Cytotoxicity Induced by Extracts of Pisolithus tinctorius Spores on Human Cancer and Normal Cell Lines—Evaluation of the Anticancer Potential

Fungi have been considered a potential source of natural anticancer drugs. However, studies on these organisms have mainly focused on compounds present in the sporocarp and mycelium. The aim of this study was to assess the anticancer potential of fungal spores using a bioassay-guided fractionation with cancer and normal cell lines. Crude extracts from spores of the basidiomycetous fungus Pisolithus tinctorius were prepared using five solvents/solvent mixtures in order to select the most effective crude extraction procedure. A dichloromethane/methanol (DCM/MeOH) mixture was found to produce the highest extraction yield, and this extract was fractionated into 11 fractions. Crude extracts and fractions were assayed for cytotoxicity in the human osteocarcinoma cell line MG63, the human breast carcinoma cell line T47D, the human colon adenocarcinoma cell line RKO, and the normal human brain capillary endothelial cell line hCMEC/D3. Cytotoxicity was assessed by the 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) reduction assay. The results showed a reduction in cancer cell viability of approximately 95% with 4 of 11 fractions without a significant reduction in viability of hCMEC/D3 cells. Data demonstrated that spores of P. tinctorius might serve as an interesting source of compounds with potential anticancer properties.

A new approach for multi-agent coalition formation and management in the scope of electricity markets

This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.

Interlimb Coordination During Step-to-Step Transition and Gait Performance

Most energy spent in walking is due to step-to-step transitions. During this phase, the interlimb coordination assumes a crucial role to meet the demands of postural and movement control. The authors review studies that have been carried out regarding the interlimb coordination during gait, as well as the basic biomechanical and neurophysiological principles of interlimb coordination. The knowledge gathered from these studies is useful for understanding step-to-step transition during gait from a motor control perspective and for interpreting walking impairments and inefficiency related to pathologies, such as stroke. This review shows that unimpaired walking is characterized by a consistent and reciprocal interlimb influence that is supported by biomechanical models, and spinal and supraspinal mechanisms. This interlimb coordination is perturbed in subjects with stroke.

Sistema de modelização tridimensional para ambientes não estruturados

A navegação de veículos autónomos em ambientes não estruturados continua a ser um problema em aberto. A complexidade do mundo real ainda é um desafio. A difícil caracterização do relevo irregular, dos objectos dinâmicos e pouco distintos(e a inexistência de referências de localização) tem sido alvo de estudo e do desenvolvimento de vários métodos que permitam de uma forma eficiente, e em tempo real, modelizar o espaço tridimensional. O trabalho realizado ao longo desta dissertação insere-se na estratégia do Laboratório de Sistemas Autónomos (LSA) na pesquisa e desenvolvimento de sistemas sensoriais que possibilitem o aumento da capacidade de percepção das plataformas robóticas. O desenvolvimento de um sistema de modelização tridimensional visa acrescentar aos projectos LINCE (Land INtelligent Cooperative Explorer) e TIGRE (Terrestrial Intelligent General proposed Robot Explorer) maior autonomia e capacidade de exploração e mapeamento. Apresentamos alguns sensores utilizados para a aquisição de modelos tridimensionais, bem como alguns dos métodos mais utilizados para o processo de mapeamento, e a sua aplicação em plataformas robóticas. Ao longo desta dissertação são apresentadas e validadas técnicas que permitem a obtenção de modelos tridimensionais. É abordado o problema de analisar a cor e geometria dos objectos, e da criação de modelos realistas que os representam. Desenvolvemos um sistema que nos permite a obtenção de dados volumétricos tridimensionais, a partir de múltiplas leituras de um Laser Range Finder bidimensional de médio alcance. Aos conjuntos de dados resultantes associamos numa nuvem de pontos coerente e referenciada. Foram desenvolvidas e implementadas técnicas de segmentação que permitem inspeccionar uma nuvem de pontos e classifica-la quanto às suas características geométricas, bem como ao tipo de estruturas que representem. São apresentadas algumas técnicas para a criação de Mapas de Elevação Digital, tendo sido desenvolvida um novo método que tira partido da segmentação efectuada

