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Currently many of the time resolved serial femtosecond (SFX) crystallography experiments are done with light driven protein systems, whereas the reaction initiation for non-light triggered enzymes remains a major bottle neck. Here, the authors present an expanded Drop-on-Tape system, where picoliter-sized droplets of a substrate or inhibitor are turbulently mixed with nanoliter sized droplets of microcrystal slurries, and they use it for time-resolved SFX measurements of inhibitor binding to lysozyme and secondly, binding of a β-lactam antibiotic to a bacterial serine β-lactamase.

ABSTRACT β-Lactamases hydrolyze β-lactam antibiotics and are major determinants of antibiotic resistance in Gram-negative pathogens. Enmetazobactam (formerly AAI101) and tazobactam are penicillanic acid sulfone (PAS) β-lactamase inhibitors that differ by an additional methyl group on the triazole ring of enmetazobactam, rendering it zwitterionic. In this study, ultrahigh-resolution X-ray crystal structures and mass spectrometry revealed the mechanism of PAS inhibition of CTX-M-15, an extended-spectrum β-lactamase (ESBL) globally disseminated among Enterobacterales. CTX-M-15 crystals grown in the presence of enmetazobactam or tazobactam revealed loss of the Ser70 hydroxyl group and formation of a lysinoalanine cross-link between Lys73 and Ser70, two residues critical for catalysis. Moreover, the residue at position 70 undergoes epimerization, resulting in formation of a d-amino acid. Cocrystallization of enmetazobactam or tazobactam with CTX-M-15 with a Glu166Gln mutant revealed the same cross-link, indicating that this modification is not dependent on Glu166-catalyzed deacylation of the PAS-acylenzyme. A cocrystal structure of enmetazobactam with CTX-M-15 with a Lys73Ala mutation indicates that epimerization can occur without cross-link formation and positions the Ser70 Cβ closer to Lys73, likely facilitating formation of the Ser70-Lys73 cross-link. A crystal structure of a tazobactam-derived imine intermediate covalently linked to Ser70, obtained after 30 min of exposure of CTX-M-15 crystals to tazobactam, supports formation of an initial acylenzyme by PAS inhibitors on reaction with CTX-M-15. These data rationalize earlier results showing CTX-M-15 deactivation by PAS inhibitors to involve loss of protein mass, and they identify a distinct mechanism of β-lactamase inhibition by these agents. IMPORTANCE β-Lactams are the most prescribed antibiotic class for treating bacterial diseases, but their continued efficacy is threatened by bacterial strains producing β-lactamase enzymes that catalyze their inactivation. The CTX-M family of ESBLs are major contributors to β-lactam resistance in Enterobacterales, preventing effective treatment with most penicillins and cephalosporins. Combining β-lactams with β-lactamase inhibitors (BLIs) is a validated route to overcome such resistance. Here, we describe how exposure to enmetazobactam and tazobactam, BLIs based on a penicillanic acid sulfone (PAS) scaffold, leads to a protein modification in CTX-M-15, resulting in irremediable inactivation of this most commonly encountered member of the CTX-M family. High-resolution X-ray crystal structures showed that PAS exposure induces formation of a cross-link between Ser70 and Lys73, two residues critical to β-lactamase function. This previously undescribed mechanism of inhibition furthers our understanding of β-lactamase inhibition by classical PAS inhibitors and provides a basis for further, rational inhibitor development.

The highly conserved, ubiquitous molecular chaperone Hsp90 is a key regulator of cellular proteostasis and environmental stress responses. In human pathogenic fungi, which kill more than 1.6 million patients each year worldwide, Hsp90 governs cellular morphogenesis, drug resistance, and virulence. Yet, our understanding of the regulatory mechanisms governing fungal Hsp90 function remains sparse. Post-translational modifications are powerful components of nature’s toolbox to regulate protein abundance and function. Phosphorylation in particular is critical in many cellular signaling pathways and errant phosphorylation can have dire consequences for the cell. In the case of Hsp90, phosphorylation affects its stability and governs its interactions with co-chaperones and clients. Thereby modulating the cell’s ability to cope with environmental stress. Candida albicans, one of the leading human fungal pathogens, causes ~750,000 life-threatening invasive infections worldwide with unacceptably high mortality rates. Yet, it remains unknown if and how Hsp90 phosphorylation affects C. albicans virulence traits. Here, we show that phosphorylation of Hsp90 is critical for expression of virulence traits. We combined proteomics, molecular evolution analyses and structural modeling with molecular biology to characterize the role of Hsp90 phosphorylation in this non-model pathogen. We demonstrated that phosphorylation negatively affects key virulence traits, such as the thermal stress response, morphogenesis, and drug susceptibility. Our results provide the first record of a specific Hsp90 phosphorylation site acting as modulator of fungal virulence. Post-translational modifications of Hsp90 could prove valuable in future exploitations as antifungal drug targets.

