377 research outputs found
The AAP gene family for amino acid permeases contributes to development of the cyst nematode Heterodera schachtii in roots of Arabidopsis
The beet cyst nematode Heterodera schachtii is able to infect Arabidopsis plants and induce feeding sites in the root. These syncytia are the only source of nutrients for the nematodes throughout their life and are a nutrient sink for the host plant. We have studied here the role of amino acid transporters for nematode development. Arabidopsis contains a large number of different amino acid transporters in several gene families but those of the AAP family were found to be especially expressed in syncytia. Arabidopsis contains 8 AAP genes and they were all strongly expressed in syncytia with the exception of AAP5 and AAP7, which were slightly downregulated. We used promoter::GUS lines and in situ RT-PCR to confirm the expression of several AAP genes and LHT1, a lysine- and histidine-specific amino acid transporter, in syncytia. The strong expression of AAP genes in syncytia indicated that these transporters are important for the transport of amino acids into syncytia and we used T-DNA mutants for several AAP genes to test for their influence on nematode development. We found that mutants of AAP1, AAP2, and AAP8 significantly reduced the number of female nematodes developing on these plants. Our study showed that amino acid transport into syncytia is important for the development of the nematodes
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The effect of high-fat diet on the morphological properties of the forelimb musculature in hypertrophic myostatin null mice
Obesity is a worldwide nutritional disorder affecting body performance including 29 skeletal muscle. Inhibition of myostatin not only increases the muscle mass but also it reduces body fat accumulation. We examined the effect of high-fat diet on the phenotypic properties of forelimb muscles from myostatin null mice. Male wild-type and myostatin null mice were fed on either normal diet or high-fat diet (45 % fat) for ten weeks. M. triceps brachii Caput longum; M. triceps brachii Caput laterale; M. triceps brachii Caput mediale; M. extensor carpi ulnaris and M. flexor carpi ulnaris were processed for fiber type composition using immunohistochemistry and morphometric analysis. Although the muscle mass revealed no change under high-fat diet, there were morphometric alterations in the absence of myostatin. We show that high-fat diet reduces the cross-sectional area of the fast (IIB and IIX) fibers in M. triceps brachii Caput longum and M. triceps brachii Caput laterale of both genotypes. In contrast, increases of fast fibers area were observed in both M. extensor carpi ulnaris of wild- type and M. flexor carpi ulnaris of myostatin null. Meanwhile, a high-fat diet increases the area of the fast IIA fibers in wild-type, myostatin null displays a muscle-dependent alteration in the area of the same fiber type. The combined high-fat diet and myostatin deletion shows no effect on the area of slow type I fibers. Despite, a high-fat diet causes a reduction in the area of the peripheral IIB fibers in both genotypes, only myostatin null shows an increase in the area of the central IIB fibers. We provide evidence that a high-fat diet induces a muscle-dependent fast to slow myofiber shift in the absence of myostatin. Taken together, the data suggest that the morphological alterations of muscle fibers under combined high-fat diet and myostatin deletion reflect a functional adaptation of the muscle to utilize the high energy intake
Descriptive Epidemiology of Hemophilia and Other Coagulation Disorders in Mansoura, Egypt: Retrospective Analysis.
