Literatura científica selecionada sobre o tema "IRM Fingerprint"

Polarisation analysis in the mid-infrared fingerprint region was carried out on thin (∼1 μm) Si and SiO2 films evaporated via glancing angle deposition (GLAD) method at 70∘ to the normal. Synchrotron-based infrared microspectroscopic measurements were carried out on the Infrared Microspectroscopy (IRM) beamline at Australian Synchrotron. Specific absorption bands, particularly Si-O-Si stretching vibration, was found to follow the angular dependence of ∼cos2θ, consistent with the absorption anisotropy. This unexpected anisotropy stems from the enhanced absorption in nano-crevices, which have orientation following the cos2θ angular dependence as revealed by Fourier transforming the image of the surface of 3D columnar films and numerical modeling of light field enhancement by sub-wavelength nano-crevices.

Chronic inflammation of skeletal muscle is the common feature of idiopathic inflammatory myopathies (IIM). Given the rarity of the disease and potential difficulty of routinely obtaining target tissue, i.e., standardized skeletal muscle, our understanding of immune signatures of the IIM spectrum remains incomplete. Further insight into the immune topography of IIM is needed to determine specific treatment targets according to clinical and immunological phenotypes. Thus, we used high-dimensional flow cytometry to investigate the immune phenotypes of anti-synthetase syndrome (ASyS), dermatomyositis (DM) and inclusion-body myositis (IBM) patients as representative entities of the IIM spectrum and compared them to healthy controls. We studied the CD8, CD4 and B cell compartments in the blood aiming to provide a contemporary overview of the immune topography of the IIM spectrum. ASyS was characterized by altered CD4 composition and expanded T follicular helper cells supporting B cell-mediated autoimmunity. For DM, unsupervised clustering identified expansion of distinct B cell subtypes highly expressing immunoglobulin G4 (IgG4) and CD38. Lastly, terminally differentiated, cytotoxic CD8 T cells distinguish IBM from other IIM. Interestingly, these terminally differentiated CD8 T cells highly expressed the integrin CD18 mediating cellular adhesion and infiltration. The distinct immune cell topography of IIM might provide the framework for targeted treatment approaches potentially improving therapeutic outcomes.

Chronic inflammation of skeletal muscle is the common feature of idiopathic inflammatory myopathies (IIM). Given the rarity of the disease and potential difficulty of routinely obtaining target tissue, i.e., standardized skeletal muscle, our understanding of immune signatures of the IIM spectrum remains incomplete. Further insight into the immune topography of IIM is needed to determine specific treatment targets according to clinical and immunological phenotypes. Thus, we used high-dimensional flow cytometry to investigate the immune phenotypes of anti-synthetase syndrome (ASyS), dermatomyositis (DM) and inclusion-body myositis (IBM) patients as representative entities of the IIM spectrum and compared them to healthy controls. We studied the CD8, CD4 and B cell compartments in the blood aiming to provide a contemporary overview of the immune topography of the IIM spectrum. ASyS was characterized by altered CD4 composition and expanded T follicular helper cells supporting B cell-mediated autoimmunity. For DM, unsupervised clustering identified expansion of distinct B cell subtypes highly expressing immunoglobulin G4 (IgG4) and CD38. Lastly, terminally differentiated, cytotoxic CD8 T cells distinguish IBM from other IIM. Interestingly, these terminally differentiated CD8 T cells highly expressed the integrin CD18 mediating cellular adhesion and infiltration. The distinct immune cell topography of IIM might provide the framework for targeted treatment approaches potentially improving therapeutic outcomes.

Chronic inflammation of skeletal muscle is the common feature of idiopathic inflammatory myopathies (IIM). Given the rarity of the disease and potential difficulty of routinely obtaining target tissue, i.e., standardized skeletal muscle, our understanding of immune signatures of the IIM spectrum remains incomplete. Further insight into the immune topography of IIM is needed to determine specific treatment targets according to clinical and immunological phenotypes. Thus, we used high-dimensional flow cytometry to investigate the immune phenotypes of anti-synthetase syndrome (ASyS), dermatomyositis (DM) and inclusion-body myositis (IBM) patients as representative entities of the IIM spectrum and compared them to healthy controls. We studied the CD8, CD4 and B cell compartments in the blood aiming to provide a contemporary overview of the immune topography of the IIM spectrum. ASyS was characterized by altered CD4 composition and expanded T follicular helper cells supporting B cell-mediated autoimmunity. For DM, unsupervised clustering identified expansion of distinct B cell subtypes highly expressing immunoglobulin G4 (IgG4) and CD38. Lastly, terminally differentiated, cytotoxic CD8 T cells distinguish IBM from other IIM. Interestingly, these terminally differentiated CD8 T cells highly expressed the integrin CD18 mediating cellular adhesion and infiltration. The distinct immune cell topography of IIM might provide the framework for targeted treatment approaches potentially improving therapeutic outcomes.