Understanding allostery in enzymes and tools to identify it offer promising alternative strategies to inhibitor development. Through a combination of equilibrium and nonequilibrium molecular dynamics simulations, we identify allosteric effects and communication pathways in two prototypical class A β-lactamases, TEM-1 and KPC-2, which are important determinants of antibiotic resistance. The nonequilibrium simulations reveal pathways of communication operating over distances of 30 Å or more. Propagation of the signal occurs through cooperative coupling of loop dynamics. Notably, 50% or more of clinically relevant amino acid substitutions map onto the identified signal transduction pathways. This suggests that clinically important variation may affect, or be driven by, differences in allosteric behavior, providing a mechanism by which amino acid substitutions may affect the relationship between spectrum of activity, catalytic turnover, and potential allosteric behavior in this clinically important enzyme family. Simulations of the type presented here will help in identifying and analyzing such differences.

Carbapenems are important antibacterials and are both substrates and inhibitors of some β-lactamases. We report studies on the reaction of the unusual carbapenem biapenem, with the subclass B1 metallo-β-lactamases VIM-1 and VIM-2 and the class A serine-β-lactamase KPC-2. X-ray diffraction studies with VIM-2 crystals treated with biapenem reveal the opening of the β-lactam ring to form a mixture of the (2S)-imine and enamine complexed at the active site. NMR studies on the reactions of biapenem with VIM-1, VIM-2, and KPC-2 reveal the formation of hydrolysed enamine and (2R)- and (2S)-imine products. The combined results support the proposal that SBL/MBL-mediated carbapenem hydrolysis results in a mixture of tautomerizing enamine and (2R)- and (2S)-imine products, with the thermodynamically favoured (2S)-imine being the major observed species over a relatively long-time scale. The results suggest that prolonging the lifetimes of β-lactamase carbapenem complexes by optimising tautomerisation of the nascently formed enamine to the (2R)-imine and likely more stable (2S)-imine tautomer is of interest in developing improved carbapenems.

Methylated RNA bases influence many life processes, but current detection methods lack the ability to detect individual methylations in single cells. Here, the authors use fluorescence hybridization probes sensitive to methylation to detect specific epitranscriptomic modifications at the single-cell level.

The plasmid-encoded MCR-1 enzyme modifies bacterial lipid A, thus conferring resistance to the antibiotic colistin. Here, Yang et al. show that MCR-1 expression can decrease in vitro growth rate, fitness and immune stimulation, and can reduce virulence in a Galleria mellonella infection model.

[This corrects the article DOI: 10.1016/j.heliyon.2022.e09898.].

Carbapenem-resistant bacteria pose a major health threat by expressing metallo-β-lactamases (MβLs), enzymes able to hydrolyse these life-saving drugs. Here the authors use biophysical and computational methods and show that different MβLs share the same reaction mechanism, suggesting new strategies for drug design.

Bacterial beta-lactamases are responsible for resistance to beta-lactams, the most important family of antibiotics. Here, the authors reveal cyclic boronate inhibitors that are active against both serine- and metallo-beta-lactamases and represent a promising strategy for combined antimicrobial treatments.

