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Research project (§ 26 & § 27)
Duration
: 2022-10-15 - 2024-07-31
The HIV-1 envelope spike (Env) bears a cluster of oligomannose-type glycans that is a target for broadly neutralizing antibodies (bnAbs). However, while nAbs to this cluster, dubbed the high-mannose patch (HMP), are known to develop in at least some HIV-infected individuals, past attempts to elicit similar antibodies by immunization have been largely unsuccessful. Most previous approaches have involved presenting clusters of natural or synthetic high-mannose glycans on the surface of carrier proteins. The difficulty in eliciting high-mannose-targeting nAbs by immunization is believed to relate, at least in part, to the ‘self’ nature of the targeted glycans.
The approach that we are pursuing is based on the scientific premise that antigenic mimicry of mammalian host structures can stimulate cross-reactive antibodies if such mimics are presented in the proper ‘foreign’ milieu. Our overarching hypothesis is that, upon immunization, an antigenic mimic of mammalian oligomannose will more readily elicit antibodies that bind the HMP than native or synthetic oligomannose. In our progress report, we show that a CRM197-conjugate of our lead oligomannose mimetic is bound with high avidity by various HMP-specific bnAbs as well as their germline precursors. Furthermore, human antibody transgenic mice immunized with this neoglycoconjugate yield antibodies that bind recombinant HIV-1 SOSIP trimers, albeit only when the conjugate is formulated in the TLR4-stimulating Th1-adjuvant GLA-SE.
We expect our findings to help sharpen our strategy and critically inform the pursuit of future preclinical studies. Results from this research could inform other HIV vaccine design strategies also.
Research project (§ 26 & § 27)
Duration
: 2023-04-01 - 2032-03-31
This project investigates different usage modes of plant-derived antioxidants, such as tocopherol derivatives or polyphenols, from various biorefinery scenarios. A focus lies on lipophilic plant extractives on one side, and tannins (gallotannins and ellagitannins) on the other side.
The antioxidants will be tested first as stabilizers in the Lyocell process (cellulose fiber manufacture), where they are supposed to limit homolytic and hetrolytic side reactions, especially the autocatalytic degradation of the solvent N-methylmorpholine-N-oxide, while at the same time limiting the generation of strong chromophores.
Research project (§ 26 & § 27)
Duration
: 2022-06-01 - 2025-05-31
The final sensorial quality of a wine is the result of a multitude of interactions between all the chemical components within the wine and specific environmental factors such as the temperature of the wine. Since influenced by numerous factors such as grape varieties, growing conditions, climate change, yeast strains, wine making technologies, human experiences, the evaluation and preservation of wine quality – in terms of reproducibility from year to year - is nowadays the main challenge for both wine producers and wine science community. Viticultural practices aim primarily at producing high quality grapes that would reflect varietal flavours and aromas and/or characters typical for a specific region or terroir. In Austria, Districtus Austriae Controllatus (DAC) is a classification for regionally typical quality wine that provides products of distinction in wine market. An accurate evaluation and assessment of the wine quality, identity and typicity is of high significance for vintners to perform proper wine classification and target marketing.
The aim of this project is on grape and wine quality evaluation, and regional typical quality characterization and prediction using elemental and sensory analysis, non-targeted and targeted metabolomics, spectroscopic approaches, and artificial intelligence. Grape quality is the most important factor for making high quality wine and some grape metabolites can have a strong relation to the wine quality. The relationship between the grape metabolites and the wine quality will be explored using non-targeted metabolomics and spectroscopic approaches and wine quality prediction models generated by artificial intelligence and machine learning algorithms. Of particular focus in this project is providing detailed chemical characterization that elucidates the influence of the Viennese wine growing region (origin) on Viennese Gemischter Satz DAC and Grüner Veltliner.
As final output of the project, software, apps and a unique quality mark tag will be developed, for wine quality prediction and authenticity assessment based on established databases. This solution will be designed and developed to prove the identity and authenticity of each bottle and trace them. In turn, the outcomes of this project aim to both support origin marketing and future maintenance of wine production processes and wine quality in Vienna.