1,415 research outputs found

    Planar Differential Growth Rates Initiate Precise Fold Positions in Complex Epithelia

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    Tissue folding is a fundamental process that shapes epithelia into complex 3D organs. The initial positioning of folds is the foundation for the emergence of correct tissue morphology. Mechanisms forming individual folds have been studied, but the precise positioning of folds in complex, multi-folded epithelia is less well-understood. We present a computational model of morphogenesis, encompassing local differential growth and tissue mechanics, to investigate tissue fold positioning. We use the Drosophila wing disc as our model system and show that there is spatial-temporal heterogeneity in its planar growth rates. This differential growth, especially at the early stages of development, is the main driver for fold positioning. Increased apical layer stiffness and confinement by the basement membrane drive fold formation but influence positioning to a lesser degree. The model successfully predicts the in vivo morphology of overgrowth clones and wingless mutants via perturbations solely on planar differential growth in silico

    Designing fuzzy rule based classifier using self-organizing feature map for analysis of multispectral satellite images

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    We propose a novel scheme for designing fuzzy rule based classifier. An SOFM based method is used for generating a set of prototypes which is used to generate a set of fuzzy rules. Each rule represents a region in the feature space that we call the context of the rule. The rules are tuned with respect to their context. We justified that the reasoning scheme may be different in different context leading to context sensitive inferencing. To realize context sensitive inferencing we used a softmin operator with a tunable parameter. The proposed scheme is tested on several multispectral satellite image data sets and the performance is found to be much better than the results reported in the literature.Comment: 23 pages, 7 figure

    Stress relaxation in epithelial monolayers is controlled by the actomyosin cortex

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    Epithelial monolayers are one-cell thick tissue sheets that separate internal and external environments. As part of their function, they have to withstand extrinsic mechanical stresses applied at high strain rates. However, little is known about how monolayers respond to mechanical deformations. Here, by subjecting suspended epithelial monolayers to stretch, we find that they dissipate stresses on a minute time-scale in a process that involves an increase in monolayer length, pointing to active remodelling of cell architecture during relaxation. Strikingly, monolayers consisting of tens of thousands of cells relax stress with similar dynamics to single rounded cells and both respond similarly to perturbations of actomyosin. By contrast, cell-cell junctional complexes and intermediate filaments do not relax tissue stress, but form stable connections between cells, allowing monolayers to behave rheologically as single cells. Taken together our data show that actomyosin dynamics governs the rheological properties of epithelial monolayers, dissipating applied stresses, and enabling changes in monolayer length.Peer ReviewedPostprint (published version

    Cardiorespiratory fitness levels and their association with cardiovascular profile in patients with rheumatoid arthritis: a cross-sectional study.

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    OBJECTIVE: The aim of this study was to investigate the association of different physical fitness levels [assessed by the maximal oxygen uptake (VO2max) test] with cardiovascular disease (CVD) risk factors in patients with RA. METHODS: A total of 150 RA patients were assessed for cardiorespiratory fitness with a VO2max test and, based on this, were split in three groups using the 33rd (18.1 ml/kg/min) and 66th (22.4 ml/kg/min) centiles. Classical and novel CVD risk factors [blood pressure, body fat, insulin resistance, cholesterol, triglycerides, high-density lipoprotein (HDL), physical activity, CRP, fibrinogen and white cell count], 10-year CVD risk, disease activity (DAS28) and severity (HAQ) were assessed in all cases. RESULTS: Mean VO2max for all RA patients was 20.9 (s.d. 5.7) ml/kg/min. The 10-year CVD risk (P = 0.003), systolic blood pressure (P = 0.039), HDL (P = 0.017), insulin resistance and body fat (both at P < 0.001), CRP (P = 0.005), white blood cell count (P = 0.015) and fibrinogen (P < 0.001) were significantly different between the VO2max tertiles favouring the group with the higher VO2max levels. In multivariate analyses of variance, VO2max was significantly associated with body fat (P < 0.001), HDL (P = 0.007), insulin resistance (P < 0.003) and 10-year CVD risk (P < 0.001), even after adjustment for DAS28, HAQ and physical activity. CONCLUSION: VO2max levels are alarmingly low in RA patients. Higher levels of VO2max are associated with a better cardiovascular profile in this population. Future studies need to focus on developing effective behavioural interventions to improve cardiorespiratory fitness in RA

    Recognising facial expressions in video sequences

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    We introduce a system that processes a sequence of images of a front-facing human face and recognises a set of facial expressions. We use an efficient appearance-based face tracker to locate the face in the image sequence and estimate the deformation of its non-rigid components. The tracker works in real-time. It is robust to strong illumination changes and factors out changes in appearance caused by illumination from changes due to face deformation. We adopt a model-based approach for facial expression recognition. In our model, an image of a face is represented by a point in a deformation space. The variability of the classes of images associated to facial expressions are represented by a set of samples which model a low-dimensional manifold in the space of deformations. We introduce a probabilistic procedure based on a nearest-neighbour approach to combine the information provided by the incoming image sequence with the prior information stored in the expression manifold in order to compute a posterior probability associated to a facial expression. In the experiments conducted we show that this system is able to work in an unconstrained environment with strong changes in illumination and face location. It achieves an 89\% recognition rate in a set of 333 sequences from the Cohn-Kanade data base