Hemophilia represent the most severe inherited bleeding disorder (INB), it’s thought to affect inviduals from all geographical areas in equal frequency. In Egypt which has a population of approximately (80million) consanguineous marriage are frequent, therefore autosomal recessive coagulation disorders reach a higher prevalence than in many other countries
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Multipotency of skeletal muscle stem cells on their native substrate and the expression of Connexin 43 during adoption of adipogenic and osteogenic fate
Skeletal muscle contains a resident stem cell population called Satellite cells (SC) which have a huge capacity to regenerate damaged tissue. Transplantation of a single fiber consisting of less than ten cells is able to generate tens of thousands of myonuclei within a matter of a few weeks (Collins et al., 2005). SC take their name from their peripheral position relative to the muscle fiber (Mauro, 1961). They are located under the basal lamina, in direct contact with the sarcolemma of muscle
fibers. In undamaged muscle, they are relatively metabolically inactive as indicated by their low cytoplasmic content and they exist in a quiescent state. However, they express certain markers including Pax7 that
aid their identification (Zammit et al., 2006). Upon muscle damage, SC become activated by inducing a number of genes including MyoD that encodes a member of the Myogenic Determination Factor family (MRF) of transcriptions factors (Zammit et al., 2006). Activation of SC permits cell division as well as migration. Initially, SC migrate under the basal lamina but then take up a supra-basal position by remodeling their overlying extra-cellular matrix (Otto et al., 2011). Activated SC can either revert to their quiescent state by down-regulating MyoD while maintaining Pax7 or can commit to myogenic differentiation by shutting off Pax7
expression and inducing the expression o
A Novel Approach to Image Retrieval for Vision-Based Positioning Utilizing Graph Topology
This research introduces a novel approach to improve vision-based positioning in the absence of GNSS signals. Specifically, we address the challenge posed by obstacles that alter image information or features, making retrieving the query image from the database difficult. While the Bag of Visual Words (BoVW) is a widely used image retrieval technique, it has a limitation in representing each image with a single histogram vector or vocabulary of visual words, i.e., the emergence of obstacles can introduce new features to the query image, resulting in different visual words. Our study overcomes this limitation by clustering the features of each image using the k-means method and generating a graph for each class. Each node or key point in the graph obtains additional information from its direct neighbors using functions employed in graph neural networks, functioning as a feedforward network with constant parameters. This process generates new embedding nodes, and eventually, global pooling is applied to produce one vector for each graph, representing each image with graph vectors based on objects or feature classes. As a result, each image is represented with graph vectors based on objects or feature classes. In the presence of obstacles covering one or more graphs, there is sufficient information from the query image to retrieve the most relevant image from the database. Our approach was applied to indoor positioning applications, with the database collected in Bolz Hall at The Ohio State University. Traditional BoVW techniques struggle to properly retrieve most query images from the database due to obstacles like humans or recently deployed objects that alter image features. In contrast, our approach has shown progress in image retrieval by representing each image with multiple graph vectors, depending on the number of objects in the image. This helps prevent or mitigate changes in image features caused by obstacles covering or adding features to the image, as demonstrated in the results
IMPROVING CAMERA POSE ESTIMATION USING SWARM PARTICLE ALGORITHMS
Most computer vision and photogrammetry applications rely on accurately estimating the camera pose, such as visual navigation, motion tracking, stereo photogrammetry, and structure from motion. The Essential matrix is a well-known model in computer vision that provides information about the relative orientation between two images, including the rotation and translation, for calibrated cameras with a known camera matrix. To estimate the Essential matrix, the camera calibration matrices, which include focal length and principal point location must be known, and the estimation process typically requires at least five matching points and the use of robust algorithms, such as RANSAC to fit a model to the data as a robust estimator. From the usually large number of matched points, choosing five points, the Essential matrix can be determined based on a simple solution, which could be good or bad. Obtaining a globally optimal and accurate camera pose estimation, however, requires additional steps, such as using evolutionary algorithms (EA) or swarm algorithms (SA), to prevent getting trapped in local optima by searching for solutions within a potentially huge solution space.This paper aims to introduce an improved method for estimating the Essential matrix using swarm particle algorithms that are known to efficiently solve complex problems. Various optimization techniques, including EAs and SAs, such as Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Improved Gray Wolf Optimization (IGWO), Genetic Algorithm (GA), Salp Swarm Algorithm (SSA) and Whale Optimization Algorithm (WOA), are explored to obtain the global minimum of the reprojection error for the five-point Essential matrix estimation based on using symmetric geometric error cost function. The experimental results on a dataset with known camera orientation demonstrate that the IGWO method has achieved the best score compared to other techniques and significantly speeds up the camera pose estimation for larger number of point pairs in contrast to traditional methods that use the collinearity equations in an iterative adjustment.</p
