The geography of recent genetic ancestry across Europe

The recent genealogical history of human populations is a complex mosaic formed by individual migration, large-scale population movements, and other demographic events. Population genomics datasets can provide a window into this recent history, as rare traces of recent shared genetic ancestry are detectable due to long segments of shared genomic material. We make use of genomic data for 2,257 Europeans (the POPRES dataset) to conduct one of the first surveys of recent genealogical ancestry over the past three thousand years at a continental scale. We detected 1.9 million shared genomic segments, and used the lengths of these to infer the distribution of shared ancestors across time and geography. We find that a pair of modern Europeans living in neighboring populations share around 10-50 genetic common ancestors from the last 1500 years, and upwards of 500 genetic ancestors from the previous 1000 years. These numbers drop off exponentially with geographic distance, but since genetic ancestry is rare, individuals from opposite ends of Europe are still expected to share millions of common genealogical ancestors over the last 1000 years. There is substantial regional variation in the number of shared genetic ancestors: especially high numbers of common ancestors between many eastern populations likely date to the Slavic and/or Hunnic expansions, while much lower levels of common ancestry in the Italian and Iberian peninsulas may indicate weaker demographic effects of Germanic expansions into these areas and/or more stably structured populations. Recent shared ancestry in modern Europeans is ubiquitous, and clearly shows the impact of both small-scale migration and large historical events. Population genomic datasets have considerable power to uncover recent demographic history, and will allow a much fuller picture of the close genealogical kinship of individuals across the world.Comment: Full size figures available from http://www.eve.ucdavis.edu/~plralph/research.html; or html version at http://ralphlab.usc.edu/ibd/ibd-paper/ibd-writeup.xhtm

Business opportunities analysis using GIS: the retail distribution sector

[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

Routes for breaching and protecting genetic privacy

We are entering the era of ubiquitous genetic information for research, clinical care, and personal curiosity. Sharing these datasets is vital for rapid progress in understanding the genetic basis of human diseases. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we technically map threats to genetic privacy and discuss potential mitigation strategies for privacy-preserving dissemination of genetic data.Comment: Draft for comment

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

Acknowledgments We thank Reik V. Donner for inspiring suggestions that initialized the work presented herein. Jan H. Feldhoff is credited for providing us with the STARS simulation data and for his contributions to fruitful discussions. Comments by the anonymous reviewers are gratefully acknowledged as they led to substantial improvements of the manuscript.Peer reviewedPublisher PD

Association between the -455T>C promoter polymorphism of the APOC3 gene and the metabolic syndrome in a multi-ethnic sample

<p>Abstract</p> <p>Background</p> <p>Common polymorphisms in the promoter of the <it>APOC3 </it>gene have been associated with hypertriglyceridemia and may impact on phenotypic expression of the metabolic syndrome (MetS). The rs7566605 marker, located near the <it>INSIG2 </it>gene, has been found to be associated with obesity, making it also a potential genetic determinant for MetS. The objective of this study is to examine the <it>APOC3 </it>-455T>C and the <it>INSIG2 </it>rs7566605 polymorphisms as potential genetic determinants for MetS in a multi-ethnic sample.</p> <p>Methods</p> <p>Subjects were genotyped for both the <it>APOC3 </it>-455T>C and <it>INSIG2 </it>rs7566605 polymorphisms, and classified for the presence or absence of MetS (NCEP ATP III and IDF definitions). The total study population included 2675 subjects (≥18 years of age) from six different geographical ancestries.</p> <p>Results</p> <p>For the overall study population, the prevalence of MetS was 22.6% (NCEP ATP III definition). Carriers of ≥1 copy of <it>APOC3 </it>-455C were more likely to have MetS (NCEP ATP III definition) than noncarriers (carrier odds ratio 1.73, 95% CI 1.40 to 2.14, adjusting for age and study group). The basis of the association was related not only to a higher proportion of -455C carriers meeting the triglyceride and high-density lipoprotein cholesterol criteria, but also the blood pressure criteria compared with wild-type homozygotes. Plasma apo C-III concentrations were not associated with <it>APOC3 </it>-455T>C genotype. The <it>INSIG2 </it>rs7566605 polymorphism was not associated with MetS or measures of obesity.</p> <p>Conclusion</p> <p>Meta-analysis of the sample of multiple geographic ancestries indicated that the functional -455T>C promoter polymorphism in <it>APOC3 </it>was associated with an approximately 2-fold increased risk of MetS, whereas the <it>INSIG2 </it>rs7566605 polymorphism was not associated with MetS.</p

