Host-Switching Does not Circumvent the Ni-based Defence of the Ni hyperaccumulator \u3ci\u3eStreptanthus polygaloides\u3c/i\u3e (Brassicaceae)

Elevated tissue concentrations of metals have been shown to defend metal-hyperaccumulating plants against both herbivores and pathogens. Tolerance of metal-based defences presents a challenge to herbivores, because heavy metals cannot be degraded or metabolized. One strategy that herbivores can employ to counter high-metal defences is dietary dilution, or host switching. Highly mobile herbivores are most likely to use this strategy, but less mobile lepidopteran larvae can also Improve their performance on toxic hosts if early instar development occurs on more favourable hosts. We examined the effects of host switching on growth and survival of a generalist folivore. Specifically, we tested the hypothesis that early larval development on non-toxic hosts could improve larval performance of the beet armyworm, Spodoptera exigua, an high-Ni Streptanthus polygaloides, a Ni hyperaccumulator. Initial larval performance (weight gain) was lowest for insects switched to high-N! hosts. Decreased initial larval performance was also noted for insects switched from lettuce to low-Ni S. polygaloides, but these larvae recovered quickly. Original host identity (lettuce or low-Ni S. polygaloides) did not affect subsequent larval performance. By day 8 of the feeding trials, all larvae switched to high-Ni hosts had died. We conclude that polyphagous Spodoptera larvae are unable to counter NI-based defences via host switching

Chapter 2: Aerospace Materials Characteristics

No abstract availabl

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Asymmetric Error Correction Models for the Oil-Gasoline Price Relationship

The existing literature on price asymmetries does not systematically investigate the sensitivity of the empirical results to the choice of a particular econometric specification. This paper fills this gap by providing a detailed comparison of the three most popular models designed to describe asymmetric price behaviour, namely asymmetric ECM, autoregressive threshold ECM and ECM with threshold cointegration. Each model is estimated on a common monthly dataset for the gasoline markets of France, Germany, Italy, Spain and UK over the period 1985-2003. All models are able to capture the temporal delay in the reaction of retail prices to changes in spot gasoline and crude oil prices, as well as some evidence of asymmetric behaviour. However, the type of market and the number of countries which are characterized by asymmetric oil-gasoline price relations vary across models. The asymmetric ECM yields some evidence of asymmetry for all countries, mainly at the distribution stage. The threshold ECM strongly rejects the null hypothesis of symmetric price behaviour, particularly in the case of France and Germany. Finally, the ECM with threshold cointegration finds long-run asymmetry for each country in the reaction of retail prices to oil price changes

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Does Hyperaccumulated Nickel Affect Leaf Decomposition? A Field Test Using \u3ci\u3eSenecio Coronatus\u3c/i\u3e (Asteraceae) in South Africa

Nickel hyperaccumulator plants contain unusually elevated levels of Ni (\u3e1,000 mg Ni kg−1). The high Ni concentration of hyperaccumulator tissues may affect ecosystem processes such as decomposition, but this has yet to be studied under field conditions. We used Senecio coronatus Thunb. (Harv.) from two pairs of serpentine sites: one member of each pair contained a hyperaccumulator population and the other a non-hyperaccumulator population. Our main goal was to determine if leaf Ni status (hyperaccumulator or non-hyperaccumulator) affected leaf decomposition rate on serpentine sites. We also used a non-serpentine site on which leaves from all four S. coronatus populations were placed to compare decomposition at a single location. Dried leaf fragments were put into fine-mesh (0.1 mm) nylon decomposition bags and placed on field sites in mid-summer (early February) 2000. Sets of bags were recovered after 1, 3.5, and 8 months, their contents dried and weighed, and the Ni concentration and total Ni content of high-Ni leaves was measured. For the serpentine sites, there was no significant effect of leaf Ni status or site type on decomposition rates at 1 and 3.5 months. By 8 months, leaf Ni status and site type significantly influenced decomposition on one pair of sites: hyperaccumulator leaves decomposed more slowly than non-hyperaccumulator leaves, and leaves of both types decomposed more slowly on the non-hyperaccumulator site. At the non-serpentine site, the highest-Ni leaves (15,000 mg Ni kg−1) decomposed more slowly than all others, but leaves containing 9,200 mg Ni kg−1 did not decompose more slowly than non-hyperaccumulator leaves. Nickel in decomposing hyperaccumulator leaves was released rapidly: after 1 month 57–68% of biomass was lost and only 9–28% of original Ni content remained. We conclude that very high (\u3e10,000 mg Ni kg−1) leaf Ni concentrations may slow decomposition and that Ni is released at high rates that may impact co-occurring litter- and soil-dwelling organisms

Elemental Patterns in Ni Hyperaccumulating and Non-Hyperaccumulating Ultramafic Soil Populations of \u3ci\u3eSenecio coronatus\u3c/i\u3e

