A geoprocessing approach for studying and controlling schistosomiasis in the state of Minas Gerais, Brazil

Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.

Quantified set inversion with applications to control

This paper describes a new reliable method, based on modal interval analysis (MIA) and set inversion (SI) techniques, for the characterization of solution sets defined by quantified constraints satisfaction problems (QCSP) over continuous domains. The presented methodology, called quantified set inversion (QSI), can be used over a wide range of engineering problems involving uncertain nonlinear models. Finally, an application on parameter identification is presented

A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data

Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process

Alternative PCR protocol using a single primer set for assessing DNA quality in several tissues from a large variety of mammalian species living in areas endemic for leishmaniasis

The aim of this work was to establish a modified pre-diagnostic polymerase chain reaction (PCR) protocol using a single primer set that enables successful amplification of a highly conserved mammalian sequence in order to determine overall sample DNA quality for multiple mammalian species that inhabit areas endemic for leishmaniasis. The gene encoding interphotoreceptor retinoid-binding protein (IRBP), but not other conserved genes, was efficiently amplified in DNA samples from tail skin, ear skin, bone marrow, liver and spleen from all of the species tested. In tissue samples that were PCR-positive for Leishmania, we found that DNA from 100%, 55% and 22% of the samples tested resulted in a positive PCR reaction for the IRBP, beta-actin and beta-globin genes, respectively. Nucleotide sequencing of an IRBP amplicon resolved any questions regarding the taxonomical classification of a rodent, which was previously based simply on the morphological features of the animal. Therefore, PCR amplification and analysis of the IRBP amplicon are suitable for pre-diagnostically assessing DNA quality and identifying mammalian species living in areas endemic to leishmaniasis and other diseases.

Map of ecological networks for landscape planning

This paper presents a method based on a geographical information system (GIS) to model ecological networks in a fragmented landscape. The ecological networks are generated with the help of a landscape model (which integrate human activities) and with a wildlife dispersal model. The main results are maps which permit the analysis and the understanding of the impact of human activities on wildlife dispersal. Three applications in a study area are presented: ecological networks at the landscape scale, conflicting areas at the farmstead scale and ecological distance between biotopes. These applications show the flexibility of the model and its potential to give information on ecological networks at different planning scales.

Histology-driven data mining of lipid signatures from multiple imaging mass spectrometry analyses: application to human colorectal cancer liver metastasis biopsies.

Imaging mass spectrometry (IMS) represents an innovative tool in the cancer research pipeline, which is increasingly being used in clinical and pharmaceutical applications. The unique properties of the technique, especially the amount of data generated, make the handling of data from multiple IMS acquisitions challenging. This work presents a histology-driven IMS approach aiming to identify discriminant lipid signatures from the simultaneous mining of IMS data sets from multiple samples. The feasibility of the developed workflow is evaluated on a set of three human colorectal cancer liver metastasis (CRCLM) tissue sections. Lipid IMS on tissue sections was performed using MALDI-TOF/TOF MS in both negative and positive ionization modes after 1,5-diaminonaphthalene matrix deposition by sublimation. The combination of both positive and negative acquisition results was performed during data mining to simplify the process and interrogate a larger lipidome into a single analysis. To reduce the complexity of the IMS data sets, a sub data set was generated by randomly selecting a fixed number of spectra from a histologically defined region of interest, resulting in a 10-fold data reduction. Principal component analysis confirmed that the molecular selectivity of the regions of interest is maintained after data reduction. Partial least-squares and heat map analyses demonstrated a selective signature of the CRCLM, revealing lipids that are significantly up- and down-regulated in the tumor region. This comprehensive approach is thus of interest for defining disease signatures directly from IMS data sets by the use of combinatory data mining, opening novel routes of investigation for addressing the demands of the clinical setting.

Current cytogenetic map of the common shrew, Sorex araneus L.: localization of 7 genes and 4 microsatellites

Here we present information on the assignment of 7 genes, ACADVL, ADORA3, ATP7A, MTMR4, MYH2, HBB, TSPAN-3, and 4 common shrew microsatellites to chromosomes of the common shrew (Sorex araneus) and on the current status of its cytogenetic map. Comparative mapping data were used for the analysis of evolutionary chromosomal rearrangements in the common shrew genome.

