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

Forage yield and quality of intercropped corn and soybean in narrow strips

Maize-soybean intercropping can increase forage quality with no detrimental effect on dry matter (DM) yield. The objective of this study was to compare corn-soybean intercrop in narrow strips with corn as monocrop in terms of DM yield and forage quality. This study was conducted in Matamoros, Coahuila (Mexico) in 2006 and 2007. Intercrops were established in rows spaced 0.50 m apart, evaluating alternate corn-soybean strips with one, two, three, and four rows per crop, and a treatment using an alternate twin-row planting pattern per crop, with a 1.0-m row-spacing. As control treatments, monocrops of corn in rows 0.76 m apart and soybean in rows 0.50 m apart were evaluated. A randomized complete block design with four replications was employed. Corn-soybean intercrop produced DM yields similar to those of monocropped corn due to higher corn yields in border rows adjacent to soybean. Crude protein (CP) yields per hectare in intercrop treatments were higher (27.5 to 42.8%) than those of monocropped corn, due to greater CP concentrations in intercrops (16 to 21 g kg�1). When soybean was harvested at the beginning maturity stage (R7), neutral detergent fiber concentration was reduced by 60 to 63 g kg�1 in corn-soybean intercropping compared to corn monocrop. Acid detergent fiber was not altered by intercropping. Results indicate that maize-soybean intercrop in narrow strips can provide forage quality advantages without affecting yield.La asociación maíz-soya puede incrementar la calidad del forraje sin disminuir el rendimiento de materia seca (MS). El objetivo del estudio fue comparar la asociación maíz-soya en franjas angostas con maíz en unicultivo en términos de rendimiento de MS y calidad de forraje. El estudio se realizó en 2006 y 2007 en Matamoros, Coahuila, México. Las asociaciones se establecieron en surcos a 0,50 m, en franjas alternas de maíz y soya con uno, dos, tres y cuatro surcos por cultivo y un tratamiento en surcos alternos a 1 m con doble hilera del mismo cultivo. Los testigos fueron maíz y soya en unicultivo establecidos en surcos a 0,76 m y 0,50 m, respectivamente. Se utilizó un diseño experimental de bloques completos al azar con cuatro repeticiones. La asociación maíz-soya produjo rendimientos de MS similares a maíz en unicultivo como resultado de un mayor rendimiento del maíz en los surcos adyacentes a la soya. Debido al mayor contenido de proteína cruda (PC) (16 a 21 g kg�1), las asociaciones produjeron rendimientos de PC ha�1 superiores a maíz en unicultivo entre 27,5 y 42,8%. Cuando la soya se cosechó en la fase de inicio de maduración (R7), el contenido de fibra detergente neutro en las asociaciones se redujo entre 60 y 63 g kg�1 en relación a maíz en unicultivo. La concentración de fibra detergente ácido no fue modificada con la asociación. Los resultados indican que la calidad de forraje puede mejorarse con la asociación maíz-soya en franjas angostas sin afectar el rendimiento

Circulating microRNAs in sera correlate with soluble biomarkers of immune activation but do not predict mortality in ART treated individuals with HIV-1 infection: A case control study

10.1371/journal.pone.0139981PLoS ONE1010e013998

Flower Development

Flowers are the most complex structures of plants. Studies of Arabidopsis thaliana, which has typical eudicot flowers, have been fundamental in advancing the structural and molecular understanding of flower development. The main processes and stages of Arabidopsis flower development are summarized to provide a framework in which to interpret the detailed molecular genetic studies of genes assigned functions during flower development and is extended to recent genomics studies uncovering the key regulatory modules involved. Computational models have been used to study the concerted action and dynamics of the gene regulatory module that underlies patterning of the Arabidopsis inflorescence meristem and specification of the primordial cell types during early stages of flower development. This includes the gene combinations that specify sepal, petal, stamen and carpel identity, and genes that interact with them. As a dynamic gene regulatory network this module has been shown to converge to stable multigenic profiles that depend upon the overall network topology and are thus robust, which can explain the canalization of flower organ determination and the overall conservation of the basic flower plan among eudicots. Comparative and evolutionary approaches derived from Arabidopsis studies pave the way to studying the molecular basis of diverse floral morphologies