967 research outputs found

    Engineering of camel chymosin for improved cheese properties

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    More than 20 Mio tons of cheese are produced world-wide per year. By improving cheese yield and quality through process optimization, the amount of milk needed for manufacturing can be reduced significantly. Chymosin, an aspartic acid protease, is initiating milk coagulation in cheese manufacturing by cleaving off the glycomacropeptide (GMP) from the surface of casein micelles. Non-specific proteolysis of casein molecules by chymosin during this milk clotting process releases soluble peptides into the whey, resulting in protein losses from the cheese. The ratio between specific clotting activity (C) and non-specific proteolysis (P) of a coagulant can therefore be used as predictor for cheese yield. During ripening of the cheese, remaining coagulant continues proteolytic break-down of the caseins with significant impact on cheese properties. While the main proteolytic activity, the release of N-terminal peptides from alphaS1 casein (alphaS1-N), is associated with cheese softening and loss of firmness, cleavage of the C-terminal end of beta casein (beta-C) contributes to unwanted bitterness of the cheese [1]. The chymosin from Bos taurus (bovine chymosin) is traditionally used as milk coagulant in cheese manufacture. However, the homologous enzyme from Camelus dromedarius (camel chymosin) has been shown to be a superior alternative for various cheese types, since it reveals higher specific activity (C) and specificity (C/P) for the milk clotting reaction [2], as well as lower alphaS1 and beta casein proteolysis during ripening (Fig. 1). Please click Additional Files below to see the full abstract

    Multidimensional engineering of Chymosin for efficient cheese production by machine learning guided directed evolution

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    The global cheese market today exceeds $100B/year. Chymosin (a.k.a. rennin) is an aspartic endopeptidase produced by the stomach lining of new-born mammals. During cheese production chymosin is added to the milk where it cleaves the glycomacropeptide (GMP) from the surface of casein micelles to initiate milk coagulation. Current commercial recombinant chymosin enzymes derived from Bos taurus (cow) or Camelus dromedarius (camel) are limited in their proteolytic specificity leading to incomplete milk-to-cheese conversion. Increasing the chymosin specificity for GMP cleavage would significantly decrease the amount of milk needed for cheese production thereby reducing cost and decreasing environmental footprint of the dairy industry. Separate from milk coagulation, chymosin dependent release of N-terminal peptides from alphaS1 casein during cheese ripening leads to unwanted softening, accompanied with cheese loss during industrial processing such as slicing and shredding. Furthermore, chymosin dependent cleavage of the C-terminal end of beta casein contributes to unwanted bitterness of the cheese. Improvement of chymosin proteolytic specificity in both milk coagulation and cheese ripening is consequently of high commercial relevance. Please click Additional Files below to see the full abstract

    Quantum limited sensitivity of SET-based displacement detectors

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    We consider a model of a quantum-mechanical resonator capacitively coupled to a single electron transistor (SET). The tunnel current in the SET is modulated by the vibrations of the resonator, and thus the system operates as a displacement detector. We analyze the effect of the back-action noise of charge fluctuations in the SET onto the dynamics of the resonator and evaluate the displacement sensitivity of the system. The relation between the "classical" and "quantum" parts of the SET charge noise and their effect on the measured system are also discussed.Comment: 4 pages, 2 eps fig

    Well-being, multidisciplinary work and a skillful team:essential elements of successful treatment in severe challenging behavior in dementia

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    Objective: Conceptualize successful treatment of persons with dementia and severe challenging behavior as perceived by professionals. Methods: In this concept mapping study 82 experts in dementia care participated. The study followed two phases of data collection: (1) an online brainstorm where participants completed the focus prompt: ‘I consider the treatment of people with severe challenging behavior in dementia successful if.’; (2) individual sorting and rating of the collected statements followed by data analysis using multidimensional scaling and hierarchical cluster analysis, resulting in a concept map. Results: Three clusters were identified, the first addressing treatment outcomes and the latter two addressing treatment processes, each divided into sub-clusters: (1) well-being, comprising well-being of the person with dementia and all people directly involved; (2) multidisciplinary analysis and treatment, comprising multidisciplinary analysis, process conditions, reduction in psychotropic drugs, and person-centered treatment; and (3) attitudes and skills of those involved, comprising consistent approach by the team, understanding behavior, knowing how to respond to behavior, and open attitudes. Conclusions: Successful treatment in people with dementia and severe challenging behavior focuses on well-being of all people involved wherein attention to treatment processes including process conditions is essential to achieve this.</p

    Well-being, multidisciplinary work and a skillful team:essential elements of successful treatment in severe challenging behavior in dementia

    Get PDF
    Objective: Conceptualize successful treatment of persons with dementia and severe challenging behavior as perceived by professionals. Methods: In this concept mapping study 82 experts in dementia care participated. The study followed two phases of data collection: (1) an online brainstorm where participants completed the focus prompt: ‘I consider the treatment of people with severe challenging behavior in dementia successful if.’; (2) individual sorting and rating of the collected statements followed by data analysis using multidimensional scaling and hierarchical cluster analysis, resulting in a concept map. Results: Three clusters were identified, the first addressing treatment outcomes and the latter two addressing treatment processes, each divided into sub-clusters: (1) well-being, comprising well-being of the person with dementia and all people directly involved; (2) multidisciplinary analysis and treatment, comprising multidisciplinary analysis, process conditions, reduction in psychotropic drugs, and person-centered treatment; and (3) attitudes and skills of those involved, comprising consistent approach by the team, understanding behavior, knowing how to respond to behavior, and open attitudes. Conclusions: Successful treatment in people with dementia and severe challenging behavior focuses on well-being of all people involved wherein attention to treatment processes including process conditions is essential to achieve this.</p
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