Neutrophil swarms require LTB4 and integrins at sites of cell death in vivo

Neutrophil recruitment from blood to extravascular sites of sterile or infectious tissue damage is a hallmark of early innate immune responses, and the molecular events leading to cell exit from the bloodstream have been well defined1,2. Once outside the vessel, individual neutrophils often show extremely coordinated chemotaxis and cluster formation reminiscent of the swarming behaviour of insects3,4,5,6,7,8,9,10,11. The molecular players that direct this response at the single-cell and population levels within the complexity of an inflamed tissue are unknown. Using two-photon intravital microscopy in mouse models of sterile injury and infection, we show a critical role for intercellular signal relay among neutrophils mediated by the lipid leukotriene B4, which acutely amplifies local cell death signals to enhance the radius of highly directed interstitial neutrophil recruitment. Integrin receptors are dispensable for long-distance migration12, but have a previously unappreciated role in maintaining dense cellular clusters when congregating neutrophils rearrange the collagenous fibre network of the dermis to form a collagen-free zone at the wound centre. In this newly formed environment, integrins, in concert with neutrophil-derived leukotriene B4 and other chemoattractants, promote local neutrophil interaction while forming a tight wound seal. This wound seal has borders that cease to grow in kinetic concert with late recruitment of monocytes and macrophages at the edge of the displaced collagen fibres. Together, these data provide an initial molecular map of the factors that contribute to neutrophil swarming in the extravascular space of a damaged tissue. They reveal how local events are propagated over large-range distances, and how auto-signalling produces coordinated, self-organized neutrophil-swarming behaviour that isolates the wound or infectious site from surrounding viable tissue

Differential Dynamic Microscopy to characterize Brownian motion and bacteria motility

We have developed a lab work module where we teach undergraduate students how to quantify the dynamics of a suspension of microscopic particles, measuring and analyzing the motion of those particles at the individual level or as a group. Differential Dynamic Microscopy (DDM) is a relatively recent technique that precisely does that and constitutes an alternative method to more classical techniques such as dynamics light scattering (DLS) or video particle tracking (VPT). DDM consists in imaging a particle dispersion with a standard light microscope and a camera. The image analysis requires the students to code and relies on digital Fourier transform to obtain the intermediate scattering function, an autocorrelation function that characterizes the dynamics of the dispersion. We first illustrate DDM on the textbook case of colloids where we measure the diffusion coefficient. Then we show that DDM is a pertinent tool to characterize biologic systems such as motile bacteria i.e.bacteria that can self propel, where we not only determine the diffusion coefficient but also the velocity and the fraction of motile bacteria. Finally, so that our paper can be used as a tutorial to the DDM technique, we have joined to this article movies of the colloidal and bacterial suspensions and the DDM algorithm in both Matlab and Python to analyze the movies

Caractérisation multi-échelle de l'anisotropie d'une texture

L'estimation des caractéristiques texturales d'un objet est un problème classique en traitement des images. En présence de textures directionnelles, parmi les différentes classes d'attributs généralement recherchées, l'anisotropie de la texture peut être un indicateur extrêmement utile à l'identification des propriétés physiques de l'objet étudié. Toutefois, nous montrerons que l'étude de cet attribut textural est intimement liée à la notion d'échelle d'observation de la texture. Dans ce papier, nous présenterons donc à cet effet une méthode d'estimation de l'orientation d'une texture à une échelle donnée et un indicateur de l'anisotropie correspondante. Des résultats seront présentés sur des images naturelles et de synthèse

Comparison of optical sensors discrimination ability using spectral libraries

In remote sensing, the ability to discriminate different land covers or material types is directly linked with the spectral resolution and sampling provided by the optical sensor. Previous studies showed that the spectral resolution is a critical issue, especially in complex environment. In spite of the increasing availability of hyperspectral data, multispectral optical sensors onboard various satellites are acquiring everyday a massive amount of data with a relatively poor spectral resolution (i.e. usually about 4 to 7 spectral bands). These remotely sensed data are intensively used for Earth observation regardless of their limited spectral resolution. In this paper, we studied seven of these optical sensors: Pleiades, QuickBird, SPOT5, Ikonos, Landsat TM, Formosat and Meris. This study focuses on the ability of each sensor to discriminate different materials according to its spectral resolution. We used four different spectral libraries which contains around 2500 spectra of materials and land covers with a fine spectral resolution. These spectra were convolved with the Relative Spectral Responses (RSR) of each sensor to create spectra at the sensors’ resolutions. Then, these reduced spectra were compared using separability indexes (Divergence, Transformed divergence, Bhattacharyya, Jeffreys-Matusita) and machine learning tools. In the experiments, we highlighted that the spectral bands configuration could lead to important differences in classification accuracy according to the context of application (e.g. urban area)

