26 research outputs found
RNA interference in Lepidoptera: an overview of successful and unsuccessful studies and implications for experimental design
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Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation
RNA interference in Lepidoptera: An overview of successful and unsuccessful studies and implications for experimental design
Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed
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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
The Members of bHLH Transcription Factor Superfamily Are Required for Female Reproduction in the Red Flour Beetle, Tribolium castaneum
Proteins containing the basic Helix-Loop-Helix (bHLH) domain function as transcription factors and play important roles during the development of various metazoans including insects, nematodes and vertebrates. Insect genomes contain more than 50 bHLH transcription factors, but the function of only a few of these proteins in regulation of female reproduction is known. Using RNA interference, we have tested knock-down in the expression of genes coding for bHLH transcription factors in newly emerged adult females to determine their function in regulation of female reproduction in the red flour beetle, Tribolium castaneum. Knock-down in the expression of genes coding for four bHLH transcription factors (TcSRC, TcSim1, TcAsh and TcDaughterless) caused mortality in the female beetles. In addition, knocking-down the expression of 16 bHLH genes affected oogenesis and knock-down in the expression of 13 genes affected embryogenesis. Two genes TcSide1 and TcSpineless are required for both oogenesis and embryogenesis. Thus, the data reported here showed that 31 bHLH transcription factors are required for female survival, reproduction and embryogenesis
Recombinant Cactus binds recombinant Rel protein homodimers but binding to Relish is competed by Ank-H4 and Ank-N5.
<p>(A) Outcome of co-immunoprecipitation experiments in which three different molar ratios of recombinant Cactus was added to each Rel protein homodimer. Following immunoprecipitation each sample was separated by SDS-PAGE and visualized on immunoblots using an anti-His antibody. The first lane of the blot shows the molecular weight markers (M) in kilodaltons (kDa), while the second lane shows the control experiment, which lacked an NF-κB but contained all other co-immunoprecipitation components. Note that Cactus was not captured in the control experiment but was captured when recombinant Dif, Dorsal or Relish was present. The absence of Cactus with a 1∶ 1 molar ratio of Cactus∶ Relish suggests a lower affinity for this NF-κB than for Dif or Dorsal homodimers. The background band at ca. 50 kDa is due to the large amount of Protein A from the immunoprecipitation. (B and C) Ank proteins compete with Cactus for binding to recombinant Relish. Recombinant Cactus and Relish were incubated with increasing molar ratios of recombinant Ank-H4 (B) or Ank-N5 (C) followed by immunoprecipitation, SDS-PAGE separation and immunoblotting using an anti-His antibody. The molar ratio of Ank-H4 or Ank-N5 to Cactus is shown below each immunoblot.</p
Polydnavirus Ank Proteins Bind NF-κB Homodimers and Inhibit Processing of Relish
<div><p>Recent studies have greatly increased understanding of how the immune system of insects responds to infection, whereas much less is known about how pathogens subvert immune defenses. Key regulators of the insect immune system are Rel proteins that form Nuclear Factor-κB (NF-κB) transcription factors, and inhibitor κB (IκB) proteins that complex with and regulate NF-κBs. Major mortality agents of insects are parasitoid wasps that carry immunosuppressive polydnaviruses (PDVs). Most PDVs encode ank genes that share features with IκBs, while our own prior studies suggested that two ank family members from <em>Microplitis demolitor</em> bracovirus (MdBV) (Ank-H4 and Ank-N5) behave as IκB mimics. However, the binding affinities of these viral mimics for Rel proteins relative to endogenous IκBs remained unclear. Surface plasmon resonance (SPR) and co-immunoprecipitation assays showed that the IκB Cactus from <em>Drosophila</em> bound Dif and Dorsal homodimers more strongly than Relish homodimers. Ank-H4 and –N5 bound Dif, Dorsal and Relish homodimers with higher affinity than the IκB domain of Relish (Rel-49), and also bound Relish homodimers more strongly than Cactus. Ank-H4 and –N5 inhibited processing of compound Relish and reduced the expression of several antimicrobial peptide genes regulated by the Imd signaling pathway in <em>Drosophila</em> mbn2 cells. Studies conducted in the natural host <em>Pseudoplusia includens</em> suggested that parasitism by <em>M. demolitor</em> also activates NF-κB signaling and that MdBV inhibits this response. Overall, our data provide the first quantitative measures of insect and viral IκB binding affinities, while also showing that viral mimics disable Relish processing.</p> </div
Kinetic titration sensorgrams of NF-κB/IκB interactions.
<p>Each recombinant Rel protein homodimer was injected sequentially over a surface with immobilized Cactus, Rel-49, Ank-H4, or Ank-N5 for 60 or 90 s at a flow rate of 30 µL per min, with a 120 s dissociation phase between injections. The concentration of NF-κB was doubled each injection. The sensorgram represents the response units (RU) from the blank-subtracted IκB coated surface (ordinate) with respect to time in seconds (abscisa). The dark lines represent the experimental data and the red lines represent the fit to a simple 1∶1 interaction model. See <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1002722#ppat-1002722-t001" target="_blank">Table 1</a> for the association rate constants (ka), dissociation rate constants (kd), and equilibrium dissociation constants (Kd) in decreasing order of affinity.</p
rqRT-PCR analysis of the AMP genes <i>cecropin</i> and <i>lebocin</i> in <i>P. includens</i> fat body.
<p><i>P. includens</i> fifth instars were immune challenged with sterile PBS (Control) or heat-killed bacteria in sterile PBS (Bacteria), or were infected first with a physiological dose of MdBV followed 12 h later by injection of heat-killed bacteria (MdBV+Bacteria). Total RNA was then isolated from the fat body of each larva at 0, 8 and 24 h post-immune challenge with sterile PBS or bacteria. The 0 h Control sample was standardized to a value of 1. Transcript abundance for the other treatments and time points were then expressed relative to the 0 h Control. Each treatment and time point was measured three times using independently transfected samples. Error bars indicate ± SE. Different letters above a given bar indicates that transcript abundance significantly differs.</p