Exploring the "Urban Advantage" in Access to Immunization Services: A Comparison of Zero-Dose Prevalence Between Rural, and Poor and Non-poor Urban Households Across 97 Low- and Middle-Income Countries.

Urban children are more likely to be vaccinated than rural children, but that advantage is not evenly distributed. Children living in poor urban areas face unique challenges, living far from health facilities and with lower-quality health services, which can impact their access to life-saving vaccines. Our goal was to compare the prevalence of zero-dose children in poor and non-poor urban and rural areas of low- and middle-income countries (LMICs). Zero-dose children were those who failed to receive any dose of a diphtheria-pertussis-tetanus (DPT) containing vaccine. We used data from nationally representative household surveys of 97 LMICs to investigate 201,283 children aged 12-23 months. The pooled prevalence of zero-dose children was 6.5% among the urban non-poor, 12.6% for the urban poor, and 14.7% for the rural areas. There were significant differences between these areas in 43 countries. In most of these countries, the non-poor urban children were at an advantage compared to the urban poor, who were still better off or similar to rural children. Our results emphasize the inequalities between urban and rural areas, but also within urban areas, highlighting the challenges faced by poor urban and rural children. Outreach programs and community interventions that can reach poor urban and rural communities-along with strengthening of current vaccination programs and services-are important steps to reduce inequalities and ensure that no child is left unvaccinated.

Lumbar spine intervertebral disc desiccation is associated with medical comorbidities linked to systemic inflammation.

INTRODUCTION: Symptomatic disc degeneration is a common cause of low back pain. Recently, the prevalence of low back pain has swiftly risen leading to increased patient disability and loss of work. The increase in back pain also coincides with a rapid rise in patient medical comorbidities. However, a comprehensive study evaluating a link between patient's medical comorbidities and their influence on lumbar intervertebral disc morphology is lacking in the literature. METHODS: Electronic medical records (EMR) were retrospectively reviewed to determine patient-specific medical characteristics. Magnetic resonance imaging (MRI) was evaluated for lumbar spine intervertebral disc desiccation and height loss according to the Griffith-modified Pfirrmann grading system. Bivariate and multivariable linear regression analyses assessed strength of associations between patient characteristics and lumbar spine Pfirrmann grade severity (Pfirrmann grade of the most affected lumbar spine intervertebral disc) and cumulative grades (summed Pfirrmann grades for all lumbar spine intervertebral discs). RESULTS: In total, 605 patients (304 diabetics and 301 non-diabetics) met inclusion criteria. Bivariate analysis identified older age, diabetes, American Society of Anesthesiologists (ASA) class, hypertension, chronic obstructive pulmonary disease (COPD), peripheral vascular disease, and hypothyroidism as being strongly associated with an increasing cumulative Pfirrmann grades. Multivariable models similarly found an association linking increased cumulative Pfirrmann grades with diabetes, hypothyroidism, and hypertension, while additionally identifying non-white race, heart disease, and previous lumbar surgery. Chronic pain, depression, and obstructive sleep apnea (OSA) were associated with increased Pfirrmann grades at the most affected level without an increase in cumulative Pfirrmann scores. Glucose control was not associated with increasing severity or cumulative Pfirrmann scores. CONCLUSION: These findings provide specific targets for future studies to elucidate key mechanisms by which patient-specific medical characteristics contribute to the development and progression of lumbar spine disc desiccation and height loss. LEVEL OF EVIDENCE: III (retrospective cohort).

The KH domain facilitates the substrate specificity and unwinding processivity of DDX43 helicase.