Referenciais de segurança alimentar: estudo comparativo

Perante a crescente preocupação dos consumidores, cada vez mais exigentes com os produtos e serviços que lhes são fornecidos, têm-se evidenciado esforços no sentido da aplicação prática e coordenada de uma abordagem global e integrada da segurança alimentar com o objectivo de melhorar as normas da qualidade e reforçar os sistemas de controlo em toda a cadeia alimentar, desde a exploração agrícola até ao consumidor final. Os referenciais normativos de segurança alimentar especificam os requisitos de um Sistema de Gestão da Segurança Alimentar, para organizações da cadeia de fornecimento de produtos alimentares, que pretendam demonstrar a sua aptidão para fornecer produtos seguros e o cumprimento de requisitos legais, regulamentares e de qualidade exigidos. Ao longo dos anos, diversos referenciais normativos, baseados na metodologia HACCP, foram desenvolvidos e publicados, por vários países e determinados sectores da cadeia alimentar. Perante a diversidade de referenciais existentes, cada vez mais, as organizações se questionam sobre qual o referencial de segurança alimentar a implementar. Nesta dissertação, dá-se uma contribuição no sentido da sistematização dos requisitos dos referenciais de segurança alimentar com o objectivo de suportar a respectiva comparação nomeadamente o IFS – Food, o BRC – Food, a FSSC 22000 e, de forma indirecta, a ISO 22000. Tal deve-se à necessidade de identificar o(s) referenciais de segurança alimentar a implementar numa dada organização pertencente a um dado sector de actividade. Finalmente, procede-se à realização de um estudo sobre a representatividade, número de empresas certificadas, dos referenciais em análise no mercado Nacional, Europeu e Internacional. Como conclusão genérica, é possível afirmar que, embora ao nível dos requisitos existam diferenças entre os referenciais em análise, também se verificam muitas semelhanças. Prova disso é o reconhecimento por parte da GFSI de vários destes referenciais Quanto à representatividade, verifica-se uma tendência de predomínio de determinados referenciais nos países onde foram desenvolvidos, e nos países com os quais mantêm relações comerciais mais fortes. Refere-se o Reino Unido para a BRC, e a Alemanha e França para a IFS. De salientar a importante contribuição da GFSI que, através do reconhecimento aos diversos referenciais de segurança alimentar, realizado por uma painel de especialistas e representantes de diversos sectores (industria, distribuição e serviços) está a contribuir para a respectiva harmonização e reconhecimento mundial.

Fractional dynamics of genetic algorithms using hexagonal space tessellation

The paper formulates a genetic algorithm that evolves two types of objects in a plane. The fitness function promotes a relationship between the objects that is optimal when some kind of interface between them occurs. Furthermore, the algorithm adopts an hexagonal tessellation of the two-dimensional space for promoting an efficient method of the neighbour modelling. The genetic algorithm produces special patterns with resemblances to those revealed in percolation phenomena or in the symbiosis found in lichens. Besides the analysis of the spacial layout, a modelling of the time evolution is performed by adopting a distance measure and the modelling in the Fourier domain in the perspective of fractional calculus. The results reveal a consistent, and easy to interpret, set of model parameters for distinct operating conditions.

Impostos diferidos: uma análise à sua contabilização mediante a dimensão das empresas

Dissertação de Mestrado Apresentado ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do grau de Mestre em Contabilidade e Finanças, sob a orientação de: Orientador: Doutor José Campos Amorim Coorientadora: Doutora Albertina Paula Monteiro

Using data mining techniques to support breast cancer diagnosis

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.

MicroRNA-375 plays a dual role in prostate carcinogenesis

Background: Prostate cancer (PCa), a highly incident and heterogeneous malignancy, mostly affects men from developed countries. Increased knowledge of the biological mechanisms underlying PCa onset and progression are critical for improved clinical management. MicroRNAs (miRNAs) deregulation is common in human cancers, and understanding how it impacts in PCa is of major importance. MiRNAs are mostly downregulated in cancer, although some are overexpressed, playing a critical role in tumor initiation and progression. We aimed to identify miRNAs overexpressed in PCa and subsequently determine its impact in tumorigenesis. Results: MicroRNA expression profiling in primary PCa and morphological normal prostate (MNPT) tissues identified 17 miRNAs significantly overexpressed in PCa. Expression of three miRNAs, not previously associated with PCa, was subsequently assessed in large independent sets of primary tumors, in which miR-182 and miR-375 were validated, but not miR-32. Significantly higher expression levels of miR-375 were depicted in patients with higher Gleason score and more advanced pathological stage, as well as with regional lymph nodes metastases. Forced expression of miR-375 in PC-3 cells, which display the lowest miR-375 levels among PCa cell lines, increased apoptosis and reduced invasion ability and cell viability. Intriguingly, in 22Rv1 cells, which displayed the highest miR-375 expression, knockdown experiments also attenuated the malignant phenotype. Gene ontology analysis implicated miR-375 in several key pathways deregulated in PCa, including cell cycle and cell differentiation. Moreover, CCND2 was identified as putative miR-375 target in PCa, confirmed by luciferase assay. Conclusions: A dual role for miR-375 in prostate cancer progression is suggested, highlighting the importance of cellular context on microRNA targeting.