Age, microbiota, and T cells shape diverse individual IgA repertoires in the intestine

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.

Measurement of charged-particle event shape variables in inclusive √(s)=7 TeV proton-proton interactions with the ATLAS detector

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.

Differential roles of Rho-kinase and myosin light chain kinase in regulating shape, adhesion, and migration of HT1080 fibrosarcoma cells

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.

Statistical finite element model for bone shape and biomechanical properties

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.

Statistical shape analysis via principal factor analysis

Statistical shape analysis techniques commonly employed in the medical imaging community, such as active shape models or active appearance models, rely on principal component analysis (PCA) to decompose shape variability into a reduced set of interpretable components. In this paper we propose principal factor analysis (PFA) as an alternative and complementary tool to PCA providing a decomposition into modes of variation that can be more easily interpretable, while still being a linear efficient technique that performs dimensionality reduction (as opposed to independent component analysis, ICA). The key difference between PFA and PCA is that PFA models covariance between variables, rather than the total variance in the data. The added value of PFA is illustrated on 2D landmark data of corpora callosa outlines. Then, a study of the 3D shape variability of the human left femur is performed. Finally, we report results on vector-valued 3D deformation fields resulting from non-rigid registration of ventricles in MRI of the brain.