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- Delsing, Louise, et al.
(författare)
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Barrier properties and transcriptome expression in human iPSC-derived models of the blood-brain barrier
- 2018
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Ingår i: Stem Cells. - : AlphaMed Press, Inc.. - 1066-5099 .- 1549-4918. ; 36:12, s. 1816-1827
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Tidskriftsartikel (refereegranskat)abstract
- Cell-based models of the blood-brain barrier (BBB) are important for increasing the knowledge of BBB formation, degradation and brain exposure of drug substances. Human models are preferred over animal models because of inter-species differences in BBB structure and function. However, access to human primary BBB tissue is limited and has shown degeneration of BBB functions in vitro. Human induced pluripotent stem cells (iPSCs) can be used to generate relevant cell types to model the BBB with human tissue. We generated a human iPSC-derived model of the BBB that includes endothelial cells in co-culture with pericytes, astrocytes and neurons. Evaluation of barrier properties showed that the endothelial cells in our co-culture model have high transendothelial electrical resistance, functional efflux and ability to discriminate between CNS permeable and non-permeable substances. Whole genome expression profiling revealed transcriptional changes that occur in co-culture, including upregulation of tight junction proteins such as claudins and neurotransmitter transporters. Pathway analysis implicated changes in the WNT, TNF and PI3K-Akt pathways upon co-culture. Our data suggests that co-culture of iPSC-derived endothelial cells promotes barrier formation on a functional and transcriptional level. The information about gene expression changes in co-culture can be used to further improve iPSC-derived BBB models through selective pathway manipulation.
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- Jensen, Poul Erik H., et al.
(författare)
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Detection and kinetics of persistent neutralizing anti-interferon-beta antibodies in patients with multiple sclerosis : Results from the ABIRISK prospective cohort study
- 2019
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Ingår i: Journal of Neuroimmunology. - : Elsevier. - 0165-5728 .- 1872-8421. ; 326, s. 19-27
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Tidskriftsartikel (refereegranskat)abstract
- Two validated assays, a bridging ELISA and a luciferase-based bioassay, were compared for detection of anti-drug antibodies (ADA) against interferon-beta (IFN-β) in patients with multiple sclerosis. Serum samples were tested from patients enrolled in a prospective study of 18 months. In contrast to the ELISA, when IFN-β-specific rabbit polyclonal and human monoclonal antibodies were tested, the bioassay was the more sensitive to detect IFN-β ADA in patients' sera. For clinical samples, selection of method of ELISA should be evaluated prior to the use of a multi-tiered approach. A titer threshold value is reported that may be used as a predictor for persistently positive neutralizing ADA.
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- Synnergren, Jane, 1967-, et al.
(författare)
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Integration of Biomedical Big Data Requires Efficient Batch Effect Reduction
- 2018
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Ingår i: 10th International Conference on Bioinformatics and Computational Biology (BICOB). - 9781943436118 - 9781510858664 ; , s. 76-82
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Konferensbidrag (refereegranskat)abstract
- Efficiency in dealing with batch effects will be the next frontier in large-scale biological data analysis, particularly when involving the integration of different types of datasets. Large-scale omics techniques have quickly developed during the last decade and huge amounts of data are now generated, which has started to revolutionize the area of medical research. With the increase in the volume of data across the whole spectrum of biology, problems related to data analytics are continuously increasing as analysis and interpretation of these large volumes of molecular data has become a real challenge. Tremendous efforts have been made to obtain data from various molecular levels and the most recent trends show that more and more researchers now are trying to integrate data of various molecular types to inform hypotheses and biological questions. Tightly connected to this work are the batch-related biases that commonly are apparent between different datasets, but these problems are often not tackled. In present study the ComBat algorithm was applied and evaluated on two different data integration problems. Results show that the batch effects present in the integrated datasets efficiently could be removed by applying the ComBat algorithm.
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