932 resultados para Electromagnetism in medicine.
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Radiotherapy is commonly planned on the basis of physical dose received by the tumour and surrounding normal tissue, with margins added to address the possibility of geometric miss. However, recent experimental evidence suggests that intercellular signalling results in a given cell's survival also depending on the dose received by neighbouring cells. A model of radiation-induced cell killing and signalling was used to analyse how this effect depends on dose and margin choices. Effective Uniform Doses were calculated for model tumours in both idealised cases with no delivery uncertainty and more realistic cases incorporating geometric uncertainty. In highly conformal irradiation, a lack of signalling from outside the target leads to reduced target cell killing, equivalent to under-dosing by up to 10% compared to large uniform fields. This effect is significantly reduced when higher doses per fraction are considered, both increasing the level of cell killing and reducing margin sensitivity. These effects may limit the achievable biological precision of techniques such as stereotactic radiotherapy even in the absence of geometric uncertainties, although it is predicted that larger fraction sizes reduce the relative contribution of cell signalling driven effects. These observations may contribute to understanding the efficacy of hypo-fractionated radiotherapy.
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The number of elderly patients requiring hospitalisation in Europe is rising. With a greater proportion of elderly people in the population comes a greater demand for health services and, in particular, hospital care. Thus, with a growing number of elderly patients requiring hospitalisation competing with non-elderly patients for a fixed (and in some cases, decreasing) number of hospital beds, this results in much longer waiting times for patients, often with a less satisfactory hospital experience. However, if a better understanding of the recurring nature of elderly patient movements between the community and hospital can be developed, then it may be possible for alternative provisions of care in the community to be put in place and thus prevent readmission to hospital. The research in this paper aims to model the multiple patient transitions between hospital and community by utilising a mixture of conditional Coxian phase-type distributions that incorporates Bayes' theorem. For the purpose of demonstration, the results of a simulation study are presented and the model is applied to hospital readmission data from the Lombardy region of Italy.
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Thesis submitted to Faculdade de Ciências e Tecnologia from Universidade Nova de Lisboa in partial fulfillment of the requirements for the obtention of the degree of Master of Science in Biotechnology
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Les nanoparticules (NPs) sont définies comme des particules ayant au moins une dimension comprise entre 1 à 100 nanomètres. Plusieurs études in vitro et in vivo indiquent que les NPs pourraient constituer un risque potentiel pour la santé des personnes les synthétisant ou les manipulant lors de leur incorporation dans d’autres matériaux. La nanotoxicologie est un domaine de recherche émergeant. Les propriétés physico-chimiques particulières des NPs sont responsables d’interférences non spécifiques entre les nanomatériaux et certains des composants des essais in vitro pouvant mener à de faux résultats. L’inhalation a été identifiée comme une voie d’exposition présentant un risque important de toxicité. Dans le cadre de ce projet, nous avons utilisé la lignée de cellules épithéliales alvéolaires humaines, A549. Nous avons étudié chez cette lignée les conséquences de l’exposition aux points quantiques (PQs), NPs d’intérêt pour leurs applications potentielles en médecine (nanovecteur ou nanosonde). La mise au point des conditions expérimentales (interférence entre l’essai LDH et le milieu de culture) a permis de valider les essais de cytotoxicité MTS et LDH en présence des PQs. Nous avons montré que les PQs présentaient une cytotoxicité à court et long terme, et nous avons par la suite étudié un des mécanismes de toxicité potentielle, la mesure du cadmium (Cd2+) libéré des PQs. Nous avons déterminé que la mesure du Cd2+ comportait plusieurs interférences qui invalident cet essai. En conclusion, notre étude a permis d’identifier des interférences qui remettent en question plusieurs conclusions d’études publiées qui n’ont pas vérifié l’existence de telles interférences.