The K-homology (KH) domain is a nucleic acid-binding domain present in many proteins. Recently, we found that the DEAD-box helicase DDX43 contains a KH domain in its N-terminus; however, its function remains unknown. Here, we purified recombinant DDX43 KH domain protein and found that it prefers binding ssDNA and ssRNA. Electrophoretic mobility shift assay and NMR revealed that the KH domain favors pyrimidines over purines. Mutational analysis showed that the GXXG loop in the KH domain is involved in pyrimidine binding. Moreover, we found that an alanine residue adjacent to the GXXG loop is critical for binding. Systematic evolution of ligands by exponential enrichment, chromatin immunoprecipitation-seq, and cross-linking immunoprecipitation-seq showed that the KH domain binds C-/T-rich DNA and U-rich RNA. Bioinformatics analysis suggested that the KH domain prefers to bind promoters. Using 15N-heteronuclear single quantum coherence NMR, the optimal binding sequence was identified as TTGT. Finally, we found that the full-length DDX43 helicase prefers DNA or RNA substrates with TTGT or UUGU single-stranded tails and that the KH domain is critically important for sequence specificity and unwinding processivity. Collectively, our results demonstrated that the KH domain facilitates the substrate specificity and processivity of the DDX43 helicase.

Next-generation sequencing-guided identification and reconstruction of antibody CDR combinations from phage selection outputs.

Next-generation sequencing (NGS) technologies have been employed in several phage display platforms for analyzing natural and synthetic antibody sequences and for identifying and reconstructing single-chain variable fragments (scFv) and antigen-binding fragments (Fab) not found by conventional ELISA screens. In this work, we developed an NGS-assisted antibody discovery platform by integrating phage-displayed, single-framework, synthetic Fab libraries. Due to limitations in attainable read and amplicon lengths, NGS analysis of Fab libraries and selection outputs is usually restricted to either VH or VL. Since this information alone is not sufficient for high-throughput reconstruction of Fabs, we developed a rapid and simple method for linking and sequencing all diversified CDRs in phage Fab pools. Our method resulted in a reliable and straightforward platform for converting NGS information into Fab clones. We used our NGS-assisted Fab reconstruction method to recover low-frequency rare clones from phage selection outputs. While previous studies chose rare clones for rescue based on their relative frequencies in sequencing outputs, we chose rare clones for reconstruction from less-frequent CDRH3 lengths. In some cases, reconstructed rare clones (frequency ∼0.1%) showed higher affinity and better specificity than high-frequency top clones identified by Sanger sequencing, highlighting the significance of NGS-based approaches in synthetic antibody discovery.

Associations of clinical and inflammatory biomarker clusters with juvenile idiopathic arthritis categories.

OBJECTIVE: To identify discrete clusters comprising clinical features and inflammatory biomarkers in children with JIA and to determine cluster alignment with JIA categories. METHODS: A Canadian prospective inception cohort comprising 150 children with JIA was evaluated at baseline (visit 1) and after six months (visit 2). Data included clinical manifestations and inflammation-related biomarkers. Probabilistic principal component analysis identified sets of composite variables, or principal components, from 191 original variables. To discern new clinical-biomarker clusters (clusters), Gaussian mixture models were fit to the data. Newly-defined clusters and JIA categories were compared. Agreement between the two was assessed using Kruskal-Wallis analyses and contingency plots. RESULTS: Three principal components recovered 35% (three clusters) and 40% (five clusters) of the variance in patient profiles in visits 1 and 2, respectively. None of the clusters aligned precisely with any of the seven JIA categories but rather spanned multiple categories. Results demonstrated that the newly defined clinical-biomarker lustres are more homogeneous than JIA categories. CONCLUSION: Applying unsupervised data mining to clinical and inflammatory biomarker data discerns discrete clusters that intersect multiple JIA categories. Results suggest that certain groups of patients within different JIA categories are more aligned pathobiologically than their separate clinical categorizations suggest. Applying data mining analyses to complex datasets can generate insights into JIA pathogenesis and could contribute to biologically based refinements in JIA classification.

Clinical and associated inflammatory biomarker features predictive of short-term outcomes in non-systemic juvenile idiopathic arthritis.

