4 research outputs found

    Characterization of Polymer Membranes by MALDI Mass-Spectrometric Imaging Techniques

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    For physical and chemical characterization of polymers, a wide range of analytical methods is available. Techniques like NMR and X-ray are often combined for a detailed characterization of polymers used in medical applications. Over the past few years, MALDI mass-spectrometry has been developed as a powerful tool for space-resolved analysis, not least because of its mass accuracy and high sensitivity. MALDI imaging techniques combine the potential of mass-spectrometric analysis with imaging as additional spatial information. MALDI imaging enables the visualization of localization and distribution of biomolecules, chemical compounds, and other molecules on different surfaces. In this study, surfaces of polymeric dialyzer membranes, consisting of polysulfone (PS) and polyvinylpyrrolidone (PVP), were investigated, regarding chemical structure and the compound’s distribution. Flat membranes as well as hollow fiber membranes were analyzed by MALDI imaging. First, analysis parameters like laser intensity and laser raster step size (spatial resolution in resulting image) were established in accordance with polymer’s characteristics. According to the manufacturing process, luminal and abluminal membrane surfaces are characterized by differences in chemical composition and physical characteristics. The MALDI imaging demonstrated that the abluminal membrane surface consists more of polysulfone than polyvinylpyrrolidone, and the luminal membrane surface displayed more PVP than PS. The addition of PVP as hydrophilic modifier to polysulfone-based membranes increases the biocompatibility of the dialysis membranes. The analysis of polymer distribution is a relevant feature for characterization of dialysis membranes. In conclusion, MALDI imaging is a powerful technique for polymer membrane analysis, regarding not only detection and identification of polymers but also localization and distribution in membrane surfaces

    Bioinformatic analysis of identified biomarkers.

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    <p><b>A.</b> Gene ontology analysis shows proteins involved in fatty acid binding. platelet degranulation. serine protease inhibitor activity and hydrogen peroxide catabolic processes. <b>B</b> Interaction network of identified biomarker candidates involving 18 out of the 19 proteins. Proteins involved in inflammation. acute phase response (including cellular adhesion). signaling via lipid-mediated pathways (including transport) and activation of proteolytic cascades. as well as transcriptional activity are indicated. Red diamonds indicate proteins which are significant after correction for multiple testing. and grey ones are the remainder of the query set. Circles indicate gap-fillers which were added to connect proteins via protein-protein interactions. Direct association between the significant biomarker set are indicated by a bold line. and relate to immune response (immunoglobulin cluster). protease inhibitor activity. and an activation of the peroxisome proliferator-activated receptor signaling pathway/CDC42 signal transduction pathway. as suggested through APOA1 interactions. <b>C.</b> Kyoto encyclopedia of genes and genomes pathway analysis. Statistically relevant biomarker proteins were mapped onto KEGG pathway maps and showed an involvement of fibril formation and inhibition of fibrinolysis in the coagulation cascade and association with arachidonic acid metabolism.</p

    Proteins in vitreous humor detected by CE-MS and identified by LC-MS/MS analysis.

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    <p>*Uniprot accession numbers that can be found on <a href="http://www.uniprot.org" target="_blank">www.uniprot.org</a>; ** Number of peptides observed by CE-MS analysis and sequenced by LC-MS/MS for each identified protein; *** Percentage of peptide coverage of the protein sequence; ****, Number of peptides observed by CE-MS and sequenced by LC-MS/MS in controls or cases.</p
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