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Tachykinin and opioid peptides play a central role in pain transmission, modulation and inhibition. The treatment of pain is very important in medicine and many studies using NK1 receptor antagonists failed to show significant analgesic effects in humans. Recent investigations suggest that both pronociceptive tachykinins and the analgesic opioid systems are important for normal pain sensation. The analysis of opioid peptides in Tac1-/- spinal cord tissues offers a great opportunity to verify the influence of the tachykinin system on specific opioid peptides. The objectives of this study were to develop a HPLC–MS/MRM assay to quantify targeted peptides in spinal cord tissues. Secondly, we wanted to verify if the Tac1-/- mouse endogenous opioid system is hampered and therefore affect significantly the pain modulatory pathways. Targeted neuropeptides were analyzed by high performance liquid chromatography linear ion trap mass spectrometry. Our results reveal that EM-2, Leu-Enk and Dyn A were down-regulated in Tac1-/- spinal cord tissues. Interestingly, Dyn A was almost 3 fold down-regulated (p < 0.0001). No significant concentration differences were observed in mouse Tac1-/- spinal cords for Met-Enk and CGRP. The analysis of Tac1-/- mouse spinal cords revealed noteworthy decreases of EM-2, Leu-Enk and Dyn A concentrations which strongly suggest a significant impact on the endogenous pain-relieving mechanisms. These observations may have insightful impact on future analgesic drug developments and therapeutic strategies.
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Ketamine is widely used in medicine in combination with several benzodiazepines including midazolam. The objectives of this study were to develop a novel HPLC-MS/SRM method capable of quantifying ketamine and norketamine using an isotopic dilution strategy in biological matrices and study the formation of norketamine, the principal metabolite of ketamine with and without the presence of midazolam, a well-known CYP3A substrate. The chromatographic separation was achieved using a Thermo Betasil Phenyl 100 x 2 mm column combined with an isocratic mobile phase composed of acetonitrile, methanol, water and formic acid (60:20:20:0.4) at a flow rate of 300 μL/min. The mass spectrometer was operating in selected reaction monitoring mode and the analytical range was set at 0.05–50 μM. The precision (%CV) and accuracy (%NOM) observed were ranging from 3.9–7.8 and 95.9.2–111.1% respectively. The initial rate of formation of norketamine was determined using various ketamine concentration and Km values of 18.4 μM, 13.8 μM and 30.8 μM for rat, dog and human liver S9 fractions were observed respectively. The metabolic stability of ketamine on liver S9 fractions was significantly higher in human (T1/2 = 159.4 min) compared with rat (T1/2 = 12.6 min) and dog (T1/2 = 7.3 min) liver S9 fractions. Moreover significantly lower IC50 and Ki values observed in human compared with rat and dog liver S9 fractions. Experiments with cDNA expressed CYP3A enzymes showed the formation of norketamine is mediated by CYP3A but results suggest an important contribution from others isoenzymes, most likely CYP2C particularly in rat.
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In this paper, a novel fast method for modeling mammograms by deterministic fractal coding approach to detect the presence of microcalcifications, which are early signs of breast cancer, is presented. The modeled mammogram obtained using fractal encoding method is visually similar to the original image containing microcalcifications, and therefore, when it is taken out from the original mammogram, the presence of microcalcifications can be enhanced. The limitation of fractal image modeling is the tremendous time required for encoding. In the present work, instead of searching for a matching domain in the entire domain pool of the image, three methods based on mean and variance, dynamic range of the image blocks, and mass center features are used. This reduced the encoding time by a factor of 3, 89, and 13, respectively, in the three methods with respect to the conventional fractal image coding method with quad tree partitioning. The mammograms obtained from The Mammographic Image Analysis Society database (ground truth available) gave a total detection score of 87.6%, 87.6%, 90.5%, and 87.6%, for the conventional and the proposed three methods, respectively.
