1,735 research outputs found

    Physical Properties and Seasonal Behavior of H2O, HDO, CO2 and Trace Gases on Mars: Quantitative Mapping from Earth-Based Observatories

    Get PDF
    Since 1997, we have used high-resolution (R greater than 40000) spectrometers on ground based-telescopes to study molecules that have astrobiological significance in Mars' atmosphere. We have used the NASA-IRTF, Keck II, and VLT telescopes in the 1.0-5.0 micron range. The spectrometer is set at a wavelength to detect specific molecules. Spectral/spatial images are produced. Extracts from these images provide column densities centered at latitude/longitude locations (resolution ~400km at sub-Earth point). We have mapped the O2 singlet-Delta emission (a proxy for ozone), HDO, and H2O for seasonal dates throughout the Martian year. Previously undiscovered isotopic bands of CO2 have been identified along with isotopic forms of CO. We are searching for other molecules that have astrobiological importance and have successfully measured methane in Mars' atmosphere

    Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space

    Get PDF
    Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multidrug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDR-TB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e. the Moran’s coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird (spatial resolution = 0.61 m) data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centres, using a 10 m2 grid-based algorithm. Geographical information system (GIS)- gridded measurements of each health centre were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDRTB covariates. Pearson’s correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS® module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases, using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centres and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran’s coefficient into uncorrelated, orthogonal map pattern components which revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations

    PET imaging of in vivo caspase-3/7 activity following myocardial ischemia-reperfusion injury with the radiolabeled isatin sulfonamide analogue [(18)F]WC-4-116

    Get PDF
    The utility of [(18)F]WC-4-116, a PET tracer for imaging caspase-3 activation, was evaluated in an animal model of myocardial apoptosis. [(18)F]WC-4-116 was injected into rats at 3 hours after a 30 min period of ischemia induced by temporary occlusion of the left anterior descending coronary artery in Sprague-Dawley rats. [(18)F]WC-4-116 uptake was quantified by 1) autoradiography, 2) microPET imaging studies, and 3) post-PET biodistribution studies. MicroPET imaging also assessed uptake of the non-caspase-3-targeted tracer [(18)F]ICMT-18 at 3 hours postischemia. Enzyme assays and Western blotting assessed caspase-3 activation in both at-risk and not-at-risk regions. Caspase-3 enzyme activity increased in the at-risk but not in the not-at-risk myocardium. Quantitative autoradiographic analysis of [(18)F]WC-4-116 demonstrated nearly 2-fold higher uptake in the ischemia-reperfusion (IR) versus sham animals. [(18)F]WC-4-116 microPET imaging studies demonstrated that the IR animals was similarly elevated in relation to sham. [(18)F]ICMT-18 uptake did not increase in at-risk myocardium despite evidence of caspase-3 activation. Biodistribution studies with [(18)F]WC-4-116 confirmed the microPET findings. These data indicate that the caspase-3-PET tracer [(18)F]WC-4-116 can noninvasively image in vivo caspase activity during myocardial apoptosis and may be useful for clinical imaging in humans

    Remote and field level quantification of vegetation covariates for malaria mapping in three rice agro-village complexes in Central Kenya

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>We examined algorithms for malaria mapping using the impact of reflectance calibration uncertainties on the accuracies of three vegetation indices (VI)'s derived from QuickBird data in three rice agro-village complexes Mwea, Kenya. We also generated inferential statistics from field sampled vegetation covariates for identifying riceland <it>Anopheles arabiensis </it>during the crop season. All aquatic habitats in the study sites were stratified based on levels of rice stages; flooded, land preparation, post-transplanting, tillering, flowering/maturation and post-harvest/fallow. A set of uncertainty propagation equations were designed to model the propagation of calibration uncertainties using the red channel (band 3: 0.63 to 0.69 ÎĽm) and the near infra-red (NIR) channel (band 4: 0.76 to 0.90 ÎĽm) to generate the Normalized Difference Vegetation Index (NDVI) and the Soil Adjusted Vegetation Index (SAVI). The Atmospheric Resistant Vegetation Index (ARVI) was also evaluated incorporating the QuickBird blue band (Band 1: 0.45 to 0.52 ÎĽm) to normalize atmospheric effects. In order to determine local clustering of riceland habitats <it>Gi*(d) </it>statistics were generated from the ground-based and remotely-sensed ecological databases. Additionally, all riceland habitats were visually examined using the spectral reflectance of vegetation land cover for identification of highly productive riceland <it>Anopheles </it>oviposition sites.</p> <p>Results</p> <p>The resultant VI uncertainties did not vary from surface reflectance or atmospheric conditions. Logistic regression analyses of all field sampled covariates revealed emergent vegetation was negatively associated with mosquito larvae at the three study sites. In addition, floating vegetation (-ve) was significantly associated with immature mosquitoes in Rurumi and Kiuria (-ve); while, turbidity was also important in Kiuria. All spatial models exhibit positive autocorrelation; similar numbers of log-counts tend to cluster in geographic space. The spectral reflectance from riceland habitats, examined using the remote and field stratification, revealed post-transplanting and tillering rice stages were most frequently associated with high larval abundance and distribution.</p> <p>Conclusion</p> <p>NDVI, SAVI and ARVI generated from QuickBird data and field sampled vegetation covariates modeled cannot identify highly productive riceland <it>An. arabiensis </it>aquatic habitats. However, combining spectral reflectance of riceland habitats from QuickBird and field sampled data can develop and implement an Integrated Vector Management (IVM) program based on larval productivity.</p

    Spatially targeting Culex quinquefasciatus aquatic habitats on modified land cover for implementing an Integrated Vector Management (IVM) program in three villages within the Mwea Rice Scheme, Kenya

    Get PDF
    BACKGROUND: Continuous land cover modification is an important part of spatial epidemiology because it can help identify environmental factors and Culex mosquitoes associated with arbovirus transmission and thus guide control intervention. The aim of this study was to determine whether remotely sensed data could be used to identify rice-related Culex quinquefasciatus breeding habitats in three rice-villages within the Mwea Rice Scheme, Kenya. We examined whether a land use land cover (LULC) classification based on two scenes, IKONOS at 4 m and Landsat Thematic Mapper at 30 m could be used to map different land uses and rice planted at different times (cohorts), and to infer which LULC change were correlated to high density Cx. quinquefasciatus aquatic habitats. We performed a maximum likelihood unsupervised classification in Erdas Imagine V8.7(® )and generated three land cover classifications, rice field, fallow and built environment. Differentially corrected global positioning systems (DGPS) ground coordinates of Cx. quinquefasciatus aquatic habitats were overlaid onto the LULC maps generated in ArcInfo 9.1(®). Grid cells were stratified by levels of irrigation (well-irrigated and poorly-irrigated) and varied according to size of the paddy. RESULTS: Total LULC change between 1988–2005 was 42.1 % in Kangichiri, 52.8 % in Kiuria and and 50.6 % Rurumi. The most frequent LULC changes was rice field to fallow and fallow to rice field. The proportion of aquatic habitats positive for Culex larvae in LULC change sites was 77.5% in Kangichiri, 72.9% in Kiuria and 73.7% in Rurumi. Poorly – irrigated grid cells displayed 63.3% of aquatic habitats among all LULC change sites. CONCLUSION: We demonstrate that optical remote sensing can identify rice cultivation LULC sites associated with high Culex oviposition. We argue that the regions of higher Culex abundance based on oviposition surveillance sites reflect underlying differences in abundance of larval habitats which is where limited control resources could be concentrated to reduce vector larval abundance
    • …
    corecore