Genetic divergence in cocoa progenies for backcrossing program to witches' broom disease resistance

Backcrossing has been little used in cacao breeding, particularly due to the long time required to transfer genes and recover the genetic background of the recurrent parent. The objective of this study was to select individuals, resulting from the backcross CEPEC-42 x SIC-19, genetically related to the recurrent parent SIC-19 by using RAPD molecular markers, among those with resistance to witches' broom. Of the 31 plants that clustered with SIC-19, 18 from the replanted material remained free of the disease in the field, with good vegetative aspect and, therefore can be used for backcross to reach the desired objective.

Prediction of genetic gain from selection indices for disease resistance in papaya hybrids

In order to select superior hybrids for the concentration of favorable alleles for resistance to papaya black spot, powdery mildew and phoma spot, 67 hybrids were evaluated in two seasons, in 2007, in a randomized block design with two replications. Genetic gains were estimated from the selection indices of Smith & Hazel, Pesek & Baker, Williams, Mulamba & Mock, with selection intensity of 22.39%, corresponding to 15 hybrids. The index of Mulamba & Mock showed gains more suitable for the five traits assessed when it was used the criterion of economic weight tentatively assigned. Together, severity of black spot on leaves and on fruits, characteristics considered most relevant to the selection of resistant materials, expressed percentage gain of -44.15%. In addition, there were gains for other characteristics, with negative predicted selective percentage gain. The results showed that the index of Mulamba & Mock is the most efficient procedure for simultaneous selection of papaya hybrid resistant to black spot, powdery mildew and phoma spot.

Genetic diversity in sugar apple (Annona squamosa L.) by using RAPD markers

Genetic diversity in a collection of 64 sugar apple accessions collected from different municipalities in northern Minas Gerais was assessed by RAPD analysis. Using 20 selected RAPD primers 167 fragments were generated, of which 48 were polymorphic (28.7%) producing an average of 2.4 polymorphic fragments per primer. Low percentage of polymorphism (< 29%) was observed by using the set of primers indicating low level of genetic variation among the 64 accessions evaluated. Genetic relationships were estimated using Jaccard's coefficient of similarity. Accessions from different municipalities clustered together indicating no correlation between molecular grouping and geographical origin. The dendrogram revealed five clusters. The first cluster grouped C19 and G29 accessions collected from the municipalities of Verdelândia and Monte Azul, respectively. The second cluster grouped G16 and B11 accessions collected from the municipalities of Monte Azul and Coração de Jesus, respectively. The remaining accessions were grouped in three clusters, with 8, 15 and 37 accessions, respectively. In summary, RAPD showed a low percentage of polymorphism in the germplasm collection.

Genetic divergence of tomato subsamples

Understanding the genetic variability of a species is crucial for the progress of a genetic breeding program and requires characterization and evaluation of germplasm. This study aimed to characterize and evaluate 101 tomato subsamples of the Salad group (fresh market) and two commercial controls, one of the Salad group (cv. Fanny) and another of the Santa Cruz group (cv. Santa Clara). Four experiments were conducted in a randomized block design with three replications and five plants per plot. The joint analysis of variance was performed and characteristics with significant complex interaction between control and experiment were excluded. Subsequently, the multicollinearity diagnostic test was carried out and characteristics that contributed to severe multicollinearity were excluded. The relative importance of each characteristics for genetic divergence was calculated by the Singh's method (Singh, 1981), and the less important ones were excluded according to Garcia (1998). Results showed large genetic divergence among the subsamples for morphological, agronomic and organoleptic characteristics, indicating potential for genetic improvement. The characteristics total soluble solids, mean number of good fruits per plant, endocarp thickness, mean mass of marketable fruit per plant, total acidity, mean number of unmarketable fruit per plant, internode diameter, internode length, main stem thickness and leaf width contributed little to the genetic divergence between the subsamples and may be excluded in future studies.

Genetic Jacobinism in the republic of choice

Revista de Filosofia da Unidade de Investigação em Ciência, Tecnologia e Sociedade da Universidade Lusófona

Occupational exposure to environmental tobacco smoke in hospitality venues: are genetic- or proteomics-based biomarkers predictive of respiratory diseases?

