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  • 1
    ISSN: 0006-3592
    Keywords: immobilized cells ; abrasion ; mechanical stability ; fatigue ; Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: The mechanical stability of biocatalyst particles in bioreactors is of crucial importance for applications of immobilized-cell technology in bioconversions. The common methods for evaluation of the strength of polymer beads (mostly force-to-fracture or tensile tests) are, however, not yet proven to be relevant for the assessment of their mechanical stability in bioreactors. Therefore, we tested fracture properties of gel materials and investigated their relevance for abrasion in bioreactors. Abrasion of gel beads was assumed to be a continuous fracturing of the bead surface. At first, three rheological properties were considered: stress at fracture; strain at fracture; and the total fracture energy. If stress at fracture is the most important property, beads having a similar fracture energy, but a smaller stress at fracture, would abrade faster in a bioreactor than beads with a larger stress at fracture; if fracture energy the determining factor, beads that require less energy to fracture would abrade faster than those having a larger fracture energy for the same fracture stress. To determine this, beads of κ-carrageenan and agar (at two different polymer concentrations) were tested for abrasion in four identical bubble columns under the same operating conditions. Agar beads were expected to abrade faster than those of carrageenan because agar had either a lower stress at fracture or a lower fracture energy. However, no correlation between fracture properties and abrasion rate was found in any of the combinations tested. Carrageenan beads abraded faster than those of agar in all combinations. Furthermore, both the stress and strain at fracture of agar and carrageenan beads decreased during the run and those of carrageenan decreased faster, suggesting that the gels are liable to fatigue in different ways. This hypothesis was confirmed by oscillating experiments in which gel samples were subjected to repeated compressions below their fracture levels. Their resistance to compression clearly decreased with the number of oscillations. Fatigue is probably related to the development of microcracks and microfracture propagation within the material. We concluded that: (a) the use of tests based on bead rupture do not provide relevant information on the mechanical stability of gel beads to abrasion; and (b) abrasion of polymer beads is likely to be related to fatigue of the gel materials. © 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 56: 517-529, 1997.
    Additional Material: 9 Ill.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2023-12-14
    Description: The physiology of every living cell is regulated at some level by transporter proteins which constitute a relevant portion of membrane-bound proteins and are involved in the movement of ions, small and macromolecules across bio-membranes. The importance of transporter proteins is unquestionable. The prediction and study of previously unknown transporters can lead to the discovery of new biological pathways, drugs and treatments. Here we present PortPred, a tool to accurately identify transporter proteins and their substrate starting from the protein amino acid sequence. PortPred successfully combines pre-trained deep learning-based protein embeddings and machine learning classification approaches and outperforms other state-of-the-art methods. In addition, we present a comparison of the most promising protein sequence embeddings (Unirep, SeqVec, ProteinBERT, ESM-1b) and their performances for this specific task.
    Language: English
    Type: article , doc-type:article
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  • 3
    Publication Date: 2023-11-20
    Description: Computational approaches are practical when investigating putative peroxisomal proteins and for sub-peroxisomal protein localization in unknown protein sequences. Nowadays, advancements in computational methods and Machine Learning (ML) can be used to hasten the discovery of novel peroxisomal proteins and can be combined with more established computational methodologies. Here, we explain and list some of the most used tools and methodologies for novel peroxisomal protein detection and localization.
    Language: German
    Type: bookpart , doc-type:bookPart
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