Nickel hyperaccumulation can defend plants against herbivores and pathogens. However, variability in plant tissue elemental concentrations in space and time will influence the effectiveness of this defense. We investigated a South African Ni hyperaccumulator, Senecio coronatus Thunb. (Harv.), for variation in nine elements (Ni plus Ca, Cu, Fe, K, Mg, Mn, P and Zn) between populations and between above-ground and below-ground plant organs (leaves, roots). Plant material was collected from four populations growing on ultramafic soils in the vicinity of Badplaas, Mpumalanga Province, South Africa. Concentrations of Ca, Cu, Fe, K, Mg, Mn, Ni, P and Zn were determined in dry-ashed samples. Two-way analysis of variance of data for each element revealed considerable variation in S. coronatus plant chemistry. Leaf concentrations of all elements except Cu were generally greater than root concentrations. Population-level variation was found for Ca, Fe, Mn, P, Ni and Zn, and of these all but P showed significant two-way interactions as well. Significant positive correlations were found between some pairs of elements: in hyperaccumulator roots (Ni–Ca, K–Mg), non-hyperaccumulator roots (Fe–Mn, Fe–Zn, Fe–Cu, Cu–Zn), hyperaccumulator leaves (P–Mg, P–Fe, P–Mn, Fe–Mg) and non-hyperaccumulator leaves (P–Mn, P–Ca, Ca–Mn). Two populations hyperaccumulated Ni in leaves (means of 12,000 and 8800 μg Ni/g) whereas the others did not (means of 120 and 130 μg Ni/g). Such extreme population-level variation in Ni accumulation ability is unusual among Ni hyperaccumulator species: its physiological basis and possible consequences for plant elemental defense deserve further investigation

Host-Herbivore Studies of \u3ci\u3eStenoscepa\u3c/i\u3e sp. (Orthoptera: Pyrgomorphidae), a High-Ni Herbivore of the South African Ni Hyperaccumulator \u3ci\u3eBerkheya coddii\u3c/i\u3e (Asteraceae)

Nymphs of Stenoscepa sp. feed on leaves of the Ni hyperaccumulator Berkheya coddii at serpentine sites in Mpumalanga Province, South Africa. These sites contain Ni hyperaccumulators, Ni accumulators, and plants with Ni concentrations in the normal range. We conducted studies to: (i) determine the whole‐body metal concentration of nymphs (including those starved to empty their guts); (ii) compare Stenoscepa sp. nymphs against other grasshoppers in the same habitat for whole‐body metal concentrations; and (iii) compare the suitability of Ni hyperaccumulator and Ni accumulator plants as food sources for Stenoscepa sp. and other grasshoppers. Stenoscepa nymphs had extremely high whole‐body Ni concentrations (3 500 μg Ni/g). This was partly due to food in the gut, as starved insects contained less Ni (950 μg Ni/g). Stenoscepa nymphs survived significantly better than other grasshoppers collected from either a serpentine or a non‐serpentine site when offered high‐Ni plants as food. In a host preference test among four Berkheya species (two Ni hyperaccumulators and two Ni accumulators), Stenoscepa sp. preferred leaves of the Ni hyperaccumulator species. A preference experiment using leaves of three Senecio species (of which one species, Senecio coronatus, was represented by both a Ni hyperaccumulator and a Ni accumulator population) showed that Stenoscepa sp. preferred Ni accumulator Senecio coronatus leaves to all other choices. We conclude that Stenoscepa sp. is extremely Ni‐tolerant. Stenoscepa sp. nymphs prefer leaves of hyperaccumulator Berkheya species, but elevated Ni concentration alone does not determine their food preference. We suggest that the extremely high whole‐body Ni concentration of Stenoscepa nymphs may affect food web relationships in these serpentine communities

Metal Concentrations of Insects Associated With the South Africa Ni Hyperaccumulator \u3ci\u3eBerkheya coddii\u3c/i\u3e (Asterceae)

The high levels of some metals in metal hyperaccumulator plants may be transferred to insect associates. We surveyed insects collected from the South African Ni hyperaccumulator Berkheya coddii to document whole‐body metal concentrations (Co, Cr, Cu, Mg, Mn, Ni, Pb, Zn). We also documented the concentrations of these metals in leaves, stems and inflorescences, finding extremely elevated levels of Ni (4 700–16 000 ∞g/g) and high values (5–34 ∞g/g) for Co, Cr, and Pb. Of 26 insect morphotypes collected from B. coddii, seven heteropterans, one coleopteran, and one orthopteran contained relatively high concentrations of Ni (\u3e 500 ∞g/g). The large number of high‐Ni heteropterans adds to discoveries of others (from California USA and New Caledonia) and suggests that members of this insect order may be particularly Ni tolerant. Nymphs of the orthopteran (Stenoscepa) contained 3 500 ∞g Ni/g, the greatest Ni concentration yet reported for an insect. We also found two beetles with elevated levels of Mg (\u3e 2 800 ∞g/g), one beetle with elevated Cu (\u3e 70 ∞g/g) and one heteropteran with an elevated level of Mn (\u3e 200 ∞g/g). Our results show that insects feeding on a Ni hyperaccumulator can mobilize Ni into food webs, although we found no evidence of Ni biomagnification in either herbivore or carnivore insect taxa. We also conclude that some insects associated with hyperaccumulators can contain Ni levels that are high enough to be toxic to vertebrates