The deep ocean is the largest habitat for life on Earth, though the microorganisms that occupy this unique environmental niche remain largely unexplored. Due to the significant logistical and operational challenges associated with accessing the deep ocean, bioprospecting programmes that seek to generate novel products from marine organisms have, to date, focused predominantly on samples recovered from shallow seas. For this reason, the deep ocean remains a largely untapped resource of novel microbiological life and associated natural products. Here we report the establishment of the Bristol Sponge Microbiome Collection (BISECT), a unique repository of deep-sea microorganisms and associated metabolites isolated from the microbiota of marine sponges, recovered from previously unsurveyed regions of the mid Atlantic Ocean, at depths of 0.3–3 km. An integrated biodiscovery pipeline comprising molecular, genetic, bioinformatic and analytical tools is also described, which is being applied to interrogate this collection. The potential of this approach is illustrated using data reporting our initial efforts to identify antimicrobial natural product lead compounds. Prospects for the use of BISECT to address allied pharmaceutical needs, along with mechanisms of access to the collection are also discussed

The khmer package is a freely available software library for working efficiently with fixed length DNA words, or k-mers. khmer provides implementations of a probabilistic k-mer counting data structure, a compressible De Bruijn graph representation, De Bruijn graph partitioning, and digital normalization. khmer is implemented in C++ and Python, and is freely available under the BSD license at https://github.com/dib-lab/khmer/.

Metallo-β-lactamases (MBLs) hydrolyze almost all classes of β-lactam antibiotic, including carbapenems-currently first choice drugs for opportunistic infections by Gram-negative bacterial pathogens. MBL inhibitor development is complicated by the diversity within this group of enzymes, and by the appearance of new enzymes that continue to be identified both as chromosomal genes and on mobile genetic elements. One such newly discovered MBL is DIM-1, a mobile enzyme originally discovered in the opportunist pathogen Pseudomonas stutzeri but subsequently identified in other species and locations. DIM-1 is a subclass B1 MBL more closely related to the TMB-1, GIM-1 and IMP enzymes than to other clinically encountered MBLs such as VIM and NDM; and possesses Arg, rather than the more usual Lys, at position 224 in the putative substrate binding site. Here we report the crystallization and structure determination of DIM-1. DIM-1 possesses a binuclear metal center with a 5 (rather than the more usual 4) co-ordinate tri-histidine (Zn1) site and both 4- and 5-co-ordinate Cys-His-Asp- (Zn2) sites observed in the two molecules of the crystallographic asymmetric unit. These data indicate a degree of variability in metal co-ordination geometry in the DIM-1 active site, as well as facilitating inclusion of DIM-1 in structure-based MBL inhibitor discovery programmes.

The 'radical S-adenosyl-L-methionine (AdoMet)' enzyme Cfr methylates adenosine 2503 of the 23S rRNA in the peptidyltransferase centre (P-site) of the bacterial ribosome. This modification protects host bacteria, notably methicillin-resistant Staphylococcus aureus (MRSA), from numerous antibiotics, including agents (e.g. linezolid, retapamulin) that were developed to treat such organisms. Cfr contains a single [4Fe-4S] cluster that binds two separate molecules of AdoMet during the reaction cycle. These are used sequentially to first methylate a cysteine residue, Cys338; and subsequently generate an oxidative radical intermediate that facilitates methyl transfer to the unreactive C8 (and/or C2) carbon centres of adenosine 2503. How the Cfr active site, with its single [4Fe-4S] cluster, catalyses these two distinct activities that each utilise AdoMet as a substrate remains to be established. Here, we use absorbance and electron paramagnetic resonance (EPR) spectroscopy to investigate the interactions of AdoMet with the [4Fe-4S] clusters of wild-type Cfr and a Cys338 Ala mutant, which is unable to accept a methyl group. Cfr binds AdoMet with high (∼ 10 µM) affinity notwithstanding the absence of the RNA cosubstrate. In wild-type Cfr, where Cys338 is methylated, AdoMet binding leads to rapid oxidation of the [4Fe-4S] cluster and production of 5'-deoxyadenosine (DOA). In contrast, while Cys338 Ala Cfr binds AdoMet with equivalent affinity, oxidation of the [4Fe-4S] cluster is not observed. Our results indicate that the presence of a methyl group on Cfr Cys338 is a key determinant of the activity of the enzyme towards AdoMet, thus enabling a single active site to support two distinct modes of AdoMet cleavage.

