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  • 1
    Online Resource
    Online Resource
    Phenolic Compounds : Types, Effects and Research. (2017)
    Hauppauge :Nova Science Publishers, Incorporated,
    Details
    Keywords: Phenols. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (259 pages)
    Edition: 1st ed.
    ISBN: 9781536120547
    Series Statement: Analytical Chemistry and Microchemistry
    URL: https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=4882765
    DDC: 663/.2
    Language: English
    Note: Intro -- Contents -- Preface -- Chapter 1 -- Natural Phenolic Compounds and Parkinson's Disease -- Abstract -- 1. Introduction -- 2. Parkinson's Disease (PD) -- 3. In Vitro and In Vivo Neurotoxic-Based Models -- 4. Bioavailability of Phenolic Compounds and Metabolites in Brain -- 5. Relationship between Flavonoids and Parkinson's Disease -- 6. Mechanism of Protective Effects of Flavonoids in Neurodegeneration Diseases -- 6.1. Antioxidant Properties -- 6.2. Modulation of Cell Signaling Pathways -- 6.2.1. PI3K/Akt Pathway -- 6.2.2. ERK1/2 Pathway -- 6.2.3. PKC Pathway -- 6.2.4. JNK and p38 Pathway -- 6.3. Anti-Inflammatory Properties -- 6.4. Cerebrovascular Function Improvement -- Conclusion -- References -- Chapter 2 -- Understanding the Relationship between Wine Phenolic Compounds and Sensory Properties: Bitterness and Astringency -- Abstract -- 1. Grape Phenolic Compounds -- 2. Relevance of Phenolic Compounds -- 2.1. Phenolic Compounds and Human Health -- 2.2. Phenolic Compounds and Wine -- 3. Wine Astringency Mouthfeel and Bitterness -- 3.1. Astringency -- 3.2. Bitterness -- 4. Wine Sensory Interactions -- 4.1. Taste-Aroma Interactions -- 4.2. Taste-Taste and Taste-Astringency Interactions -- Conclusion -- References -- Chapter 3 -- Bioactive Phenolic Compounds: Extraction Procedures and Methods of Analysis -- Abstract -- 1. Phenolic Compounds -- 1.1. Flavonoids -- 1.2. Non-Flavonoids -- 2. Overview of Methodologies for Extraction and Analysis of Phenolic Compounds -- 2.1. Extraction Methods -- 2.2. Spectrophotometric Methods -- 2.2.1. Total Phenolic Compounds -- 2.2.2. Tannins -- 2.2.3. Anthocyanins -- 2.2.4. Ortho-Dyphenols -- 2.3. Chromatographic Methods -- 2.4. Other Methods -- 3. Antioxidant Capacity -- 4. Overview of Methodologies for the Analysis of the Antioxidant Capacity -- 4.1. Methods Using SET Reaction Mechanisms. , 4.1.1. Radical 2,2-Diphenyl-1-Picrylhydrazyl (DPPH) -- 4.1.2. Trolox Equivalent Antioxidant Capacity (TEAC) -- 4.1.3. Ferric Reducing Antioxidant Power (FRAP) -- 4.1.4. Copper Reduction Assay (CUPRAC) -- 4.2. Methods Using HAT Reaction Mechanisms -- 4.2.1. Total Radical-Trapping Antioxidant Parameter (TRAP) -- 4.2.2. Oxygen Radical Absorbance Capacity (ORAC) -- 4.2.3. Total Oxidant Scavenging Capacity (TOSC) -- 4.2.4. Crocin or Beta-Carotene Bleaching -- 4.2.5. Chemiluminescence (CL) -- 5. Conclusion -- References -- Chapter 4 -- Metabolite Profiling of Chlorogenic Acid Derivatives after the Ingestion of Coffee -- Abstract -- 1. Introduction -- 2. Materials and Methods -- 2.1. Chemicals -- 2.2. Study Design -- 2.3. Coffee Sample Preparation -- 2.4. Urine Sample Preparation -- 2.5. Instrumental Analysis and Methods -- 3. Results -- 3.1. Coffee Composition -- 3.2. Urine Samples Analysis -- Conclusion -- Acknowledgments -- References -- Chapter 5 -- Phenolic Compounds in Plant Materials: Problems and New Analytical Solutions -- Abstract -- 1. Introduction -- 2. Separation Conditions -- 3. Detection Methods in HPLC -- 3.1. Spectrophotometric and Fluorescence Detection -- 3.2. Mass Spectrometry Detection -- 4. Sample Preparation Methods -- 4.1. Extraction -- 4.2. Hydrolysis -- 5. Stability of Phenolic Compounds in Different Extraction Modes -- Conclusion -- References -- Chapter 6 -- Phenolic Compounds in Wine: Types, Color Effects and Research -- Abstract -- 1. Introduction -- 2. Phenolic Compounds -- 2.1. Non-Flavonoid Compounds -- 2.1.1. Phenolic Acids -- 2.1.1.1. Hydroxybenzoic Acids -- 2.1.1.2. Hydroxycinnamic Acids -- 2.1.2. Stilbenes -- 2.1.3. Hydrolyzable Tannins -- 2.1.4. Fermentation Products -- 2.2. Flavonoid Compounds -- 2.2.1. Flavanols -- 2.2.2. Flavonols -- 2.2.3. Anthocyanins -- 2.3. Wine Aging: Polymers and Reactions. , 3. Main Effects of Phenolics in Wine -- 3.1. Color -- 3.1.1. pH -- 3.1.2. Co-Pigmentation -- 3.1.3. Phenolic Reactions -- 3.1.3.1. Pyranoanthocyanins -- 3.1.3.2. Polymeric Pigments -- 3.2. Antioxidant Capacity -- 3.3. Flavor -- 3.3.1. Astringency and Structure -- 3.3.2. Aroma -- Conclusion -- References -- Chapter 7 -- Cover Crops in Viticulture: A Strategy to Modify Grape and Wine Phenolic Composition -- Abstract -- 1. Vineyard Soil Management -- (a) Bare Soil, Free of Vegetation -- (b) Covered Soil -- 1.1. Cover Crops Impact on the Vineyard -- 1.1.1. Impact of the Cover Crops on the Grapevine Water Status -- 1.1.2. Cover Crops Impact in the Grapevine Nutritional Status -- 1.1.2.1. Grapevine Nitrogen Nutrition Status -- 1.1.2.2. Other Macronutrients Grapevine Nutrition -- 1.1.2.3. Grapevine Micronutrients Nutrition -- 1.1.3. Other Cover Crops Effects on Vineyards -- 1.2. Cover Crops Effect on the Grape and Wine -- Phenolic Compounds -- 2. Conclusion -- References -- Chapter 8 -- Biological Properties of Phenolic Compounds from Industrial Wastes -- Abstract -- 1. Phenolic Compounds -- 2. Industrial Wastes -- 3. Phenolic Compounds in Winery Wastes -- 4. Phenolic Compounds in Olive Oil Industry Wastes -- 5. Recovery of Phenolic Compounds from Other Wastes -- Conclusion -- References -- Index -- Blank Page.
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  • 2
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    Chromophoric signatures of microbial by-products in the dark ocean (2016)
    Wiley-Blackwell
    Details
    Publication Date: 2016-07-15
    Description: Detailed examination of the absorption spectra from dark ocean samples allowed us to identify and deconvolve two distinct chromophores centered at 302 nm (UV) and 415 nm (Visible) from the exponential decay curve characteristic of humic substances. The UV chromophore was ubiquitous in intermediate and deep waters and it has been proposed as the secondary absorption peak of nitrate. The Visible chromophore was prominent at the central and intermediate water masses of the North Pacific and it has been proposed as cytochrome c. Subtraction of the modeled absorption spectra of the two chromophores from the measured absorption spectrum of the samples lead to a spectral slope overestimation by 13.3 ± 6.0% for S 275-295 and 14.8 ± 10.6% for S 350-400 . To only consider the chromophoric fraction of DOM, the absorption spectra of nitrate should be subtracted in samples with a [NO 3 - ]:a 302 ratio 〉 70 μM m.
    Print ISSN: 0094-8276
    Electronic ISSN: 1944-8007
    Topics: Geosciences , Physics
    Published by Wiley-Blackwell on behalf of American Geophysical Union (AGU).