Chronic inflammation of skeletal muscle is the common feature of idiopathic inflammatory myopathies (IIM). Given the rarity of the disease and potential difficulty of routinely obtaining target tissue, i.e., standardized skeletal muscle, our understanding of immune signatures of the IIM spectrum remains incomplete. Further insight into the immune topography of IIM is needed to determine specific treatment targets according to clinical and immunological phenotypes. Thus, we used high-dimensional flow cytometry to investigate the immune phenotypes of anti-synthetase syndrome (ASyS), dermatomyositis (DM) and inclusion-body myositis (IBM) patients as representative entities of the IIM spectrum and compared them to healthy controls. We studied the CD8, CD4 and B cell compartments in the blood aiming to provide a contemporary overview of the immune topography of the IIM spectrum. ASyS was characterized by altered CD4 composition and expanded T follicular helper cells supporting B cell-mediated autoimmunity. For DM, unsupervised clustering identified expansion of distinct B cell subtypes highly expressing immunoglobulin G4 (IgG4) and CD38. Lastly, terminally differentiated, cytotoxic CD8 T cells distinguish IBM from other IIM. Interestingly, these terminally differentiated CD8 T cells highly expressed the integrin CD18 mediating cellular adhesion and infiltration. The distinct immune cell topography of IIM might provide the framework for targeted treatment approaches potentially improving therapeutic outcomes.

Chronic inflammation of skeletal muscle is the common feature of idiopathic inflammatory myopathies (IIM). Given the rarity of the disease and potential difficulty of routinely obtaining target tissue, i.e., standardized skeletal muscle, our understanding of immune signatures of the IIM spectrum remains incomplete. Further insight into the immune topography of IIM is needed to determine specific treatment targets according to clinical and immunological phenotypes. Thus, we used high-dimensional flow cytometry to investigate the immune phenotypes of anti-synthetase syndrome (ASyS), dermatomyositis (DM) and inclusion-body myositis (IBM) patients as representative entities of the IIM spectrum and compared them to healthy controls. We studied the CD8, CD4 and B cell compartments in the blood aiming to provide a contemporary overview of the immune topography of the IIM spectrum. ASyS was characterized by altered CD4 composition and expanded T follicular helper cells supporting B cell-mediated autoimmunity. For DM, unsupervised clustering identified expansion of distinct B cell subtypes highly expressing immunoglobulin G4 (IgG4) and CD38. Lastly, terminally differentiated, cytotoxic CD8 T cells distinguish IBM from other IIM. Interestingly, these terminally differentiated CD8 T cells highly expressed the integrin CD18 mediating cellular adhesion and infiltration. The distinct immune cell topography of IIM might provide the framework for targeted treatment approaches potentially improving therapeutic outcomes.

Chronic inflammation of skeletal muscle is the common feature of idiopathic inflammatory myopathies (IIM). Given the rarity of the disease and potential difficulty of routinely obtaining target tissue, i.e., standardized skeletal muscle, our understanding of immune signatures of the IIM spectrum remains incomplete. Further insight into the immune topography of IIM is needed to determine specific treatment targets according to clinical and immunological phenotypes. Thus, we used high-dimensional flow cytometry to investigate the immune phenotypes of anti-synthetase syndrome (ASyS), dermatomyositis (DM) and inclusion-body myositis (IBM) patients as representative entities of the IIM spectrum and compared them to healthy controls. We studied the CD8, CD4 and B cell compartments in the blood aiming to provide a contemporary overview of the immune topography of the IIM spectrum. ASyS was characterized by altered CD4 composition and expanded T follicular helper cells supporting B cell-mediated autoimmunity. For DM, unsupervised clustering identified expansion of distinct B cell subtypes highly expressing immunoglobulin G4 (IgG4) and CD38. Lastly, terminally differentiated, cytotoxic CD8 T cells distinguish IBM from other IIM. Interestingly, these terminally differentiated CD8 T cells highly expressed the integrin CD18 mediating cellular adhesion and infiltration. The distinct immune cell topography of IIM might provide the framework for targeted treatment approaches potentially improving therapeutic outcomes.

