Human T-cell lymphotropic virus type I infection among Japanese immigrants in Peru

AbstractObjective: A prospective study was conducted to determine the prevalence of human T-cell lymphotropic virus type I (HTLV-I) infection among healthy Japanese migrants and their descendents in Peru.Methods: A total of 407 persons were enrolled at the Peruvian-Japanese Medical Center in Lima during routine visits for health evaluations. Each study volunteer was interviewed to obtain clinical and epidemiologic data, and a blood sample was obtained for HTLV-I testing. Sera samples were initially tested for antibody by enzyme-linked immunosorbent assay (ELISA). All ELISA reactive sera were further tested by Western Blot assay, and the results were recorded in accordance with the manufacturer's recommendations.Results: Among the 407 study volunteers, HTLV-I infection was demonstrated in 6.8% (19280) of females and 3.2% (4127) of males. Infection rates significantly increased with age, with 28.5% of volunteers over 80 years of age being positive (P < 0.05). The migrants from Japan had the highest infection rate (15.8%), whereas none of the second generation volunteers were positive (P < 0.05). The incidence among those with ancestors from Okinawa was 9.3%, and for those with ancestors from the central zone of Japan, 1.2% (P < 0.05).Conclusions: These data indicated that HTLV-I infection rates were highest among the older volunteers from Okinawa and Kyushu, and that evidence of infection was not found among their offspring

Influence of socio-economic, demographic and climate factors on the regional distribution of dengue in the United States and Mexico

Unidad de excelencia María de Maeztu CEX2019-000940-MBackground: This study examines the impact of climate, socio-economic and demographic factors on the incidence of dengue in regions of the United States and Mexico. We select factors shown to predict dengue at a local level and test whether the association can be generalized to the regional or state level. In addition, we assess how different indicators perform compared to per capita gross domestic product (GDP), an indicator that is commonly used to predict the future distribution of dengue. Methods: A unique spatial-temporal dataset was created by collating information from a variety of data sources to perform empirical analyses at the regional level. Relevant regions for the analysis were selected based on their receptivity and vulnerability to dengue. A conceptual framework was elaborated to guide variable selection. The relationship between the incidence of dengue and the climate, socio-economic and demographic factors was modelled via a Generalized Additive Model (GAM), which also accounted for the spatial and temporal auto-correlation. Results: The socio-economic indicator (representing household income, education of the labour force, life expectancy at birth, and housing overcrowding), as well as more extensive access to broadband are associated with a drop in the incidence of dengue; by contrast, population growth and inter-regional migration are associated with higher incidence, after taking climate into account. An ageing population is also a predictor of higher incidence, but the relationship is concave and flattens at high rates. The rate of active physicians is associated with higher incidence, most likely because of more accurate reporting. If focusing on Mexico only, results remain broadly similar, however, workforce education was a better predictor of a drop in the incidence of dengue than household income. Conclusions: Two lessons can be drawn from this study: first, while higher GDP is generally associated with a drop in the incidence of dengue, a more granular analysis reveals that the crucial factors are a rise in education (with fewer jobs in the primary sector) and better access to information or technological infrastructure. Secondly, factors that were shown to have an impact of dengue at the local level are also good predictors at the regional level. These indices may help us better understand factors responsible for the global distribution of dengue and also, given a warming climate, may help us to better predict vulnerable populations on a larger scale

Universality of finite-size corrections to the number of critical percolation clusters

Monte-Carlo simulations on a variety of 2d percolating systems at criticality suggest that the excess number of clusters in finite systems over the bulk value of nc is a universal quantity, dependent upon the system shape but independent of the lattice and percolation type. Values of nc are found to high accuracy, and for bond percolation confirm the theoretical predictions of Temperley and Lieb, and Baxter, Temperley, and Ashley, which we have evaluated explicitly in terms of simple algebraic numbers. Predictions for the fluctuations are also verified for the first time.Comment: 13 pages, 2 figs., Latex, submitted to Phys. Rev. Let

Scale-free brain functional networks

Functional magnetic resonance imaging (fMRI) is used to extract {\em functional networks} connecting correlated human brain sites. Analysis of the resulting networks in different tasks shows that: (a) the distribution of functional connections, and the probability of finding a link vs. distance are both scale-free, (b) the characteristic path length is small and comparable with those of equivalent random networks, and (c) the clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these properties, typical of scale-free small world networks, reflect important functional information about brain states.Comment: 4 pages, 5 figures, 2 table

Cross-over behaviour in a communication network

We address the problem of message transfer in a communication network. The network consists of nodes and links, with the nodes lying on a two dimensional lattice. Each node has connections with its nearest neighbours, whereas some special nodes, which are designated as hubs, have connections to all the sites within a certain area of influence. The degree distribution for this network is bimodal in nature and has finite variance. The distribution of travel times between two sites situated at a fixed distance on this lattice shows fat fractal behaviour as a function of hub-density. If extra assortative connections are now introduced between the hubs so that each hub is connected to two or three other hubs, the distribution crosses over to power-law behaviour. Cross-over behaviour is also seen if end-to-end short cuts are introduced between hubs whose areas of influence overlap, but this is much milder in nature. In yet another information transmission process, namely, the spread of infection on the network with assortative connections, we again observed cross-over behaviour of another type, viz. from one power-law to another for the threshold values of disease transmission probability. Our results are relevant for the understanding of the role of network topology in information spread processes.Comment: 12 figure