Cause-specific contributions to sex differences in adult mortality among whites and African Americans between 1960 and 1995

The purpose of this paper is to describe trends in sex differences in mortality in young adulthood and in middle age among African Americans and whites in the United States between 1960 and 1995. We examine trends in all-cause mortality and estimate the contribution of leading causes of death to the change in the sex difference in mortality over time. Between 1960 and 1995 the sex difference in mortality increased for African Americans and whites at ages 15-39 and declined for whites but increased for African Americans at ages 40-64. Our results reveal considerable variation in the sex difference in mortality by cause of death as well as in the contribution various causes of death make to the change in the sex mortality difference over time.cause of death, mortality, USA

Educational differences in cause-specific mortality in the United States

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The Learning Agreement Pilot in Lancashire, England: supporting young people in jobs without training

The Learning Agreement Pilot (LAP) began in April 2006 in eight areas in England as part of the Government’s continuing commitment to improving the skills base of young people. Lancashire is one of the LAP areas, and CXL (formerly Connexions Lancashire) is working in partnership with the local Learning and Skills Council to re-engage in learning those 16 and 17-year-olds who are in jobs with no accredited training. CXL commissioned an evaluation of the first year of the Lancashire LAP, focussing on both its delivery and its impact on young people and employers. The Department for Children, Schools and Families (DCSF) commissioned two separate evaluations of the first year of the LAP nationally, one focussing on delivery and management issues and one focussing on a model of youth re-engagement to test aspects of policy

Black-White Differentials in Cause-Specific Mortality in the United States during the 1980s: The Role of Medical Care and Health Behaviors

In this paper, we examine black-white differences in cause-specific mortality during the 1980s when black-white disparities in mortality widened in the United States. We group causes of death to those amenable to medical intervention, those closely linked to health behaviors or residential location, and all other causes combined. At older ages, we treat cardiovascular disease, stroke, and forms of cancer not amenable to medical or behavioral intervention as distinct causes. We conduct separate analyses by gender and age group. Causes of death amenable to medical intervention and those linked to health behaviors and residential location accounted for over 60% of the absolute black-white difference in male and female mortality at ages 25-44, male mortality at ages 45-74, but somewhat less than 50% of the black-white difference in female mortality at these older ages. The relative black excess risk was most pronounced for causes amenable to medical intervention with and without adjustment for socio-demographic characteristics

Integrative omics approaches provide biological and clinical insights : examples from mitochondrial diseases

High-throughput technologies for genomics, transcriptomics, proteomics, and metabolomics, and integrative analysis of these data, enable new, systems-level insights into disease pathogenesis. Mitochondrial diseases are an excellent target for hypothesis-generating omics approaches, as the disease group is mechanistically exceptionally complex. Although the genetic background in mitochondrial diseases is in either the nuclear or the mitochondrial genome, the typical downstream effect is dysfunction of the mitochondrial respiratory chain. However, the clinical manifestations show unprecedented variability, including either systemic or tissue-specific effects across multiple organ systems, with mild to severe symptoms, and occurring at any age. So far, the omics approaches have provided mechanistic understanding of tissue-specificity and potential treatment options for mitochondrial diseases, such as metabolome remodeling. However, no curative treatments exist, suggesting that novel approaches are needed. In this Review, we discuss omics approaches and discoveries with the potential to elucidate mechanisms of and therapies for mitochondrial diseases.Peer reviewe

Enhanced differential expression statistics for data-independent acquisition proteomics

We describe a new reproducibility-optimization method ROPECA for statistical analysis of proteomics data with a specific focus on the emerging data-independent acquisition (DIA) mass spectrometry technology. ROPECA optimizes the reproducibility of statistical testing on peptide-level and aggregates the peptide-level changes to determine differential protein-level expression. Using a 'gold standard' spike-in data and a hybrid proteome benchmark data we show the competitive performance of ROPECA over conventional protein-based analysis as well as state-of-the-art peptide-based tools especially in DIA data with consistent peptide measurements. Furthermore, we also demonstrate the improved accuracy of our method in clinical studies using proteomics data from a longitudinal human twin study

Statistical and machine learning methods to study human CD4+ T cell proteome profiles

Mass spectrometry proteomics has become an important part of modern immunology, making major contributions to understanding protein expression levels, subcellular localizations, posttranslational modifications, and interactions in various immune cell populations. New developments in both experimental and computational techniques offer increasing opportunities for exploring the immune system and the molecular mechanisms involved in immune responses. Here, we focus on current computational approaches to infer relevant information from large mass spectrometry based protein profiling datasets, covering the different steps of the analysis from protein identification and quantification to further mining and modelling of the protein abundance data. Additionally, we provide a summary of the key proteome profiling studies on human CD4+ T cells and their different subtypes in health and disease

Integrating probe-level expression changes across generations of Affymetrix arrays

There is an urgent need for bioinformatic methods that allow integrative analysis of multiple microarray data sets. While previous studies have mainly concentrated on reproducibility of gene expression levels within or between different platforms, we propose a novel meta-analytic method that takes into account the vast amount of available probe-level information to combine the expression changes across different studies. We first show that the comparability of relative expression changes and the consistency of differentially expressed genes between different Affymetrix array generations can be considerably improved by determining the expression changes at the probe-level and by considering the latest information on probe-level sequence matching instead of the probe annotations provided by the manufacturer. With the improved probe-level expression change estimates, data from different generations of Affymetrix arrays can be combined more effectively. This will allow for the full exploitation of existing results when designing and analyzing new experiments

Whole-History Rating: A Bayesian Rating System for Players of Time-Varying Strength

International audienceWhole-History Rating (WHR) is a new method to estimate the time-varying strengths of players involved in paired comparisons. Like many variations of the Elo rating system, the whole-history approach is based on the dynamic Bradley-Terry model. But, instead of using incremental approximations, WHR directly computes the exact maximum a posteriori over the whole rating history of all players. This additional accuracy comes at a higher computational cost than traditional methods, but computation is still fast enough to be easily applied in real time to large-scale game servers (a new game is added in less than 0.001 second). Experiments demonstrate that, in comparison to Elo, Glicko, TrueSkill, and decayed-history algorithms, WHR produces better predictions

Protein Sequence Annotation Tool (PSAT): a centralized web-based meta-server for high-throughput sequence annotations

The EC2KEGG output for the RV1423 analysis sorted in ascending order by the FDR value. (XLSX 58 kb