Fructo-oligosaccharides separation and purification by simulated moving bed chromatography

The interest on oligosaccharides such as fructo-oligosaccharides (FOS) has strongly increased in recent years for food and pharmaceutical applications, mainly due to their improved technological and functional properties. FOS can be produced by fermentative processes from sucrose, and can be found in mixture with other mono- and di-saccharides and salts, at the end of the process [1]. Unlike FOS, the small saccharides (SGF), namely fructose, glucose and sucrose in the mixture, are known to be cariogenic, caloric and do not present prebiotic activity. The purification of FOS from the other sugars can represent and important increment on the economic value of the final product, which can be further used in diabetic and dietetic food [2]. Different strategies have been developed for this purpose, including microbial treatment [3], ultra and nano-filtration, activated charcoal systems [4], or ion-exchange chromatography [5]. Ion exchange resins may be then used in batch or continuous chromatographic processes, as Simulated Moving Bed (SMB) chromatography, to purify sugars. A screening of different commercial resins was previously done in order to select the most suitable to separate the oligosaccharides [5]. The resin Diaion 535Ca showed an increased recovery yield and purity of FOS (92 and 90%, respectively). In the present work, the separation process was implemented in the SMB, using the selected resin, namely. Equilibrium adsorption isotherms were determined by the Retention Time Method (RTM), for each single sugar. The resin was afterwards packed in eight SMB columns, and tested in the pilot plant. Different operation parameters, including switching time, extra time, internal flow-rates and operating pump flow-rates for feed, raffinate, desorbent, eluent and recycling streams, were tested in the plant. The separation of fructose from glucose and FOS from the SGF was evaluated. Firstly, the separation of a binary sugar mixture of fructose/sucrose (~ 50/50%) was performed followed by the separation of FOS from a fermentative broth. Fructose was purified from 53 to 76% and sucrose from 47 to 77%. FOS and SGF were purified from 50 to 67%. The implementation of UV detectors between the SMB columns allowed following the sugar concentration profile online during the separation process. The accurate selection of the operating parameters was made using the concentration signal obtained and showed to be a crucial step for an improved separation

Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation model ORCHIDEE - Part 1: Simulating historical global burned area and fire regimes

Journal Article© 2014 Author(s). Fire is an important global ecological process that influences the distribution of biomes, with consequences for carbon, water, and energy budgets. Therefore it is impossible to appropriately model the history and future of the terrestrial ecosystems and the climate system without including fire. This study incorporates the process-based prognostic fire module SPITFIRE into the global vegetation model ORCHIDEE, which was then used to simulate burned area over the 20th century. Special attention was paid to the evaluation of other fire regime indicators such as seasonality, fire size and fire length, next to burned area. For 2001-2006, the simulated global spatial extent of fire agrees well with that given by satellite-derived burned area data sets (L3JRC, GLOBCARBON, GFED3.1), and 76-92% of the global burned area is simulated as collocated between the model and observation, depending on which data set is used for comparison. The simulated global mean annual burned area is 346 Mha yrg'1, which falls within the range of 287-384 Mha yrg'1 as given by the three observation data sets; and is close to the 344 Mha yrg'1 by the GFED3.1 data when crop fires are excluded. The simulated long-term trend and variation of burned area agree best with the observation data in regions where fire is mainly driven by climate variation, such as boreal Russia (1930-2009), along with Canada and US Alaska (1950-2009). At the global scale, the simulated decadal fire variation over the 20th century is only in moderate agreement with the historical reconstruction, possibly because of the uncertainties of past estimates, and because land-use change fires and fire suppression are not explicitly included in the model. Over the globe, the size of large fires (the 95th quantile fire size) is underestimated by the model for the regions of high fire frequency, compared with fire patch data as reconstructed from MODIS 500 m burned area data. Two case studies of fire size distribution in Canada and US Alaska, and southern Africa indicate that both number and size of large fires are underestimated, which could be related with short fire patch length and low daily fire size. Future efforts should be directed towards building consistent spatial observation data sets for key parameters of the model in order to constrain the model error at each key step of the fire modelling

Recent global and regional trends in burned area and their compensating environmental controls