This study examines associations between media use and mental health for adolescents prior to and during the COVID-19 pandemic. Using two separate datasets that sampled adolescents (8th, 10th, and 12th graders) in 2018 (n = 31,825) and 2020 (n = 1,523), mental health (hopelessness and happiness), media use (time spent using a variety of media), and personal health habits (sleep) were assessed. Overall, we found that there were significant differences by year in adolescent hopelessness, with adolescents reporting less hopelessness in 2020 (during COVID-19) than in 2018 (pre COVID-19). There were not ​practical significant differences in adolescent happiness and loneliness. Adolescents also reported getting more sleep in our 2020 sample than the 2018 sample. Adolescents in 2020 spent significantly more time watching movies and video chatting, but less time texting and on social media than adolescents in 2018. Finally, we found that time spent video chatting and sleep had a different relationship with various aspects of mental health (happiness, hopelessness, or loneliness) in 2018 vs. 2020.

This article arises from a research study that aimed to contribute to a better understanding of the essential nature of collaborative relationships between English as an Additional Language (EAL) and mainstream subject teachers at an international secondary school in Ukraine. The research focuses on how EAL teachers support EAL learners in the mainstream classroom through collaborative practices. The article draws on qualitative data from interviews and field notes with Language & Literature, Science and EAL teachers. The interviews investigated how EAL and mainstream collaboration help support EAL learners in the mainstream classroom, and which co-planning strategies most effectively encourage collaboration, as well as EAL and mainstream teachers' views and experiences about co-planning and working collaboratively. Arising from these data, discussion focuses on the disconnect between collaboration in theory and in practice. The article concludes that although effective collaborative strategies often exist, school language policies need to include scheduled collaborative planning time between EAL and the mainstream, and that professional development for mainstream teachers should be led by EAL teachers in order to foster more balanced content and language classroom teaching.

Abstract Background Income has been extensively studied and utilized as a determinant of health. There are several sources of income expressed as gross domestic product (GDP) per capita, but there are no time series that are complete for the years between 1950 and 2015 for the 210 countries for which data exist. It is in the interest of population health research to establish a global time series that is complete from 1950 to 2015. Methods We collected GDP per capita estimates expressed in either constant US dollar terms or international dollar terms (corrected for purchasing power parity) from seven sources. We applied several stages of models, including ordinary least-squares regressions and mixed effects models, to complete each of the seven source series from 1950 to 2015. The three US dollar and four international dollar series were each averaged to produce two new GDP per capita series. Results and discussion Nine complete series from 1950 to 2015 for 210 countries are available for use. These series can serve various analytical purposes and can illustrate myriad economic trends and features. The derivation of the two new series allows for researchers to avoid any series-specific biases that may exist. The modeling approach used is flexible and will allow for yearly updating as new estimates are produced by the source series. Conclusion GDP per capita is a necessary tool in population health research, and our development and implementation of a new method has allowed for the most comprehensive known time series to date.

Abstract Background InterVA is a widely disseminated tool for cause of death attribution using information from verbal autopsies. Several studies have attempted to validate the concordance and accuracy of the tool, but the main limitation of these studies is that they compare cause of death as ascertained through hospital record review or hospital discharge diagnosis with the results of InterVA. This study provides a unique opportunity to assess the performance of InterVA compared to physician-certified verbal autopsies (PCVA) and alternative automated methods for analysis. Methods Using clinical diagnostic gold standards to select 12,542 verbal autopsy cases, we assessed the performance of InterVA on both an individual and population level and compared the results to PCVA, conducting analyses separately for adults, children, and neonates. Following the recommendation of Murray et al., we randomly varied the cause composition over 500 test datasets to understand the performance of the tool in different settings. We also contrasted InterVA with an alternative Bayesian method, Simplified Symptom Pattern (SSP), to understand the strengths and weaknesses of the tool. Results Across all age groups, InterVA performs worse than PCVA, both on an individual and population level. On an individual level, InterVA achieved a chance-corrected concordance of 24.2% for adults, 24.9% for children, and 6.3% for neonates (excluding free text, considering one cause selection). On a population level, InterVA achieved a cause-specific mortality fraction accuracy of 0.546 for adults, 0.504 for children, and 0.404 for neonates. The comparison to SSP revealed four specific characteristics that lead to superior performance of SSP. Increases in chance-corrected concordance are attained by developing cause-by-cause models (2%), using all items as opposed to only the ones that mapped to InterVA items (7%), assigning probabilities to clusters of symptoms (6%), and using empirical as opposed to expert probabilities (up to 8%). Conclusions Given the widespread use of verbal autopsy for understanding the burden of disease and for setting health intervention priorities in areas that lack reliable vital registrations systems, accurate analysis of verbal autopsies is essential. While InterVA is an affordable and available mechanism for assigning causes of death using verbal autopsies, users should be aware of its suboptimal performance relative to other methods.

