29 resultados para Candida antigen diagnosis

em Instituto Politécnico do Porto, Portugal


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Antibodies against gliadin are used to detect celiac disease (CD) in patients. An electrochemical immunosensor for the voltammetric detection of human anti-gliadin antibodies (AGA) IgA and AGA IgG in real serum samples is proposed. The transducer surface consists of screen-printed carbon electrodes modified with a carbon nanotube/gold nanoparticle hybrid system, which provides a very useful surface for the amplification of the immunological interactions. The immunosensing strategy is based on the immobilization of gliadin, the antigen for the autoantibodies of interest, onto the nanostructured surface. The antigen–antibody interaction is recorded using alkaline phosphatase labeled anti-human antibodies and a mixture of 3-indoxyl phosphate with silver ions (3-IP/Ag+) was used as the substrate. The analytical signal is based on the anodic redissolution of the enzymatically generated silver by cyclic voltammetry. The electrochemical behavior of this immunosensor was carefully evaluated assessing aspects as sensitivity, non-specific binding and matrix effects, and repeatability and reproducibility. The results were supported with a commercial ELISA test.

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This work presents the development of a low cost sensor device for the diagnosis of breast cancer in point-of-care, made with new synthetic biomimetic materials inside plasticized poly(vinyl chloride), PVC, membranes, for subsequent potentiometric detection. This concept was applied to target a conventional biomarker in breast cancer: Breast Cancer Antigen (CA15-3). The new biomimetic material was obtained by molecularly-imprinted technology. In this, a plastic antibody was obtained by polymerizing around the biomarker that acted as an obstacle to the growth of the polymeric matrix. The imprinted polymer was specifically synthetized by electropolymerization on an FTO conductive glass, by using cyclic voltammetry, including 40 cycles within -0.2 and 1.0 V. The reaction used for the polymerization included monomer (pyrrol, 5.0×10-3 mol/L) and protein (CA15-3, 100U/mL), all prepared in phosphate buffer saline (PBS), with a pH of 7.2 and 1% of ethylene glycol. The biomarker was removed from the imprinted sites by proteolytic action of proteinase K. The biomimetic material was employed in the construction of potentiometric sensors and tested with regard to its affinity and selectivity for binding CA15-3, by checking the analytical performance of the obtained electrodes. For this purpose, the biomimetic material was dispersed in plasticized PVC membranes, including or not a lipophilic ionic additive, and applied on a solid conductive support of graphite. The analytical behaviour was evaluated in buffer and in synthetic serum, with regard to linear range, limit of detection, repeatability, and reproducibility. This antibody-like material was tested in synthetic serum, and good results were obtained. The best devices were able to detect 5 times less CA15-3 than that required in clinical use. Selectivity assays were also performed, showing that the various serum components did not interfere with this biomarker. Overall, the potentiometric-based methods showed several advantages compared to other methods reported in the literature. The analytical process was simple, providing fast responses for a reduced amount of analyte, with low cost and feasible miniaturization. It also allowed the detection of a wide range of concentrations, diminishing the required efforts in previous sample pre-treating stages.

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This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.

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The activity of Control Center operators is important to guarantee the effective performance of Power Systems. Operators’ actions are crucial to deal with incidents, especially severe faults like blackouts. In this paper, we present an Intelligent Tutoring approach for training Portuguese Control Center operators in tasks like incident analysis and diagnosis, and service restoration of Power Systems. Intelligent Tutoring System (ITS) approach is used in the training of the operators, having into account context awareness and the unobtrusive integration in the working environment. Several Artificial Intelligence techniques were criteriously used and combined together to obtain an effective Intelligent Tutoring environment, namely Multiagent Systems, Neural Networks, Constraint-based Modeling, Intelligent Planning, Knowledge Representation, Expert Systems, User Modeling, and Intelligent User Interfaces.

