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Type: Article × Subject: Multivariant analysis ×

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    Detection of Protein Glycosylation Using Tip-Enhanced Raman Scattering
    (Columbus, Ohio : American Chemical Society, 2016) Cowcher, David P.; Deckert-Gaudig, Tanja; Brewster, Victoria L.; Ashton, Lorna; Deckert, Volker; Goodacre, Royston
    The correct glycosylation of biopharmaceutical glycoproteins and their formulations is essential for them to have the desired therapeutic effect on the patient. It has recently been shown that Raman spectroscopy can be used to quantify the proportion of glycosylated protein from mixtures of native and glycosylated forms of bovine pancreatic ribonuclease (RNase). Here we show the first steps toward not only the detection of glycosylation status but the characterization of glycans themselves from just a few protein molecules at a time using tip-enhanced Raman scattering (TERS). While this technique generates complex data that are very dependent on the protein orientation, with the careful development of combined data preprocessing, univariate and multivariate analysis techniques, we have shown that we can distinguish between the native and glycosylated forms of RNase. Many glycoproteins contain populations of subtly different glycoforms; therefore, with stricter orientation control, we believe this has the potential to lead to further glycan characterization using TERS, which would have use in biopharmaceutical synthesis and formulation research.
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    Pre- And post-adoption beliefs about the diffusion and continuation of biogas-based cooking fuel technology in Pakistan
    (Basel : MDPI AG, 2019) Yasmin, N.; Grundmann, P.
    A high level of acceptance and adoption is necessary to facilitate the widespread utilization of renewable energy technologies for cooking, as such utilization is essential for displacing the population's massive dependence on fossil fuels and solid biomass. Economic and demographic aspects have been the focus of recent literature in exploring the adoption phenomenon of biogas technology. However, literature to date has given little attention to the behavioral factors and the perceptions of the end-users. Our study does not only include behavioral factors, but it employs a hybrid model to explore the continued attentions of users based on their post-adoption beliefs and performance expectations. Using a survey conducted in Pakistan in 2017, the study conducts a multivariate analysis through structural equation modeling to measure the effect of pre- and post-adoption beliefs and expectation on adoption and the continuing intention of households towards biogas technology. Results show that the acceptance of the households towards biogas technology is highly influenced by their perceptions on the benefits, as well as their trust in the technology. The perceived cost and risk attached to the technology are found to be negatively correlated with the acceptance. Households' intentions to continue the use of biogas technology is highly influenced by the satisfaction level of the users of biogas technology. With the integrated model of adoption and continuation, the study illustrates the dynamic process in obtaining a deeper understanding of a user's behavior to better formulate the policies for increasing the rate of technology adoption.