In the present work, the combination of chemical and enzymatic methods to obtain neoglycoproteins is described. Three bovine serum albumin (BSA)-conjugates, BSA-GalNAcα-, BSA-Gal(β1-3)GalNAc(α-, and ...BSA-Neu5Ac(α2-3)Gal(β1-3)GalNAc(α-, were prepared. αGalNAc derivatives were galactosylated employing crude β-galactosidase from bovine testes. The use of oversaturated donor solutions (pNPβGal) enhanced the yields up to 60%. This method was verified using divalent structures as acceptors, that rendered di- and tri-galactosylated products. Further treatment of the disaccharides with CMP-Neu5Ac and α2-3 sialyltransferase from pork liver led to formation of trisaccharides. Finally, mono-, di-, and trisaccharides were coupled to BSA employing a thiolic group introduced into the protein for Michael addition to a maleinimide group in the spacer-arm of the saccharide components. The results were monitored by HPLC and MALDI-TOF.
5-Azido-3-oxa-pentyl beta-D-galactopyranoside was prepared from diethylene glycol monochlorohydrin and used as a model of oligosaccharide hapten. After deprotection, a series of amides bearing ...thiophilic groups had been obtained through the terminal amino function and essayed in coupling reactions with thiolated BSA. Also several Lewis human blood group oligosaccharides had been conjugated with thiolated BSA demonstrating the usefulness of the methodology.
In this study β1–3 linked analogues of the T-antigen determinant were synthesized in preparative scale by transgalactosylation using β-galactosidase from bovine testes to give synthetic antigens. ...Acceptors with modifications of the sugar residue such as α-glycosylated spacers, as well as GlcNAc-αOR- and 2dGal-αOR-substrates opened further possibilities for galactosylation.
Modified acceptor substrates opened further possibilities for the galactosidase-catalyzed synthesis of bioactive disaccharides using β-galactosidase from bovine testes.
The National COVID-19 Chest Imaging Database (NCCID) is a centralized UK database of thoracic imaging and corresponding clinical data. It is made available by the National Health Service Artificial ...Intelligence (NHS AI) Lab to support the development of machine learning tools focused on Coronavirus Disease 2019 (COVID-19). A bespoke cleaning pipeline for NCCID, developed by the NHSx, was introduced in 2021. We present an extension to the original cleaning pipeline for the clinical data of the database. It has been adjusted to correct additional systematic inconsistencies in the raw data such as patient sex, oxygen levels and date values. The most important changes will be discussed in this paper, whilst the code and further explanations are made publicly available on GitLab. The suggested cleaning will allow global users to work with more consistent data for the development of machine learning tools without being an expert. In addition, it highlights some of the challenges when working with clinical multi-center data and includes recommendations for similar future initiatives.
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