What we talk about when we talk about "global mindset": managerial cognition in multinational corporations

Recent developments in the global economy and in multinational corporations have placed significant emphasis on the cognitive orientations of managers, giving rise to a number of concepts such as “global mindset” that are presumed to be associated with the effective management of multinational corporations (MNCs). This paper reviews the literature on global mindset and clarifies some of the conceptual confusion surrounding the construct. We identify common themes across writers, suggesting that the majority of studies fall into one of three research perspectives: cultural, strategic, and multidimensional. We also identify two constructs from the social sciences that underlie the perspectives found in the literature: cosmopolitanism and cognitive complexity and use these two constructs to develop an integrative theoretical framework of global mindset. We then provide a critical assessment of the field of global mindset and suggest directions for future theoretical and empirical research

Vetufebrus ovatus n. gen., n. sp. (Haemospororida: Plasmodiidae) vectored by a streblid bat fly (Diptera: Streblidae) in Dominican amber

This is the publisher’s final pdf. The published article is copyrighted by BioMed Central Ltd. and can be found at: http://www.parasitesandvectors.com/.Background: Both sexes of bat flies in the families Nycteribiidae and Streblidae (Diptera: Hippoboscoidea) reside in\ud the hair or on the wing membranes of bats and feed on blood. Members of the Nycteribiidae transmit bat malaria\ud globally however extant streblids have never been implemented as vectors of bat malaria. The present study\ud shows that during the Tertiary, streblids also were vectors of bat malaria.\ud Results: A new haemospororidan, Vetufebrus ovatus, n. gen., n. sp., (Haemospororida: Plasmodiidae) is described\ud from two oocysts attached to the midgut wall and sporozoites in salivary glands and ducts of a fossil bat fly\ud (Diptera: Streblidae) in Dominican amber. The new genus is characterized by ovoid oocysts, short, stubby\ud sporozoites with rounded ends and its occurrence in a fossil streblid. This is the first haemosporidian reported from\ud a streblid bat fly and shows that representatives of the Hippoboscoidea were vectoring bat malaria in the New\ud World by the mid-Tertiary.\ud Conclusions: This report is the first evidence of an extant or extinct streblid bat fly transmitting malaria.\ud Discovering a mid-tertiary malarial parasite in a fossil streblid that closely resembles members of a malarial genus\ud found in nycteribiid bat flies today shows how little we know about the vector associations of streblids. While no\ud malaria parasites have been found in extant streblids, they probably occur and it is possible that streblids were the\ud earliest lineage of flies that transmitted bat malaria to Chiroptera

Clonal hematopoiesis and risk of prostate cancer in large samples of European ancestry men.

Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk

Coherent anti-Stokes Raman scattering imaging of lipids in cancer metastasis

<p>Abstract</p> <p>Background</p> <p>Lipid-rich tumours have been associated with increased cancer metastasis and aggressive clinical behaviours. Nonetheless, pathologists cannot classify lipid-rich tumours as a clinically distinctive form of carcinoma due to a lack of mechanistic understanding on the roles of lipids in cancer development.</p> <p>Methods</p> <p>Coherent anti-Stokes Raman scattering (CARS) microscopy is employed to study cancer cell behaviours in excess lipid environments <it>in vivo </it>and <it>in vitro</it>. The impacts of a high fat diet on cancer development are evaluated in a Balb/c mice cancer model. Intravital flow cytometry and histology are employed to enumerate cancer cell escape to the bloodstream and metastasis to lung tissues, respectively. Cancer cell motility and tissue invasion capability are also evaluated in excess lipid environments.</p> <p>Results</p> <p>CARS imaging reveals intracellular lipid accumulation is induced by excess free fatty acids (FFAs). Excess FFAs incorporation onto cancer cell membrane induces membrane phase separation, reduces cell-cell contact, increases surface adhesion, and promotes tissue invasion. Increased plasma FFAs level and visceral adiposity are associated with early rise in circulating tumour cells and increased lung metastasis. Furthermore, CARS imaging reveals FFAs-induced lipid accumulation in primary, circulating, and metastasized cancer cells.</p> <p>Conclusion</p> <p>Lipid-rich tumours are linked to cancer metastasis through FFAs-induced physical perturbations on cancer cell membrane. Most importantly, the revelation of lipid-rich circulating tumour cells suggests possible development of CARS intravital flow cytometry for label-free detection of early-stage cancer metastasis.</p