The apparent decline in the global incidence of fire between 1996 and 2015, as measured by satellite- observations of burned area, has been related to socioeconomic and land use changes. However, recent decades have also seen changes in climate and vegetation that influence fire and fire-enabled vegetation models do not reproduce the apparent decline. Given that the satellite-derived burned area datasets are still relatively short (<20 years), this raises questions both about the robustness of the apparent decline and what causes it. We use two global satellite-derived burned area datasets and a data-driven fire model to (1) assess the spatio-temporal robustness of the burned area trends and (2) to relate the trends to underlying changes in temperature, precipitation, human population density and vegetation conditions. Although the satellite datasets and simulation all show a decline in global burned area over ~20 years, the trend is not significant and is strongly affected by the start and end year chosen for trend analysis and the year-to-year variability in burned area. The global and regional trends shown by the two satellite datasets are poorly correlated for the common overlapping period (2001–2015) and the fire model simulates changes in global and regional burned area that lie within the uncertainties of the satellite datasets. The model simulations show that recent increases in temperature would lead to increased burned area but this effect is compensated by increasing wetness or increases in population, both of which lead to declining burned area. Increases in vegetation cover and density associated with recent greening trends lead to increased burned area in fuel-limited regions. Our analyses show that global and regional burned area trends result from the interaction of compensating trends in controls of wildfire at regional scales

Recent global and regional trends in burned area and their compensating environmental controls

The apparent decline in the global incidence of fire between 1996 and 2015, as measured by satellite-observations of burned area, has been related to socioeconomic and land use changes. However, recent decades have also seen changes in climate and vegetation that influence fire and fire-enabled vegetation models do not reproduce the apparent decline. Given that the satellite-derived burned area datasets are still relatively short (<20 years), this raises questions both about the robustness of the apparent decline and what causes it. We use two global satellite-derived burned area datasets and a data-driven fire model to (1) assess the spatio-temporal robustness of the burned area trends and (2) to relate the trends to underlying changes in temperature, precipitation, human population density and vegetation conditions. Although the satellite datasets and simulation all show a decline in global burned area over ~20 years, the trend is not significant and is strongly affected by the start and end year chosen for trend analysis and the year-to-year variability in burned area. The global and regional trends shown by the two satellite datasets are poorly correlated for the common overlapping period (2001–2015) and the fire model simulates changes in global and regional burned area that lie within the uncertainties of the satellite datasets. The model simulations show that recent increases in temperature would lead to increased burned area but this effect is compensated by increasing wetness or increases in population, both of which lead to declining burned area. Increases in vegetation cover and density associated with recent greening trends lead to increased burned area in fuel-limited regions. Our analyses show that global and regional burned area trends result from the interaction of compensating trends in controls of wildfire at regional scales

Global ecosystems and fire: multi-model assessment of fire-induced tree cover and carbon storage reduction

In this study, we use simulations from seven global vegetation models to provide the first multi‐model estimate of fire impacts on global tree cover and the carbon cycle under current climate and anthropogenic land use conditions, averaged for the years 2001‐2012. Fire reduces the tree covered area and vegetation carbon storage by 10%. Regionally the effects are much stronger, up to 20% for certain latitudinal bands, and 17% in savanna regions. Global fire effects on total carbon storage and carbon turnover times are lower with the effect on gross primary productivity (GPP) close to zero. We find the strongest impacts of fire in savanna regions. Climatic conditions in regions with the highest burned area differ from regions with highest absolute fire impact, which are characterized by higher precipitation. Our estimates of fire‐induced vegetation change are lower than previous studies. We attribute these differences to different definitions of vegetation change and effects of anthropogenic land use, which were not considered in previous studies and decreases the impact of fire on tree cover. Accounting for fires significantly improves the spatial patterns of simulated tree cover, which demonstrates the need to represent fire in dynamic vegetation models. Based upon comparisons between models and observations, process understanding and representation in models, we assess a higher confidence in the fire impact on tree cover and vegetation carbon compared to GPP, total carbon storage and turnover times. We have higher confidence in the spatial patterns compared to the global totals of the simulated fire impact. As we used an ensemble of state‐of‐the‐art fire models, including effects of land use and the ensemble median or mean compares better to observational datasets than any individual model, we consider the here presented results to be the current best estimate of global fire effects on ecosystems

The status and challenge of global fire modelling

This is the final version of the article. Available from European Geosciences Union / Copernicus Publications via the DOI in this record.The discussion paper version of this article was published in Biogeosciences Discussions on 25 January 2016 and is in ORE at http://hdl.handle.net/10871/34451Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.Stijn Hantson and Almut Arneth acknowledge support by the EU FP7 projects BACCHUS (grant agreement no. 603445) and LUC4C (grant agreement no. 603542). This work was supported, in part, by the German Federal Ministry of Education and Research (BMBF), through the Helmholtz Association and its research programme ATMO, and the HGF Impulse and Networking fund. The MC-FIRE model development was supported by the global change research programmes of the Biological Resources Division of the US Geological Survey (CA 12681901,112-), the US Department of Energy (LWT-6212306509), the US Forest Service (PNW96–5I0 9 -2-CA), and funds from the Joint Fire Science Program. I. Colin Prentice is supported by the AXA Research Fund under the Chair Programme in Biosphere and Climate Impacts, part of the Imperial College initiative Grand Challenges in Ecosystems and the Environment. Fang Li was funded by the National Natural Science Foundation (grant agreement no. 41475099 and no. 2010CB951801). Jed O. Kaplan was supported by the European Research Council (COEVOLVE 313797). Sam S. Rabin was funded by the National Science Foundation Graduate Research Fellowship, as well as by the Carbon Mitigation Initiative. Allan Spessa acknowledges funding support provided by the Open University Research Investment Fellowship scheme. FireMIP is a non-funded community initiative and participation is open to all. For more information, contact Stijn Hantson ([email protected])