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We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal
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In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is often associated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcifications is performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcifications have been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the sense of adding new features not only related to the shape
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Considering the difficulty in the insulin dosage selection and the problem of hyper- and hypoglycaemia episodes in type 1 diabetes, dosage-aid systems appear as tremendously helpful for these patients. A model-based approach to this problem must unavoidably consider uncertainty sources such as the large intra-patient variability and food intake. This work addresses the prediction of glycaemia for a given insulin therapy face to parametric and input uncertainty, by means of modal interval analysis. As result, a band containing all possible glucose excursions suffered by the patient for the given uncertainty is obtained. From it, a safer prediction of possible hyper- and hypoglycaemia episodes can be calculated
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Evaluation processes in clinical practice have not been well, being their study focused on the technical issues concerning these processes. This study tried an approach to the evaluation processes through the analysis of perceptions from teachers and students about the methodology of evaluation considering the teachinglearning processes performed in a clinical practice of the Medicine Program –Universidad El Bosque from Bogota. With this purpose we conducted interviews with teachers and students searching the manner in which the evaluative, learning and teaching processes are done; then we analyzed the perception from both agents concerning the way these processes are related. The interviews were categorized bath deductively and inductively, and then contrasted with some current theories of learning, teaching and evaluation in medicine. The study showed that nowadays the evaluation and, in general, the educative processes are affected by several factors which are associated to the manner the professional practice is developed, and the educative process of the current teachers. We concluded there is no congrency between the approach of the evaluation, mainly conductivist, and the learning and teaching strategies mainly constructivist. This fact cause dissent in teachers and students.
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In this paper, Bayesian decision procedures previously proposed for dose-escalation studies in healthy volunteers are reviewed and evaluated. Modifications are made to the expression of the prior distribution in order to make the procedure simpler to implement and a more relevant criterion for optimality is introduced. The results of an extensive simulation exercise to establish the proper-ties of the procedure and to aid choice between designs are summarized, and the way in which readers can use simulation to choose a design for their own trials is described. The influence of the value of the within-subject correlation on the procedure is investigated and the use of a simple prior to reflect uncertainty about the correlation is explored. Copyright (c) 2005 John Wiley & Sons, Ltd.
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Motivated by a matched case-control study to investigate potential risk factors for meningococcal disease amongst adolescents, we consider the analysis of matched case-control studies where disease incidence, and possibly other risk factors, vary with time of year. For the cases, the time of infection may be recorded. For controls, however, the recorded time is simply the time of data collection, which is shortly after the time of infection for the matched case, and so depends on the latter. We show that the effect of risk factors and interactions may be adjusted for the time of year effect in a standard conditional logistic regression analysis without introducing any bias. We also show that, if the time delay between data collection for cases and controls is constant, provided this delay is not very short, estimates of the time of year effect are approximately unbiased. In the case that the length of the delay varies over time, the estimate of the time of year effect is biased. We obtain an approximate expression for the degree of bias in this case. Copyright © 2004 John Wiley & Sons, Ltd.
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Pharmacovigilance, the monitoring of adverse events (AEs), is an integral part in the clinical evaluation of a new drug. Until recently, attempts to relate the incidence of AEs to putative causes have been restricted to the evaluation of simple demographic and environmental factors. The advent of large-scale genotyping, however, provides an opportunity to look for associations between AEs and genetic markers, such as single nucleotides polymorphisms (SNPs). It is envisaged that a very large number of SNPs, possibly over 500 000, will be used in pharmacovigilance in an attempt to identify any genetic difference between patients who have experienced an AE and those who have not. We propose a sequential genome-wide association test for analysing AEs as they arise, allowing evidence-based decision-making at the earliest opportunity. This gives us the capability of quickly establishing whether there is a group of patients at high-risk of an AE based upon their DNA. Our method provides a valid test which takes account of linkage disequilibrium and allows for the sequential nature of the procedure. The method is more powerful than using a correction, such as idák, that assumes that the tests are independent. Copyright © 2006 John Wiley & Sons, Ltd.