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Celiac disease (CD) is an autoimmune enteropathy, characterized by an inappropriate T-cell-mediated immune response to the ingestion of certain dietary cereal proteins in genetically susceptible individuals. This disorder presents environmental, genetic, and immunological components. CD presents a prevalence of up to 1% in populations of European ancestry, yet a high percentage of cases remain underdiagnosed. The diagnosis and treatment should be made early since untreated disease causes growth retardation and atypical symptoms, like infertility or neurological disorders. The diagnostic criteria for CD, which requires endoscopy with small bowel biopsy, have been changing over the last few decades, especially due to the advent of serological tests with higher sensitivity and specificity. The use of serological markers can be very useful to rule out clinical suspicious cases and also to help monitor the patients, after adherence to a gluten-free diet. Since the current treatment consists of a life-long glutenfree diet, which leads to significant clinical and histological improvement, the standardization of an assay to assess in an unequivocal way gluten in gluten-free foodstuff is of major importance.

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Little is known on the expression of the tumour-associated carbohydrate antigen sialyl-Tn (STn), in bladder cancer. We report here that 75% of the high-grade bladder tumours, presenting elevated proliferation rates and high risk of recurrence/progression expressed STn. However, it was mainly found in non-proliferative areas of the tumour, namely in cells invading the basal and muscle layers. STn was also found in tumour-adjacent mucosa, which suggests its dependence on a field effect of the tumour. Furthermore, it was not expressed by the normal urothelium, demonstrating the cancer-specific nature of this antigen. STn expression correlated with that of sialyltransferase ST6GalNAc.I, its major biosynthetic enzyme. The stable expression of ST6GalNAc.I in the bladder cancer cell line MCR induced STn expression and a concomitant increase of cell motility and invasive capability. Altogether, these results indicate for the first time a link between STn expression and malignancy in bladder cancer. Hence, therapies targeting STn may constitute new treatment approaches for these tumours.

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The first electrochemical immunosensor (EI) for the detection of antibodies against deamidated gliadin peptides (DGP) is described here. A disposable nanohybrid screen-printed carbon electrode modified with DGP was employed as the transducer's sensing surface. Real serumsampleswere successfully assayed and the results were corroborated with an ELISA kit. The presented EI is a promising analytical tool for celiac disease diagnosis.

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The latest medical diagnosis devices enable the performance of e-diagnosis making the access to these services easier, faster and available in remote areas. However this imposes new communications and data interchange challenges. In this paper a new XML based format for storing cardiac signals and related information is presented. The proposed structure encompasses data acquisition devices, patient information, data description, pathological diagnosis and waveform annotation. When compared with similar purpose formats several advantages arise. Besides the full integrated data model it may also be noted the available geographical references for e-diagnosis, the multi stream data description, the ability to handle several simultaneous devices, the possibility of independent waveform annotation and a HL7 compliant structure for common contents. These features represent an enhanced integration with existent systems and an improved flexibility for cardiac data representation.

