863 resultados para shape recognitions
Resumo:
Intestinal immunoglobulin A (IgA) ensures host defense and symbiosis with our commensal microbiota. Yet previous studies hint at a surprisingly low diversity of intestinal IgA, and it is unknown to what extent the diverse Ig arsenal generated by somatic recombination and diversification is actually used. In this study, we analyze more than one million mouse IgA sequences to describe the shaping of the intestinal IgA repertoire, its determinants, and stability over time. We show that expanded and infrequent clones combine to form highly diverse polyclonal IgA repertoires with very little overlap between individual mice. Selective homing allows expanded clones to evenly seed the small but not large intestine. Repertoire diversity increases during aging in a dual process. On the one hand, microbiota-, T cell-, and transcription factor RORγt-dependent but Peyer's patch-independent somatic mutations drive the diversification of expanded clones, and on the other hand, new clones are introduced into the repertoire of aged mice. An individual's IgA repertoire is stable and recalled after plasma cell depletion, which is indicative of functional memory. These data provide a conceptual framework to understand the dynamic changes in the IgA repertoires to match environmental and intrinsic stimuli.
Resumo:
The measurement of charged-particle event shape variables is presented in inclusive inelastic pp collisions at a center-of-mass energy of 7 TeV using the ATLAS detector at the LHC. The observables studied are the transverse thrust, thrust minor, and transverse sphericity, each defined using the final-state charged particles' momentum components perpendicular to the beam direction. Events with at least six charged particles are selected by a minimum-bias trigger. In addition to the differential distributions, the evolution of each event shape variable as a function of the leading charged-particle transverse momentum, charged-particle multiplicity, and summed transverse momentum is presented. Predictions from several Monte Carlo models show significant deviations from data.
Resumo:
We present evidence for differential roles of Rho-kinase and myosin light chain kinase (MLCK) in regulating shape, adhesion, migration, and chemotaxis of human fibrosarcoma HT1080 cells on laminin-coated surfaces. Pharmacological inhibition of Rho-kinase by Y-27632 or inhibition of MLCK by W-7 or ML-7 resulted in significant attenuation of constitutive myosin light chain phosphorylation. Rho-kinase inhibition resulted in sickle-shaped cells featuring long, thin F-actin-rich protrusions. These cells adhered more strongly to laminin and migrated faster. Inhibition of MLCK in contrast resulted in spherical cells and marked impairment of adhesion and migration. Inhibition of myosin II activation with blebbistatin resulted in a morphology similar to that induced by Y-27632 and enhanced migration and adhesion. Cells treated first with blebbistatin and then with ML-7 also rounded up, suggesting that effects of MLCK inhibition on HT1080 cell shape and motility are independent of inhibition of myosin activity.
Resumo:
We present a framework for statistical finite element analysis combining shape and material properties, and allowing performing statistical statements of biomechanical performance across a given population. In this paper, we focus on the design of orthopaedic implants that fit a maximum percentage of the target population, both in terms of geometry and biomechanical stability. CT scans of the bone under consideration are registered non-rigidly to obtain correspondences in position and intensity between them. A statistical model of shape and intensity (bone density) is computed by means of principal component analysis. Afterwards, finite element analysis (FEA) is performed to analyse the biomechanical performance of the bones. Realistic forces are applied on the bones and the resulting displacement and bone stress distribution are calculated. The mechanical behaviour of different PCA bone instances is compared.
Resumo:
We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies. Our methods were motivated by and are illustrated with a state-of-the-art study of neuronal tracts in multiple sclerosis patients and healthy controls. Using the tools we have developed, we were able to find those locations along the tract most affected by the disease. However, our methods are general and highly relevant to many functional data sets. In addition to the application to one-dimensional tract profiles illustrated here, higher-dimensional extensions of the methodology could have direct applications to other biological data including functional and structural MRI.