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- Aarestrup, FM, et al.
(författare)
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Towards a European health research and innovation cloud (HRIC)
- 2020
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Ingår i: Genome medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 12:1, s. 18-
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Tidskriftsartikel (refereegranskat)abstract
- The European Union (EU) initiative on the Digital Transformation of Health and Care (Digicare) aims to provide the conditions necessary for building a secure, flexible, and decentralized digital health infrastructure. Creating a European Health Research and Innovation Cloud (HRIC) within this environment should enable data sharing and analysis for health research across the EU, in compliance with data protection legislation while preserving the full trust of the participants. Such a HRIC should learn from and build on existing data infrastructures, integrate best practices, and focus on the concrete needs of the community in terms of technologies, governance, management, regulation, and ethics requirements. Here, we describe the vision and expected benefits of digital data sharing in health research activities and present a roadmap that fosters the opportunities while answering the challenges of implementing a HRIC. For this, we put forward five specific recommendations and action points to ensure that a European HRIC: i) is built on established standards and guidelines, providing cloud technologies through an open and decentralized infrastructure; ii) is developed and certified to the highest standards of interoperability and data security that can be trusted by all stakeholders; iii) is supported by a robust ethical and legal framework that is compliant with the EU General Data Protection Regulation (GDPR); iv) establishes a proper environment for the training of new generations of data and medical scientists; and v) stimulates research and innovation in transnational collaborations through public and private initiatives and partnerships funded by the EU through Horizon 2020 and Horizon Europe.
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| 4. |
- Papadopoulos, N G, et al.
(författare)
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Mechanisms of virus-induced asthma exacerbations: state-of-the-art. A GA2LEN and InterAirways document.
- 2007
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Ingår i: Allergy. - : Wiley. - 0105-4538 .- 1398-9995. ; 62:5, s. 457-70
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Forskningsöversikt (refereegranskat)abstract
- Viral infections of the respiratory tract are the most common precipitants of acute asthma exacerbations. Exacerbations are only poorly responsive to current asthma therapies and new approaches to therapy are needed. Viruses, most frequently human rhinoviruses (RV), infect the airway epithelium, generate local and systemic immune responses, as well as neural responses, inducing inflammation and airway hyperresponsiveness. Using in vitro and in vivo experimental models the role of various proinflammatory or anti-inflammatory mediators, antiviral responses and molecular pathways that lead from infection to symptoms has been partly unravelled. In particular, mechanisms of susceptibility to viral infection have been identified and the bronchial epithelium appeared to be a key player. Nevertheless, additional understanding of the integration between the diverse elements of the antiviral response, especially in the context of allergic airway inflammation, as well as the interactions between viral infections and other stimuli that affect airway inflammation and responsiveness may lead to novel strategies in treating and/or preventing asthma exacerbations. This review presents the current knowledge and highlights areas in need of further research.
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| 5. |
- Sabatier, Pierre, et al.
(författare)
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An integrative proteomics method identifies a regulator of translation during stem cell maintenance and differentiation
- 2021
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- To characterize molecular changes during cell type transitions, the authors develop a method to simultaneously measure protein expression and thermal stability changes. They apply this approach to study differences between human pluripotent stem cells, their progenies, parental and allogeneic cells. Detailed characterization of cell type transitions is essential for cell biology in general and particularly for the development of stem cell-based therapies in regenerative medicine. To systematically study such transitions, we introduce a method that simultaneously measures protein expression and thermal stability changes in cells and provide the web-based visualization tool ProteoTracker. We apply our method to study differences between human pluripotent stem cells and several cell types including their parental cell line and differentiated progeny. We detect alterations of protein properties in numerous cellular pathways and components including ribosome biogenesis and demonstrate that modulation of ribosome maturation through SBDS protein can be helpful for manipulating cell stemness in vitro. Using our integrative proteomics approach and the web-based tool, we uncover a molecular basis for the uncoupling of robust transcription from parsimonious translation in stem cells and propose a method for maintaining pluripotency in vitro.
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| 7. |
- Zubarev, Roman A., et al.
(författare)
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Identification of dominant signaling pathways from proteomics expression data
- 2008
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Ingår i: Journal of Proteomics. - : Elsevier BV. - 1874-3919. ; 71:1, s. 89-96
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Tidskriftsartikel (refereegranskat)abstract
- The availability of the results of high-throughput analyses coming from 'omic' technologies has been one of the major driving forces of pathway biology. Analytical pathway biology strives to design a 'pathway search engine', where the input is the 'omic' data and the output is the list of activated or dominant pathways in a given sample. Here we describe the first attempt to design and validate such a pathway search engine using as input expression proteomics data. The engine represents a specific workflow in computational tools developed originally for mRNA analysis (BMC Bioinformatics 2006, 7 (Suppl 2), S13). Using our own datasets as well as data from recent proteomics literature we demonstrate that different dominant pathways (EGF, TGF(beta), stress, and Fas pathways) can be correctly identified even from limited datasets. Pathway search engines can find application in a variety of proteomics-related fields, from fundamental molecular biology to search for novel types of disease biomarkers.
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