Chronic inflammation of skeletal muscle is the common feature of idiopathic inflammatory myopathies (IIM). Given the rarity of the disease and potential difficulty of routinely obtaining target tissue, i.e., standardized skeletal muscle, our understanding of immune signatures of the IIM spectrum remains incomplete. Further insight into the immune topography of IIM is needed to determine specific treatment targets according to clinical and immunological phenotypes. Thus, we used high-dimensional flow cytometry to investigate the immune phenotypes of anti-synthetase syndrome (ASyS), dermatomyositis (DM) and inclusion-body myositis (IBM) patients as representative entities of the IIM spectrum and compared them to healthy controls. We studied the CD8, CD4 and B cell compartments in the blood aiming to provide a contemporary overview of the immune topography of the IIM spectrum. ASyS was characterized by altered CD4 composition and expanded T follicular helper cells supporting B cell-mediated autoimmunity. For DM, unsupervised clustering identified expansion of distinct B cell subtypes highly expressing immunoglobulin G4 (IgG4) and CD38. Lastly, terminally differentiated, cytotoxic CD8 T cells distinguish IBM from other IIM. Interestingly, these terminally differentiated CD8 T cells highly expressed the integrin CD18 mediating cellular adhesion and infiltration. The distinct immune cell topography of IIM might provide the framework for targeted treatment approaches potentially improving therapeutic outcomes.

Biometrics is the automatic identification of individuals based on physiological and behavioral characteristics. In today's technologically advanced digital world, it is regarded as the new digital key. There are two operating modes for biometric systems: identification and verification. The most popular biometric modalities are fingerprints, which are employed in many different industries and professions. Three distinct thinning methods are examined in this study. The proposed work looks into how thinning affects fingerprints, as well as minutiae extraction and texture feature analysis. To improve the quality of the fingerprints, thinning techniques such as Zhang- Suen's, Halls, and Guo Halls have been used. In terms of minutiae extraction, the thinning methods were compared. The minutiae points obtained were used to elaborate on the precision rate of fingerprints after processing. The simulations were run, and the experimental data was examined.