Abstract Background Verbal autopsy can be a useful tool for generating cause of death data in data-sparse regions around the world. The Symptom Pattern (SP) Method is one promising approach to analyzing verbal autopsy data, but it has not been tested rigorously with gold standard diagnostic criteria. We propose a simplified version of SP and evaluate its performance using verbal autopsy data with accompanying true cause of death. Methods We investigated specific parameters in SP's Bayesian framework that allow for its optimal performance in both assigning individual cause of death and in determining cause-specific mortality fractions. We evaluated these outcomes of the method separately for adult, child, and neonatal verbal autopsies in 500 different population constructs of verbal autopsy data to analyze its ability in various settings. Results We determined that a modified, simpler version of Symptom Pattern (termed Simplified Symptom Pattern, or SSP) performs better than the previously-developed approach. Across 500 samples of verbal autopsy testing data, SSP achieves a median cause-specific mortality fraction accuracy of 0.710 for adults, 0.739 for children, and 0.751 for neonates. In individual cause of death assignment in the same testing environment, SSP achieves 45.8% chance-corrected concordance for adults, 51.5% for children, and 32.5% for neonates. Conclusions The Simplified Symptom Pattern Method for verbal autopsy can yield reliable and reasonably accurate results for both individual cause of death assignment and for determining cause-specific mortality fractions. The method demonstrates that verbal autopsies coupled with SSP can be a useful tool for analyzing mortality patterns and determining individual cause of death from verbal autopsy data.

Abstract Background Computer-coded verbal autopsy (CCVA) is a promising alternative to the standard approach of physician-certified verbal autopsy (PCVA), because of its high speed, low cost, and reliability. This study introduces a new CCVA technique and validates its performance using defined clinical diagnostic criteria as a gold standard for a multisite sample of 12,542 verbal autopsies (VAs). Methods The Random Forest (RF) Method from machine learning (ML) was adapted to predict cause of death by training random forests to distinguish between each pair of causes, and then combining the results through a novel ranking technique. We assessed quality of the new method at the individual level using chance-corrected concordance and at the population level using cause-specific mortality fraction (CSMF) accuracy as well as linear regression. We also compared the quality of RF to PCVA for all of these metrics. We performed this analysis separately for adult, child, and neonatal VAs. We also assessed the variation in performance with and without household recall of health care experience (HCE). Results For all metrics, for all settings, RF was as good as or better than PCVA, with the exception of a nonsignificantly lower CSMF accuracy for neonates with HCE information. With HCE, the chance-corrected concordance of RF was 3.4 percentage points higher for adults, 3.2 percentage points higher for children, and 1.6 percentage points higher for neonates. The CSMF accuracy was 0.097 higher for adults, 0.097 higher for children, and 0.007 lower for neonates. Without HCE, the chance-corrected concordance of RF was 8.1 percentage points higher than PCVA for adults, 10.2 percentage points higher for children, and 5.9 percentage points higher for neonates. The CSMF accuracy was higher for RF by 0.102 for adults, 0.131 for children, and 0.025 for neonates. Conclusions We found that our RF Method outperformed the PCVA method in terms of chance-corrected concordance and CSMF accuracy for adult and child VA with and without HCE and for neonatal VA without HCE. It is also preferable to PCVA in terms of time and cost. Therefore, we recommend it as the technique of choice for analyzing past and current verbal autopsies.