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  • 3
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    The Effect of Modelling Mechanistically Phytoplankton Photo-physiology on the Seasonal Cycle of Primary Production in Polar Regions (2020)
    In:  EPIC3Ocean Sciences Meeting 2020, San Diego, USA, 2020-02-16-2020-02-21
    Details
    Publication Date: 2020-03-03
    Description: The ability of global models in simulating the seasonality of biogeochemical cycles constrains their reliability for projections of primary production and ocean carbon uptake. In particular, the phasing and amplitude of the seasonal cycle of primary production affect the net flux of carbon between the ocean and the atmosphere. Models’ characterization of the seasonal cycle of primary production in high latitudes generally shows an amplitude and/or phasing bias of the spring-summer bloom. The question that we tackle in this study is to which extent model simulations of the seasonal cycle of primary production would benefit from a more mechanistic description of the links between phytoplankton physiology and environmental drivers. To explore that question we worked with the Regulated Ecosystem model version 2 (REcoM2) integrated within the Finite-Element Sea-Ice Ocean Model (FESOM). We included in the phytoplankton growth model a photodamage term that decreases the amount of active photosynthetic pigments when light becomes supersaturating. Eventually, the interplay between light-dependent photodamage and nutrient-dependent new synthesis of pigments determines the photosynthetic capacity of the cells. The immediate effect is that the model is able to simulate variations in the stoichiometry of phytoplankton with light, nutrients and temperature in better agreement with observations. Regarding the seasonal variations of primary production in polar regions, model simulations show a less steep increase of biomass and net primary production during the growing season and lower biomass concentrations at the peak of the bloom. However, the start of the bloom happens relatively early when compared to satellite observations. We suggest to further evaluate the role of other environmental factors interacting with the physiology of primary producers and driving both bottom-up (e.g. vertical mixing) and top-down (e.g. grazing) control of the spring bloom in polar regions.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 4
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    In-vivo single-cell fluorescence and size-scaling of phytoplankton chlorophyll content (2017)
    American Society for Microbiology
    In:  EPIC3Applied and Environmental Microbiology, American Society for Microbiology, 83(7), pp. 1-16, ISSN: 1098-5336
    Details
    Publication Date: 2017-06-14
    Description: In unicellular phytoplankton, the size scaling exponent of chlorophyll content per cell decreases with increasing light limitation. Empirical studies have ex- plored this allometry by combining data from several species, using average values of pigment content and cell size for each species. The resulting allometry thus in- cludes phylogenetic and size scaling effects. The possibility of measuring single-cell fluorescence with imaging-in-flow cytometry devices allows the study of the size scaling of chlorophyll content at both the inter- and intraspecific levels. In this work, the changing allometry of chlorophyll content was estimated for the first time for single phytoplankton populations by using data from a series of incubations with monocultures exposed to different light levels. Interspecifically, our experiments con- firm previous modeling and experimental results of increasing size scaling exponents with increasing irradiance. A similar pattern was observed intraspecifically but with a larger variability in size scaling exponents. Our results show that size-based pro- cesses and geometrical approaches explain variations in chlorophyll content. We also show that the single-cell fluorescence measurements provided by imaging-in-flow devices can be applied to field samples to understand the changes in the size de- pendence of chlorophyll content in response to environmental variables affecting primary production.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
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  • 5
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    Variability in the Chlorophyll to Carbon ratio: contrasting in situ and satellite data with models (2016)
    In:  EPIC3Colour and Light in the Ocean from Earth Observation (CLEO), ESA-ESRIN Frascatti, Italy, 2016-09-06-2016-09-08
    Details
    Publication Date: 2018-05-03
    Description: Phytoplankton biomass is often inferred from chlorophyll, however, since biogeochemistry in the ocean is coupled mostly to carbon, models need to convert chlorophyll to carbon biomass. The chlorophyll to carbon (Chl:C) ratio in phytoplankton is variable, and although there are species specific differences, most of the variability is driven by acclimation to changing nutrient and light-conditions. Many models include variable Chl:C ratios to account for the effects of photoacclimation, however results can be very different depending on the model used. Can we improve the way photoacclimation of phytoplankton to different light conditions is modelled? A diagnostic Chl:C ratio can describe properly the balanced growth of phytoplankton populations, but modelling separately the dynamics of carbon and chlorophyll could help to predict the variability observed matching situations of balanced and not balanced growth. Our current model, REcoM, is a global ecosystem model based on the phytoplankton growth model from Geider et al. (1998) which runs coupled to the MIT global circulation model. We compared the Chl:C ratios from that model with observations, showing that the model was able to represent some general patterns, but also faced some deficiencies. Within the project IPSO (Improving the prediction of photophysiology in the Southern Ocean by accounting for iron limitation, optical properties and spectral satellite data information) the modelling group of the Alfred Wegener Institute aims to explore two ways for refining the model. First, we will compare several phytoplankton growth models that treat differently the chlorophyll synthesis term with in situ data of Chl:C ratios gathered at local scale. In a next step, we will extend this analysis to compare modelling options with satellite chlorophyll data. The improvement of photophysiology description in the model is expected to provide a more accurate estimation of chlorophyll content on a global basis.
