Разработка методики оптической идентификации сварных соединений

Выпускная квалификационная работа содержит 110 стр., 27 рис., 35 табл., 41 источник, 9 приложений. Объектами исследования являются методы оптической двумерной и трехмерной реконструкции. Цель работы – разработать методику идентификации сварных соединений контейнеров с ОЯТ и РАО. В процессе исследования проводилась разработка методики идентификации текстурных особенностей поверхностей сварных соединений, рассмотрены вопросы технологии и компонентов систем реконструкции, рассмотрены аспекты социальной ответственности и финансового менеджмента. В результате исследования разработана методики идентификации сварных соединений с помощью оптических методов сканирования. Значимость работы состоит в том, что система позволяет увеличить эффективность систем идентификации учетных единиц.Master's thesis consist of 110 pages, 27 illustrations, 41 references and 9 attaches. The objects of research are methods of optical two-dimensional and three-dimensional reconstruction. Purpose of this work is to develop methodology for the identification containers welds with spent nuclear fuel and radioactive waste. The study was carried out to develop methods of identification textural features of surfaces of welds, the issues of technology and components renovation systems, considered aspects of social responsibility and financial management. This study developed a technique of identification of welded joints using optical scanning techniques. The significance of the work lies in the fact that the system allows to increase the efficiency identification systems

Stretch in Focus: 2D Inplane Cell Stretch Systems for Studies of Cardiac Mechano-Signaling

Mechanobiology is a rapidly growing interdisciplinary research field, involving biophysics, molecular and cell biology, biomedical engineering, and medicine. Rapid progress has been possible due to emerging devices and tools engineered for studies of the effect of mechanical forces, such as stretch or shear force, impacting on biological cells and tissues. In response to such mechanical stimuli, cells possess various mechanosensors among which mechanosensitive ion channels are molecular transducers designed to convert mechanical stimuli into electrical and/or biochemical intracellular signals on millisecond time scales. To study their role in cellular signaling pathways, devices have been engineered that enable application of different strain protocols to cells allowing for determination of the stress-strain relationship or other, preferably optical, readouts. Frequently, these devices are mounted on fluorescence microscopes, allowing simultaneous investigation of cellular mechanotransduction processes combined with live-cell imaging. Mechanical stress in organs/tissues can be complex and multiaxial, e.g., in hollow organs, like lung alveoli, bladder, or the heart. Therefore, biomedical engineers have, in recent years, developed devices based on elastomeric membranes for application of biaxial or multiaxial stretch to 2D substrate-adhered or even 3D-embedded cells. Here, we review application of stretch technologies to cellular mechanotransduction with a focus on cardiovascular systems. We also present new results obtained by our IsoStretcher device to examine mechanosensitivity of adult ventricular cardiomyocytes. We show that sudden isotropic stretch of cardiomyocytes can already trigger arrhythmic Ca2+ transients on the single cell level

Exploring language as the “in-between”

Assuming a performative notion of language, this contribution addresses how language functions as a symbolic means and asks for its function for the dialogical self. In accordance with a non-individualistic notion, individuals are related to each other within and by virtue of an in-between. This in-between is called “spacetime of language”: a dynamic evolving across time, perceived as linguistic forms with their chronotopology and the positionings of the performers (self as-whom to other as-whom). With respect to the linguistic forms, the specificity of language functioning is described by Bühler’s term of displacement. The effect of displacement is to generate sharedness by inducing a movement the partners follow, going beyond their actual, sensitive contact. Symbolic displacement, expanding Bühler’s notion, is particularly interesting with regard to the dialogical self: it permits the social construction of several perspectives on self, other, and reality—positions and voices informing the self’s performances

Label‐free analysis of inflammatory tissue remodeling in murine lung tissue based on multiphoton microscopy, Raman spectroscopy and machine learning

Abstract Inflammatory fibrotic tissue remodeling can lead to severe morbidity. Histopathology grading requires extraction of biopsies and elaborate tissue processing. Label‐free optical technologies can provide diagnostic readout without preparation and artificial stainings and show potential for in vivo applications. Here, we present an integration of Raman spectroscopy (RS) and multiphoton microscopy for joint investigation of the bio‐chemical composition and morphological features related to cellular components and connective tissue. Both modalities show that collagen signatures were significantly increased in a murine fibrosis model. Furthermore, autofluorescence signatures assigned to immune cells show high correlation with disease severity. RS indicates increased levels of elastin and lipids. Further, we investigated the effect of joint data sets on prediction performance in machine learning models. Although binary classification did not benefit from adding more features, multi‐class classification was improved by integrated data sets

Na(+)-D-glucose cotransporter SGLT1 is pivotal for intestinal glucose absorption and glucose-dependent incretin secretion.