Adaptation Algorithm and Theory Based on Generalized Discrepancy

We present a new algorithm for domain adaptation improving upon a discrepancy minimization algorithm previously shown to outperform a number of algorithms for this task. Unlike many previous algorithms for domain adaptation, our algorithm does not consist of a fixed reweighting of the losses over the training sample. We show that our algorithm benefits from a solid theoretical foundation and more favorable learning bounds than discrepancy minimization. We present a detailed description of our algorithm and give several efficient solutions for solving its optimization problem. We also report the results of several experiments showing that it outperforms discrepancy minimization

The STAR Silicon Strip Detector (SSD)

The STAR Silicon Strip Detector (SSD) completes the three layers of the Silicon Vertex Tracker (SVT) to make an inner tracking system located inside the Time Projection Chamber (TPC). This additional fourth layer provides two dimensional hit position and energy loss measurements for charged particles, improving the extrapolation of TPC tracks through SVT hits. To match the high multiplicity of central Au+Au collisions at RHIC the double sided silicon strip technology was chosen which makes the SSD a half million channels detector. Dedicated electronics have been designed for both readout and control. Also a novel technique of bonding, the Tape Automated Bonding (TAB), was used to fullfill the large number of bounds to be done. All aspects of the SSD are shortly described here and test performances of produced detection modules as well as simulated results on hit reconstruction are given.Comment: 11 pages, 8 figures, 1 tabl

Multi-resolution texture classification based on local image orientation

The aim of this paper is to evaluate quantitatively the discriminative power of the image orientation in the texture classification process. In this regard, we have evaluated the performance of two texture classification schemes where the image orientation is extracted using the partial derivatives of the Gaussian function. Since the texture descriptors are dependent on the observation scale, in this study the main emphasis is placed on the implementation of multi-resolution texture analysis schemes. The experimental results were obtained when the analysed texture descriptors were applied to standard texture databases

Phenotypic characteristics of the p.Asn215Ser (p.N215S) GLA mutation in male and female patients with Fabry disease: A multicenter Fabry Registry study.

BackgroundThe p.Asn215Ser or p.N215S GLA variant has been associated with late-onset cardiac variant of Fabry disease.MethodsTo expand on the scarce phenotype data, we analyzed natural history data from 125 p.N215S patients (66 females, 59 males) enrolled in the Fabry Registry (NCT00196742) and compared it with data from 401 patients (237 females, 164 males) harboring mutations associated with classic Fabry disease. We evaluated interventricular septum thickness (IVST), left ventricular posterior wall thickness (LVPWT), estimated glomerular filtration rate and severe clinical events.ResultsIn p.N215S males, mildly abnormal mean IVST and LVPWT values were observed in patients aged 25-34 years, and values gradually increased with advancing age. Mean values were similar to those of classic males. In p.N215S females, these abnormalities occurred primarily in patients aged 55-64 years. Severe clinical events in p.N215S patients were mainly cardiac (males 31%, females 8%) while renal and cerebrovascular events were rare. Renal impairment occurred in 17% of p.N215S males (mostly in patients aged 65-74 years), and rarely in females (3%).Conclusionp.N215S is a disease-causing mutation with severe clinical manifestations found primarily in the heart. Cardiac involvement may become as severe as in classic Fabry patients, especially in males

Investigating carbon materials nanostructure using image orientation statistics

International audienceA new characterization method of the lattice fringe images of turbostratic carbons is proposed. This method is based on the computation of their orientation field without explicit detection of fringes. It allows meaningful insights into the material nanostructure and nanotexture at several scales, either qualitatively or quantitatively. The calculation of pairwise spatial statistics of the orientation field at short distance provides measurements of the coherence lengths along any direction, in particular along and orthogonally to the layers. These statistics also allow representing orientation coherence patterns typical of the observed nanostructure. At larger distances, the mean disorientation of the fringes is computed and information about the homogeneity of the sample is obtained. An experimental validation is carried out on various artificial images and an application to the characterization of four bulk turbostratic carbons is provided