Spatiotemporal dynamics of Puumala hantavirus associated with its rodent host, Myodes glareolus

Many viruses significantly impact human and animal health. Understanding the population dynamics of these viruses and their hosts can provide important insights for epidemiology and virus evolution. Puumala virus (PUUV) is a European hantavirus that may cause regional outbreaks of hemorrhagic fever with renal syndrome in humans. Here, we analyzed the spatiotemporal dynamics of PUUV circulating in local populations of its rodent reservoir host, the bank vole (Myodes glareolus) during eight years. Phylogenetic and population genetic analyses of all three genome segments of PUUV showed strong geographical structuring at a very local scale. There was a high temporal turnover of virus strains in the local bank vole populations, but several virus strains persisted through multiple years. Phylodynamic analyses showed no significant changes in the local effective population sizes of PUUV, although vole numbers and virus prevalence fluctuated widely. Microsatellite data demonstrated also a temporally persisting subdivision between local vole populations, but these groups did not correspond to the subdivision in the virus strains. We conclude that restricted transmission between vole populations and genetic drift play important roles in shaping the genetic structure and temporal dynamics of PUUV in its natural host which has several implications for zoonotic risks of the human population.

Computer vision profiling of neurite outgrowth dynamics reveals spatiotemporal modularity of Rho GTPase signaling

Rho guanosine triphosphatases (GTPases) control the cytoskeletal dynamics that power neurite outgrowth. This process consists of dynamic neurite initiation, elongation, retraction, and branching cycles that are likely to be regulated by specific spatiotemporal signaling networks, which cannot be resolved with static, steady-state assays. We present NeuriteTracker, a computer-vision approach to automatically segment and track neuronal morphodynamics in time-lapse datasets. Feature extraction then quantifies dynamic neurite outgrowth phenotypes. We identify a set of stereotypic neurite outgrowth morphodynamic behaviors in a cultured neuronal cell system. Systematic RNA interference perturbation of a Rho GTPase interactome consisting of 219 proteins reveals a limited set of morphodynamic phenotypes. As proof of concept, we show that loss of function of two distinct RhoA-specific GTPase-activating proteins (GAPs) leads to opposite neurite outgrowth phenotypes. Imaging of RhoA activation dynamics indicates that both GAPs regulate different spatiotemporal Rho GTPase pools, with distinct functions. Our results provide a starting point to dissect spatiotemporal Rho GTPase signaling networks that regulate neurite outgrowth.

A community-based assessment of the spatiotemporal distribution of influenza in a U.S.-Mexico border county during the spring 2009 novel H1N1 swine-origin influenza A pandemic

This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^

Ozone and fine particulate matter association with CVD and COPD emergency room visits in Harris County, Texas: Spatiotemporal analysis

