464 research outputs found

    Cognition in stroke rehabilitation and recovery research: Consensus-based core recommendations from the second Stroke Recovery and Rehabilitation Roundtable

    Get PDF
    Cognitive impairment is an important target for rehabilitation as it is common following stroke, is associated with reduced quality of life and interferes with motor and other types of recovery interventions. Cognitive function following stroke was identified as an important, but relatively neglected area during the first Stroke Recovery and Rehabilitation Roundtable (SRRR I), leading to a Cognition Working Group being convened as part of SRRR II. There is currently insufficient evidence to build consensus on specific approaches to cognitive rehabilitation. However, we present recommendations on the integration of cognitive assessments into stroke recovery studies generally and define priorities for ongoing and future research for stroke recovery and rehabilitation. A number of promising interventions are ready to be taken forward to trials to tackle the gap in evidence for cognitive rehabilitation. However, to accelerate progress requires that we coordinate efforts to tackle multiple gaps along the whole translational pathway

    The Antioxidant Potential of the Mediterranean Diet in Patients at High Cardiovascular Risk: An In-Depth Review of the PREDIMED

    Get PDF
    Cardiovascular disease (CVD) is the leading global cause of death. Diet is known to be important in the prevention of CVD. The PREDIMED trial tested a relatively low-fat diet versus a high-fat Mediterranean diet (MedDiet) for the primary prevention of CVD. The resulting reduction of the CV composite outcome resulted in a paradigm shift in CV nutrition. Though many dietary factors likely contributed to this effect, this review focuses on the influence of the MedDiet on endogenous antioxidant systems and the effect of dietary polyphenols. Subgroup analysis of the PREDIMED trial revealed increased endogenous antioxidant and decreased pro-oxidant activity in the MedDiet groups. Moreover, higher polyphenol intake was associated with lower incidence of the primary outcome, overall mortality, blood pressure, inflammatory biomarkers, onset of new-onset type 2 diabetes mellitus (T2DM), and obesity. This suggests that polyphenols likely contributed to the lower incidence of the primary event in the MedDiet groups. In this article, we summarize the potential benefits of polyphenols found in the MedDiet, specifically the PREDIMED cohort. We also discuss the need for further research to confirm and expand the findings of the PREDIMED in a non-Mediterranean population and to determine the exact mechanisms of action of polyphenols

    Estimating the Duration of Pertussis Immunity Using Epidemiological Signatures

    Get PDF
    Case notifications of pertussis have shown an increase in a number of countries with high rates of routine pediatric immunization. This has led to significant public health concerns over a possible pertussis re-emergence. A leading proposed explanation for the observed increase in incidence is the loss of immunity to pertussis, which is known to occur after both natural infection and vaccination. Little is known, however, about the typical duration of immunity and its epidemiological implications. Here, we analyze a simple mathematical model, exploring specifically the inter-epidemic period and fade-out frequency. These predictions are then contrasted with detailed incidence data for England and Wales. We find model output to be most sensitive to assumptions concerning naturally acquired immunity, which allows us to estimate the average duration of immunity. Our results support a period of natural immunity that is, on average, long-lasting (at least 30 years) but inherently variable

