962 resultados para Ultrasonics in medicine


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Palpable mass is a common complaint presented to the breast surgeon. It is very uncommon for patients to report breast mass associated with palpable masses in other superficial structures. When these masses are related to systemic granulomatous diseases, the diagnosis and initiation of specific therapy can be challenging. The purpose of this paper is to report a case initially assessed by the breast surgeon and ultimately diagnosed as granulomatous variant of T-cell lymphoma, and discuss the main systemic granulomatous diseases associated with palpable masses involving the breast.

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During the last ten years, graphene oxide has been explored in many applications due to its remarkable electroconductivity, thermal properties and mobility of charge carriers, among other properties. As discussed in this review, the literature suggests that a total characterization of graphene oxide must be conducted because oxidation debris (synthesis impurities) present in the graphene oxides could act as a graphene oxide surfactant, stabilizing aqueous dispersions. It is also important to note that the structure models of graphene oxide need to be revisited because of significant implications for its chemical composition and its direct covalent functionalization. Another aspect that is discussed is the need to consider graphene oxide surface chemistry. The hemolysis assay is recommended as a reliable test for the preliminary assessment of graphene oxide toxicity, biocompatibility and cell membrane interaction. More recently, graphene oxide has been extensively explored for drug delivery applications. An important increase in research efforts in this emerging field is clearly represented by the hundreds of related publications per year, including some reviews. Many studies have been performed to explore the graphene oxide properties that enable it to deliver more than one activity simultaneously and to combine multidrug systems with photothermal therapy, indicating that graphene oxide is an attractive tool to overcome hurdles in cancer therapies. Some strategic aspects of the application of these materials in cancer treatment are also discussed. In vitro studies have indicated that graphene oxide can also promote stem cell adhesion, growth and differentiation, and this review discusses the recent and pertinent findings regarding graphene oxide as a valuable nanomaterial for stem cell research in medicine. The protein corona is a key concept in nanomedicine and nanotoxicology because it provides a biomolecular identity for nanomaterials in a biological environment. Understanding protein corona-nanomaterial interactions and their influence on cellular responses is a challenging task at the nanobiointerface. New aspects and developments in this area are discussed.

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Our previous study showed that electroacupuncture (EA) increases the concentration and reorganisation of collagen in a rat model of tendon healing. However, the ultrastructure of collagen fibrils after acupuncture is unknown. To assess the effect of acupuncture protocols on the ultrastructure of collagen fibrils during tendon healing. Sixty-four rats were divided into the following groups: non-tenotomised (normal group), tenotomised (teno group), tenotomised and subjected to manual acupuncture at ST36 (ST36 group), BL57 (BL57 group) and ST36+BL57 (SB group) and EA at ST36+BL57 (EA group). The mass-average diameter (MAD) and the reorganisation of collagen fibril diameters were determined during the three phases of tendon healing (at 7, 14 and 21 days). The MAD increased during the three phases of healing in the SB group. In the EA group, MAD increased initially but was reduced at day 21. The reorganisation of collagen fibrils was improved in the EA and SB groups at days 14 and 21, respectively. EA at day 21 appeared to reduce the reorganisation. These results indicate that the use of EA up to day 14 and manual acupuncture at ST36+BL57 up to day 21 improve the ultrastructure of collagen fibrils, indicating strengthening of the tendon structure. These data suggest a potential role for acupuncture in rehabilitation protocols.

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OBJETIVO: caracterizar a inserção de egressos do Curso de Fonoaudiologia da Universidade Estadual Paulista (UNESP) - Marília, em Programas de Pós-Graduação (PPG) Stricto Sensu brasileiros. MÉTODO: foram utilizadas listas de graduados e Curriculum Vitae do egresso e do orientador. RESULTADOS: dos 537 formados, 16,57% cursaram/estavam cursando PPG e destes, 98,88% em mestrado e 37,08% também em doutorado. Na grande área de conhecimento, 50% dos egressos de mestrado vincularam-se predominantemente a programas em Ciências da Saúde, 31,80% em Ciências Humanas e 13,64% em Linguística, Letras e Artes. No doutorado, 33, 33% em Ciências Humanas, 30,30% em Ciências da Saúde e em Linguística, Letras e Artes. Quanto à área de conhecimento, predominou a vinculação, no mestrado, de 30,68% em Fonoaudiologia, 28,41% em Educação, 13,64% em Linguística e 9,09% em Medicina I; e, no doutorado, de 33,33% em Educação, 30,30% em Linguística e 9,09% em Fonoaudiologia; 55,68% dissertações e 51,52% teses focalizaram a linguagem. A UNESP predominou com 39,77% no mestrado e 48,48% no doutorado. Predominou a vinculação a Programas com conceito 4 para 52,27% dos egressos do mestrado e 45,45% do doutorado. Quando constou a informação (55,68%), todos receberam fomento. O Teste de Razão de Verossimilhança não indicou diferenças significativas dos percentuais obtidos entre o mestrado e o doutorado. CONCLUSÃO: os resultados superaram os apresentados para o mesmo Estado, mostraram a característica interdisciplinar da Ciência Fonoaudiológica e o predomínio de temática em linguagem.