Abstract Background Verbal autopsy (VA) is used to estimate the causes of death in areas with incomplete vital registration systems. The King and Lu method (KL) for direct estimation of cause-specific mortality fractions (CSMFs) from VA studies is an analysis technique that estimates CSMFs in a population without predicting individual-level cause of death as an intermediate step. In previous studies, KL has shown promise as an alternative to physician-certified verbal autopsy (PCVA). However, it has previously been impossible to validate KL with a large dataset of VAs for which the underlying cause of death is known to meet rigorous clinical diagnostic criteria. Methods We applied the KL method to adult, child, and neonatal VA datasets from the Population Health Metrics Research Consortium gold standard verbal autopsy validation study, a multisite sample of 12,542 VAs where gold standard cause of death was established using strict clinical diagnostic criteria. To emulate real-world populations with varying CSMFs, we evaluated the KL estimations for 500 different test datasets of varying cause distribution. We assessed the quality of these estimates in terms of CSMF accuracy as well as linear regression and compared this with the results of PCVA. Results KL performance is similar to PCVA in terms of CSMF accuracy, attaining values of 0.669, 0.698, and 0.795 for adult, child, and neonatal age groups, respectively, when health care experience (HCE) items were included. We found that the length of the cause list has a dramatic effect on KL estimation quality, with CSMF accuracy decreasing substantially as the length of the cause list increases. We found that KL is not reliant on HCE the way PCVA is, and without HCE, KL outperforms PCVA for all age groups. Conclusions Like all computer methods for VA analysis, KL is faster and cheaper than PCVA. Since it is a direct estimation technique, though, it does not produce individual-level predictions. KL estimates are of similar quality to PCVA and slightly better in most cases. Compared to other recently developed methods, however, KL would only be the preferred technique when the cause list is short and individual-level predictions are not needed.

Abstract Background Verbal autopsies provide valuable information for studying mortality patterns in populations that lack reliable vital registration data. Methods for transforming verbal autopsy results into meaningful information for health workers and policymakers, however, are often costly or complicated to use. We present a simple additive algorithm, the Tariff Method (termed Tariff), which can be used for assigning individual cause of death and for determining cause-specific mortality fractions (CSMFs) from verbal autopsy data. Methods Tariff calculates a score, or "tariff," for each cause, for each sign/symptom, across a pool of validated verbal autopsy data. The tariffs are summed for a given response pattern in a verbal autopsy, and this sum (score) provides the basis for predicting the cause of death in a dataset. We implemented this algorithm and evaluated the method's predictive ability, both in terms of chance-corrected concordance at the individual cause assignment level and in terms of CSMF accuracy at the population level. The analysis was conducted separately for adult, child, and neonatal verbal autopsies across 500 pairs of train-test validation verbal autopsy data. Results Tariff is capable of outperforming physician-certified verbal autopsy in most cases. In terms of chance-corrected concordance, the method achieves 44.5% in adults, 39% in children, and 23.9% in neonates. CSMF accuracy was 0.745 in adults, 0.709 in children, and 0.679 in neonates. Conclusions Verbal autopsies can be an efficient means of obtaining cause of death data, and Tariff provides an intuitive, reliable method for generating individual cause assignment and CSMFs. The method is transparent and flexible and can be readily implemented by users without training in statistics or computer science.

In this article we demonstrate the net acceleration of relativistic electrons using a direct, in-vacuum interaction with a laser. In the experiment, an electron beam from a conventional accelerator is first energy modulated at optical frequencies in an inverse-free-electron-laser and bunched in a chicane. This is followed by a second stage optical accelerator to obtain net acceleration. The optical phase between accelerator stages is monitored and controlled in order to scan the accelerating phase and observe net acceleration and deceleration. Phase jitter measurements indicate control of the phase to ∼13° allowing for stable net acceleration of electrons with lasers.

We report the production of optically spaced attosecond electron microbunches produced by the inverse free-electron-laser (IFEL) process. The IFEL is driven by a Ti:sapphire laser synchronized with the electron beam. The IFEL is followed by a magnetic chicane that converts the energy modulation into the longitudinal microbunch structure. The microbunch train is characterized by observing coherent optical transition radiation (COTR) at multiple harmonics of the bunching. Experimental results are compared with 1D analytic theory showing good agreement. Estimates of the bunching factors are given and correspond to a microbunch length of 410 attosec FWHM. The formation of stable attosecond electron pulse trains marks an important step towards direct laser acceleration.