    Body image, body dissatisfaction and weight status in south asian children: a cross-sectional study

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    Background Childhood obesity is a continuing problem in the UK and South Asian children represent a group that are particularly vulnerable to its health consequences. The relationship between body dissatisfaction and obesity is well documented in older children and adults, but is less clear in young children, particularly South Asians. A better understanding of this relationship in young South Asian children will inform the design and delivery of obesity intervention programmes. The aim of this study is to describe body image size perception and dissatisfaction, and their relationship to weight status in primary school aged UK South Asian children. Methods Objective measures of height and weight were undertaken on 574 predominantly South Asian children aged 5-7 (296 boys and 278 girls). BMI z-scores, and weight status (underweight, healthy weight, overweight or obese) were calculated based on the UK 1990 BMI reference charts. Figure rating scales were used to assess perceived body image size (asking children to identify their perceived body size) and dissatisfaction (difference between perceived current and ideal body size). The relationship between these and weight status were examined using multivariate analyses. Results Perceived body image size was positively associated with weight status (partial regression coefficient for overweight/obese vs. non-overweight/obese was 0.63 (95% CI 0.26-0.99) and for BMI z-score was 0.21 (95% CI 0.10-0.31), adjusted for sex, age and ethnicity). Body dissatisfaction was also associated with weight status, with overweight and obese children more likely to select thinner ideal body size than healthy weight children (adjusted partial regression coefficient for overweight/obese vs. non-overweight/obese was 1.47 (95% CI 0.99-1.96) and for BMI z-score was 0.54 (95% CI 0.40-0.67)). Conclusions Awareness of body image size and increasing body dissatisfaction with higher weight status is established at a young age in this population. This needs to be considered when designing interventions to reduce obesity in young children, in terms of both benefits and harms

    Automatic Network Fingerprinting through Single-Node Motifs

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    Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs---a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.Comment: 16 pages (4 figures) plus supporting information 8 pages (5 figures

    A genetic approach for building different alphabets for peptide and protein classification

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    <p>Abstract</p> <p>Background</p> <p>In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task is performed by a multi-classifier system where each classifier (Linear or Radial Basis function Support Vector Machines) is trained using features extracted by different reduced alphabets. Each alphabet is constructed by a Genetic Algorithm whose objective function is the maximization of the area under the ROC-curve obtained in several classification problems.</p> <p>Results</p> <p>The new approach has been tested in three peptide classification problems: HIV-protease, recognition of T-cell epitopes and prediction of peptides that bind human leukocyte antigens. The tests demonstrate that the idea of training a pool classifiers by reduced alphabets, created using a Genetic Algorithm, allows an improvement over other state-of-the-art feature extraction methods.</p> <p>Conclusion</p> <p>The validity of the novel strategy for creating reduced alphabets is demonstrated by the performance improvement obtained by the proposed approach with respect to other reduced alphabets-based methods in the tested problems.</p

    The Influence of Recovery and Training Phases on Body Composition, Peripheral Vascular Function and Immune System of Professional Soccer Players

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    Professional soccer players have a lengthy playing season, throughout which high levels of physical stress are maintained. The following recuperation period, before starting the next pre-season training phase, is generally considered short but sufficient to allow a decrease in these stress levels and therefore a reduction in the propensity for injury or musculoskeletal tissue damage. We hypothesised that these physical extremes influence the body composition, blood flow, and endothelial/immune function, but that the recuperation may be insufficient to allow a reduction of tissue stress damage. Ten professional football players were examined at the end of the playing season, at the end of the season intermission, and after the next pre-season endurance training. Peripheral blood flow and body composition were assessed using venous occlusion plethysmography and DEXA scanning respectively. In addition, selected inflammatory and immune parameters were analysed from blood samples. Following the recuperation period a significant decrease of lean body mass from 74.4±4.2 kg to 72.2±3.9 kg was observed, but an increase of fat mass from 10.3±5.6 kg to 11.1±5.4 kg, almost completely reversed the changes seen in the pre-season training phase. Remarkably, both resting and post-ischemic blood flow (7.3±3.4 and 26.0±6.3 ml/100 ml/min) respectively, were strongly reduced during the playing and training stress phases, but both parameters increased to normal levels (9.0±2.7 and 33.9±7.6 ml/100 ml/min) during the season intermission. Recovery was also characterized by rising levels of serum creatinine, granulocytes count, total IL-8, serum nitrate, ferritin, and bilirubin. These data suggest a compensated hypo-perfusion of muscle during the playing season, followed by an intramuscular ischemia/reperfusion syndrome during the recovery phase that is associated with muscle protein turnover and inflammatory endothelial reaction, as demonstrated by iNOS and HO-1 activation, as well as IL-8 release. The data provided from this study suggest that the immune system is not able to function fully during periods of high physical stress. The implications of this study are that recuperation should be carefully monitored in athletes who undergo intensive training over extended periods, but that these parameters may also prove useful for determining an individual's risk of tissue stress and possibly their susceptibility to progressive tissue damage or injury
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