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The efficacy of photodynamic therapy (PDT) depends on a variety of parameters: concentration of the photosensitizer at the time of treatment, light wavelength, fluence, fluence rate, availability of oxygen within the illuminated volume, and light distribution in the tissue. Dosimetry in PDT requires the congregation of adequate amounts of light, drug, and tissue oxygen. The adequate dosimetry should be able to predict the extension of the tissue damage. Photosensitizer photobleaching rate depends on the availability of molecular oxygen in the tissue. Based on photosensitizers photobleaching models, high photobleaching has to be associated with high production of singlet oxygen and therefore with higher photodynamic action, resulting in a greater depth of necrosis. The purpose of this work is to show a possible correlation between depth of necrosis and the in vivo photosensitizer (in this case, Photogem (R)) photodegradation during PDT. Such correlation allows possibilities for the development of a real time evaluation of the photodynamic action during PDT application. Experiments were performed in a range of fluence (0-450 J/cm(2)) at a constant fluence rate of 250 mW/cm(2) and applying different illumination times (0-1800 s) to achieve the desired fluence. A quantity was defined (psi) as the product of fluorescence ratio (related to the photosensitizer degradation at the surface) and the observed depth of necrosis. The correlation between depth of necrosis and surface fluorescence signal is expressed in psi and could allow, in principle, a noninvasive monitoring of PDT effects during treatment. High degree of correlation is observed and a simple mathematical model to justify the results is presented.

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In this work an iterative strategy is developed to tackle the problem of coupling dimensionally-heterogeneous models in the context of fluid mechanics. The procedure proposed here makes use of a reinterpretation of the original problem as a nonlinear interface problem for which classical nonlinear solvers can be applied. Strong coupling of the partitions is achieved while dealing with different codes for each partition, each code in black-box mode. The main application for which this procedure is envisaged arises when modeling hydraulic networks in which complex and simple subsystems are treated using detailed and simplified models, correspondingly. The potentialities and the performance of the strategy are assessed through several examples involving transient flows and complex network configurations.

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Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

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This paper presents a framework to build medical training applications by using virtual reality and a tool that helps the class instantiation of this framework. The main purpose is to make easier the building of virtual reality applications in the medical training area, considering systems to simulate biopsy exams and make available deformation, collision detection, and stereoscopy functionalities. The instantiation of the classes allows quick implementation of the tools for such a purpose, thus reducing errors and offering low cost due to the use of open source tools. Using the instantiation tool, the process of building applications is fast and easy. Therefore, computer programmers can obtain an initial application and adapt it to their needs. This tool allows the user to include, delete, and edit parameters in the functionalities chosen as well as storing these parameters for future use. In order to verify the efficiency of the framework, some case studies are presented.

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Research Foundation of the State of Sao Paulo (FAPESP)

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State of Sao Paulo Research Foundation (FAPESP)

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This work discusses the determination of the breathing patterns in time sequence of images obtained from magnetic resonance (MR) and their use in the temporal registration of coronal and sagittal images. The registration is made without the use of any triggering information and any special gas to enhance the contrast. The temporal sequences of images are acquired in free breathing. The real movement of the lung has never been seen directly, as it is totally dependent on its surrounding muscles and collapses without them. The visualization of the lung in motion is an actual topic of research in medicine. The lung movement is not periodic and it is susceptible to variations in the degree of respiration. Compared to computerized tomography (CT), MR imaging involves longer acquisition times and it is preferable because it does not involve radiation. As coronal and sagittal sequences of images are orthogonal to each other, their intersection corresponds to a segment in the three-dimensional space. The registration is based on the analysis of this intersection segment. A time sequence of this intersection segment can be stacked, defining a two-dimension spatio-temporal (2DST) image. The algorithm proposed in this work can detect asynchronous movements of the internal lung structures and lung surrounding organs. It is assumed that the diaphragmatic movement is the principal movement and all the lung structures move almost synchronously. The synchronization is performed through a pattern named respiratory function. This pattern is obtained by processing a 2DST image. An interval Hough transform algorithm searches for synchronized movements with the respiratory function. A greedy active contour algorithm adjusts small discrepancies originated by asynchronous movements in the respiratory patterns. The output is a set of respiratory patterns. Finally, the composition of coronal and sagittal image pairs that are in the same breathing phase is realized by comparing of respiratory patterns originated from diaphragmatic and upper boundary surfaces. When available, the respiratory patterns associated to lung internal structures are also used. The results of the proposed method are compared with the pixel-by-pixel comparison method. The proposed method increases the number of registered pairs representing composed images and allows an easy check of the breathing phase. (C) 2010 Elsevier Ltd. All rights reserved.