Les accidents vasculaires cérébraux (AVC), cause majeure de mortalité et d'invalidité à long terme dans le monde, nécessitent un diagnostic rapide et précis pour optimiser les résultats du traitement. Les techniques d'imagerie actuelles, en particulier l'IRM, sont essentielles pour évaluer l'étendue des lésions cérébrales et guider les interventions thérapeutiques. Toutefois, les protocoles IRM traditionnels prennent souvent beaucoup de temps et peuvent manquer de la précision requise pour une analyse détaillée du tissu cérébral ischémique, ce qui limite leur utilité dans les situations d'AVC aiguës où le temps est un facteur essentiel.L'IRM Fingerprint (MRF) est une solution relativement nouvelle qui permet d'estimer simultanément plusieurs paramètres quantitatifs cérébraux à partir d'acquisitions rapides haute résolution en utilisant une approche de recherche par dictionnaire. Cependant, son extension pour les estimations microvasculaires (textit{e.g.} volume sanguin cérébral (CBV) ou diamètre des vaisseaux sanguins (R)) et d'oxygénation du cerveau repose actuellement sur l'injection d'agents de contraste exogènes (CA) qui limitent l'application clinique et la vitesse d'acquisition. Dans cette thèse, nous avons cherché à résoudre ces limitations en développant une nouvelle technique intégrée d'IRM Fingerprint sans agent de contraste, améliorée par intelligence artificielle (IA) et adaptée aux urgences des AVC.Tout d'abord, nous avons développé et adapté des techniques MRF multiparamétriques standard basées sur des séquences à écho de gradient spoilé. En implémentant dans ces outils des corrections d'artefacts du scanner, la compression des dictionnaires et des reconstructions en espace réduit, nous avons pu générer des cartes de relaxométrie (T1,T2) et des contrastes d'IRM standard à partir d'une seule séquence MRF. Cependant, les informations microvasculaires fournies par notre nouveau modèle MRF multi-compartiments chez les volontaires humains souffraient d'un faible rapport signal/bruit.Nous nous sommes donc concentrés sur un nouveau design de séquence MRF basée sur des séquences GRE équilibrées et leur remarquable sensibilité aux inhomogénéités du champ magnétique. Après une étude théorique et textit{in-silico} sur les sensibilités des séquences générales à l'effet BOLD (Blood Oxygen Level Dependent) et l'impact des paramètres d'acquisition MRF, nous avons conçu une nouvelle séquence MRF-bSSFP qui estime simultanément des cartes de relaxométrie (T1,T2,T2*,M0), de champs magnétiques (B1,B0) et de propriétés microvasculaires (CBV,R) sans qu'il soit nécessaire d'injecter un produit de contraste. En utilisant un nouveau pipeline pour ces simulations MRF, nous avons testé notre méthode sur une cohorte de volontaires humains.Nous avons ensuite développé des méthodes de reconstruction avancées pour les acquisitions MRF à haute dimension en s'appuyant sur des modèles de faible rang et des réseaux neuronaux profonds. Enfin, nous avons utilisé notre pipeline de simulation combiné à des réseaux neuronaux récurrents pour accélérer nos temps de calcul d'un facteur 800 et permettre l'inclusion des effets de diffusion de l'eau. Cette approche a été testée sur des données précliniques rétrospectives comprenant des animaux sains et des animaux ayant subi un AVC et les résultats ont suggéré que des estimations supplémentaires de l'ADC ou de l'oxygénation sanguine pouvaient être mesurées avec notre nouvelle séquence MRF bSSFP.Après une validation et une optimisation minutieuses, ce travail méthodologique fournira une solution d'imagerie efficace, alignée sur les contraintes de temps critiques des soins de l'AVC en phase aigu. Notre protocole général pour les acquisitions MRF à haute dimension incluant les effets des microvascularités pourrait également être utilisé dans diverses autres pathologies cérébrales
Stroke, a major cause of mortality and long-term disability worldwide, necessitates rapid and accurate diagnosis to optimize treatment outcomes. Current imaging techniques, particularly MRI, are critical for assessing the extent of brain injury and guiding therapeutic interventions. However, traditional MRI protocols are often time-consuming and may lack the precision required for detailed analysis of ischemic brain tissue, limiting their utility in acute stroke settings where time is of the essence.Magnetic Resonance Fingerprinting (MRF) is a relatively new solution to simultaneously map several brain quantitative parameters from fast, high-resolution acquisitions using a dictionary search approach. However, its extension for microvascular (e.g. cerebral blood volume (CBV) or blood vessel diameter (R)) and brain oxygenation estimates currently relies on the injection of exogenous contrast agents (CA) that limit the clinical application and acquisition speed. In this thesis, we aimed to address these limitations by developing a novel and integrated, artificial intelligence (AI) augmented contrast-free MRF technique tailored for stroke emergencies.First, we developed and adapted standard multiparametric MRF techniques based on spoiled gradient echo MRI sequences. Using scanner artifacts corrections, dictionary compression, and subspace reconstruction, we were able to generate fast relaxometry (T1,T2) maps and standard MRI contrasts from a single MRF sequence. However, the microvascular information provided by our new multi-compartment MRF model in human volunteers suffered from a low signal-to-noise ratio.We thus focused on a new MRF sequence design based on balanced GRE sequences and their remarkable sensitivity to magnetic field inhomogeneities. After a theoretical and textit{in-silico} study on general sequences sensitivities to the Blood Oxygen Level Dependent (BOLD) effect and the impact of MRF acquisition parameters, we designed a new MRF-bSSFP sequence that simultaneously estimate relaxometry (T1,T2,T2*,M0), magnetic fields (B1,B0), and microvascular properties (CBV,R) without the need for CA injection. Using a new pipeline for MRF simulations, the proposed method was tested in a cohort of human volunteers.Our method was further refined by developing advanced reconstruction methods for high dimensional MRF acquisitions relying on low-rank models and deep neural networks. We finally used our simulation framework combined with Recurrent Neural Networks to fasten our computation times by a factor of 800 and allow the inclusion of water-diffusion effects. This approach was tested in retrospective preclinical data including healthy and stroke animals and the results suggested that additional estimates of ADC or blood oxygenation could be measured with our new bSSFP MRF sequence.After careful validation and optimization, this methodological work could provide an efficient imaging solution that aligns with the critical time constraints of acute stroke care. Our general framework for high dimensional MRF acquisitions that include microstructure effects could also be used in various other pathologies

AbstractDigitalization in battery production, as well as the increase and stabilization of product quality of lithium-ion battery cells, require the elimination of information gaps between processes to enable the traceability of components and process steps to the finished product. In lithium-ion battery cell manufacturing, using a traceability system is considered a promising approach to reduce scrap rates and enable more efficient production. Today, traceability is possible from the assembled cell onwards. However, with a view to the new EU battery regulation, complete traceability down to the material needs to be ensured. One of the challenges in this context is to ensure both, traceability in continuous electrode production and cell-specific identification within the production chain. This paper presents an approach for identifying individual electrode segments without identification markers, using the individual microstructure of the electrode surface. The Fraunhofer Institute for Manufacturing Engineering and Automation IPA and the Fraunhofer Institute for Physical Measurement Techniques IPM are further developing and testing an identification technique known as Track & Trace Fingerprint. This technique is dedicated to serialization within battery production as part of the joint project DigiBattPro 4.0 and to be implemented at the Center for Digitalized Battery Cell Manufacturing (ZDB) of Fraunhofer IPA.

