Female genital tract shedding of HIV-1 is rare in women with suppressed HIV-1 in plasma

Objective: Determine the frequency of genital HIV-1 shedding in a large cohort of women on long-term suppressive antiretroviral therapy (ART) and its association with mucosal inflammation.Design:We measured levels of HIV-1 RNA and inflammation biomarkers in cervicovaginal lavage (CVL) from HIV-seropositive women enrolled in the Women's Interagency HIV Study (WIHS).Methods:HIV-1 was quantified (Abbott RealTime HIV-1 assay) from CVL samples of 332 WIHS participants with and without clinical evidence of genital inflammation at the time of CVL collection; participants had suppressed plasma viral load (PVL; limit of quantitation less than 20-4000copies/ml depending on year of collection) for a median of 7.1 years [interquartile range (IQR) 3.4-9.8, Group 1] or for a median of 1.0 years (IQR=0.5-1.0, Group 2). Twenty-two biomarkers of inflammation were measured in CVL to compare with clinical markers.Results:HIV-1 was detected in 47% of 38 pre-ART CVL samples (median 668copies/ml) and detection in CVL was associated with higher pre-ART PVL. HIV-1 was detected in only 1 of 38 CVL samples from these women on suppressive antiretroviral therapy for 1 year. No HIV-1 RNA was detected in 294 CVL samples from a cross-sectional set of women with suppressed PVL for a median of 7 years. Clinical inflammation markers were correlated with inflammatory biomarkers in CVL specimens, although genital inflammation was not associated with measurable genital HIV-1 shedding in these WIHS participants on ART.Conclusion:ART that suppresses HIV-1 in the plasma of women also prevents genital tract HIV-1 shedding, even in the presence of genital tract inflammation. Copyright © 2019 The Author(s)

Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance and batch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is the result of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumor-infiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment. Tumor-infiltrating lymphocytes (TILs) were identified from standard pathology cancer images by a deep-learning-derived \u201ccomputational stain\u201d developed by Saltz et al. They processed 5,202 digital images from 13 cancer types. Resulting TIL maps were correlated with TCGA molecular data, relating TIL content to survival, tumor subtypes, and immune profiles

Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

BACKGROUND: Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. METHODS: The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. FINDINGS: Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. INTERPRETATION: This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing

Performance Analysis of Clustering Techniques for Object Oriented Segmentation of Satellite Images

This paper presents a new approach for color based image segmentation by applying Fuzzy c-means algorithm. This segmentation process includes a new mechanism for clustering the elements of high –resolution images in order to improve precision and reduce computation time. Normally, due to the progress in spatial resolution of satellite imagery, the methods of segment-based image analysis for Fuzzy c-means (FCM) clustering is one of well-known unsupervised clustering techniques, which can be used for unsupervised image segmentation. The measurement data considered from an unsupervised fuzzy clustering technique is only used to reveal the underlying structure of the data and segment the image in regions with similar spectral properties. So this method has not relationship betwee

An Object Oriented Model for the Classification of Satellite Image using Data Mining Techniques

The current paper had the objective of determining the coffee plantation area and its temporal variation for one interesting region of the Lavras county, Minas Gerais. The data was obtained from satellite images taken from LANDSAT-5/TM in 1997 and 1999. The results showed that the multi temporal classification as well as the post-classification correction allowed a better coffee zoning area. More over, a more precise observation could be made in relation to the coffee area increment