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The effect of caloric restriction on the forelimb skeletal muscle fibers of 1 the hypertrophic myostatin null mice
Skeletal muscle mass loss has a broad impact on body performance and physical activity. Muscle wasting occurs due to genetic mutation as in muscular dystrophy, age-related muscle loss (sarcopenia) as well as in chronic wasting disorders as in cancer cachexia. Food restriction reduces muscle mass underpinned by increased muscle protein break down. However the influence of dietary restriction on the morphometry and phenotype of forelimb muscles in a genetically modified myostatin null mice are not fully characterized. The effect of a five week dietary limitation on five anatomically and structurally different forelimb muscles was examined. C57/BL6 wild type (Mstn+/+) and myostatin null (Mstn-/-) mice were either given a standard rodent normal daily diet ad libitum (ND) or 60% food restriction (FR) for a 5 week period. M. triceps brachii Caput laterale (T.lateral), M. triceps brachii Caput longum (T.long), M. triceps brachii Caput mediale (T.medial), M. extensor carpi ulnaris (ECU) and M. flexor carpi ulnaris (FCU) were dissected, weighted and processed for immunohistochemistry. Muscle mass, fibers cross sectional areas (CSA) and myosin heavy chain types IIB, IIX, IIA and type I were analyzed. We provide evidence that caloric restriction results in muscle specific weight reduction with the fast myofibers being more prone to atrophy. We show that slow fibers are less liable to dietary restriction induced muscle atrophy. The effect of dietary restriction was more pronounced in Mstn-/- muscles to implicate the oxidative fibers compared to Mstn+/+. Furthermore, peripherally located myofibers are more susceptible to dietary induced reduction compared to deep fibers. We additionally report that dietary restriction alters the glycolytic phenotype of the Mstn-/- into the oxidative form in a muscle dependent manner
FEATURE MATCHING ENHANCEMENT USING THE GRAPH NEURAL NETWORK (GNN-RANSAC)
Improving the performance of feature matching plays a key role in computers vision and photogrammetry applications, such as fast image recognition, Structure from Motion (SFM), aerial triangulation, Visual Simultaneous Localization and Mapping (VSLAM), etc., where the RANSAC algorithm is frequently used for outlier detection; note that RANSAC is the most widely used robust approach in photogrammetry and computer vision for outlier detection. It is known that the outlier ratio used in RANSAC primarily determines the number of trial runs needed, which eventually, determines the computation time. Over time, different methods have been proposed to reject the false-positive correspondences and improve RANSAC, such as GR_RANSAC, SuperGlue, and LPRANSAC. The specific objective of this study is to propose a filtering algorithm based on Graph Neural Networks (GNN), as a pre-processing step before RANSAC, which can result in improvements for rejecting the outliers. The research is based on the idea that descriptors of corresponding points, as well as their spatial relationship, should be similar in image sequences. In graph representation, built by the adjacency matrix of data (nodes features), there should be similarity for corresponding points that are close to each other in the image domain. From the many GNNs techniques, Graph Attention Networks (GATs) were selected for this study as they assign different importance to each neighbour’s contribution as anisotropic operations, so the features of neighbour nodes are not considered in the same way, unlike other GNNs techniques. In our approach, we build a graph in each image, because the similarity of the two-dimensional spatial relationships between points in the image domain of consecutive images should be similar. Then during processing, points with any significantly different neighbours are considered as outliers. Next, the points can be updated in the GNN layer. GNN-RANSAC is tested experimentally on real image pairs. Clearly, the proposed pre-filtering increases the inlier ratio and results in faster convergence compared to ordinary RANSAC, making it attractive for real-time applications. Furthermore, there is no need to learn the features
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Local overexpression of the myostatin propeptide increases glucose transporter expression and enhances skeletal muscle glucose disposal
Insulin resistance (IR) in skeletal muscle is a prerequisite for type 2 diabetes and is often associated with obesity. IR also develops alongside muscle atrophy in older individuals in sarcopenic obesity. The molecular defects that underpin this syndrome are not well characterized, and there is no licensed treatment. Deletion of the transforming growth factor-β family member myostatin, or sequestration of the active peptide by overexpression of the myostatin propeptide/latency-associated peptide (ProMyo) results in both muscle hypertrophy and reduced obesity and IR. We aimed to establish whether local myostatin inhibition would have a paracrine/autocrine effect to enhance glucose disposal beyond that simply generated by increased muscle mass, and the mechanisms involved. We directly injected adeno-associated virus expressing ProMyo in right tibialis cranialis/extensor digitorum longus muscles of rats and saline in left muscles and compared the effects after 17 days. Both test muscles were increased in size (by 7 and 11%) and showed increased radiolabeled 2-deoxyglucose uptake (26 and 47%) and glycogen storage (28 and 41%) per unit mass during an intraperitoneal glucose tolerance test. This was likely mediated through increased membrane protein levels of GLUT1 (19% higher) and GLUT4 (63% higher). Interestingly, phosphorylation of phosphoinositol 3-kinase signaling intermediates and AMP-activated kinase was slightly decreased, possibly because of reduced expression of insulin-like growth factor-I in these muscles. Thus, myostatin inhibition has direct effects to enhance glucose disposal in muscle beyond that expected of hypertrophy alone, and this approach may offer potential for the therapy of IR syndrome
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