Environmental tobacco smoke (ETS) is recognized as an occupational hazard in the hospitality industry. Although Portuguese legislation banned smoking in most indoor public spaces, it is still allowed in some restaurants/bars, representing a potential risk to the workers’ health, particularly for chronic respiratory diseases. The aims of this work were to characterize biomarkers of early genetic effects and to disclose proteomic signatures associated to occupational exposure to ETS and with potential to predict respiratory diseases development. A detailed lifestyle survey and clinical evaluation (including spirometry) were performed in 81 workers from Lisbon restaurants. ETS exposure was assessed through the level of PM 2.5 in indoor air and the urinary level of cotinine. The plasma samples were immunodepleted and analysed by 2D-SDSPAGE followed by in-gel digestion and LC-MS/MS. DNA lesions and chromosome damage were analysed innlymphocytes and in exfoliated buccal cells from 19 cigarette smokers, 29 involuntary smokers, and 33 non-smokers not exposed to tobacco smoke. Also, the DNA repair capacity was evaluated using an ex vivo challenge comet assay with an alkylating agent (EMS). All workers were considered healthy and recorded normal lung function. Interestingly, following 2D-DIGE-MS (MALDI-TOF/TOF), 61 plasma proteins were found differentially expressed in ETS-exposed subjects, including 38 involved in metabolism, acute-phase respiratory inflammation, and immune or vascular functions. On the other hand, the involuntary smokers showed neither an increased level of DNA/chromosome damage on lymphocytes nor an increased number of micronuclei in buccal cells, when compared to non-exposed non-smokers. Noteworthy, lymphocytes challenge with EMS resulted in a significantly lower level of DNA breaks in ETS-exposed as compared to non-exposed workers (P<0.0001) suggestive of an adaptive response elicited by the previous exposure to low levels of ETS. Overall, changes in proteome may be promising early biomarkers of exposure to ETS. Likewise, alterations of the DNA repair competence observed upon ETS exposure deserves to be further understood. Work supported by Fundação Calouste Gulbenkian, ACSS and FCT/Polyannual Funding Program.

Determinação de autoanticorpos em doentes com suspeita de hepatite autoimune e cirrose biliar primária

O diagnóstico de doença hepática autoimune em doentes com patologia hepática implica a exclusão de outras causas de lesão hepática como vírica, alcoólica, tóxica, devido a alterações genéticas ou metabólicas, esteatose hepática não alcoólica e uma criteriosa avaliação de dados clínicos, bioquímicos, histológicos e colangiográficos especificas destas patologias (Invernizzi et al 2007) O diagnóstico e tratamento precoces destas patologias são fundamentais para a prevenção da alta morbilidade e mortalidade associada a estes doentes. O despiste de patologia hepática autoimune assenta na utilização de testes serológicos para a deteção de autoanticorpos associados a estas patologias. O conhecimento destes testes e a interpretação dos resultados obtidos revelam-se fundamentais para o diagnóstico ou exclusão destas doenças (Beuers 2005). Deste modo, foi objetivo deste trabalho a pesquisa e identificação de autoanticorpos em uso clínico: ANA, AMA, AML, ANCA, Anti-SLA/LP, anti-LKM, anti-LC1 e anti-actina F, em doentes com suspeita de HAI e CBP em que foi excluída causa vírica, alcoólica e tóxica. O trabalho incidiu particularmente na comparação dos resultados do perfil de autoanticorpos de pedidos feitos ao exterior com os resultados obtidos recorrendo à utilização de um novo kit de imunoblot, e assim determinar a relevância da introdução da pesquisa dos novos autoanticorpos e avaliar a relação custo/benefício da implementação do kit BlueDot liver da D-tek® na rotina laboratorial do serviço de Patologia Clínica do Hospital Pedro Hispano. Os resultados encontrados foram de 100% de concordância entre os métodos de imunofluorescência indireta e imunoblot, e Elisa e Imunoblot. Deste modo seria uma boa estratégia a implementação desta última técnica na rotina laboratorial uma vez que proporciona uma rápida disponibilização dos resultados para o clínico, antecipando desta forma o diagnóstico e o início rápido do tratamento em benefício do doente. Por outro lado, quando analisámos a relação custo/beneficio, seria vantajosa a implementação desta técnica uma vez que o laboratório dispõe de capacidade técnica, e o custo de aquisição do kit não excede o valor praticado atualmente correspondendo a uma poupança de 51%.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Optimal dispatch with reactive power compensation by Genetic Algorithm

This paper presents a Unit Commitment model with reactive power compensation that has been solved by Genetic Algorithm (GA) optimization techniques. The GA has been developed a computational tools programmed/coded in MATLAB. The main objective is to find the best generations scheduling whose active power losses are minimal and the reactive power to be compensated, subjected to the power system technical constraints. Those are: full AC power flow equations, active and reactive power generation constraints. All constraints that have been represented in the objective function are weighted with a penalty factors. The IEEE 14-bus system has been used as test case to demonstrate the effectiveness of the proposed algorithm. Results and conclusions are dully drawn.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Modern cancer epidemiological research: genetic polymorphisms and environment

Individual cancer susceptibility seems to be related to factors such as changes in oncogenes and tumor suppressor genes expression, and differences in the action of metabolic enzymes and DNA repair regulated by specific genes. Epidemiological studies on genetic polymorphisms of human xenobiotics metabolizing enzymes and cancer have revealed low relative risks. Research considering genetic polymorphisms prevalence jointly with environmental exposures could be relevant for a better understanding of cancer etiology and the mechanisms of carcinogenesis and also for new insights on cancer prognosis. This study reviews the approaches of molecular epidemiology in cancer research, stressing case-control and cohort designs involving genetic polymorphisms, and factors that could introduce bias and confounding in these studies. Similarly to classical epidemiological research, genetic polymorphisms requires considering aspects of precision and accuracy in the study design.