Expression of PROKR1 and PROKR2 in Human Enteric Neural Precursor Cells and Identification of Sequence Variants Suggest a Role in HSCR

Background. The enteric nervous system (ENS) is entirely derived from neural crest and its normal development is regulated by specific molecular pathways. Failure in complete ENS formation results in aganglionic gut conditions such as Hirschsprung's disease (HSCR). Recently, PROKR1 expression has been demonstrated in mouse enteric neural crest derived cells and Prok-1 was shown to work coordinately with GDNF in the development of the ENS. Principal Findings. In the present report, ENS progenitors were isolated and characterized from the ganglionic gut from children diagnosed with and without HSCR, and the expression of prokineticin receptors was examined. Immunocytochemical analysis of neurosphere-forming cells demonstrated that both PROKR1 and PROKR2 were present in human enteric neural crest cells. In addition, we also performed a mutational analysis of PROKR1, PROKR2, PROK1 and PROK2 genes in a cohort of HSCR patients, evaluating them for the first time as susceptibility genes for the disease. Several missense variants were detected, most of them affecting highly conserved amino acid residues of the protein and located in functional domains of both receptors, which suggests a possible deleterious effect in their biological function. Conclusions. Our results suggest that not only PROKR1, but also PROKR2 might mediate a complementary signalling to the RET/GFRα1/GDNF pathway supporting proliferation/survival and differentiation of precursor cells during ENS development. These findings, together with the detection of sequence variants in PROKR1, PROK1 and PROKR2 genes associated to HSCR and, in some cases in combination with RET or GDNF mutations, provide the first evidence to consider them as susceptibility genes for HSCR.

Colour image processing

In the context of the round table the following topics related to image colour processing will be discussed: historical point of view. Studies of Aguilonius, Gerritsen, Newton and Maxwell. CIE standard (Commission International de lpsilaEclaraige). Colour models. RGB, HIS, etc. Colour segmentation based on HSI model. Industrial applications. Summary and discussion. At the end, video images showing the robustness of colour in front of B/W images will be presented

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

Coordinated effects of sequence variation on DNA binding, chromatin structure, and transcription.

DNA sequence variation has been associated with quantitative changes in molecular phenotypes such as gene expression, but its impact on chromatin states is poorly characterized. To understand the interplay between chromatin and genetic control of gene regulation, we quantified allelic variability in transcription factor binding, histone modifications, and gene expression within humans. We found abundant allelic specificity in chromatin and extensive local, short-range, and long-range allelic coordination among the studied molecular phenotypes. We observed genetic influence on most of these phenotypes, with histone modifications exhibiting strong context-dependent behavior. Our results implicate transcription factors as primary mediators of sequence-specific regulation of gene expression programs, with histone modifications frequently reflecting the primary regulatory event.

Respiratory self-navigated postcontrast whole-heart coronary MR angiography: initial experience in patients.

PURPOSE: To assess the diagnostic performance of respiratory self-navigation for whole-heart coronary magnetic resonance (MR) angiography in a patient cohort referred for diagnostic cardiac MR imaging. MATERIALS AND METHODS: Written informed consent was obtained from all participants for this institutional review board-approved study. Self-navigated coronary MR angiography was performed after administration of a contrast agent in 78 patients (mean age, 48.5 years ± 20.7 [standard deviation]; 53 male patients) referred for cardiac MR imaging because of coronary artery disease (n = 40), cardiomyopathy (n = 14), congenital anomaly (n = 17), or "other" (n = 7). Examination duration was recorded, and the image quality for each coronary segment was assessed with consensus reading. Vessel sharpness, length, and diameter were measured. Quantitative values in proximal, middle, and distal segments were compared by using analysis of variance and t tests. A double-blinded comparison with the results of x-ray angiography was performed when such results were available. RESULTS: When patients with different indications for cardiac MR imaging were examined with self-navigated postcontrast coronary MR angiography, whole-heart data sets with 1.15-mm isotropic spatial resolution were acquired in an average of 7.38 minutes ± 1.85. The main and proximal coronary segments could be visualized in 92.3% of cases, while the middle and distal segments could be visualized in 84.0% and 55.8% of cases, respectively. Subjective scores and vessel sharpness were significantly higher in the proximal segments than in the middle and distal segments (P < .05). Anomalies of the coronary arteries could be confirmed or excluded in all cases. Per-vessel sensitivity and specificity for stenosis detection were 64.7% and 85.0%, respectively, in the 31 patients for whom reference standard x-ray coronary angiography results were available. CONCLUSION: The self-navigated coronary MR angiography sequence shows promise for coronary imaging. However, technical improvements are needed to improve image quality, especially in the more distal coronary segments.

Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

Surface registration from range image fusion

The registration of full 3-D models is an important task in computer vision. Range finders only reconstruct a partial view of the object. Many authors have proposed several techniques to register 3D surfaces from multiple views in which there are basically two aspects to consider. First, poor registration in which some sort of correspondences are established. Second, accurate registration in order to obtain a better solution. A survey of the most common techniques is presented and includes experimental results of some of them

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

Omnidirectional Depth Computation from a Single Image

Omnidirectional cameras offer a much wider field of view than the perspective ones and alleviate the problems due to occlusions. However, both types of cameras suffer from the lack of depth perception. A practical method for obtaining depth in computer vision is to project a known structured light pattern on the scene avoiding the problems and costs involved by stereo vision. This paper is focused on the idea of combining omnidirectional vision and structured light with the aim to provide 3D information about the scene. The resulting sensor is formed by a single catadioptric camera and an omnidirectional light projector. It is also discussed how this sensor can be used in robot navigation applications

CA88, a nuclear repetitive DNA sequence identified in Schistosoma mansoni, aids in the genotyping of nine Schistosoma species of medical and veterinary importance

CA88 is the first long nuclear repetitive DNA sequence identified in the blood fluke, Schistosoma mansoni. The assembled S. mansoni sequence, which contains the CA88 repeat, has 8,887 nucleotides and at least three repeat units of approximately 360 bp. In addition, CA88 also possesses an internal CA microsatellite, identified as SmBr18. Both PCR and BLAST analysis have been used to analyse and confirm the CA88 sequence in other S. mansoni sequences in the public database. PCR-acquired nuclear repetitive DNA sequence profiles from nine Schistosoma species were used to classify this organism into four genotypes. Included among the nine species analysed were five sequences of both African and Asian lineages that are known to infect humans. Within these genotypes, three of them refer to recognised species groups. A panel of four microsatellite loci, including SmBr18 and three previously published loci, has been used to characterise the nine Schistosoma species. Each species has been identified and classified based on its CA88 DNA fingerprint profile. Furthermore, microsatellite sequences and intra-specific variation have also been observed within the nine Schistosoma species sequences. Taken together, these results support the use of these markers in studying the population dynamics of Schistosoma isolates from endemic areas and also provide new methods for investigating the relationships between different populations of parasites. In addition, these data also indicate that Schistosoma magrebowiei is not a sister taxon to Schistosoma mattheei, prompting a new designation to a basal clade.

Plane-to-plane positioning from image-based visual servoing and structured light

In this paper we face the problem of positioning a camera attached to the end-effector of a robotic manipulator so that it gets parallel to a planar object. Such problem has been treated for a long time in visual servoing. Our approach is based on linking to the camera several laser pointers so that its configuration is aimed to produce a suitable set of visual features. The aim of using structured light is not only for easing the image processing and to allow low-textured objects to be treated, but also for producing a control scheme with nice properties like decoupling, stability, well conditioning and good camera trajectory

Compression-based Image Registration

Image registration is an important component of image analysis used to align two or more images. In this paper, we present a new framework for image registration based on compression. The basic idea underlying our approach is the conjecture that two images are correctly registered when we can maximally compress one image given the information in the other. The contribution of this paper is twofold. First, we show that the image registration process can be dealt with from the perspective of a compression problem. Second, we demonstrate that the similarity metric, introduced by Li et al., performs well in image registration. Two different versions of the similarity metric have been used: the Kolmogorov version, computed using standard real-world compressors, and the Shannon version, calculated from an estimation of the entropy rate of the images

Medical image registration based on random line sampling

One of the key aspects in 3D-image registration is the computation of the joint intensity histogram. We propose a new approach to compute this histogram using uniformly distributed random lines to sample stochastically the overlapping volume between two 3D-images. The intensity values are captured from the lines at evenly spaced positions, taking an initial random offset different for each line. This method provides us with an accurate, robust and fast mutual information-based registration. The interpolation effects are drastically reduced, due to the stochastic nature of the line generation, and the alignment process is also accelerated. The results obtained show a better performance of the introduced method than the classic computation of the joint histogram