OBJECTIVE: To identify early predictors of disease activity at 18 months in JIA using clinical and biomarker profiling. METHODS: Clinical and biomarker data were collected at JIA diagnosis in a prospective longitudinal inception cohort of 82 children with non-systemic JIA, and their ability to predict an active joint count of 0, a physician global assessment of disease activity of ≤1 cm, and inactive disease by Wallace 2004 criteria 18 months later was assessed. Correlation-based feature selection and ReliefF were used to shortlist predictors and random forest models were trained to predict outcomes. RESULTS: From the original 112 features, 13 effectively predicted 18-month outcomes. They included age, number of active/effused joints, wrist, ankle and/or knee involvement, ESR, ANA positivity and plasma levels of five inflammatory biomarkers (IL-10, IL-17, IL-12p70, soluble low-density lipoprotein receptor-related protein 1 and vitamin D), at enrolment. The clinical plus biomarker panel predicted active joint count = 0, physician global assessment ≤ 1, and inactive disease after 18 months with 0.79, 0.80 and 0.83 accuracy and 0.84, 0.83, 0.88 area under the curve, respectively. Using clinical features alone resulted in 0.75, 0.72 and 0.80 accuracy, and area under the curve values of 0.81, 0.78 and 0.83, respectively. CONCLUSION: A panel of five plasma biomarkers combined with clinical features at the time of diagnosis more accurately predicted short-term disease activity in JIA than clinical characteristics alone. If validated in external cohorts, such a panel may guide more rationally conceived, biologically based, personalized treatment strategies in early JIA.

Intraflagellar transport velocity is governed by the number of active KIF17 and KIF3AB motors and their motility properties under load.

Homodimeric KIF17 and heterotrimeric KIF3AB are processive, kinesin-2 family motors that act jointly to carry out anterograde intraflagellar transport (IFT), ferrying cargo along microtubules (MTs) toward the tips of cilia. How IFT trains attain speeds that exceed the unloaded rate of the slower, KIF3AB motor remains unknown. By characterizing the motility properties of kinesin-2 motors as a function of load we find that the increase in KIF3AB velocity, elicited by forward loads from KIF17 motors, cannot alone account for the speed of IFT trains in vivo. Instead, higher IFT velocities arise from an increased likelihood that KIF3AB motors dissociate from the MT, resulting in transport by KIF17 motors alone, unencumbered by opposition from KIF3AB. The rate of transport is therefore set by an equilibrium between a faster state, where only KIF17 motors move the train, and a slower state, where at least one KIF3AB motor on the train remains active in transport. The more frequently the faster state is accessed, the higher the overall velocity of the IFT train. We conclude that IFT velocity is governed by (i) the absolute numbers of each motor type on a given train, (ii) how prone KIF3AB is to dissociation from MTs relative to KIF17, and (iii) how prone both motors are to dissociation relative to binding MTs.

Video-based Education to Reduce Distress and Improve Understanding among Pediatric MRI Patients: A Randomized Controlled Study.

PURPOSE: Evaluate the effectiveness of an educational video vs. standard of care in improving relaxation and procedural understanding among pediatric patients undergoing a magnetic resonance imaging (MRI) procedure. DESIGN AND METHODS: This pilot randomized controlled trial was conducted in a large, urban academic children's hospital. Pediatric patients were randomized to receive either a 7-minute educational video or standard of care. Standardized surveys, which consisted of a 1-10 visual analog scale and open-ended questions were administered to patients to measure their level of relaxation, understanding of the procedure, and perceptions of the MRI education received. Bivariate statistics were used to compare changes in relaxation score and baseline understanding scores between study groups. Open-ended questions were analyzed using content analysis. RESULTS: A total of 50 pediatric patients completed the study. Improvements in relaxation scores and baseline procedural understanding scores were significantly higher among children 13-17 years of age who received the intervention compared to those that did not (P < 0.05). No statistically significant differences were noted in relaxation scores and procedural understanding scores among children < 13 years of age between study groups. A total of 26 patients, half from the control group and half from the intervention group responded to open-ended survey questions. Content analysis revealed that nearly all respondents perceived the educational video to increase their understanding of the MRI procedure. CONCLUSIONS: Video-based education effectively improved the relaxation and procedural understanding of children 13-17 years of age undergoing a MRI. PRACTICE IMPLICATIONS: Nurses may use video-based education to supplement existing MRI education among older children.

Global, regional, and national levels and trends in maternal mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Maternal Mortality Estimation Inter-Agency Group.

