156 research outputs found
A flexible, extensible object oriented real-time near photorealistic visualization system:the system framework design
In this paper we describe a novel, extensible visualization system currently under development at Aston University. We introduce modern programming methods, such as the use of data driven programming, design patterns, and the careful definition of interfaces to allow easy extension using plug-ins, to 3D landscape visualization software. We combine this with modern developments in computer graphics, such as vertex and fragment shaders, to create an extremely flexible, extensible real-time near photorealistic visualization system. In this paper we show the design of the system and the main sub-components. We stress the role of modern programming practices and illustrate the benefits these bring to 3D visualization. © 2006 Springer-Verlag Berlin Heidelberg
Human cytomegalovirus-induced host protein citrullination is crucial for viral replication
Citrullination is the conversion of arginine-to-citrulline by protein arginine deiminases (PADs), whose dysregulation is implicated in the pathogenesis of various types of cancers and autoimmune diseases. Consistent with the ability of human cytomegalovirus (HCMV) to induce post-translational modifications of cellular proteins to gain a survival advantage, we show that HCMV infection of primary human fibroblasts triggers PAD-mediated citrullination of several host proteins, and that this activity promotes viral fitness. Citrullinome analysis reveals significant changes in deimination levels of both cellular and viral proteins, with interferon (IFN)-inducible protein IFIT1 being among the most heavily deiminated one. As genetic depletion of IFIT1 strongly enhances HCMV growth, and in vitro IFIT1 citrullination impairs its ability to bind to 5'-ppp-RNA, we propose that viral-induced IFIT1 citrullination is a mechanism of HCMV evasion from host antiviral resistance. Overall, our findings point to a crucial role of citrullination in subverting cellular responses to viral infection
Cyclin-Dependent Kinase Activity Controls the Onset of the HCMV Lytic Cycle
The onset of human cytomegalovirus (HCMV) lytic infection is strictly synchronized with the host cell cycle. Infected G0/G1 cells support viral immediate early (IE) gene expression and proceed to the G1/S boundary where they finally arrest. In contrast, S/G2 cells can be infected but effectively block IE gene expression and this inhibition is not relieved until host cells have divided and reentered G1. During latent infection IE gene expression is also inhibited, and for reactivation to occur this block to IE gene expression must be overcome. It is only poorly understood which viral and/or cellular activities maintain the block to cell cycle or latency-associated viral IE gene repression and whether the two mechanisms may be linked. Here, we show that the block to IE gene expression during S and G2 phase can be overcome by both genotoxic stress and chemical inhibitors of cellular DNA replication, pointing to the involvement of checkpoint-dependent signaling pathways in controlling IE gene repression. Checkpoint-dependent rescue of IE expression strictly requires p53 and in the absence of checkpoint activation is mimicked by proteasomal inhibition in a p53 dependent manner. Requirement for the cyclin dependent kinase (CDK) inhibitor p21 downstream of p53 suggests a pivotal role for CDKs in controlling IE gene repression in S/G2 and treatment of S/G2 cells with the CDK inhibitor roscovitine alleviates IE repression independently of p53. Importantly, CDK inhibiton also overcomes the block to IE expression during quiescent infection of NTera2 (NT2) cells. Thus, a timely block to CDK activity not only secures phase specificity of the cell cycle dependent HCMV IE gene expression program, but in addition plays a hitherto unrecognized role in preventing the establishment of a latent-like state
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Combinatorial, additive and dose-dependent drug–microbiome associations
Data availability:
The source data for the figures are provided at Zenodo (https://doi.org/10.5281/zenodo.4728981). Raw shotgun sequencing data that support the findings of this study have been deposited at the ENA under accession codes PRJEB41311, PRJEB38742 and PRJEB37249 with public access. Raw spectra for metabolomics have been deposited in the MassIVE database under the accession codes MSV000088043 (UPLC–MS/MS) and MSV000088042 (GC–MS). The metadata on disease groups and drug intake are provided in Supplementary Tables 1–3. The demographic, clinical and phenotype metadata, and processed microbiome and metabolome data for French, German and Danish participants are available at Zenodo (https://doi.org/10.5281/zenodo.4674360).Code availability:
The new drug-aware univariate biomarker testing pipeline is available as an R package (metadeconfoundR; Birkner et al., manuscript in preparation) at Github (https://github.com/TillBirkner/metadeconfoundR) and at Zenodo (https://doi.org/10.5281/zenodo.4721078). The latest version (0.1.8) of this package was used to generate the data shown in this publication. The code used for multivariate analysis based on the VpThemAll package is available at Zenodo (https://doi.org/10.5281/zenodo.4719526). The phenotype and drug intake metadata, processed microbiome, and metabolome data and code resources are available for download at Zenodo (https://doi.org/10.5281/zenodo.4674360). The code for reproducing the figures is provided at Zenodo (https://doi.org/10.5281/zenodo.4728981).During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery1,2,3,4,5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug–host–microbiome interactions in cardiometabolic disease.This work was supported by the European Union’s Seventh Framework Program for research, technological development and demonstration under grant agreement HEALTH-F4-2012-305312 (METACARDIS). Part of this work was also supported by the EMBL, by the Metagenopolis grant ANR-11-DPBS-0001, by the H2020 European Research Council (ERC-AdG-669830) (to P.B.), and by grants from the Deutsche Forschungsgemeinschaft (SFB1365 to S.K.F. and L.M.; and SFB1052/3 A1 MS to M.S. (209933838)). Assistance Publique-Hôpitaux de Paris is the promoter of the clinical investigation (MetaCardis). M.-E.D. is supported by the NIHR Imperial Biomedical Research Centre and by grants from the French National Research Agency (ANR-10-LABX-46 (European Genomics Institute for Diabetes)), from the National Center for Precision Diabetic Medicine – PreciDIAB, which is jointly supported by the French National Agency for Research (ANR-18-IBHU-0001), by the European Union (FEDER), by the Hauts-de-France Regional Council (Agreement 20001891/NP0025517) and by the European Metropolis of Lille (MEL, Agreement 2019_ESR_11) and by Isite ULNE (R-002-20-TALENT-DUMAS), also jointly funded by ANR (ANR-16-IDEX-0004-ULNE), the Hauts-de-France Regional Council (20002845) and by the European Metropolis of Lille (MEL). R.J.A. is a member of the Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Bioscience. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent research institution at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation
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Combinatorial, additive and dose-dependent drug–microbiome associations
During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug–host–microbiome interactions in cardiometabolic disease
Using data fusion of DMARS-R-IMU and GPS data for improving attitude determination accuracy
The Mobile Rocket Base (MORABA), a division of the Space Operations and Astronaut Training Department of the German Aerospace Center, has developed and flown sounding rocket rate and attitude control systems since 1972. For determining position and attitude, some of the past missions have used a DMARS-R (Digital Miniature Attitude Reference System) roll stabilized platform produced by the Inertial Science Company. The DMARS-R is a high-precision, roll-stabilized IMU (Inertial Measurement Unit) comprising accurate angular rate and acceleration sensors and mounted on a roll-stabilized platform. Standard IMUs are inherently subject to drift in inertial position, velocity and attitude. By the fusion of GPS and with DMARS-R data, one can achieve a long-term drift-corrected IMU enabling for longer duration flight applications, such as satellite launchers, spin stabilized rockets and balloons. The main experiment of the MAIUS mission, initially planned for autumn 2015, requires accurate pointing to the Earth’s gravitational center.
The required accuracy will be obtained by the fusion of DMARS-R and GNS data to produce “drift free” attitude data for the cold gas attitude control system of the payload. The attitude correction and control algorithm will be implemented in the DMARS-R processor
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