    Repository Name: EPIC Alfred Wegener Institut
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  • 6
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    Validation methods for plankton image classification systems (2017)
    AMER SOC LIMNOLOGY OCEANOGRAPHY
    In:  EPIC3Limnology and Oceanography-Methods, AMER SOC LIMNOLOGY OCEANOGRAPHY, 15(3), pp. 221-237, ISSN: 1541-5856
    Details
    Publication Date: 2018-05-03
    Description: In recent decades, the automatic study and analysis of plankton communities using imaging techniques has advanced significantly. The effectiveness of these automated systems appears to have improved, reaching acceptable levels of accuracy. However, plankton ecologists often find that classification systems do not work as well as expected when applied to new samples. This paper proposes a methodology to assess the efficacy of learned models which takes into account the fact that the data distribution (the plankton composition of the sample) can vary between the model building phase and the production phase. As opposed to most validation methods that consider the individual organism as the unit of validation, our approach uses a validation‐by‐sample, which is more appropriate when the objective is to estimate the abundance of different morphological groups. We argue that, in these cases, the base unit to correctly estimate the error is the sample, not the individual. Thus, model assessment processes require groups of samples with sufficient variability in order to provide precise error estimates.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev
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  • 7
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    Application of FlowCAM for phytoplankton enumeration, identification and estimation of chlorophyll content per cell (2016)
    In:  EPIC3British Phycological Society 64th Annual Meeting, Bournemouth University, UK, 2016-06-22-2016-06-24
    Details
    Publication Date: 2018-05-03
    Description: The structural attributes of the planktonic community, such as abundance, size-structure or taxonomic diversity, are emergent properties of processes taking place at the cellular, individual level. The analysis of individual cells could be applied to the study of the ecosystem dynamics, both in structural and physiological terms. Techniques for the analysis of individual cells of the planktonic community have emerged in the last decades. The Flow Cytometer and Microscope (FlowCAM) is an automatic sampling device that allows the acquisition of information on a single cell basis. In the last years, standardized methodology for the use of FlowCAM has developed which allows to estimate abundance, biomass and size structure of phytoplankton community with reliability, compared to traditional techniques for plankton enumeration. Coupled with automatic classification of images, this methodology allows the identification of phytoplankton cells in broad groups, such as diatoms, dinoflagellates, ciliates and silicoflagellates. Recently, FlowCAM has been oriented to the estimation of intracellular content of different macromolecules, such as pigments or lipids. We explored the relationship between the emission of fluorescence of phytoplankton single cells measured by the FlowCAM and their chlorophyll content. Hence, from a routine analysis of natural samples it is possible to estimate quantitatively the chlorophyll content of single cells, which relates with the photosynthetic rates of the phytoplankton community and could help in the description of photoacclimation processes.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 8
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    Chlorophyll to carbon ratio derived from an ecosystem model with explicit photodamage (2017)
    In:  EPIC3ASLO Aquatic Sciences Meeting, Honolulu-Hawaii, USA, 2017-02-26-2017-03-03
    Details
    Publication Date: 2018-05-03
