| 1. |
- Fort, A, et al.
(författare)
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Biohybrid devices and encapsulation technologies for engineering a bioartificial pancreas
- 2008
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Ingår i: Cell transplantation. - : SAGE Publications. - 0963-6897 .- 1555-3892. ; 17:9, s. 997-1003
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Tidskriftsartikel (refereegranskat)abstract
- The use of cell-based treatments in the field of metabolic organs, particularly the pancreas, has seen tremendous growth in recent years. The transplantation of islet of Langerhans cells for the treatment of type 1 diabetes mellitus (T1DM) has allowed for natural glycemic control for patients plagued with hypoglycemia unawareness. The transplantation of islet cells into the portal vein of the liver, however, has presented challenges to the survival of the cells due to inflammation, vascularization, the need for systemic immunosuppression, and physical stress on the graft. New advances in the engineering of appropriate biohybrid devices and encapsulation technologies have led to promising alternatives to traditional methods.
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| 2. |
- Sundstrom, Jeffrey M., et al.
(författare)
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Phosphorylation site mapping of endogenous proteins : a combined MS and bioinformatics approach
- 2009
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 8:2, s. 798-807
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Tidskriftsartikel (refereegranskat)abstract
- We present a novel approach that combines MALDI-TOF profile analysis and bioinformatics-based inclusion criteria to comprehensively predict phosphorylation sites on a single protein of interest from limiting sample. It is technologically difficult to unambiguously identify phosphorylated residues, as many physiologically important phosphorylation sites are of too low abundance in vivo to be unambiguously assigned by mass spectrometry. Conversely, phosphorylation site prediction algorithms, while increasingly accurate, nevertheless overestimate the number of phosphorylation sites. In this study, we show that MODICAS, an MS data management and analysis tool, can be effectively merged with the bioinformatics attributes of residue conservation and phosphosite prediction to generate a short list of putative phosphorylation sites that can be subsequently verified by additional methodologies such as phosphospecific antibodies or mutational analysis. Therefore, the combination of MODICAS driven MS data analysis with bioinformatics-based filtering represents a substantial increase in the ability to putatively identify physiologically relevant phosphosites from limited starting material.
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