BackgroundAccurate childhood cancer burden data are crucial for resource planning and health policy prioritisation. Model-based estimates are necessary because cancer surveillance data are scarce or non-existent in many countries. Although global incidence and mortality estimates are available, there are no previous analyses of the global burden of childhood cancer represented in disability-adjusted life-years (DALYs).MethodsUsing the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 methodology, childhood (ages 0-19 years) cancer mortality was estimated by use of vital registration system data, verbal autopsy data, and population-based cancer registry incidence data, which were transformed to mortality estimates through modelled mortality-to-incidence ratios (MIRs). Childhood cancer incidence was estimated using the mortality estimates and corresponding MIRs. Prevalence estimates were calculated by using MIR to model survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated by multiplying age-specific cancer deaths by the difference between the age of death and a reference life expectancy. DALYs were calculated as the sum of YLLs and YLDs. Final point estimates are reported with 95% uncertainty intervals.FindingsGlobally, in 2017, there were 11·5 million (95% uncertainty interval 10·6-12·3) DALYs due to childhood cancer, 97·3% (97·3-97·3) of which were attributable to YLLs and 2·7% (2·7-2·7) of which were attributable to YLDs. Childhood cancer was the sixth leading cause of total cancer burden globally and the ninth leading cause of childhood disease burden globally. 82·2% (82·1-82·2) of global childhood cancer DALYs occurred in low, low-middle, or middle Socio-demographic Index locations, whereas 50·3% (50·3-50·3) of adult cancer DALYs occurred in these same locations. Cancers that are uncategorised in the current GBD framework comprised 26·5% (26·5-26·5) of global childhood cancer DALYs.InterpretationThe GBD 2017 results call attention to the substantial burden of childhood cancer globally, which disproportionately affects populations in resource-limited settings. The use of DALY-based estimates is crucial in demonstrating that childhood cancer burden represents an important global cancer and child health concern.FundingBill & Melinda Gates Foundation, American Lebanese Syrian Associated Charities (ALSAC), and St. Baldrick's Foundation.

BackgroundNeurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders.MethodsWe estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach.FindingsGlobally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247-308]) and second leading cause of deaths (9·0 million [8·8-9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34-44] and DALYs by 15% [9-21]) whereas their age-standardised rates decreased (deaths by 28% [26-30] and DALYs by 27% [24-31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6-46·1]), migraine (16·3% [11·7-20·8]), Alzheimer's and other dementias (10·4% [9·0-12·1]), and meningitis (7·9% [6·6-10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05-1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5-90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8-35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8-17·5] of DALYs are risk attributable).InterpretationGlobally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies.FundingBill & Melinda Gates Foundation.

BackgroundThe lifetime risk of stroke has been calculated in a limited number of selected populations. We sought to estimate the lifetime risk of stroke at the regional, country, and global level using data from a comprehensive study of the prevalence of major diseases.MethodsWe used the Global Burden of Disease (GBD) Study 2016 estimates of stroke incidence and the competing risks of death from any cause other than stroke to calculate the cumulative lifetime risks of first stroke, ischemic stroke, or hemorrhagic stroke among adults 25 years of age or older. Estimates of the lifetime risks in the years 1990 and 2016 were compared. Countries were categorized into quintiles of the sociodemographic index (SDI) used in the GBD Study, and the risks were compared across quintiles. Comparisons were made with the use of point estimates and uncertainty intervals representing the 2.5th and 97.5th percentiles around the estimate.ResultsThe estimated global lifetime risk of stroke from the age of 25 years onward was 24.9% (95% uncertainty interval, 23.5 to 26.2); the risk among men was 24.7% (95% uncertainty interval, 23.3 to 26.0), and the risk among women was 25.1% (95% uncertainty interval, 23.7 to 26.5). The risk of ischemic stroke was 18.3%, and the risk of hemorrhagic stroke was 8.2%. In high-SDI, high-middle-SDI, and low-SDI countries, the estimated lifetime risk of stroke was 23.5%, 31.1% (highest risk), and 13.2% (lowest risk), respectively; the 95% uncertainty intervals did not overlap between these categories. The highest estimated lifetime risks of stroke according to GBD region were in East Asia (38.8%), Central Europe (31.7%), and Eastern Europe (31.6%), and the lowest risk was in eastern sub-Saharan Africa (11.8%). The mean global lifetime risk of stroke increased from 22.8% in 1990 to 24.9% in 2016, a relative increase of 8.9% (95% uncertainty interval, 6.2 to 11.5); the competing risk of death from any cause other than stroke was considered in this calculation.ConclusionsIn 2016, the global lifetime risk of stroke from the age of 25 years onward was approximately 25% among both men and women. There was geographic variation in the lifetime risk of stroke, with the highest risks in East Asia, Central Europe, and Eastern Europe. (Funded by the Bill and Melinda Gates Foundation.).

