The vaginal microbiome likely influences host signaling compounds within the reproductive tract,including pro-inflammatory signals,which may play an important role during *** lactobacilli are associated with positive ...
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The vaginal microbiome likely influences host signaling compounds within the reproductive tract,including pro-inflammatory signals,which may play an important role during *** lactobacilli are associated with positive pregnancy outcome,whereas bacterial vaginosis,a dysbiosis of the vaginal microbiome,is associated with an increased risk of adverse pregnancy outcomes including preterm *** the host response could be predicted based on the taxonomic composition of the vaginal microbiome,particularly early in pregnancy,then those predictions could potentially be used to personalize intervention methods to reduce preterm birth and other adverse *** this proof of principle study,we apply multivariate strategies to analyze 16S rRNA-based taxonomic surveys in conjunction with targeted immuno-proteomic and lipidomic data from vaginal samples from 58 women enrolled in the Multi-Omic Microbiome Study-Pregnancy Initiative during early *** between the vaginal microbiome and the vaginal lipidome have not been previously *** from this study reveal significant multiple pairwise associations between microbial taxa,specific eicosanoids and sphingomyelins,and *** the biologic significance of these associations is not yet known,these results support the utility of such multi-omic approaches as a means to predict the impact of the microbiome on the host.
RNA-seq has matured and become an important tool for studying RNA biology. Here we compared two RNA-seq (Illumina sequencing by synthesis and MGI DNBSEQTM) and two microarray platforms (Illumina Expression BeadChip an...
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Summary Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea in...
Summary Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood *** We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor *** The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy *** By co-analysing geospatial trends in d
Classifying samples in incomplete datasets is a common aim for machine learning practitioners, but is non-trivial. Missing data is found in most real-world datasets and these missing values are typically imputed using...
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Fast radio bursts (FRBs) last for milliseconds and arrive at Earth from cosmological distances. While their origin(s) and emission mechanism(s) are presently unknown, their signals bear similarities with the much less...
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Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluat...
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Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the d...
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Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of ...
Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided
Background Reduced amyloid-beta-42 (Aβ42) and elevated total tau (t-tau) protein concentrations in the CSF are characteristic of Alzheimer’s disease (AD) pathology [1]. Aβ42 contributes to extracellular plaque form...
Background Reduced amyloid-beta-42 (Aβ42) and elevated total tau (t-tau) protein concentrations in the CSF are characteristic of Alzheimer’s disease (AD) pathology [1]. Aβ42 contributes to extracellular plaque formation between neurons [2]. The total level of tau, a microtubule-stabilizer in neuron axons [3], is associated with neuronal death [1]. Additionally, presence of ApoE4 (ε4) alleles is an established identifier for increased risk of AD [4]. Non-invasive imaging-based correlates of the CSF markers are lacking. This study examines correlations of novel FLAIR texture, intensity, and volume biomarkers, along with white matter lesion (WML) burden, with Aβ42, t-tau, and ε4 status. Method FLAIR volumes (n = 4044) from the ADNI database were used for analysis with CSF biomarkers. A subset (n = 921) was used for ε4 analysis based on available data. Normal-appearing brain matter (NABM) was obtained by removing CSF and WML. Macrostructural damage (MAD), microstructural damage (MID), and integrity (MII) texture biomarkers [5] were extracted from each NABM volume (Fig. 1), along with median intensity, NABM/ICV ratio, and normalized WML volume [5]. Relationships between FLAIR biomarkers and AD markers were described using parametric statistical analyses. statistical significance was set at p<0.05. Result All FLAIR biomarkers were statistically significantly correlated with CSF Aβ42 levels. All features except MID and WML burden were significantly correlated with CSF t-tau levels (Table 1). MAD, MID, and WML burden showed negative correlations with Aβ42, while MAD showed a positive correlation with t-tau. Opposite trends were seen with MII, intensity, and NABM/ICV (Fig. 2). Significant differences between groups without and with one ε4 allele were found in all FLAIR biomarkers except WML burden. Significant differences in MAD, MII and NABM/ICV were found between groups with one and two ε4 alleles (Table 2). Conclusion FLAIR biomarkers were inversely associated with CSF Aβ
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