High resolution 3D visualization of the spinal cord in a post-mortem murine model

A crucial issue in the development of therapies to treat pathologies of the central nervous system is represented by the availability of non-invasive methods to study the three-dimensional morphology of spinal cord, with a resolution able to characterize its complex vascular and neuronal organization. X-ray phase contrast micro-tomography enables a high-quality, 3D visualization of both the vascular and neuronal network simultaneously without the need of contrast agents, destructive sample preparations or sectioning. Until now, high resolution investigations of the post-mortem spinal cord in murine models have mostly been performed in spinal cords removed from the spinal canal. We present here post-mortem phase contrast micro-tomography images reconstructed using advanced computational tools to obtain high-resolution and high-contrast 3D images of the fixed spinal cord without removing the bones and preserving the richness of micro-details available when measuring exposed spinal cords. We believe that it represents a significant step toward the in-vivo application

A hard x ray split and delay unit for the HED experiment at the European XFEL

For the High Energy Density HED experiment [1] at the European XFEL [2] an x ray split and delay unit SDU is built covering photon energies from 5 keV up to 20 keV [3]. This SDU will enable time resolved x ray pump x ray probe experiments [4,5] as well as sequential diffractive imaging [6] on a femtosecond to picosecond time scale. Further, direct measurements of the temporal coherence properties will be possible by making use of a linear autocorrelation [7,8]. The set up is based on geometric wavefront beam splitting, which has successfully been implemented at an autocorrelator at FLASH [9]. The x ray FEL pulses are split by a sharp edge of a silicon mirror coated with multilayers. Both partial beams will then pass variable delay lines. For different photon energies the angle of incidence onto the multilayer mirrors will be adjusted in order to match the Bragg condition. For a photon energy of h amp; 957; 20 keV a grazing angle of amp; 952; 0.57 has to be set, which results in a footprint of the beam 6 amp; 963; on the mirror of l 98 mm. At this photon energy the reflectance of a Mo B4C multi layer coating with a multilayer period of d 3.2 nm and N 200 layers amounts to R 0.92. In order to enhance the maximum transmission for photon energies of h amp; 957; 8 keV and below, a Ni B4C multilayer coating can be applied beside the Mo B4C coating for this spectral region. Because of the different incidence angles, the path lengths of the beams will differ as a function of wavelength. Hence, maximum delays between 2.5 ps at h amp; 957; 20 keV and up to 23 ps at h amp; 957; 5 keV will be possibl

Investigation of the human pineal gland 3D organization by X-ray phase contrast tomography

Pineal gland (PG) is a part of the human brain epithalamus that plays an important role in sleep, circadian rhythm, immunity, and reproduction. The calcium deposits and lesions in PG interfere with normal function of the organ and can be associated with different health disorders including serious neurological diseases. At the moment, the detailed mechanisms of PG calcifications and PG lesions formation as well as their involvement in pathological processes are not fully understood. The deep and comprehensive study of the structure of the uncut human PG with histological details, poses a stiff challenge to most imaging techniques, due to low spatial resolution, low visibility or to exceedingly aggressive sample preparation. Here, we investigate the whole uncut and unstained human post-mortem PGs by X-ray phase contrast tomography (XPCT). XPCT is an advanced 3D imaging technique, that permits to study of both soft and calcified tissue of a sample at different scales: from the whole organ to cell structure. In our research we simultaneously resolved 3D structure of parenchyma, vascular network and calcifications. Moreover, we distinguished structural details of intact and degenerated PG tissue. We discriminated calcifications with different structure, pinealocytes nuclei and the glial cells processes. All results were validated by histology. Our research clear demonstrated that XPCT is a potential tool for the high resolution 3D imaging of PG morphological features. This technique opens a new perspective to investigate PG dysfunction and understand the mechanisms of onset and progression of diseases involving the pineal gland

DETERMINATION OF THE MOLAR RATIO AlCl3/KCl IN THE MELT ZrCl4 – KCl – AlCl3

A method for determining the molar ratio of AlCl3/KCl in the melt ZrCl4-KCl – AlCl3 has been developed. The developed technique was tested on the working melt of the rectification plant of JSC ChMZ. Frozen alloy samples were analyzed by X-ray diffractometry

Fast Generation of Best Interval Patterns for Nonmonotonic Constraints

International audienceIn pattern mining, the main challenge is the exponential explosion of the set of patterns. Typically, to solve this problem, a constraint for pattern selection is introduced. One of the first constraints proposed in pattern mining is support (frequency) of a pattern in a dataset. Frequency is an anti-monotonic function, i.e., given an infrequent pattern, all its superpatterns are not frequent. However, many other constraints for pattern selection are neither monotonic nor anti-monotonic, which makes it difficult to generate patterns satisfying these constraints.In this paper we introduce the notion of "generalized monotonicity" and Sofia algorithm that allow generating best patterns in polynomial time for some nonmonotonic constraints modulo constraint computation and pattern extension operations. In particular, this algorithm is polynomial for data on itemsets and interval tuples. In this paper we consider stability and delta-measure which are nonmonotonic constraints and apply them to interval tuple datasets. In the experiments, we compute best interval tuple patterns w.r.t. these measures and show the advantage of our approach over postfiltering approaches

Elements About Exploratory, Knowledge-Based, Hybrid, and Explainable Knowledge Discovery

International audienceKnowledge Discovery in Databases (KDD) and especially pattern mining can be interpreted along several dimensions, namely data, knowledge, problem-solving and interactivity. These dimensions are not disconnected and have a direct impact on the quality, applicability, and efficiency of KDD. Accordingly, we discuss some objectives of KDD based on these dimensions, namely exploration, knowledge orientation, hybridization, and explanation. The data space and the pattern space can be explored in several ways, depending on specific evaluation functions and heuristics, possibly related to domain knowledge. Furthermore, numerical data are complex and supervised numerical machine learning methods are usually the best candidates for efficiently mining such data. However, the work and output of numerical methods are most of the time hard to understand, while symbolic methods are usually more intelligible. This calls for hybridization, combining numerical and symbolic mining methods to improve the applicability and interpretability of KDD. Moreover, suitable explanations about the operating models and possible subsequent decisions should complete KDD, and this is far from being the case at the moment. For illustrating these dimensions and objectives, we analyze a concrete case about the mining of biological data, where we characterize these dimensions and their connections. We also discuss dimensions and objectives in the framework of Formal Concept Analysis and we draw some perspectives for future research