BACKGROUND: Millennium Development Goal 5 calls for a 75% reduction in the maternal mortality ratio (MMR) between 1990 and 2015. We estimated levels and trends in maternal mortality for 183 countries to assess progress made. Based on MMR estimates for 2015, we constructed projections to show the requirements for the Sustainable Development Goal (SDG) of less than 70 maternal deaths per 100,000 livebirths globally by 2030. METHODS: We updated the UN Maternal Mortality Estimation Inter-Agency Group (MMEIG) database with more than 200 additional records (vital statistics from civil registration systems, surveys, studies, or reports). We generated estimates of maternal mortality and related indicators with 80% uncertainty intervals (UIs) using a Bayesian model. The model combines the rate of change implied by a multilevel regression model with a time-series model to capture data-driven changes in country-specific MMRs, and includes a data model to adjust for systematic and random errors associated with different data sources. RESULTS: We had data for 171 of 183 countries. The global MMR fell from 385 deaths per 100,000 livebirths (80% UI 359-427) in 1990, to 216 (207-249) in 2015, corresponding to a relative decline of 43·9% (34·0-48·7), with 303,000 (291,000-349,000) maternal deaths worldwide in 2015. Regional progress in reducing the MMR since 1990 ranged from an annual rate of reduction of 1·8% (0·0-3·1) in the Caribbean to 5·0% (4·0-6·0) in eastern Asia. Regional MMRs for 2015 ranged from 12 deaths per 100,000 livebirths (11-14) for high-income regions to 546 (511-652) for sub-Saharan Africa. Accelerated progress will be needed to achieve the SDG goal; countries will need to reduce their MMRs at an annual rate of reduction of at least 7·5%. INTERPRETATION: Despite global progress in reducing maternal mortality, immediate action is needed to meet the ambitious SDG 2030 target, and ultimately eliminate preventable maternal mortality. Although the rates of reduction that are needed to achieve country-specific SDG targets are ambitious for most high mortality countries, countries that made a concerted effort to reduce maternal mortality between 2000 and 2010 provide inspiration and guidance on how to accomplish the acceleration necessary to substantially reduce preventable maternal deaths. FUNDING: National University of Singapore, National Institute of Child Health and Human Development, USAID, and the UNDP/UNFPA/UNICEF/WHO/World Bank Special Programme of Research, Development and Research Training in Human Reproduction.

Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement.

Measurements of health indicators are rarely available for every population and period of interest, and available data may not be comparable. The Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) define best reporting practices for studies that calculate health estimates for multiple populations (in time or space) using multiple information sources. Health estimates that fall within the scope of GATHER include all quantitative population-level estimates (including global, regional, national, or subnational estimates) of health indicators, including indicators of health status, incidence and prevalence of diseases, injuries, and disability and functioning; and indicators of health determinants, including health behaviours and health exposures. GATHER comprises a checklist of 18 items that are essential for best reporting practice. A more detailed explanation and elaboration document, describing the interpretation and rationale of each reporting item along with examples of good reporting, is available on the GATHER website.

Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement.

Gretchen Stevens and colleagues present the GATHER statement, which seeks to promote good practice in the reporting of global health estimates.

Correction: Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement.

[This corrects the article DOI: 10.1371/journal.pmed.1002056.].

Global, regional, and national levels and trends in under-5 mortality between 1990 and 2015, with scenario-based projections to 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation.