BackgroundThe lifetime risk of stroke has been calculated in a limited number of selected populations. We sought to estimate the lifetime risk of stroke at the regional, country, and global level using data from a comprehensive study of the prevalence of major diseases.MethodsWe used the Global Burden of Disease (GBD) Study 2016 estimates of stroke incidence and the competing risks of death from any cause other than stroke to calculate the cumulative lifetime risks of first stroke, ischemic stroke, or hemorrhagic stroke among adults 25 years of age or older. Estimates of the lifetime risks in the years 1990 and 2016 were compared. Countries were categorized into quintiles of the sociodemographic index (SDI) used in the GBD Study, and the risks were compared across quintiles. Comparisons were made with the use of point estimates and uncertainty intervals representing the 2.5th and 97.5th percentiles around the estimate.ResultsThe estimated global lifetime risk of stroke from the age of 25 years onward was 24.9% (95% uncertainty interval, 23.5 to 26.2); the risk among men was 24.7% (95% uncertainty interval, 23.3 to 26.0), and the risk among women was 25.1% (95% uncertainty interval, 23.7 to 26.5). The risk of ischemic stroke was 18.3%, and the risk of hemorrhagic stroke was 8.2%. In high-SDI, high-middle-SDI, and low-SDI countries, the estimated lifetime risk of stroke was 23.5%, 31.1% (highest risk), and 13.2% (lowest risk), respectively; the 95% uncertainty intervals did not overlap between these categories. The highest estimated lifetime risks of stroke according to GBD region were in East Asia (38.8%), Central Europe (31.7%), and Eastern Europe (31.6%), and the lowest risk was in eastern sub-Saharan Africa (11.8%). The mean global lifetime risk of stroke increased from 22.8% in 1990 to 24.9% in 2016, a relative increase of 8.9% (95% uncertainty interval, 6.2 to 11.5); the competing risk of death from any cause other than stroke was considered in this calculation.ConclusionsIn 2016, the global lifetime risk of stroke from the age of 25 years onward was approximately 25% among both men and women. There was geographic variation in the lifetime risk of stroke, with the highest risks in East Asia, Central Europe, and Eastern Europe. (Funded by the Bill and Melinda Gates Foundation.).

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BackgroundThe Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data.MethodsWe estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting.FindingsGlobally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 3·9% (95% uncertainty interval [UI] 3·1-4·6) from 1990 to 2017; however, the all-age YLD rate increased by 7·2% (6·0-8·4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7·9% (6·6-9·2) for males and 6·5% (5·4-7·7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs s1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-harm and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]).InterpretationGlobal all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury.FundingBill & Melinda Gates Foundation.

BackgroundThe burden of cardiovascular diseases (CVDs) remains unclear in many regions of the world.ObjectivesThe GBD (Global Burden of Disease) 2015 study integrated data on disease incidence, prevalence, and mortality to produce consistent, up-to-date estimates for cardiovascular burden.MethodsCVD mortality was estimated from vital registration and verbal autopsy data. CVD prevalence was estimated using modeling software and data from health surveys, prospective cohorts, health system administrative data, and registries. Years lived with disability (YLD) were estimated by multiplying prevalence by disability weights. Years of life lost (YLL) were estimated by multiplying age-specific CVD deaths by a reference life expectancy. A sociodemographic index (SDI) was created for each location based on income per capita, educational attainment, and fertility.ResultsIn 2015, there were an estimated 422.7 million cases of CVD (95% uncertainty interval: 415.53 to 427.87 million cases) and 17.92 million CVD deaths (95% uncertainty interval: 17.59 to 18.28 million CVD deaths). Declines in the age-standardized CVD death rate occurred between 1990 and 2015 in all high-income and some middle-income countries. Ischemic heart disease was the leading cause of CVD health lost globally, as well as in each world region, followed by stroke. As SDI increased beyond 0.25, the highest CVD mortality shifted from women to men. CVD mortality decreased sharply for both sexes in countries with an SDI >0.75.ConclusionsCVDs remain a major cause of health loss for all regions of the world. Sociodemographic change over the past 25 years has been associated with dramatic declines in CVD in regions with very high SDI, but only a gradual decrease or no change in most regions. Future updates of the GBD study can be used to guide policymakers who are focused on reducing the overall burden of noncommunicable disease and achieving specific global health targets for CVD.