846 resultados para COMPUTER-AIDED MOLECULAR DESIGN
Resumo:
An elastomeric, healable, supramolecular polymer blend comprising a chain-folding polyimide and a telechelic polyurethane with pyrenyl end groups is compatibilized by aromatic pi-pi stacking between the pi-electron-deficient diimide groups and the pi-electron-rich pyrenyl units. This interpolymer interaction is the key to forming a tough, healable, elastomeric material. Variable-temperature FTIR analysis of the bulk material also conclusively demonstrates the presence of hydrogen bonding, which complements the pi-pi stacking interactions. Variable-temperature SAXS analysis shows that the healable polymeric blend has a nanophase-separated morphology and that the X-ray contrast between the two types of domain increases with increasing temperature, a feature that is repeatable over several heating and cooling cycles. A fractured sample of this material reproducibly regains more than 95% of the tensile modulus, 91% of the elongation to break, and 77% of the modulus of toughness of the pristine material.
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We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.
Resumo:
Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.
Resumo:
A supramolecular polymer based upon two complementary polymer components is formed by sequential deposition from solution in THF, using a piezoelectric drop-on-demand inkjet printer. Highly efficient cycloaddition or ‘click’ chemistry afforded a well-defined poly(ethylene glycol) featuring chain-folding diimide end groups, which possesses greatly enhanced solubility in THF relative to earlier materials featuring random diimide sequences. Blending the new polyimide with a complementary poly(ethylene glycol) system bearing pyrene end groups (which bind to the chain-folding diimide units) overcomes the limited solubility encountered previously with chain-folding polyimides in inkjet printing applications. The solution state properties of the resulting polymer blend were assessed via viscometry to confirm the presence of a supramolecular polymer before depositing the two electronically complementary polymers by inkjet printing techniques. The novel materials so produced offer an insight into ways of controlling the properties of printed materials through tuning the structure of the polymer at the (supra)molecular level.
Resumo:
This paper describes a new module of the expert system SISTEMAT used for the prediction of the skeletons of neolignans by (13)C NMR, (1)H NMR and botanical data obtained from the literature. SISTEMAT is composed of MACRONO, SISCONST, C13MACH, H1MACH and SISOCBOT programs, each analyzing data of the neolignan in question to predict the carbon skeleton of the compound. From these results, the global probability is computed and the most probable skeleton predicted. SISTEMAT predicted the skeletons of 75% of the 20 neolignans tested, in a rapid and simple procedure demonstrating its advantage for the structural elucidation of new compounds.
A Comparative Analysis between Ultrasonometry and Computer-Aided Tomography to Evaluate Bone Healing
Resumo:
An ultrasonometric and computed-tomographic study of bone healing was undertaken using a model of a transverse mid-shaft osteotomy of sheep tibiae fixed with a semi-flexible external fixator. Fourteen sheep were operated and divided into two groups of seven according to osteotomy type, either regular or by segmental resection. The animals were killed on the 90th postoperative day and the tibiae resected for the in vitro direct contact transverse and axial measurement of ultrasound propagation velocity (UV) followed by quantitative computer-aided tomography (callus density and volume) through the osteotomy site. The intact left tibiae were used for control, being examined in a symmetrical diaphyseal segment. Regular osteotomies healed with a smaller and more mature callus than resection osteotomies. Axial UV was consistently and significantly higher (p?=?0.01) than transverse UV and both transverse and axial UV were significantly higher for the regular than for the segmental resection osteotomy. Transverse UV did not differ significantly between the intact and operated tibiae (p?=?0.20 for regular osteotomy; p?=?0.02 for resection osteotomy), but axial UV was significantly higher for the intact tibiae. Tomographic callus density was significantly higher for the regular than for the resection osteotomy and higher than both for the intact tibiae, presenting a strong positive correlation with UV. Callus volume presented an opposite behavior, with a negative correlation with UV. We conclude that UV is at least as precise as quantitative tomography for providing information about the healing state of both regular and resection osteotomy. (C) 2011 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 30:10761082, 2012
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Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r(2) = 0.98 and q(2) = 0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pK(i) values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.
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Die Kernmagnetresonanz (NMR) ist eine vielseitige Technik, die auf spin-tragende Kerne angewiesen ist. Seit ihrer Entdeckung ist die Kernmagnetresonanz zu einem unverzichtbaren Werkzeug in unzähligen Anwendungen der Physik, Chemie, Biologie und Medizin geworden. Das größte Problem der NMR ist ihre geringe Sensitivtät auf Grund der sehr kleinen Energieaufspaltung bei Raumtemperatur. Für Protonenspins, die das größte magnetogyrische Verhältnis besitzen, ist der Polarisationsgrad selbst in den größten verfügbaren Magnetfeldern (24 T) nur ~7*10^(-5).rnDurch die geringe inhärente Polarisation ist folglich eine theoretische Sensitivitätssteigerung von mehr als 10^4 möglich. rnIn dieser Arbeit wurden verschiedene technische Aspekte und unterschiedliche Polarisationsagenzien für Dynamic Nuclear Polarization (DNP) untersucht.rnDie technische Entwicklung des mobilen Aufbaus umfasst die Verwendung eines neuen Halbach Magneten, die Konstruktion neuer Probenköpfe und den automatisierten Ablauf der Experimente mittels eines LabVIEW basierten Programms. Desweiteren wurden zwei neue Polarisationsagenzien mit besonderen Merkmalen für den Overhauser und den Tieftemperatur DNP getestet. Zusätzlich konnte die Durchführbarkeit von NMR Experimenten an Heterokernen (19F und 13C) im mobilen Aufbau bei 0,35 T gezeigt werden. Diese Ergebnisse zeigen die Möglichkeiten der Polarisationstechnik DNP auf, wenn Heterokerne mit einem kleinen magnetogyrischen Verhältnis polarisiert werden müssen.rnDie Sensitivitätssteigerung sollte viele neue Anwendungen, speziell in der Medizin, ermöglichen.
Resumo:
To retrospectively analyze the performance of a commercial computer-aided diagnosis (CAD) software in the detection of pulmonary nodules in original and energy-subtracted (ES) chest radiographs.
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Image overlay projection is a form of augmented reality that allows surgeons to view underlying anatomical structures directly on the patient surface. It improves intuitiveness of computer-aided surgery by removing the need for sight diversion between the patient and a display screen and has been reported to assist in 3-D understanding of anatomical structures and the identification of target and critical structures. Challenges in the development of image overlay technologies for surgery remain in the projection setup. Calibration, patient registration, view direction, and projection obstruction remain unsolved limitations to image overlay techniques. In this paper, we propose a novel, portable, and handheld-navigated image overlay device based on miniature laser projection technology that allows images of 3-D patient-specific models to be projected directly onto the organ surface intraoperatively without the need for intrusive hardware around the surgical site. The device can be integrated into a navigation system, thereby exploiting existing patient registration and model generation solutions. The position of the device is tracked by the navigation system’s position sensor and used to project geometrically correct images from any position within the workspace of the navigation system. The projector was calibrated using modified camera calibration techniques and images for projection are rendered using a virtual camera defined by the projectors extrinsic parameters. Verification of the device’s projection accuracy concluded a mean projection error of 1.3 mm. Visibility testing of the projection performed on pig liver tissue found the device suitable for the display of anatomical structures on the organ surface. The feasibility of use within the surgical workflow was assessed during open liver surgery. We show that the device could be quickly and unobtrusively deployed within the sterile environment.