22 research outputs found

    Anemia prevalence and associated factors among school age children in Accra and Kumasi metropolis in Ghana

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    Anemia remains a serious public health concern, globally, affecting learning ability and physical development of children. Anemic children are at a  higher risk of diminished economic productivity and low earning capacity in adulthood due to impaired school performance and reduced work  capacity. Anemia contributes to about a quarter of Africa’s nutrition-related Disability Adjusted Life Years. The objective of this study was to  determine the prevalence of anemia and its associated risk factors among school-aged children (SAC) between ages 9 and 15 years in urban Ghana.  The analysis included a randomly selected subsample of 1,634 children from a larger study on nutrition of SAC enrolled between 2009 and 2012 in  private and public basic schools in the Accra and Kumasi Metropolis in Ghana. Socio-demographic and household characteristics were collected with  questionnaires. Weight and height were taken to the nearest 0.1kg and 0.1cm, respectively. Dietary information was collected using a food  frequency questionnaire. Data were analyzed using IBM SPSS Statistic version 23. The relationship between hemoglobin levels and socio-  demographic variables, and predictors of hemoglobin levels were determined using Chi-square and binary logistic regression. The mean  hemoglobin concentration of the study participants was 12.9±1.3 g/dL. In Kumasi, SAC had higher mean hemoglobin concentration (13.1±1.2 g/dL)  compared to those from Accra (12.6±1.3 g/dL; p=0.001). Mean hemoglobin concentration was significantly higher among males than females  (13.0±1.4 g/dL vs 12.8±1.2 g/dL; p=0.002). Prevalence of anemia was 20.4%; mild anemia was most common (13.6% of total sample). Anemia cases  were higher in public schools (24.6%) compared to private (18.2%). Two-thirds of anemia cases (64.0%) were from schools in Accra. Males had significantly higher prevalence of anemia (26.5%) than females (15.9%; p <0.05). In the adjusted logistic regression model, only city of residence (OR+1.65, 95% CI: 1.44–1.83), thinness (OR=2.60, 95% CI: 1.11-5.75), stunting (OR=1.85, 95% CI: 1.99-3.10) and overweight (OR=0.60, 95% CI: 0.36-0.94) were significantly associated with anemia. In this study, anemia was significantly associated with location and nutritional status

    The nutritional phenotype in the age of metabolomics

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    The concept of the nutritional phenotype is proposed as a defined and integrated set of genetic, proteomic, metabolomic, functional, and behavioral factors that, when measured, form the basis for assessment of human nutritional status. The nutritional phenotype integrates the effects of diet on disease/wellness and is the quantitative indication of the paths by which genes and environment exert their effects on health. Advances in technology and in fundamental biological knowledge make it possible to define and measure the nutritional phenotype accurately in a cross section of individuals with various states of health and disease. This growing base of data and knowledge could serve as a resource for all scientific disciplines involved in human health. Nutritional sciences should be a prime mover in making key decisions that include: what environmental inputs (in addition to diet) are needed; what genes/proteins/metabolites should be measured; what end-point phenotypes should be included; and what informatics tools are available to ask nutritionally relevant questions. Nutrition should be the major discipline establishing how the elements of the nutritional phenotype vary as a function of diet. Nutritional sciences should also be instrumental in linking the elements that are responsive to diet with the functional outcomes in organisms that derive from them. As the first step in this initiative, a prioritized list of genomic, proteomic, and metabolomic as well as functional and behavioral measures that defines a practically useful subset of the nutritional phenotype for use in clinical and epidemiological investigations must be developed. From this list, analytic platforms must then be identified that are capable of delivering highly quantitative data on these endpoints. This conceptualization of a nutritional phenotype provides a concrete form and substance to the recognized future of nutritional sciences as a field addressing diet, integrated metabolism, and health

    Perspectives on multiscale modelling and experiments to accelerate materials development for fusion