A critical task in utilizing quantum physics in many application fields is circuit design using reversible quantum gates. Using decomposition techniques enables transformation of unitary matrices into fundamental quantum gates. Any 3x3 reversible quantum gate can be decomposed into single-qubit rotation gates and two qubit CNOT gates. In this chapter, quantum implementations of FRSG1, URG, JTF1 and R gates into CNOT gates and single qubit U3 gates with different optimization levels on a platform provided by IBM have been discussed. FRSG1 and JTF1 gates are important in applications like Stochastic computing, fingerprint authentication system, and parity generation circuits. URG gate is better in terms of number of complex functions and can be utilized to design quantum comparator circuits. R gate plays an important role in inverting and duplicating a signal. In FRSG1, URG, JTF1 and R gates, the implementation count of single qubit gates decreases by 56%, 11%, 71%, and 62%, respectively and the count of two qubit gates reduces by 15%, 26%, 41%, and 5% respectively after optimization.

Rapid detection of pathogens and hazardous elements in fresh fruits and vegetables after harvest requires the use of advanced sensor technology at each step in the farm-to-consumer or farm-to-processing sequence. Fourier-transform infrared (FTIR) spectroscopy and the complementary Raman spectroscopy, an advanced optical technique based on light scattering will be investigated for rapid and on-site assessment of produce safety. Paving the way toward the development of this innovative methodology, specific original objectives were to (1) identify and distinguish different serotypes of Escherichia coli, Listeria monocytogenes, Salmonella typhimurium, and Bacillus cereus by FTIR and Raman spectroscopy, (2) develop spectroscopic fingerprint patterns and detection methodology for fungi such as Aspergillus, Rhizopus, Fusarium, and Penicillium (3) to validate a universal spectroscopic procedure to detect foodborne pathogens and non-pathogens in food systems. The original objectives proposed were very ambitious hence modifications were necessary to fit with the funding. Elaborate experiments were conducted for sensitivity, additionally, testing a wide range of pathogens (more than selected list proposed) was also necessary to demonstrate the robustness of the instruments, most crucially, algorithms for differentiating a specific organism of interest in mixed cultures was conceptualized and validated, and finally neural network and chemometric models were tested on a variety of applications. Food systems tested were apple juice and buffer systems. Pathogens tested include Enterococcus faecium, Salmonella enteritidis, Salmonella typhimurium, Bacillus cereus, Yersinia enterocolitis, Shigella boydii, Staphylococus aureus, Serratiamarcescens, Pseudomonas vulgaris, Vibrio cholerae, Hafniaalvei, Enterobacter cloacae, Enterobacter aerogenes, E. coli (O103, O55, O121, O30 and O26), Aspergillus niger (NRRL 326) and Fusarium verticilliodes (NRRL 13586), Saccharomyces cerevisiae (ATCC 24859), Lactobacillus casei (ATCC 11443), Erwinia carotovora pv. carotovora and Clavibacter michiganense. Sensitivity of the FTIR detection was 103CFU/ml and a clear differentiation was obtained between the different organisms both at the species as well as at the strain level for the tested pathogens. A very crucial step in the direction of analyzing mixed cultures was taken. The vector based algorithm was able to identify a target pathogen of interest in a mixture of up to three organisms. Efforts will be made to extend this to 10-12 key pathogens. The experience gained was very helpful in laying the foundations for extracting the true fingerprint of a specific pathogen irrespective of the background substrate. This is very crucial especially when experimenting with solid samples as well as complex food matrices. Spectroscopic techniques, especially FTIR and Raman methods are being pursued by agencies such as DARPA and Department of Defense to combat homeland security. Through the BARD US-3296-02 feasibility grant, the foundations for detection, sample handling, and the needed algorithms and models were developed. Successive efforts will be made in transferring the methodology to fruit surfaces and to other complex food matrices which can be accomplished with creative sampling methods and experimentation. Even a marginal success in this direction will result in a very significant breakthrough because FTIR and Raman methods, in spite of their limitations are still one of most rapid and nondestructive methods available. Continued interest and efforts in improving the components as well as the refinement of the procedures is bound to result in a significant breakthrough in sensor technology for food safety and biosecurity.