National Health System Virtual Library Viability Project (Spain)

Introduction: The ICT progress and development are making the set up of virtual libraries easier, with great advantages for users in terms of immediate access to vast amounts of library information, online resources, and services. Most of the Autonomous Spanish Regions are presently working on the establishment of virtual libraries with the aim of optimising economic resources destined to subscribe bibliographic information sources and offering qualified documentary services to Public Health System Professionals. The Ministry of Health and Social Policy, an institution unifying health matters, issued this Project to study the National Health System Virtual Library creation viability, in order to guarantee relevant scientific information access equity. Objectives: - To study the National Health System (NHS) Virtual Library set up viability. - To elaborate the Spanish territory health information resource map. - To identify the appropriate technological model. - To identify the documentary services to be offered. - To identify the more optimum functional, structural model. - To identify the economic model. Method: - To create a chart organization for the project´s management. - To organize Work groups. - To elaborate a standardised survey model for the libraries of the autonomous regions. Results: - Identification of the different Autonomous Region libraries of health models. - Recommendations for the NHS Virtual Library: - Functional, structural model - Technological model - Financial-economic model Conclusions: The fact that the Virtual Library would be an invaluable space for access to quality scientific information, as well as that the minimum services could be offered to every NHS user regardless of geographical situation, is confirmed. Accordingly, we thought about three different models to develop the Virtual Library, depending on this initial analysis, which will allow us to establish the most suitable model for the Spanish National Health System, considering its economic, functional and technological recommendations. It would be necessary to do a study for the NHS Virtual Library Set Up following the recommendations arising from this Project.

The connectome mapper: an open-source processing pipeline to map connectomes with MRI.

Researchers working in the field of global connectivity analysis using diffusion magnetic resonance imaging (MRI) can count on a wide selection of software packages for processing their data, with methods ranging from the reconstruction of the local intra-voxel axonal structure to the estimation of the trajectories of the underlying fibre tracts. However, each package is generally task-specific and uses its own conventions and file formats. In this article we present the Connectome Mapper, a software pipeline aimed at helping researchers through the tedious process of organising, processing and analysing diffusion MRI data to perform global brain connectivity analyses. Our pipeline is written in Python and is freely available as open-source at www.cmtk.org.

A new training set-up for trans-apical aortic valve replacement.

Trans-apical aortic valve replacement (AVR) is a new and rapidly growing therapy. However, there are only few training opportunities. The objective of our work is to build an appropriate artificial model of the heart that can replace the use of animals for surgical training in trans-apical AVR procedures. To reduce the necessity for fluoroscopy, we pursued the goal of building a translucent model of the heart that has nature-like dimensions. A simplified 3D model of a human heart with its aortic root was created in silico using the SolidWorks Computer-Aided Design (CAD) program. This heart model was printed using a rapid prototyping system developed by the Fab@Home project and dip-coated two times with dispersion silicone. The translucency of the heart model allows the perception of the deployment area of the valved-stent without using heavy imaging support. The final model was then placed in a human manikin for surgical training on trans-apical AVR procedure. Trans-apical AVR with all the necessary steps (puncture, wiring, catheterization, ballooning etc.) can be realized repeatedly in this setting.

Gap probabilities for the cardinal sine

We study the zero set of random analytic functions generated by a sum of the cardinal sine functions which form an orthogonal basis for the Paley-Wiener space. As a model case, we consider real-valued Gaussian coefficients. It is shown that the asymptotic probability that there is no zero in a bounded interval decays exponentially as a function of the length.

Phylogenetic approach reveals that virus genotype largely determines HIV set-point viral load.

HIV virulence, i.e. the time of progression to AIDS, varies greatly among patients. As for other rapidly evolving pathogens of humans, it is difficult to know if this variance is controlled by the genotype of the host or that of the virus because the transmission chain is usually unknown. We apply the phylogenetic comparative approach (PCA) to estimate the heritability of a trait from one infection to the next, which indicates the control of the virus genotype over this trait. The idea is to use viral RNA sequences obtained from patients infected by HIV-1 subtype B to build a phylogeny, which approximately reflects the transmission chain. Heritability is measured statistically as the propensity for patients close in the phylogeny to exhibit similar infection trait values. The approach reveals that up to half of the variance in set-point viral load, a trait associated with virulence, can be heritable. Our estimate is significant and robust to noise in the phylogeny. We also check for the consistency of our approach by showing that a trait related to drug resistance is almost entirely heritable. Finally, we show the importance of taking into account the transmission chain when estimating correlations between infection traits. The fact that HIV virulence is, at least partially, heritable from one infection to the next has clinical and epidemiological implications. The difference between earlier studies and ours comes from the quality of our dataset and from the power of the PCA, which can be applied to large datasets and accounts for within-host evolution. The PCA opens new perspectives for approaches linking clinical data and evolutionary biology because it can be extended to study other traits or other infectious diseases.

Iowa Transportation Map, 2004

State of Iowa transportation road map produced by the Department of Transportation.