BACKGROUND: In 2000, world leaders agreed on the Millennium Development Goals (MDGs). MDG 4 called for a two-thirds reduction in the under-5 mortality rate between 1990 and 2015. We aimed to estimate levels and trends in under-5 mortality for 195 countries from 1990 to 2015 to assess MDG 4 achievement and then intended to project how various post-2015 targets and observed rates of change will affect the burden of under-5 deaths from 2016 to 2030. METHODS: We updated the UN Inter-agency Group for Child Mortality Estimation (UN IGME) database with 5700 country-year datapoints. As of July, 2015, the database contains about 17 000 country-year datapoints for mortality of children younger than 5 years for 195 countries, and includes all available nationally-representative data from vital registration systems, population censuses, household surveys, and sample registration systems. We used these data to generate estimates, with uncertainty intervals, of under-5 (age 0-4 years) mortality using a Bayesian B-spline bias-reduction model (B3 model). This model includes a data model to adjust for systematic biases associated with different types of data sources. To provide insights into the global and regional burden of under-5 deaths associated with post-2015 targets, we constructed five scenario-based projections for under-5 mortality from 2016 to 2030 and estimated national, regional, and global under-5 mortality rates up to 2030 for each scenario. RESULTS: The global under-5 mortality rate has fallen from 90·6 deaths per 1000 livebirths (90% uncertainty interval 89·3-92·2) in 1990 to 42·5 (40·9-45·6) in 2015. During the same period, the annual number of under-5 deaths worldwide dropped from 12·7 million (12·6 million-13·0 million) to 5·9 million (5·7 million-6·4 million). The global under-5 mortality rate reduced by 53% (50-55%) in the past 25 years and therefore missed the MDG 4 target. Based on point estimates, two regions-east Asia and the Pacific, and Latin America and the Caribbean-achieved the MDG 4 target. 62 countries achieved the MDG 4 target, of which 24 were low-income and lower-middle income countries. Between 2016 and 2030, 94·4 million children are projected to die before the age of 5 years if the 2015 mortality rate remains constant in each country, and 68·8 million would die if each country continues to reduce its mortality rate at the pace estimated from 2000 to 2015. If all countries achieve the Sustainable Development Goal of an under-5 mortality rate of 25 or fewer deaths per 1000 livebirths by 2030, we project 56·0 million deaths by 2030. About two-thirds of all sub-Saharan African countries need to accelerate progress to achieve this target. INTERPRETATION: Despite substantial progress in reducing child mortality, concerted efforts remain necessary to avoid preventable under-5 deaths in the coming years and to accelerate progress in improving child survival further. Urgent actions are needed most in the regions and countries with high under-5 mortality rates, particularly those in sub-Saharan Africa and south Asia. FUNDING: None.

Global, regional, and national causes of child mortality in 2000-13, with projections to inform post-2015 priorities: an updated systematic analysis.

BACKGROUND: Trend data for causes of child death are crucial to inform priorities for improving child survival by and beyond 2015. We report child mortality by cause estimates in 2000-13, and cause-specific mortality scenarios to 2030 and 2035. METHODS: We estimated the distributions of causes of child mortality separately for neonates and children aged 1-59 months. To generate cause-specific mortality fractions, we included new vital registration and verbal autopsy data. We used vital registration data in countries with adequate registration systems. We applied vital registration-based multicause models for countries with low under-5 mortality but inadequate vital registration, and updated verbal autopsy-based multicause models for high mortality countries. We used updated numbers of child deaths to derive numbers of deaths by causes. We applied two scenarios to derive cause-specific mortality in 2030 and 2035. FINDINGS: Of the 6·3 million children who died before age 5 years in 2013, 51·8% (3·257 million) died of infectious causes and 44% (2·761 million) died in the neonatal period. The three leading causes are preterm birth complications (0·965 million [15·4%, uncertainty range (UR) 9·8-24·5]; UR 0·615-1·537 million), pneumonia (0·935 million [14·9%, 13·0-16·8]; 0·817-1·057 million), and intrapartum-related complications (0·662 million [10·5%, 6·7-16·8]; 0·421-1·054 million). Reductions in pneumonia, diarrhoea, and measles collectively were responsible for half of the 3·6 million fewer deaths recorded in 2013 versus 2000. Causes with the slowest progress were congenital, preterm, neonatal sepsis, injury, and other causes. If present trends continue, 4·4 million children younger than 5 years will still die in 2030. Furthermore, sub-Saharan Africa will have 33% of the births and 60% of the deaths in 2030, compared with 25% and 50% in 2013, respectively. INTERPRETATION: Our projection results provide concrete examples of how the distribution of child causes of deaths could look in 15-20 years to inform priority setting in the post-2015 era. More evidence is needed about shifts in timing, causes, and places of under-5 deaths to inform child survival agendas by and beyond 2015, to end preventable child deaths in a generation, and to count and account for every newborn and every child. FUNDING: Bill & Melinda Gates Foundation.