    Business opportunities analysis using GIS: the retail distribution sector

    Full text link
    [EN] The retail distribution sector is facing a difficult time as the current landscape is characterized by ever-increasing competition. In these conditions, the search for an appropriate location strategy has the potential to become a differentiating and competitive factor. Although, in theory, an increasing level of importance is placed on geography because of its key role in understanding the success of a business, this is not the case in practice. For this reason, the process outlined in this paper has been specifically developed to detect new business locations. The methodology consists of a range of analyzes with Geographical Information Systems (GISs) from a marketing point of view. This new approach is called geomarketing. First, geodemand and geocompetition are located on two separate digital maps using spatial and non-spatial databases. Second, a third map is obtained by matching this information with the demand not dealt with properly by the current commercial offer. Third, the Kernel density allows users to visualize results, thus facilitating decision-making by managers, regardless of their professional background. The advantage of this methodology is the capacity of GIS to handle large amounts of information, both spatial and non-spatial. A practical application is performed in Murcia (Spain) with 100 supermarkets and data at a city block level, which is the highest possible level of detail. This detection process can be used in any commercial distribution company, so it can be generalized and considered a global solution for retailers.Roig Tierno, H.; Baviera-Puig, A.; Buitrago Vera, JM. (2013). Business opportunities analysis using GIS: the retail distribution sector. Global Business Perspectives. 1(3):226-238. doi:10.1007/s40196-013-0015-6S22623813Alarcón, S. (2011). The trade credit in the Spanish agrofood industry. Mediterranean Journal of Economics, Agriculture and Environment (New Medit), 10(2), 51–57.Alcaide, J. C., Calero, R., & Hernández, R. (2012). Geomarketing. Marketing territorial para vender y fidelizar más. Madrid: ESIC.Applebaum, W., & Cohen, S. B. (1961). The dynamics of store trading areas and market equilibrium. Annals of the Association of American Geographers, 51(1), 73–101.Baviera-Puig, A., Buitrago-Vera, J. M., Escriba, C., & Clemente, J. S. (2009). Geomarketing: Aplicación de los sistemas de información geográfica al marketing. Paper presented at the Octava Conferencia Iberoamericana en Sistemas, Cibernética e Informática, Orlando, FL.Baviera-Puig, A., Buitrago-Vera, J. M., & Mas-Verdú, F. (2012). Trade areas and knowledge-intensive services: The case of a technology centre. Management Decision, 50(8), 1412–1424.Baviera-Puig, A., Buitrago-Vera, J. M., & Rodríguez-Barrio, J. E. (2013). Un modelo de geomarketing para la localización de supermercados: Diseño y aplicación práctica. Documentos de Trabajo de la Cátedra Fundación Ramón Areces de Distribución Comercial (DOCFRADIS), 1, 1–27.Berumen, S. A., & Llamazares, F. (2007). La utilidad los métodos de decisión multicriterio (como el AHP) en un entorno de competitividad creciente. Cuadernos de administración, 20(34), 65–87.Birkin, M., Clarke, G., & Clarke, M. (2002). Retail geography and intelligent network planning. Chichester: Wiley.Chasco, C. (2003). El geomarketing y la distribución commercial. Investigación y Márketing, 79, 6–13.Chen, R. J. C. (2007). Significance and variety of geographic information system (GIS) applications in retail, hospitality, tourism, and consumer services. Journal of Retailing and Consumer Services, 14, 247–248.Church, R. L. (2002). Geographical information systems and location science. Computers and Operations Research, 29, 541–562.Church, R. L., & Murray, A. T. (2009). Business site selection, location analysis and GIS. Hoboken, NJ: Wiley.Clarke, G. (1998). Changing methods of location planning for retail companies. GeoJournal, 45, 289–298.Clarkson, R. M., Clarke-Hill, C. M., & Robinson, T. (1996). UK supermarket location assessment. International Journal of Retail and Distribution Management, 24(6), 22–33.Davis, P. (2006). Spatial competition in retail markets: Movie theaters. The RAND Journal of Economics, 37(4), 964–982.Ghosh, A., & McLafferty, S. L. (1982). Locating stores in uncertain environments: A scenario planning approach. Journal of Retailing, 58(4), 5–22.Härdle, W. (1991). Smoothing techniques with implementation in S. Nueva York, NY: Springer.Harris, B., & Batty, M. (1993). Locational models, geographical information, and planning support systems. Journal of Planning Education and Research, 12, 184–198.Hernandez, T. (2007). Enhancing retail location