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    Prediction of material performance in fusion reactor environments relies on computational modelling, and will continue to do so until the first generation of fusion power plants come on line and allow long-term behaviour to be observed. In the meantime, the modelling is supported by experiments that attempt to replicate some aspects of the eventual operational conditions. In 2019, a group of leading experts met under the umbrella of the IEA to discuss the current position and ongoing challenges in modelling of fusion materials and how advanced experimental characterisation is aiding model improvement. This review draws from the discussions held during that workshop. Topics covering modelling of irradiation-induced defect production and fundamental properties, gas behaviour, clustering and segregation, defect evolution and interactions are discussed, as well as new and novel multiscale simulation approaches, and the latest efforts to link modelling to experiments through advanced observation and characterisation techniques.MRG, SLD, and DRM acknowledge funding by the RCUK Energy Programme [grant number EP/T012250/1]. Part of this work has been carried out within the framework of the EUROFusion Consortium and has received funding from the Euratom research and training programme 2014–2018 and 2019–2020 under grant Agreement No. 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission. JRT acknowledges funding from the US Department of Energy (DOE) through grant DE-SC0017899. ZB, LY,BDW, and SJZ acknowledge funding through the US DOE Fusion Energy Sciences grant DE-SC0006661ZB, LY and BDW also were partially supported from the US DOE Office of Science, Office of Fusion Energy Sciences and Office of Advanced Scientific Computing Research through the Scientific Discovery through Advanced Computing (SciDAC) project on Plasma-Surface Interactions. JMa acknowledges support from the US-DOEs Office of Fusion Energy Sciences (US-DOE), project DE-SC0019157. Pacific Northwest National Laboratory is operated by Battelle Memorial Institute for the US Department of Energy (DOE) under contract DE-AC05-76RL01830. YO and YZ were supported as part of the Energy Dissipation to Defect Evolution (EDDE), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under contract number DE-AC05-00OR22725. TS and TT are supported by JSPS KAKENHI Grant Number 19K05338

    A Hierarchical Approach to Cooperativity in Macromolecular and Self-Assembling Binding Systems

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    The study of complex macromolecular binding systems reveals that a high number of states and processes are involved in their mechanism of action, as has become more apparent with the sophistication of the experimental techniques used. The resulting information is often difficult to interpret because of the complexity of the scheme (large size and profuse interactions, including cooperative and self-assembling interactions) and the lack of transparency that this complexity introduces into the interpretation of the indexes traditionally used to describe the binding properties. In particular, cooperative behaviour can be attributed to very different causes, such as direct chemical modification of the binding sites, conformational changes in the whole structure of the macromolecule, aggregation processes between different subunits, etc. In this paper, we propose a novel approach for the analysis of the binding properties of complex macromolecular and self-assembling systems. To quantify the binding behaviour, we use the global association quotient defined as Kc = [occupied sites]/([free sites] L), L being the free ligand concentration. Kc can be easily related to other measures of cooperativity (such as the Hill number or the Scatchard plot) and to the free energies involved in the binding processes at each ligand concentration. In a previous work, it was shown that Kc could be decomposed as an average of equilibrium constants in two ways: intrinsic constants for Adair binding systems and elementary constants for the general case. In this study, we show that these two decompositions are particular cases of a more general expression, where the average is over partial association quotients, associated with subsystems from which the system is composed. We also show that if the system is split into different subsystems according to a binding hierarchy that starts from the lower, microscopic level and ends at the higher, aggregation level, the global association quotient can be decomposed following the hierarchical levels of macromolecular organisation. In this process, the partial association quotients of one level are expressed, in a recursive way, as a function of the partial quotients of the level that is immediately below, until the microscopic level is reached. As a result, the binding properties of very complex macromolecular systems can be analysed in detail, making the mechanistic explanation of their behaviour transparent. In addition, our approach provides a model-independent interpretation of the intrinsic equilibrium constants in terms of the elementary ones
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