Global, regional and national levels and trends of preterm birth rates for 1990 to 2014: protocol for development of World Health Organization estimates.

BACKGROUND: The official WHO estimates of preterm birth are an essential global resource for assessing the burden of preterm birth and developing public health programmes and policies. This protocol describes the methods that will be used to identify, critically appraise and analyse all eligible preterm birth data, in order to develop global, regional and national level estimates of levels and trends in preterm birth rates for the period 1990 - 2014. METHODS: We will conduct a systematic review of civil registration and vital statistics (CRVS) data on preterm birth for all WHO Member States, via national Ministries of Health and Statistics Offices. For Member States with absent, limited or lower-quality CRVS data, a systematic review of surveys and/or research studies will be conducted. Modelling will be used to develop country, regional and global rates for 2014, with time trends for Member States where sufficient data are available. Member States will be invited to review the methodology and provide additional eligible data via a country consultation before final estimates are developed and disseminated. DISCUSSION: This research will be used to generate estimates on the burden of preterm birth globally for 1990 to 2014. We invite feedback on the methodology described, and call on the public health community to submit pertinent data for consideration. TRIAL REGISTRATION: Registered at PROSPERO CRD42015027439 CONTACT: pretermbirth@who.int.

Revised simulation model does not predict rebound in gonorrhoea prevalence where core groups are treated in the presence of antimicrobial resistance.

OBJECTIVES: To determine the effects of using discrete versus continuous quantities of people in a compartmental model examining the contribution of antimicrobial resistance (AMR) to rebound in the prevalence of gonorrhoea. METHODS: A previously published transmission model was reconfigured to represent the occurrence of gonorrhoea in discrete persons, rather than allowing fractions of infected individuals during simulations. RESULTS: In the revised model, prevalence only rebounded under scenarios reproduced from the original paper when AMR occurrence was increased by 10(5) times. In such situations, treatment of high-risk individuals yielded outcomes very similar to those resulting from treatment of low-risk and intermediate-risk individuals. Otherwise, in contrast with the original model, prevalence was the lowest when the high-risk group was treated, supporting the current policy of targeting treatment to high-risk groups. CONCLUSIONS: Simulation models can be highly sensitive to structural features. Small differences in structure and parameters can substantially influence predicted outcomes and policy prescriptions, and must be carefully considered.

Neonatal cause-of-death estimates for the early and late neonatal periods for 194 countries: 2000-2013.

OBJECTIVE: To estimate cause-of-death distributions in the early (0-6 days of age) and late (7-27 days of age) neonatal periods, for 194 countries between 2000 and 2013. METHODS: For 65 countries with high-quality vital registration, we used each country's observed early and late neonatal proportional cause distributions. For the remaining 129 countries, we used multinomial logistic models to estimate these distributions. For countries with low child mortality we used vital registration data as inputs and for countries with high child mortality we used neonatal cause-of-death distribution data from studies in similar settings. We applied cause-specific proportions to neonatal death estimates from the United Nations Inter-agency Group for Child Mortality Estimation, by country and year, to estimate cause-specific risks and numbers of deaths. FINDINGS: Over time, neonatal deaths decreased for most causes. Of the 2.8 million neonatal deaths in 2013, 0.99 million deaths (uncertainty range: 0.70-1.31) were estimated to be caused by preterm birth complications, 0.64 million (uncertainty range: 0.46-0.84) by intrapartum complications and 0.43 million (uncertainty range: 0.22-0.66) by sepsis and other severe infections. Preterm birth (40.8%) and intrapartum complications (27.0%) accounted for most early neonatal deaths while infections caused nearly half of late neonatal deaths. Preterm birth complications were the leading cause of death in all regions of the world. CONCLUSION: The neonatal cause-of-death distribution differs between the early and late periods and varies with neonatal mortality rate level. To reduce neonatal deaths, effective interventions to address these causes must be incorporated into policy decisions.