68 research outputs found

    PicU, a second serine protease autotransporter of uropathogenic Escherichia coli

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    Escherichia coli is the major Æ;tiological agent of urinary tract infections (UTI). Like diarrhoeagenic strains of E. coli , uropathogenic isolates possess virulence determinants that distinguish them from commensal strains and allow them to produce the clinical manifestations associated with UTI. Several autotransporter proteins have been associated with the ability of E. coli , and other Gram-negative bacteria, to cause disease. Recently, we described the existence within uropathogenic E. coli (UPEC) strains of Sat, a toxin of the serine protease autotransporter of Enterobacteriaceae (SPATE) subfamily. Using features common to proteins secreted via the autotransporter pathway we have identified nine additional autotransporter proteins from the genomic sequence data of UPEC CFT073. Surprisingly, two additional members of the SPATE subfamily were identified. One protein, designated PicU, was homologous to the Pic protein identified in Shigella flexneri and enteroaggregative E. coli . The PicU protein was expressed and investigated for functional activity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72222/1/S0378-1097_03_00862-0.pd

    Population Health Metrics Research Consortium gold standard verbal autopsy validation study: design, implementation, and development of analysis datasets

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    Background: Verbal autopsy methods are critically important for evaluating the leading causes of death in populations without adequate vital registration systems. With a myriad of analytical and data collection approaches, it is essential to create a high quality validation dataset from different populations to evaluate comparative method performance and make recommendations for future verbal autopsy implementation. This study was undertaken to compile a set of strictly defined gold standard deaths for which verbal autopsies were collected to validate the accuracy of different methods of verbal autopsy cause of death assignment.Methods: Data collection was implemented in six sites in four countries: Andhra Pradesh, India; Bohol, Philippines; Dar es Salaam, Tanzania; Mexico City, Mexico; Pemba Island, Tanzania; and Uttar Pradesh, India. The Population Health Metrics Research Consortium (PHMRC) developed stringent diagnostic criteria including laboratory, pathology, and medical imaging findings to identify gold standard deaths in health facilities as well as an enhanced verbal autopsy instrument based on World Health Organization (WHO) standards. A cause list was constructed based on the WHO Global Burden of Disease estimates of the leading causes of death, potential to identify unique signs and symptoms, and the likely existence of sufficient medical technology to ascertain gold standard cases. Blinded verbal autopsies were collected on all gold standard deaths.Results: Over 12,000 verbal autopsies on deaths with gold standard diagnoses were collected (7,836 adults, 2,075 children, 1,629 neonates, and 1,002 stillbirths). Difficulties in finding sufficient cases to meet gold standard criteria as well as problems with misclassification for certain causes meant that the target list of causes for analysis was reduced to 34 for adults, 21 for children, and 10 for neonates, excluding stillbirths. To ensure strict independence for the validation of methods and assessment of comparative performance, 500 test-train datasets were created from the universe of cases, covering a range of cause-specific compositions.Conclusions: This unique, robust validation dataset will allow scholars to evaluate the performance of different verbal autopsy analytic methods as well as instrument design. This dataset can be used to inform the implementation of verbal autopsies to more reliably ascertain cause of death in national health information systems

    Using Verbal Autopsy to Measure Causes of Death: the Comparative Performance of Existing Methods.

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    Monitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability. We investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution. Three automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause. Physician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices

    Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

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    Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB

    Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

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    A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

    Population-based rates, timing and causes of maternal deaths, stillbirths, and neonatal deaths in south Asia and sub-Saharan Africa: a multi-country prospective cohort study