decision support: The development and application of geovisualization. Journal of Retailing and Consumer Services, 14, 249–258.Hernandez, T., & Bennison, D. (2000). The art and science of retail location decisions. International Journal of Retail and Distribution Management, 28(8), 357–367.Huff, D. (1963). Defining and estimating a trade area. Journal of Marketing, 28, 34–38.Instituto Nacional de Estadística (INE). (2011). Padrón de habitantes 2011. http://www.ine.es . Accessed 9 Oct 2012.Kelly, J. P., Freeman, D. C., & Emlen, J. M. (1993). Competitive impact model for site selection: The impact of competition, sales generators and own store cannibalization. The International Review of Retail, Distribution and Consumer Research, 3, 237–259.Latour, P., & Le Floc’h, J. (2001). Géomarketing: Principes, méthodes et applications. París: Éditions d’Organisation.Mendes, A. B., & Themido, I. H. (2004). Multi-outlet retail site location assessment. International Transactions in Operational Research, 11, 1–18.Moreno, A. (1991). Modelización cartográfica de densidades mediante estimadores Kernel. Treballs de la Societat Catalana de Geografia, 6(30), 155–170.Moreno, A. (2007). Obtención de capas raster de densidad. In A. Moreno (Coord.), Sistemas y Análisis de la información Geográfica. Manual de autoaprendizaje con ArcGIS (pp. 685–691). Madrid: Editorial RA-MA.Murad, A. A. (2003). Creating a GIS application for retail centers in Jeddah City. International Journal of Applied Earth Observation and Geoinformation, 4, 329–338.Murad, A. A. (2007). Using GIS for retail planning in Jeddah City. American Journal of Applied Sciences, 4(10), 820–826.Musyoka, S. M., Mutyauvyu, S. M., Kiema, J. B. K., Karanja, F. N., & Siriba, D. N. (2007). Market segmentation using geographic information systems (GIS). A case study of the soft drink industry in Kenya. Marketing Intelligence and Planning, 25(6), 632–642.Nielsen Database. (2012). Retailers Database. http://www.nielsen.com/global/en.html . Accessed 12 Oct 2012.Ozimec, A. M., Natter, M., & Reutterer, T. (2010). Geographical information systems-based marketing decisions: Effects of alternative visualizations on decision quality. Journal of Marketing, 74, 94–110.Reilly, W. J. (1931). The law of retail gravitation. New York: Knickerbocker Press.Rob, M. A. (2003). Some challenges of integrating spatial and non-spatial datasets using a geographical information system. Information Technology for Development, 10, 171–178.Rosenblatt, M. (1956). Remarks on some nonparametric estimates of a density functions. Annals of Mathematical Statistic, 27, 832–837.Sede Electrónica del Catastro. (2012). Datos Catastrales. https://www.sedecatastro.gob.es . Accessed 10 Oct 2012.Silverman, B. W. (1986). Density estimation for statistics and data analysis. London: Chapman and Hall.Sleight, P., Harris, R., & Webber, R. (2005). Geodemographics, GIS and neighbourhood targeting. Chichester: Wiley.Suárez-Vega, R., Santos-Peñate, D. R., & Dorta-González, P. (2012). Location models and GIS tools for retail site location. Applied Geography, 35, 12–22.Thaler, R. (1986). The psychology and economics conference handbook: Comments on Simon, on Einhorn and Hogarth, and on Tversky and Kahneman. The Journal of Business, 59(4), 279–284.Wood, S., & Reynolds, J. (2012). Leveraging locational insights within retail store development? Assessing the use of location planners’ knowledge in retail marketing. Geoforum, 43, 1076–1087

    Restoring brain function after stroke - bridging the gap between animals and humans

    Get PDF
    Stroke is the leading cause of complex adult disability in the world. Recovery from stroke is often incomplete, which leaves many people dependent on others for their care. The improvement of long-term outcomes should, therefore, be a clinical and research priority. As a result of advances in our understanding of the biological mechanisms involved in recovery and repair after stroke, therapeutic opportunities to promote recovery through manipulation of poststroke plasticity have never been greater. This work has almost exclusively been carried out in preclinical animal models of stroke with little translation into human studies. The challenge ahead is to develop a mechanistic understanding of recovery from stroke in humans. Advances in neuroimaging techniques now enable us to reconcile behavioural accounts of recovery with molecular and cellular changes. Consequently, clinical trials can be designed in a stratified manner that takes into account when an intervention should be delivered and who is most likely to benefit. This approach is expected to lead to a substantial change in how restorative therapeutic strategies are delivered in patients after stroke
    corecore