<0.001). CONCLUSIONS The ChAd3 vaccine boosted with MVA elicited B-cell and T-cell immune responses to ZEBOV that were superior to those induced by the ChAd3 vaccine alone. (Funded by the Wellcome Trust and others; ClinicalTrials.gov number, NCT02240875.

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs.Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.Molecular Epidemiolog

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. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

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. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

Disruptive contrast in animal camouflage

Camouflage typically involves colour patterns that match the background. However, it has been argued that concealment may be achieved by strategic use of apparently conspicuous markings. Recent evidence supports the theory that the presence of contrasting patterns placed peripherally on an animal's body (disruptive coloration) provides survival advantages. However, no study has tested a key prediction from the early literature that disruptive coloration is effective even when some colour patches do not match the background and have a high contrast with both the background and adjacent pattern elements (disruptive contrast). We test this counter-intuitive idea that conspicuous patterns might aid concealment, using artificial moth-like targets with pattern elements designed to match or mismatch the average luminance (lightness) of the trees on which they were placed. Disruptive coloration was less effective when some pattern elements did not match the background luminance. However, even non-background-matching disruptive patterns reduced predation relative to equivalent non-disruptive patterns or to unpatterned controls. Therefore, concealment may still be achieved even when an animal possesses markings not found in the background. Disruptive coloration may allow animals to exploit backgrounds on which they are not perfectly matched, and to possess conspicuous markings while still retaining a degree of camouflage

Predator perception and the interrelation between different forms of protective coloration

Animals possess a range of defensive markings to reduce the risk of predation, including warning colours, camouflage, eyespots and mimicry. These different strategies are frequently considered independently, and with little regard towards predator vision, even though they may be linked in various ways and can be fully understood only in terms of predator perception. For example, camouflage and warning coloration need not be mutually exclusive, and may frequently exploit similar features of visual perception. This paper outlines how different forms of protective markings can be understood from predator perception and illustrates how this is fundamental in determining the mechanisms underlying, and the interrelation between, different strategies. Suggestions are made for future work, and potential mechanisms discussed in relation to various forms of defensive coloration, including disruptive coloration, eyespots, dazzle markings, motion camouflage, aposematism and mimicry

Data from: Phylogenetic comparative analysis supports aposematic colouration–body size association in millipede assassins (Hemiptera: Reduviidae: Ectrichodiinae)

The diversity of colour patterns and its importance in interactions with the environment make colouration in animals an intriguing research focus. Aposematic colouration is positively correlated with body size in certain groups of animals, suggesting that warning colours are more effective or that crypsis is harder to achieve in larger animals. Surprisingly, this relationship has not been recovered in studies investigating insects, which may have been confounded by a focus on aposematic taxa that are also gregarious. Millipede assassin bugs (Hemiptera: Reduviidae: Ectrichodiinae) comprise species with cryptic and aposematic colour patterns across a range of body sizes, are typically solitary as adults, and are thus an excellent model for investigating a possible association between colouration and body size. Here, we use a comprehensive phylogeny for Ectrichodiinae, ancestral state reconstruction of colouration, and phylogenetic comparative methods to test for a colouration-body size association. The ancestor of Ectrichodiinae is reconstructed as cryptically coloured, with multiple subsequent transitions between aposematic and cryptic colouration. Aposematic colouration is positively associated with male body length and supports the hypothesis that selection on Ectrichodiinae body size may influence evolutionary transitions between aposematic and cryptic colouration or alternatively that selection for aposematic colouration influences body size evolution