A parametric shell analysis of the shuttle 51-L SRB AFT field joint

Following the Shuttle 51-L accident, an investigation was conducted to determine the cause of the failure. Investigators at the Langley Research Center focused attention on the structural behavior of the field joints with O-ring seals in the steel solid rocket booster (SRB) cases. The shell-of-revolution computer program BOSOR4 was used to model the aft field joint of the solid rocket booster case. The shell model consisted of the SRB wall and joint geometry present during the Shuttle 51-L flight. A parametric study of the joint was performed on the geometry, including joint clearances, contact between the joint components, and on the loads, induced and applied. In addition combinations of geometry and loads were evaluated. The analytical results from the parametric study showed that contact between the joint components was a primary contributor to allowing hot gases to blow by the O-rings. Based upon understanding the original joint behavior, various proposed joint modifications are shown and analyzed in order to provide additional insight and information. Finally, experimental results from a hydro-static pressurization of a test rocket booster case to study joint motion are presented and verified analytically

Usefulness of primary care electronic networks to assess the incidence of chlamydia, diagnosed by general practitioners

Background: Chlamydia is the most common curable sexually transmitted infection (STI) in the Netherlands. The majority of chlamydia diagnoses are made by general practitioners (GPs). Baseline data from primary care will facilitate the future evaluation of the ongoing large population-based screening in the Netherlands. The aim of this study was to assess the usefulness of electronic medical records for monitoring the incidence of chlamydia cases diagnosed in primary care in the Netherlands. Methods. In the electronic records of two regional and two national networks, we identified chlamydia diagnoses by means of ICPC codes (International Classification of Primary Care), laboratory results in free text and the prescription of antibiotics. The year of study was 2007 for the two regional networks and one national network, for the other national network the year of study was 2005. We calculated the incidence of diagnosed chlamydia cases per sex, age group and degree of urbanization. Results: A large diversity was observed in the way chlamydia episodes were coded in the four different GP networks and how easily information concerning chlamydia diagnoses could be extracted. The overall incidence ranged from 103.2/100,000 to 590.2/100,000. Differences were partly related to differences between patient populations. Nevertheless, we observed similar trends in the incidence of chlamydia diagnoses in all networks and findings were in line with earlier reports. Conclusions: Electronic patient records, originally intended for individual patient care in general practice, can be an additional source of data for monitoring chlamydia incidence in primary care and can be of use in assessing the future impact of population-based chlamydia screening programs. To increase the usefulness of data we recommend more efforts to standardize registration by (specific) ICPC code and laboratory results across the existing GP networks

Probabilistic Inference of Transcription Factor Binding from Multiple Data Sources

An important problem in molecular biology is to build a complete understanding of transcriptional regulatory processes in the cell. We have developed a flexible, probabilistic framework to predict TF binding from multiple data sources that differs from the standard hypothesis testing (scanning) methods in several ways. Our probabilistic modeling framework estimates the probability of binding and, thus, naturally reflects our degree of belief in binding. Probabilistic modeling also allows for easy and systematic integration of our binding predictions into other probabilistic modeling methods, such as expression-based gene network inference. The method answers the question of whether the whole analyzed promoter has a binding site, but can also be extended to estimate the binding probability at each nucleotide position. Further, we introduce an extension to model combinatorial regulation by several TFs. Most importantly, the proposed methods can make principled probabilistic inference from multiple evidence sources, such as, multiple statistical models (motifs) of the TFs, evolutionary conservation, regulatory potential, CpG islands, nucleosome positioning, DNase hypersensitive sites, ChIP-chip binding segments and other (prior) sequence-based biological knowledge. We developed both a likelihood and a Bayesian method, where the latter is implemented with a Markov chain Monte Carlo algorithm. Results on a carefully constructed test set from the mouse genome demonstrate that principled data fusion can significantly improve the performance of TF binding prediction methods. We also applied the probabilistic modeling framework to all promoters in the mouse genome and the results indicate a sparse connectivity between transcriptional regulators and their target promoters. To facilitate analysis of other sequences and additional data, we have developed an on-line web tool, ProbTF, which implements our probabilistic TF binding prediction method using multiple data sources. Test data set, a web tool, source codes and supplementary data are available at: http://www.probtf.org

Global gene expression profiling of myeloid immune cell subsets in response to in vitro challenge with porcine circovirus 2b

Compelling evidence suggests that the early interaction between porcine circovirus 2 (PCV-2) and the innate immune system is the key event in the pathogenesis of Post-Weaning Multisystemic Wasting Syndrome (PMWS). Furthermore, PCV2 has been detected in bone-marrow samples, potentially enabling an easy spread and reservoir for the virus. To assess the gene-expression differences induced by an in-vitro PCV2b infection in different three different myeloid innate immune cell subsets generated from the same animal, we used the Agilent Porcine Gene Expression Microarray (V2). Alveolar macrophages (AMØs), monocyte-derived dendritic cells (MoDCs) and bone-marrow cells (BMCs) were generated from each animal, and challenged with a UK-isolate of a PCV2 genotype b-strain at a MOI of 0.5. Remarkably, analysis showed a highly distinct and cell-type dependent response to PCV2b challenge. Overall, MoDCs showed the most marked response to PCV2b challenge in vitro and revealed a key role for TNF in the interaction with PCV2b, whereas only few genes were affected in BMCs and AMØs. These observations were further supported by an enrichment of genes in the downstream NF-κB Signalling pathway as well as an up regulation of genes with pro-apoptotic functions post-challenge. PCV2b challenge increases the expression of a large number of immune-related and pro-apoptotic genes mainly in MoDC, which possibly explain the increased inflammation, granulomatous inflammation and lymphocyte depletion seen in PMWS-affected pigs