    Description: Phytoplankton biomass is often inferred from chlorophyll (Chl), however, biogeochemistry in the ocean is coupled mostly to carbon. The Chl to carbon (Chl:C) ratio is variable and most of the variability is driven by acclimation to changing nutrient and light-conditions. Our current model, REcoM, is a global ecosystem model based on the phytoplankton growth model from Geider et al. (1998) which runs coupled to the MIT global circulation model. Geider’s model describes separately the dynamics of carbon, nitrogen and Chl, from temperature, light and nutrients. Hence, it allows to account for the effects of external conditions on cell quotas. Loss terms in phytoplankton growth need to be described within the ecosystem model. In one version, the degradation of Chl had been treated for simplicity as a constant rate. With this parameterization, although the Chl distribution correlated well with satellite Chl, Chla:C ratios deviated from previous reported values for global ocean. We therefore propose to regulate the degradation of Chl considering the degree of light saturation of the photosynthetic apparatus which, ultimately, reflects increased damage to Chl at high irradiances. This new parameterization provides Chl values highly correlated with satellite Chl and Chla:C ratios in a realistic range of values. We show that the modelled relationship of Chl:C with growth rate fits with results from lab experiments under balanced growth conditions. The question that remains is whether not only the range but also the patterns of Chla:C ratios at global scale are accurate. To asses that, we compare model output with new in situ and published data of Chl:C ratios.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 9
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    Chlorophyll to Carbon Ratio Derived From a Global Ecosystem Model With Photodamage (2018)
    Wiley
    In:  EPIC3Global Biogeochemical Cycles, Wiley, 32(5), pp. 799-816, ISSN: 0886-6236
    Details
    Publication Date: 2018-07-31
    Description: Phytoplankton harvests light by integrating chlorophyll in protein‐pigment complexes (photosystems) that are variable in number and size. In ecosystem models, the capacity of light harvesting is described as the pool of chlorophyll. Since most of the variability in phytoplankton chlorophyll content is driven by acclimation to changing nutrient and light conditions, photoacclimation is generally parameterized as a regulation of chlorophyll synthesis with changing light. However, photosystems can also be degraded, and of the few process‐based models that have been proposed in the literature for the representation of their degradation and repair, none of them have been extended to more realistic conditions offered by pelagic biogeochemical models. We proposed three potential parameterizations to treat the degradation of photosystems as a function of light intensity and included them as a source of variation in the size of the chlorophyll pool in Regulated Ecosystem Model
    Repository Name: EPIC Alfred Wegener Institut
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  • 10
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    Prediction of photo-protective carotenoids at global scale (2018)
    In:  EPIC3Ocean Optics Conference XXIV, Dubrovnik, 2018-10-07-2018-10-12
    Details
    Publication Date: 2018-11-30
    Description: As phytoplankton cells are exposed to natural dynamic light fields, they develop various combined mechanisms in order to optimize their light harvesting and photosynthetic electron transport. Especially under high light conditions algal cells evolve various physiological protective mechanisms to dispose excess light energy to prevent damage of the photosynthetic apparatus. Among these mechanisms the so-called xanthophyll cycle (XC) is one of the most important one, which avoids overexcitation of the photosynthetic systems by thermal dissipation of the excess energy. In response to high light phytoplankton cells accumulate XC-pigments to avoid the photodamage, which would cause photoinhibition. The mechanistic model for photoinhibition proposed by (Marshall, Geider & Flynn 2000) predicts how changes in light, nutrients and temperature influence the parameters of the photosynthesis-irradiance relationship. The model does not parameterize a variable XC-pigments pool size, hence, it predicts the changes in light absorption parameters that would take place with a constant XC-pigments pool. We inserted this model in the global biogeochemical model REcoM2 to predict the photo-protective needs of phytoplankton in terms of the XC-pigments pool size. Two global scale databases of HPLC pigments showed how the predicted photoprotective response correlates with photo-protective carotenoids pool at global scale, with the advantage that the model prediction is separable per phytoplankton group. Our results show higher concentration of XC-pigments in lower latitudes being non-diatom phytoplankton the main contributor. XC-pigments pool size and its relation to photosynthetic pigments are relevant when describing the light harvesting by phytoplankton at the global scale.
    Repository Name: EPIC Alfred Wegener Institut
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