Simultaneous B(0)- and B(1)+-map acquisition for fast localized shim, frequency, and RF power determination in the heart at 3 T.

High-field (>or=3 T) cardiac MRI is challenged by inhomogeneities of both the static magnetic field (B(0)) and the transmit radiofrequency field (B(1)+). The inhomogeneous B fields not only demand improved shimming methods but also impede the correct determination of the zero-order terms, i.e., the local resonance frequency f(0) and the radiofrequency power to generate the intended local B(1)+ field. In this work, dual echo time B(0)-map and dual flip angle B(1)+-map acquisition methods are combined to acquire multislice B(0)- and B(1)+-maps simultaneously covering the entire heart in a single breath hold of 18 heartbeats. A previously proposed excitation pulse shape dependent slice profile correction is tested and applied to reduce systematic errors of the multislice B(1)+-map. Localized higher-order shim correction values including the zero-order terms for frequency f(0) and radiofrequency power can be determined based on the acquired B(0)- and B(1)+-maps. This method has been tested in 7 healthy adult human subjects at 3 T and improved the B(0) field homogeneity (standard deviation) from 60 Hz to 35 Hz and the average B(1)+ field from 77% to 100% of the desired B(1)+ field when compared to more commonly used preparation methods.

Polytene chromosome map and inversion polymorphism in Drosophila mediopunctata

Drosophila mediopunctata belongs to the tripunctata group, and is one of the commonest Drosophila species collected in some places in Brazil, especially in the winter. A standard map of the polytene chromosomes is presented. The breakpoints of the naturally occurring chromosomal rearrangements are marked on the map. The distribution of breaking points through the chromosomes of D. mediopunctata is apparently non-random. Chromosomes X, II and IV show inversion polymorphisms. Chromosome II is the most polymorphic, with 17 inversions, 8 inversions in the distal region and 9 in the proximal region. Chromosome X has four different gene arrangements, while chromosome IV has only two.

Unpacking the cognitive map: the parallel map theory of hippocampal function

In the parallel map theory, the hippocampus encodes space with 2 mapping systems. The bearing map is constructed primarily in the dentate gyrus from directional cues such as stimulus gradients. The sketch map is constructed within the hippocampus proper from positional cues. The integrated map emerges when data from the bearing and sketch maps are combined. Because the component maps work in parallel, the impairment of one can reveal residual learning by the other. Such parallel function may explain paradoxes of spatial learning, such as learning after partial hippocampal lesions, taxonomic and sex differences in spatial learning, and the function of hippocampal neurogenesis. By integrating evidence from physiology to phylogeny, the parallel map theory offers a unified explanation for hippocampal function.

A method to obtain the integrated contour image in colour scenes

This paper describes a method to achieve the most relevant contours of an image. The presented method proposes to integrate the information of the local contours from chromatic components such as H, S and I, taking into account the criteria of coherence of the local contour orientation values obtained from each of these components. The process is based on parametrizing pixel by pixel the local contours (magnitude and orientation values) from the H, S and I images. This process is carried out individually for each chromatic component. If the criterion of dispersion of the obtained orientation values is high, this chromatic component will lose relevance. A final processing integrates the extracted contours of the three chromatic components, generating the so-called integrated contours image

Fas ligand-induced proinflammatory transcriptional responses in reconstructed human epidermis. Recruitment of the epidermal growth factor receptor and activation of MAP kinases.

Fas ligand (FasL) exerts potent proapoptotic and proinflammatory actions on epidermal keratinocytes and has been implicated in the pathogenesis of eczema, toxic epidermal necrolysis, and drug-induced skin eruptions. We used reconstructed human epidermis to investigate the mechanisms of FasL-induced inflammatory responses and their relationships with FasL-triggered caspase activity. Caspase activity was a potent antagonist of the pro-inflammatory gene expression triggered by FasL prior to the onset of cell death. Furthermore, we found that FasL-stimulated autocrine production of epidermal growth factor receptor (EGFR) ligands, and the subsequent activation of EGFR and ERK1 and ERK2 mitogen-activated protein kinases, were obligatory extracellular steps for the FasL-induced expression of a subset of inflammatory mediators, including CXCL8/interleukin (IL)-8, ICAM-1, IL-1alpha, IL-1beta, CCL20/MIP-3alpha, and thymic stromal lymphopoietin. These results expand the known physiological role of EGFR and its ligands from promoting keratinocyte mitogenesis and survival to mediating FasL-induced epidermal inflammation.

Improving Clustering Algorithms for Image Segmentation using Contour and Region Information

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach

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.

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.

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.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Iowa Transportation Map, 2004

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

Multiple non-collinear TF-map alignments of promoter regions

Background: The analysis of the promoter sequence of genes with similar expression patterns isa basic tool to annotate common regulatory elements. Multiple sequence alignments are on thebasis of most comparative approaches. The characterization of regulatory regions from coexpressedgenes at the sequence level, however, does not yield satisfactory results in manyoccasions as promoter regions of genes sharing similar expression programs often do not shownucleotide sequence conservation.Results: In a recent approach to circumvent this limitation, we proposed to align the maps ofpredicted transcription factors (referred as TF-maps) instead of the nucleotide sequence of tworelated promoters, taking into account the label of the corresponding factor and the position in theprimary sequence. We have now extended the basic algorithm to permit multiple promotercomparisons using the progressive alignment paradigm. In addition, non-collinear conservationblocks might now be identified in the resulting alignments. We have optimized the parameters ofthe algorithm in a small, but well-characterized collection of human-mouse-chicken-zebrafishorthologous gene promoters.Conclusion: Results in this dataset indicate that TF-map alignments are able to detect high-levelregulatory conservation at the promoter and the 3'UTR gene regions, which cannot be detectedby the typical sequence alignments. Three particular examples are introduced here to illustrate thepower of the multiple TF-map alignments to characterize conserved regulatory elements inabsence of sequence similarity. We consider this kind of approach can be extremely useful in thefuture to annotate potential transcription factor binding sites on sets of co-regulated genes fromhigh-throughput expression experiments.

Transcription factor map alignment of promoter regions

We address the problem of comparing and characterizing the promoter regions of genes with similar expression patterns. This remains a challenging problem in sequence analysis, because often the promoter regions of co-expressed genes do not show discernible sequence conservation. In our approach, thus, we have not directly compared the nucleotide sequence of promoters. Instead, we have obtained predictions of transcription factor binding sites, annotated the predicted sites with the labels of the corresponding binding factors, and aligned the resulting sequences of labels—to which we refer here as transcription factor maps (TF-maps). To obtain the global pairwise alignment of two TF-maps, we have adapted an algorithm initially developed to align restriction enzyme maps. We have optimized the parameters of the algorithm in a small, but well-curated, collection of human–mouse orthologous gene pairs. Results in this dataset, as well as in an independent much larger dataset from the CISRED database, indicate that TF-map alignments are able to uncover conserved regulatory elements, which cannot be detected by the typical sequence alignments.