To clarify the physiological role of Na(+)-D-glucose cotransporter SGLT1 in small intestine and kidney, Sglt1(-/-) mice were generated and characterized phenotypically. After gavage of d-glucose, small intestinal glucose absorption across the brush-border membrane (BBM) via SGLT1 and GLUT2 were analyzed. Glucose-induced secretion of insulinotropic hormone (GIP) and glucagon-like peptide 1 (GLP-1) in wild-type and Sglt1(-/-) mice were compared. The impact of SGLT1 on renal glucose handling was investigated by micropuncture studies. It was observed that Sglt1(-/-) mice developed a glucose-galactose malabsorption syndrome but thrive normally when fed a glucose-galactose-free diet. In wild-type mice, passage of D-glucose across the intestinal BBM was predominantly mediated by SGLT1, independent the glucose load. High glucose concentrations increased the amounts of SGLT1 and GLUT2 in the BBM, and SGLT1 was required for upregulation of GLUT2. SGLT1 was located in luminal membranes of cells immunopositive for GIP and GLP-1, and Sglt1(-/-) mice exhibited reduced glucose-triggered GIP and GLP-1 levels. In the kidney, SGLT1 reabsorbed ∼3% of the filtered glucose under normoglycemic conditions. The data indicate that SGLT1 is 1) pivotal for intestinal mass absorption of d-glucose, 2) triggers the glucose-induced secretion of GIP and GLP-1, and 3) triggers the upregulation of GLUT2

SEMPAI: a Self‐Enhancing Multi‐Photon Artificial Intelligence for Prior‐Informed Assessment of Muscle Function and Pathology

Deep learning (DL) shows notable success in biomedical studies. However, most DL algorithms work as black boxes, exclude biomedical experts, and need extensive data. This is especially problematic for fundamental research in the laboratory, where often only small and sparse data are available and the objective is knowledge discovery rather than automation. Furthermore, basic research is usually hypothesis‐driven and extensive prior knowledge (priors) exists. To address this, the Self‐Enhancing Multi‐Photon Artificial Intelligence (SEMPAI) that is designed for multiphoton microscopy (MPM)‐based laboratory research is presented. It utilizes meta‐learning to optimize prior (and hypothesis) integration, data representation, and neural network architecture simultaneously. By this, the method allows hypothesis testing with DL and provides interpretable feedback about the origin of biological information in 3D images. SEMPAI performs multi‐task learning of several related tasks to enable prediction for small datasets. SEMPAI is applied on an extensive MPM database of single muscle fibers from a decade of experiments, resulting in the largest joint analysis of pathologies and function for single muscle fibers to date. It outperforms state‐of‐the‐art biomarkers in six of seven prediction tasks, including those with scarce data. SEMPAI's DL models with integrated priors are superior to those without priors and to prior‐only approaches.The Self‐Enhancing Multi‐Photon AI (SEMPAI) that is designed specifically for basic laboratory research with microscopy is presented. It allows to integrate hypotheses and uses meta‐learning in a biologically interpretable configuration space for knowledge discovery. SEMPAI is applied to a large database of multi‐photon microscopy images of single muscle fibers to gain a deeper understanding of structure–function relationships and pathologies. image European Union's Horizon Marie Skłodowska‐Curie2021 Emerging Talents Initiative of the Friedrich‐Alexander UniversityGerman Research Foundation http://dx.doi.org/10.13039/50110000165

Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease

We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P ≤ 1 × 10−5. We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 × 10−17; including ADGC data, meta P = 5.0 × 10−21) and the MS4A gene cluster (rs610932, meta P = 1.8 × 10−14; including ADGC data, meta P = 1.2 × 10−16) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 × 10−4; including ADGC data, meta P = 8.6 × 10−9), CD33 (GERAD+, P = 2.2 × 10−4; including ADGC data, meta P = 1.6 × 10−9) and EPHA1 (GERAD+, P = 3.4 × 10−4; including ADGC data, meta P = 6.0 × 10−10)

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease.

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes