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  • 1
    Online Resource
    Online Resource
    San Diego :Elsevier Science & Technology,
    Keywords: Carbohydrates-Periodicals. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (66 pages)
    Edition: 1st ed.
    ISBN: 9780128209967
    Series Statement: Issn Series
    DDC: 547.78
    Language: English
    Note: Intro -- Advances in Carbohydrate Chemistry and Biochemistry -- Copyright -- Contents -- Contributors -- Preface -- Reference -- Chapter One: Mechanism of multivalent glycoconjugate-lectin interaction: An update -- 1. Background and historical perspective -- 2. Mechanism of multivalent lectin binding -- 2.1. Examples and mechanism of intramolecular (face-to-face) binding -- 2.1.1. The asialoglycoprotein receptor -- 2.1.2. Shiga-like toxin and cholera toxin -- 2.1.3. Vancomycin -- 2.2. Examples and mechanism of intermolecular (cross-linking) binding -- 2.2.1. Studies of multivalent glycans binding to lectins ConA and DGL -- 2.2.2. ITC determined n values, structural valency, and functional valency -- 2.2.3. Binding enthalpies increase in direct proportion to the valency of multivalent glycans -- 2.2.4. Binding entropy does not directly increase in proportion to the valency of multivalent glycans -- 2.2.5. The thermodynamic basis for enhanced affinities of multivalent analogs -- 2.2.6. The epitopes of a multivalent glycan possess a gradient of decreasing microscopic affinity constants -- 2.3. Binding of lectins to multivalent mucins -- 2.3.1. Mucins: Glycoproteins that are heavily O-glycosylated -- 2.3.2. The mechanism of lectin-mucin interaction -- 2.3.3. Affinity of lectin-mucin interaction is proportional to the length of mucins -- 2.3.4. Mechanisms of binding of lectins to mucins: The ``bind-and-jump´´ model -- 2.4. Multivalent interactions between lectins and globular glycoproteins -- 2.5. Multivalency of glycosaminoglycans (GAGs) and proteoglycans (PGs) -- 2.5.1. Glycosaminoglycans (GAGs) and proteoglycans (PGs) engage in multivalent interactions with human galectin-3 (Gal-3) -- 2.5.2. CSA and CSC, not heparin and CSB, are multivalent ligands of Gal-3. , 2.5.3. Affinity of Gal-3 depends on the chain length of GAGs: The ``bind and jump´´ mechanism -- 2.6. Scaffolds of glycoconjugates play crucial roles in multivalent interactions -- 2.6.1. Scaffolds provide physical platforms to which glycan chains are covalently linked -- 2.6.2. Lectin binding entropy becomes more favorable when a free glycan is covalently attached to a protein scaffold -- 2.6.3. Structures of protein scaffolds may limit glycan density-dependent affinity effects -- 2.6.4. Entropic advantage of glycosylation -- 2.6.5. Scaffolds of glycoconjugates play a regulatory role in the kinetics of lattice formation -- 2.6.6. Scaffolds can diversify the functions of glycoconjugates and their binding partners (lectins) -- 2.6.7. Beyond affinity and valence effects -- 2.7. Multivalency and non-covalent cross-linking -- 2.7.1. Binding of multivalent glycoconjugates/glycans to oligomeric lectins leads to the formation of non-covalent crossl ... -- 2.7.2. The structures of the multivalent glycans and lectins determines their cross-linking properties -- 3. Current and future challenges -- 4. Concluding remarks -- Acknowledgments -- References -- Chapter Two: Multivalent lectin-carbohydrate interactions: Energetics and mechanisms of binding -- 1. Introduction -- 2. Mucins: Background -- 3. Binding of lectins to mucins -- 3.1. Affinities of SBA and VML for mucins -- 3.2. Thermodynamics of SBA binding Tn-PSM -- 3.3. Thermodynamics of SBA binding 81-mer Tn-PSM -- 3.4. Thermodynamics of SBA binding 38/40-mer Tn-PSM -- 3.5. Thermodynamics of SBA binding Fd-PSM -- 3.6. Thermodynamics of VML binding Tn-PSM -- 3.7. Thermodynamics of VML binding 81-mer Tn-PSM and 38/40-mer Tn-PSM -- 3.8. Thermodynamics of VML binding Fd-PSM -- 4. Mechanisms of binding of SBA and VML to PSM: The bind and jump model -- 5. Thermodynamics of lectin-mucin cross-linking interactions. , 5.1. Hill plots show evidence of increasing negative cooperativity -- 5.2. Analysis of the stoichiometry of binding of SBA to the mucins -- 5.3. Cross-linking of lectins with the mucins correlate with decreasing favorable entropy of binding -- 6. Conclusions and perspective -- 6.1. The bind and jump model for lectin-mucin interactions -- 6.2. Implications of increasing negative cooperativity and decreasing favorable binding entropy of lectins-mucin cross-li ... -- References -- Author index -- Subject index.
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of industrial microbiology and biotechnology 12 (1993), S. 156-161 
    ISSN: 1476-5535
    Keywords: Predictive microbiology ; Modeling ; Clostridium botulinum ; Challenge test ; Risk analysis ; HACCP ; Food safety
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: Summary The effectiveness of a preservative system to prevent the growth ofClostridium botulinum can be expressed as the probability (P) that not even a single spore will be able to grow and produce toxin. Commerical canning processes for foods have been based upon this principle since the early 1920s. The safety of many current food marketing concepts depends on product formulation, processing, packaging and distribution variables. Direct measurement ofC. botulinum growth in a food system is difficult. Researchers have relied upon bioassay for botulinum toxin detection and Most Probable Number (MPN) techniques to quantifyC. botulinum growth in experimental food systems. The methods used to estimateP for a single spore to initiate growth will lead to a discussion on the use ofP as a dependent variable in predictive models. Modeling the effects of intrinsic and extrinsic processing variables on food safety will be presented.
    Type of Medium: Electronic Resource
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