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A diabetes mellitus do tipo 1 (DM1) é o distúrbio endócrino-metabólico mais frequente em crianças. É uma doença autoimune resultado da destruição selectiva das células beta pancreáticas. A velocidade de destruição das células beta pode ser rápida em algumas pessoas e lenta em outras; esta última é típica de adulto é conhecido como diabetes autoimune latente em adulto (LADA). A sua etiologia envolve factores ambientais e genéticos, dos genes envolvidos a maior contribuição vem da região do genoma onde estão localizados os genes do Complexo Principal de Histocompatibilidade (MHC). A combinação de diferentes alelos do sistema de antigénio leucocitário humano tipo II (HLAII) esta associada a susceptibilidade da doença e as principais molécula envolvidas são a DQ e DR. O estágio pré-clínico da doença se caracteriza pela presença de auto-anticorpos, sendo o anti-GAD o mais sensível nesta patologia. OBJECTIVO: Analizar a frequência dos polimorfismos HLA-DR/DQ em angolanos portadores de diabetes tipo 1, residentes em Luanda. O tipo de estudo adotado foi casocontrolo num universo de voluntários provenientes da consulta externa de hospitais e clínicas locais no período de outubro de 2012 a outubro 2013. A amostra biológica utilizada foi sangue total, tendo sido processada no laboratório LABGENE, da Faculdade de Medicina (FM) da Universidade Agostinho Neto (UNA). Os auto-anticorpos, anti-GAD, foram doseados pelo método de ELISA. O ADN genómico foi extraído à partir de sangue total periférico e tipagem genética foi realizada mediante PCR-SSP.O alelo DQB1*02 (DQ2/DQ2) (p=0,033, OR= 4, IC (1,2-13,3) foi associado a susceptibilidade da DM1; os alelos DQB1*06 (DQ6/DQ6) (p=0,000, OR=0,30, IC (0,17-0,54); *11 (p=0,011, OR=0,14, IC=0,032-0,62); *13 (p=0,006, OR=0,13, IC=0,049-0,588) e *15 (p=0,001, OR=0,044, IC=0,005-0,39) foram associados a proteção. Foi encontrado 29,2% de positividade para o anti-GAD, não houve associação significativa (p=0,69) entre a resposta positiva do anti-GAD e a idade. Não foi encontrada associação significativa (p=0,39) entre o tempo de diagnóstico e resposta humoral. Observou-se associação significativa entre os alelos de risco DQB1*02 (p=0.000) e resposta positiva para anti-GAD; da mesma maneira houve uma associação significativa para os alelos DQB1*06 (p=0,002), DRB1*11 (p=0,048); *13 (p=0,004) e *15 (p=0,021) e a resposta negativa do anti-GAD.Os dados demostram o forte envolvimentos do gene HLA-II (DQ) com a suceptibilidade a DM1 e sugere que a autoimunidade se desenvolve na presença de susceptibilidade genética, quer dizer, em associação com alelos HLA-II específicos.

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More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

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O cancro é uma das principais causas de morte em todo o mundo. Entre as mulheres, o cancro da mama é o mais frequente. A deteção precoce do cancro é de extrema importância na medida em que pode aumentar as possibilidades de cura dos pacientes e contribuir para a diminuição da taxa de mortalidade desta doença. Um método que tem contribuído para a deteção precoce do cancro é a análise de biomarcadores. Biomarcadores associados ao cancro da mama, como o Recetor 2 do Fator de Crescimento Epidérmico Humano (HER2) e o Antigénio Carbohidratado 15-3 (CA 15-3), podem ser detetados através de dispositivos como os biossensores. Neste trabalho foram desenvolvidos dois imunossensores eletroquímicos para a análise de HER2 e CA 15-3. Para ambos os sensores foram utilizados, como transdutores, elétrodos serigrafados de carbono. A superfície destes transdutores foi nanoestruturada com nanopartículas de ouro. Foram realizados imunoensaios não-competitivos (do tipo sandwich) em ambos os imunossensores, cuja estratégia consistiu na (i) imobilização do respetivo anticorpo de captura na superfície nanoestruturada dos elétrodos, (ii) bloqueio da superfície com caseína, (iii) incubação com uma mistura do analito (HER2 ou CA 15-3) e o respetivo anticorpo de deteção biotinilado, (iv) adição de estreptavidina conjugada com fosfatase alcalina (S-AP; a AP foi utilizada como marcador enzimático), (v) adição de uma mistura do substrato enzimático (3-indoxil fosfato) e nitrato de prata, e (vi) deteção do sinal analítico através da redissolução anódica, por voltametria de varrimento linear, da prata depositada enzimaticamente. Com as condições experimentais otimizadas, foi estabelecida a curva de calibração para a análise de HER2 em soro, entre 15 e 100 ng/mL, obtendo-se um limite de deteção de 4,4 ng/mL. Para o CA 15-3 a curva de calibração (em solução aquosa) foi estabelecida entre 15 e 250 U/mL, obtendo-se um limite de deteção de 37,5 U/mL. Tendo em conta o valor limite (cutoff value) estabelecido para o HER2 (15 ng/mL) pode-se comprovar a possível utilidade do imunossensor desenvolvido para o diagnóstico precoce e descentralizado do cancro da mama. No caso do CA 15-3 serão necessários estudos adicionais para se poder avaliar a utilidade do imunossensor para o diagnóstico do cancro da mama.