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This work discusses a 4D lung reconstruction method from unsynchronized MR sequential images. The lung, differently from the heart, does not have its own muscles, turning impossible to see its real movements. The visualization of the lung in motion is an actual topic of research in medicine. CT (Computerized Tomography) can obtain spatio-temporal images of the heart by synchronizing with electrocardiographic waves. The FOV of the heart is small when compared to the lung`s FOV. The lung`s movement is not periodic and is susceptible to variations in the degree of respiration. Compared to CT, MR (Magnetic Resonance) imaging involves longer acquisition times and it is not possible to obtain instantaneous 3D images of the lung. For each slice, only one temporal sequence of 2D images can be obtained. However, methods using MR are preferable because they do not involve radiation. In this paper, based on unsynchronized MR images of the lung an animated B-Repsolid model of the lung is created. The 3D animation represents the lung`s motion associated to one selected sequence of MR images. The proposed method can be divided in two parts. First, the lung`s silhouettes moving in time are extracted by detecting the presence of a respiratory pattern on 2D spatio-temporal MR images. This approach enables us to determine the lung`s silhouette for every frame, even on frames with obscure edges. The sequence of extracted lung`s silhouettes are unsynchronized sagittal and coronal silhouettes. Using our algorithm it is possible to reconstruct a 3D lung starting from a silhouette of any type (coronal or sagittal) selected from any instant in time. A wire-frame model of the lung is created by composing coronal and sagittal planar silhouettes representing cross-sections. The silhouette composition is severely underconstrained. Many wire-frame models can be created from the observed sequences of silhouettes in time. Finally, a B-Rep solid model is created using a meshing algorithm. Using the B-Rep solid model the volume in time for the right and left lungs were calculated. It was possible to recognize several characteristics of the 3D real right and left lungs in the shaded model. (C) 2007 Elsevier Ltd. All rights reserved.

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Endophytic microorganisms reside asymptomatically within plants and are a source of new bioactive products for use in medicine, agriculture, and industry. Colletotrichum (teleomorph Glomerella) is a fungus widely cited in the literature as a producer of antimicrobial substances. Identification at the species level, however, has been a problem in this type of study. Several authors have reported the presence of endophytic fungi from the medicinal plant Maytenus ilicifolia (espinheira-santa) in Brazil that has antimicrobial activity against various pathogens. Therefore, Colletotrichum strains were isolated from M. ilicifolia and identified based on morphology, RAPD markers, sequence data of the internal transcribed spacer regions (ITS-1 and ITS-2), the 5.8S gene, and species-specific PCR. The analyses suggested the presence of 2 species, Colletotrichum gloeosporioides and Colletotrichum boninense. Two morphological markers were characterized to allow C. gloeosporioides and C. boninense to be distinguished quickly and accurately. The molecular diagnosis of C. boninense was confirmed by using Coll and ITS4 primers. This species of Colletotrichum is reported for the first time in M. ilicifolia.

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This paper describes a hybrid numerical method of an inverse approach to the design of compact magnetic resonance imaging magnets. The problem is formulated as a field synthesis and the desired current density on the surface of a cylinder is first calculated by solving a Fredholm equation of the first, kind. Nonlinear optimization methods are then invoked to fit practical magnet coils to the desired current density. The field calculations are performed using a semi-analytical method. The emphasis of this work is on the optimal design of short MRI magnets. Details of the hybrid numerical model are presented, and the model is used to investigate compact, symmetric MRI magnets as well as asymmetric magnets. The results highlight that the method can be used to obtain a compact MRI magnet structure and a very homogeneous magnetic field over the central imaging volume in clinical systems of approximately 1 m in length, significantly shorter than current designs. Viable asymmetric magnet designs, in which the edge of the homogeneous region is very close to one end of the magnet system are also presented. Unshielded designs are the focus of this work. This method is flexible and may be applied to magnets of other geometries. (C) 2000 American Association of Physicists in Medicine. [S0094-2405(00)00303-5].