On-board fault management for autonomous spacecraft

The dynamic nature of the Cargo Transfer Vehicle's (CTV) mission and the high level of autonomy required mandate a complete fault management system capable of operating under uncertain conditions. Such a fault management system must take into account the current mission phase and the environment (including the target vehicle), as well as the CTV's state of health. This level of capability is beyond the scope of current on-board fault management systems. This presentation will discuss work in progress at TRW to apply artificial intelligence to the problem of on-board fault management. The goal of this work is to develop fault management systems. This presentation will discuss work in progress at TRW to apply artificial intelligence to the problem of on-board fault management. The goal of this work is to develop fault management systems that can meet the needs of spacecraft that have long-range autonomy requirements. We have implemented a model-based approach to fault detection and isolation that does not require explicit characterization of failures prior to launch. It is thus able to detect failures that were not considered in the failure and effects analysis. We have applied this technique to several different subsystems and tested our approach against both simulations and an electrical power system hardware testbed. We present findings from simulation and hardware tests which demonstrate the ability of our model-based system to detect and isolate failures, and describe our work in porting the Ada version of this system to a flight-qualified processor. We also discuss current research aimed at expanding our system to monitor the entire spacecraft

Dynamic exchange of myosin VI on endocytic structures.

The actin-based molecular motor myosin VI functions in the endocytic uptake pathway, both during the early stages of clathrin-mediated uptake and in later transport to/from early endosomes. This study uses fluorescence recovery after photobleaching (FRAP) to examine the turnover rate of myosin VI during endocytosis. The results demonstrate that myosin VI turns over dynamically on endocytic structures with a characteristic half-life common to both the large insert isoform of myosin VI on clathrin-coated structures and the no-insert isoform on early endosomes. This half-life is shared by the myosin VI-binding partner Dab2 and is identical for full-length myosin VI and the cargo-binding tail region. The 4-fold slower half-life of an artificially dimerized construct of myosin VI on clathrin-coated structures suggests that wild type myosin VI does not function as a stable dimer, but either as a monomer or in a monomer/dimer equilibrium. Taken together, these FRAP results offer insight into both the basic turnover dynamics and the monomer/dimer nature of myosin VI

Analysis of preterm deliveries below 35 weeks' gestation in a tertiary referral hospital in the UK. A case-control survey

<p>Abstract</p> <p>Background</p> <p>Preterm birth remains a major public health problem and its incidence worldwide is increasing. Epidemiological risk factors have been investigated in the past, but there is a need for a better understanding of the causes of preterm birth in well defined obstetric populations in tertiary referral centres; it is important to repeat surveillance and identify possible changes in clinical and socioeconomic factors associated with preterm delivery. The aim of this study was to identify current risk factors associated with preterm delivery and highlight areas for further research.</p> <p>Findings</p> <p>We studied women with singleton deliveries at St Michael's Hospital, Bristol during 2002 and 2003. 274 deliveries between 23-35 weeks' gestation (preterm group), were compared to 559 randomly selected control deliveries at term (37-42 weeks) using standard statistical procedures. Both groups were >80% Caucasian. Previous preterm deliveries, high maternal age (> 39 years), socioeconomic problems, smoking during pregnancy, hypertension, psychiatric disorders and uterine abnormalities were significantly associated with preterm deliveries. Both lean and obese mothers were more common in the preterm group. Women with depression/psychiatric disease were significantly more likely to have social problems, to have smoked during pregnancy and to have had previous preterm deliveries; when adjustments for these three factors were made the relationship between psychiatric disease and pregnancy outcome was no longer significant. 53% of preterm deliveries were spontaneous, and were strongly associated with episodes of threatened preterm labour. Medically indicated preterm deliveries were associated with hypertension and fetal growth restriction. Preterm premature rupture of the membranes, vaginal bleeding, anaemia and oligohydramnios were significantly increased in both spontaneous and indicated preterm deliveries compared to term controls.</p> <p>Conclusions</p> <p>More than 50% of preterm births are potentially preventable, but remain associated with risk factors such as increased uterine contractility, preterm premature rupture of the membranes and uterine bleeding whose aetiology is unknown. Despite remarkable advances in perinatal care, preterm birth continues to cause neonatal deaths and long-term morbidity. Significant breakthroughs in the management of preterm birth are likely to come from research into the mechanisms of human parturition and the pathophysiology of preterm labour using multidisciplinary clinical and laboratory approaches.</p

Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus.