This study represents a secondary analysis of the merging of emergency room visits and daily ozone and PM2.5. Although the adverse health effects of ozone and fine particulate matter have been documented in the literature, evidence regarding the health risks of these two pollutants in Harris County, Texas, is limited. Harris County (Houston) has sufficiently unique characteristics that analysis of these relationships in this setting and with the ozone and industry issues in Houston is informative. The objective of this study was to investigate the association between the joint exposure to ozone and fine particulate matter, and emergency room diagnoses of chronic obstructive pulmonary disease and cardiovascular disease in Harris County, Texas, from 2004 to 2009, with zero and one day lags. ^ The study variables were daily emergency room visits for Harris County, Texas, from 2004 to 2009, temperature, relative humidity, east wind component, north wind component, ozone, and fine particulate matter. Information about each patient's age, race, and gender was also included. The two dichotomous outcomes were emergency room visits diagnoses for chronic obstructive pulmonary disease and cardiovascular disease. Estimates of ozone and PM2.5 were interpolated using kriging, in which estimates of the two pollutants were predicted from monitoring data for every case residence zip code for every day of the six years, over 3 million estimates (one of each pollutant for each case in the database). ^ Logistic regressions were conducted to estimate odds ratios of the two outcomes. Three analyses were conducted: one for all records, another for visits during the four months of April and September of 2005 and 2009, and a third one for visits from zip codes that are close to PM2.5 monitoring stations (east area of Harris County). The last two analyses were designed to investigate special temporal and spatial characteristics of the associations. ^ The dataset included all ER visits surveyed by Safety Net from 2004 to 2009, exceeding 3 million visits for all causes. There were 95,765 COPD and 96,596 CVD cases during this six year period. A 1-μg/m3 increase in PM2.5 on the same day was associated with a 1.0% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses, a 0.4% increase in the odds of cardiovascular disease emergency room diagnoses, and a 0.2% increase in the odds of cardiovascular disease emergency room diagnoses on the following day. A 1-ppb increase in ozone was associated with a 0.1% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses on the same day. These four percentages add up to 1.7% of ER visits. That is, over the period of six years, one unit increase for both ozone and PM2.5 (joint increase), resulted in about 55,286 (3,252,102 * 0.017) extra ER visits for CVD or COPD, or 9,214 extra ER visits per year. ^ After adjustment for age, race, gender, day of the week, temperature, relative humidity, east wind component, north wind component, and wind speed, there were statistically significant associations between emergency room chronic obstructive pulmonary disease diagnosis in Harris County, Texas, with joint exposure to ozone and fine particulate matter for the same day; and between emergency room cardiovascular disease diagnosis and exposure to PM2.5 of the same day and the previous day. ^ Despite the small association between the two air pollutants and the health outcomes, this study points to important findings. Namely, the need to identify reasons for the increase of CVD and COPD ER visits over the course of the project, the statistical association between humidity (or whatever other variables for which it may serve as a surrogate) and CVD and COPD cases, and the confirmatory finding that males and blacks have higher odds for the two outcomes, as consistent with other studies. ^ An important finding of this research suggests that the number and distribution of PM2.5 monitors in Harris County - although not evenly spaced geographically—are adequate to detect significant association between exposure and the two outcomes. In addition, this study points to other potential factors that contribute to the rising incidence rates of CVD and COPD ER visits in Harris County such as population increases, patient history, life style, and other pollutants. Finally, results of validation, using a subset of the data demonstrate the robustness of the models.^

Spatiotemporal monitoring of water quality in coral reefs of Tayrona National Natural Park, Colombian Caribbean, 2011-2013

Tayrona National Natural Park (TNNP; 11°17' - 11°22' N and 73°53' - 74°12' W) is a hotspot of coral reef biodiversity in the Colombian Caribbean, located between the city of Santa Marta (>455,000 inhabitants) and several smaller river mouths (Rio Piedras, Mendihuaca, Guachaca). The region experiences a strong seasonal variation in physical parameters (temperature, salinity, wind, and water currents) due to alternating dry seasons with coastal upwelling and rainy seasons. Here, a range of water quality parameters relevant for coral reef functioning is provided. Water quality was measured directly above local coral reefs (~10 m water depth) by a monthly monitoring for up to 25 months in the four TNNP bays (Chengue, Gayraca, Neguanje, and Cinto) and at sites with different degree of exposition to winds, waves and water currents (exposed vs. sheltered sites) within each bay. The water quality parameters include: inorganic nutrient (nitrate, nitrite and soluble reactive phosphorus), chlorophyll a, particulate organic carbon and nitrogen concentrations (with a replication of n=3) as well as oxygen availability, biological oxygen demand, seawater pH, and water clarity (with a replication of n=4). This is by far the most comprehensive coral reefs water quality dataset for the region. A detailed description of the methods can be found within the referenced publications.

Image Processing Challenges in the Creation of Spatiotemporal Gene Expression Atlases of Developing Embryos

To properly understand and model animal embryogenesis it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains and cell dynamics. Such challenge has been confronted in recent years by a surge of atlases which integrate a statistically relevant number of different individuals to get robust, complete information about their spatiotemporal locations of gene patterns. This paper will discuss the fundamental image analysis strategies required to build such models and the most common problems found along the way. We also discuss the main challenges and future goals in the field.