The status and challenge of global fire modelling

This is the discussion paper version of the article. The final published version was published in Biogeosciences Vol. 13 (1), pp. 3359-3375 and is in ORE at http://hdl.handle.net/10871/22886Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what lessons may be learned from FireMIP.Stijn Hantson and Almut Arneth acknowledge support by the EU FP7 projects BACCHUS (grant agreement no. 603445) and LUC4C (grant agreement no. 603542). This work was supported, in part, by the German Federal Ministry of Education and Research (BMBF), through the Helmholtz Association and its research programme ATMO, and the HGF Impulse and Networking fund. The MC-FIRE model development was supported by the global change research programmes of the Biological Resources Division of the US Geological Survey (CA 12681901,112-), the US Department of Energy (LWT6212306509), the US Forest Service (PNW96–5I0 9 -2-CA), and funds from the Joint Fire Science Program. I. Colin Prentice is supported by the AXA Research Fund under the Chair Programme in Biosphere and Climate Impacts, part of the Imperial College initiative Grand Challenges in Ecosystems and the Environment. Fang Li was funded by the National Natural Science Foundation (grant agreement no. 41475099 and no. 2010CB951801). Jed O. Kaplan was supported by the European Research Council (COEVOLVE 313797). Sam S. Rabin was funded by the National Science Foundation Graduate Research Fellowship, as well as by the Carbon Mitigation Initiative. Allan Spessa acknowledges funding support provided by the Open University Research Investment Fellowship scheme. FireMIP is a non-funded community initiative and participation is open to all

TEM analysis of apatite surface layers observed on zinc based glass polyalkenoate cements

peer-reviewedGlass polyalkenoate cements (GPCs) are acid base cements formed by the reaction of an aqueous solution of polyalkenoic acid, usually polyacrylic acid (PAA) with an acid degradable aluminosilicate glass. The result of the reaction is cement consisting of reacted and unreacted glass particles embedded in a polysalt matrix. In addition to these conventional GPCs, aluminium free glass polyalkenoate cements based on zinc silicate glasses (Zn-GPCs) exhibit significant potential as bone cements for several reasons. Primarily, they are formulated without the inclusion of aluminium (Al) [1] in the glass phase and thus eliminate clinical complications arising from the release of the Al3+ ion from the cement in vivo. Such complications have, in the past, included aluminium induced encephalopathy [2-5] and defective mineralisation of cancellous bone [6]. Secondly, Zn-GPCs set without a significant evolution of heat, when compared with commercial bone cements such as Spineplex ® (Stryker, Limerick, Ireland). Finally, these materials can be tailored to release clinically beneficial ions into surrounding tissues [7]. In addition to Zn, these cements have been synthesized to contain strontium (Sr) [8, 9]. Both Sr and Zn inhibit osteoclastic turnover and promote osteoblastic turnover, resulting in increased bone strength and decreased fracture risk [10-14].Acceptedpeer-reviewe

Hypothermia and Fever After Organophosphorus Poisoning in Humans—A Prospective Case Series

There have been many animal studies on the effects of organophosphorus pesticide (OP) poisoning on thermoregulation with inconsistent results. There have been no prospective human studies. Our aim was to document the changes in body temperature with OP poisoning. A prospective study was conducted in a rural hospital in Polonnaruwa, Sri Lanka. We collected data on sequential patients with OP poisoning and analyzed 12 patients selected from 53 presentations who had overt signs and symptoms of OP poisoning and who had not received atropine prior to arrival. All patients subsequently received specific management with atropine and/or pralidoxime and general supportive care. Tympanic temperature, ambient temperature, heart rate, and clinical examination and interventions were recorded prospectively throughout their hospitalization. Initial hypothermia as low as 32°C was observed in untreated patients. Tympanic temperature increased over time from an early hypothermia (<35°C in 6/12 patients) to later fever (7/12 patients >38°C at some later point). While some of the late high temperatures occurred in the setting of marked tachycardia, it was also apparent that in some cases fever was not accompanied by tachycardia, making excessive atropine or severe infection an unlikely explanation for all the fevers. In humans, OP poisoning causes an initial hypothermia, and this is followed by a period of normal to high body temperature. Atropine and respiratory complications may contribute to fever but do not account for all cases