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. SIGNIFICANCE: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene.See related commentary by Choi and Brown, p. 439

Genomic copy number variation in Mus musculus.

BACKGROUND: Copy number variation is an important dimension of genetic diversity and has implications in development and disease. As an important model organism, the mouse is a prime candidate for copy number variant (CNV) characterization, but this has yet to be completed for a large sample size. Here we report CNV analysis of publicly available, high-density microarray data files for 351 mouse tail samples, including 290 mice that had not been characterized for CNVs previously. RESULTS: We found 9634 putative autosomal CNVs across the samples affecting 6.87% of the mouse reference genome. We find significant differences in the degree of CNV uniqueness (single sample occurrence) and the nature of CNV-gene overlap between wild-caught mice and classical laboratory strains. CNV-gene overlap was associated with lipid metabolism, pheromone response and olfaction compared to immunity, carbohydrate metabolism and amino-acid metabolism for wild-caught mice and classical laboratory strains, respectively. Using two subspecies of wild-caught Mus musculus, we identified putative CNVs unique to those subspecies and show this diversity is better captured by wild-derived laboratory strains than by the classical laboratory strains. A total of 9 genic copy number variable regions (CNVRs) were selected for experimental confirmation by droplet digital PCR (ddPCR). CONCLUSION: The analysis we present is a comprehensive, genome-wide analysis of CNVs in Mus musculus, which increases the number of known variants in the species and will accelerate the identification of novel variants in future studies

Evaluation of Candidate Stromal Epithelial Cross-Talk Genes Identifies Association between Risk of Serous Ovarian Cancer and TERT, a Cancer Susceptibility “Hot-Spot”

We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs) in 173 genes involved in stromal epithelial interactions in the Ovarian Cancer Association Consortium (OCAC). In the discovery stage, cases with epithelial ovarian cancer (n = 675) and controls (n = 1,162) were genotyped at 1,536 SNPs using an Illumina GoldenGate assay. Based on Positive Predictive Value estimates, three SNPs—PODXL rs1013368, ITGA6 rs13027811, and MMP3 rs522616—were selected for replication using TaqMan genotyping in up to 3,059 serous invasive cases and 8,905 controls from 16 OCAC case-control studies. An additional 18 SNPs with Pper-allele<0.05 in the discovery stage were selected for replication in a subset of five OCAC studies (n = 1,233 serous invasive cases; n = 3,364 controls). The discovery stage associations in PODXL, ITGA6, and MMP3 were attenuated in the larger replication set (adj. Pper-allele≥0.5). However genotypes at TERT rs7726159 were associated with ovarian cancer risk in the smaller, five-study replication study (Pper-allele = 0.03). Combined analysis of the discovery and replication sets for this TERT SNP showed an increased risk of serous ovarian cancer among non-Hispanic whites [adj. ORper-allele 1.14 (1.04–1.24) p = 0.003]. Our study adds to the growing evidence that, like the 8q24 locus, the telomerase reverse transcriptase locus at 5p15.33, is a general cancer susceptibility locus

Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk

DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P <7.94 x 10(-7). Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. Significance: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.Peer reviewe

Fast and efficient QTL mapper for thousands of molecular phenotypes

In order to discover quantitative trait loci, multi-dimensional genomic datasets combining DNA-seq and ChiP-/RNA-seq require methods that rapidly correlate tens of thousands of molecular phenotypes with millions of genetic variants while appropriately controlling for multiple testing