41 research outputs found

    Parametric Formulation of the Floodable Length Curve: Application Case to Offshore Patrol Vessels

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    The residual buoyancy of vessels after damage has a fundamental role in their survivability and it is implemented through adequate ship internal subdivision. Traditionally the number and the position of transverse watertight bulkheads are selected for most ships early in the design phase by means of the “floodable length curve” coupled with the concept of “margin line”. However, for naval vessels, it is more and more common during the acquisition process to explore a wide domain of feasible ships, identified with the assistance of automated processes and assessed also in terms of capabilities, among which is survivability. The generation and the comparison of a considerable number of different ship configurations is very time consuming. Therefore recourse to a parametric expression of the floodable length curve is considered to be a very efficient approach and would thus enable characterisation of the ship, in terms of survivability performance. In this paper such an approach is presented, using an offshore patrol vessel (OPV) as the case study

    Idebenone in senile dementia of Alzheimer type: a multicentre study.

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    Idebenone is a new cerebro-active drug, effective in dementia disorders, particularly indicated in primary degenerative dementias, i.e. Alzheimer's disease. This new molecule acts as an electron trapper and a free radical scavenger protecting mitochondrial membranes from lipid peroxidation. A multicentric, double-blind trial of idebenone (45 mg twice daily orally) vs. placebo was carried out on 102 elderly patients affected by Alzheimer-type dementia of mild or moderate severity. Idebenone was administered for 4 consecutive months, 45 mg twice daily. Clinical evaluations were performed at the time of enrollment (t0) and monthly thereafter (t30, t60, t90 and t120) and at follow-up (t150 ). Tolerability to idebenone treatment was good and was associated with a statistically significant improvement of memory, attention and behaviour. It is worthwhile noting that these cognitive and behavioral findings were observed after the first month of treatment with enhancement evident in the following period

    KnowVolution: Redesigning enzymes for innovations

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    Directed evolution has matured in academia and industry to a routinely applied algorithm to tailor enzyme properties1 to match especially demands in synthesis and material science. In order to free directed enzyme evolution from methodological restraints and to efficiently explore its potential, one has to balance time requirements for a directed evolution campaign, the number of generated enzyme variants, and limitations in state of the art screening technologies. For instance, saturation mutagenesis of six amino acid positions in an enzyme, which usually consists of \u3e50 amino acids, yields 64 million (206) different enzyme variants. The latter represents the upper throughput for activity-based screening systems2. In essence, protein engineers have to accept that they will not be able to sample through the theoretical obtainable sequence space of enzyme variants and smarter strategies are required for efficient directed enzyme evolution. The KnowVolution (Knowledge gaining direct evolution)3 approach represents such a directed evolution 2.0 strategy, which identifies in four phase with limited screening efforts, significantly improved enzymes variants and ensures a molecular understanding of improved enzyme properties. Three out of six in a review reported KnowVolution campaigns3 were commercialized by industrial partners; thereby limiting the number of substitutions turned out to be a key prerequisite for maintaining thermal resistance, process stability and selectivity. In addition, directed enzyme evolution by random mutagenesis will be compared to improvements that are obtainable with a variant library that contains all natural possible diversity with ONE amino acid exchange (SSM library)4. The comparison of 3000 mutations from random mutagenesis libraries with the SSM library taught us how many of the natural occurring beneficial positions are obtainable or unobtainable by state of art methodologies in directed evolution and provided first insights on general design principles to improve enzymatic resistance in organic cosolvents4 and ionic liquids4. References: (1) a.Shivange, A. V., Marienhagen, J., Mundhada, H., Schenk, A., Schwaneberg, U. (2009). Curr. Opin. Chem. Biol. 13, 19. b.Ruff, A. J., Dennig, A., Schwaneberg, U. (2013). FEBS J. 280, 2961. (2) a.Körfer, G., Pitzler, C., Vojcic, L., Martinez, R., Schwaneberg, U. (2016). Scientific Reports, 6, 1-12. b.Lülsdorf, N., Pitzler, C., Biggel, M., Martinez, R., Vojcic, L., Schwaneberg, U. (2015). Chem. Commun. 51, 8679. c.Ruff, A. J., Dennig, A., Wirtz, G., Blanusa, M., Schwaneberg, U. (2012). ACS Catalysis 2, 2724. (3) Cheng, F., Zhu, L., Schwaneberg, U. (2015). Chem. Commun. 51, 9760. a.Zhao, J., Frauenkron-Machedjou, V. J., Kardashliev, T., Ruff, A. J., Zhu, L., Bocola, M., Schwaneberg, U. (2017). Appl. Microbiol. Biotechnol., 2017, DOI: 10.1007/s00253-016-8035-1. b.Frauenkron-Machedjou, V. J., Fulton, A., Zhu, L., Bocola, M., Zhu, L., Jaeger, K.-E., Schwaneberg, U. (2015). ChemBioChem, 16, 937-945. c.Zhao, J., Kardashliev, T., Ruff, A. J., Bocola, M., Schwaneberg, U. (2014). Biotechnol. Bioeng. 111, 2380
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