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    BackgroundModelled mortality estimates have been useful for health programmes in low-income and middle-income countries. However, these estimates are often based on sparse and low-quality data. We aimed to generate high quality data about the burden, timing, and causes of maternal deaths, stillbirths, and neonatal deaths in south Asia and sub-Saharan Africa.MethodsIn this prospective cohort study done in 11 community-based research sites in south Asia and sub-Saharan Africa, between July, 2012, and February, 2016, we conducted population-based surveillance of women of reproductive age (15–49 years) to identify pregnancies, which were followed up to birth and 42 days post partum. We used standard operating procedures, data collection instruments, training, and standardisation to harmonise study implementation across sites. Verbal autopsies were done for deaths of all women of reproductive age, neonatal deaths, and stillbirths. Physicians used standardised methods for cause of death assignment. Site-specific rates and proportions were pooled at the regional level using a meta-analysis approach.FindingsWe identified 278 186 pregnancies and 263 563 births across the study sites, with outcomes ascertained for 269 630 (96·9%) pregnancies, including 8761 (3·2%) that ended in miscarriage or abortion. Maternal mortality ratios in sub-Saharan Africa (351 per 100 000 livebirths, 95% CI 168–732) were similar to those in south Asia (336 per 100 000 livebirths, 247–458), with far greater variability within sites in sub-Saharan Africa. Stillbirth and neonatal mortality rates were approximately two times higher in sites in south Asia than in sub-Saharan Africa (stillbirths: 35·1 per 1000 births, 95% CI 28·5–43·1 vs 17·1 per 1000 births, 12·5–25·8; neonatal mortality: 43·0 per 1000 livebirths, 39·0–47·3 vs 20·1 per 1000 livebirths, 14·6–27·6). 40–45% of pregnancy-related deaths, stillbirths, and neonatal deaths occurred during labour, delivery, and the 24 h postpartum period in both regions. Obstetric haemorrhage, non-obstetric complications, hypertensive disorders of pregnancy, and pregnancy-related infections accounted for more than three-quarters of maternal deaths and stillbirths. The most common causes of neonatal deaths were perinatal asphyxia (40%, 95% CI 39–42, in south Asia; 34%, 32–36, in sub-Saharan Africa) and severe neonatal infections (35%, 34–36, in south Asia; 37%, 34–39 in sub-Saharan Africa), followed by complications of preterm birth (19%, 18–20, in south Asia; 24%, 22–26 in sub-Saharan Africa).InterpretationThese results will contribute to improved global estimates of rates, timing, and causes of maternal and newborn deaths and stillbirths. Our findings imply that programmes in sub-Saharan Africa and south Asia need to further intensify their efforts to reduce mortality rates, which continue to be high. The focus on improving the quality of maternal intrapartum care and immediate newborn care must be further enhanced. Efforts to address perinatal asphyxia and newborn infections, as well as preterm birth, are critical to achieving survival goals in the Sustainable Development Goals era

    Effect of 3 Days of Oral Azithromycin on Young Children With Acute Diarrhea in Low-Resource Settings A Randomized Clinical Trial

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    Importance: World Health Organization (WHO) guidelines do not recommend routine antibiotic use for children with acute watery diarrhea. However, recent studies suggest that a significant proportion of such episodes have a bacterial cause and are associated with mortality and growth impairment, especially among children at high risk of diarrhea-associated mortality. Expanding antibiotic use among dehydrated or undernourished children may reduce diarrhea-associated mortality and improve growth. Objective: To determine whether the addition of azithromycin to standard case management of acute nonbloody watery diarrhea for children aged 2 to 23 months who are dehydrated or undernourished could reduce mortality and improve linear growth. Design, Setting, and Participants: The Antibiotics for Children with Diarrhea (ABCD) trial was a multicountry, randomized, double-blind, clinical trial among 8266 high-risk children aged 2 to 23 months presenting with acute nonbloody diarrhea. Participants were recruited between July 1, 2017, and July 10, 2019, from 36 outpatient hospital departments or community health centers in a mixture of urban and rural settings in Bangladesh, India, Kenya, Malawi, Mali, Pakistan, and Tanzania. Each participant was followed up for 180 days. Primary analysis included all randomized participants by intention to treat. Interventions: Enrolled children were randomly assigned to receive either oral azithromycin, 10 mg/kg, or placebo once daily for 3 days in addition to standard WHO case management protocols for the management of acute watery diarrhea. Main Outcomes and Measures: Primary outcomes included all-cause mortality up to 180 days after enrollment and linear growth faltering 90 days after enrollment. Results: A total of 8266 children (4463 boys [54.0%]; mean [SD] age, 11.6 [5.3] months) were randomized. A total of 20 of 4133 children in the azithromycin group (0.5%) and 28 of 4135 children in the placebo group (0.7%) died (relative risk, 0.72; 95% CI, 0.40-1.27). The mean (SD) change in length-for-age z scores 90 days after enrollment was -0.16 (0.59) in the azithromycin group and -0.19 (0.60) in the placebo group (risk difference, 0.03; 95% CI, 0.01-0.06). Overall mortality was much lower than anticipated, and the trial was stopped for futility at the prespecified interim analysis. Conclusions and Relevance: The study did not detect a survival benefit for children from the addition of azithromycin to standard WHO case management of acute watery diarrhea in low-resource settings. There was a small reduction in linear growth faltering in the azithromycin group, although the magnitude of this effect was not likely to be clinically significant. In low-resource settings, expansion of antibiotic use is not warranted. Adherence to current WHO case management protocols for watery diarrhea remains appropriate and should be encouraged. Trial Registration: ClinicalTrials.gov Identifier: NCT03130114.publishedVersionPeer reviewe

    Measurements of top-quark pair differential cross-sections in the eμe\mu channel in pppp collisions at s=13\sqrt{s} = 13 TeV using the ATLAS detector

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