Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

A simple and effective inverse projection scheme for void distribution control in topology optimization

The ability to control both the minimum size of holes and the minimum size of structural members are essential requirements in the topology optimization design process for manufacturing. This paper addresses both requirements by means of a unified approach involving mesh-independent projection techniques. An inverse projection is developed to control the minimum hole size while a standard direct projection scheme is used to control the minimum length of structural members. In addition, a heuristic scheme combining both contrasting requirements simultaneously is discussed. Two topology optimization implementations are contributed: one in which the projection (either inverse or direct) is used at each iteration; and the other in which a two-phase scheme is explored. In the first phase, the compliance minimization is carried out without any projection until convergence. In the second phase, the chosen projection scheme is applied iteratively until a solution is obtained while satisfying either the minimum member size or minimum hole size. Examples demonstrate the various features of the projection-based techniques presented.

Methylation patterns revealed by MSAP profiling in genetically stable somatic embryogenic cultures of Ocotea catharinensis (Lauraceae)

Ocotea catharinensis is a rare tree species indigenous to the Atlantic rainforest of South America. In spite of its value as a hardwood species, it is in danger of extinction. The species erratically produces seeds showing irregular flowering and slow growth. Therefore, plants are not easily replaced. Tissue culture-based techniques are commonly used for obtaining living material for tree propagation and in vitro preservation. Therefore, a high-frequency somatic embryogenic system was developed for the species. In the present work, the genetic fidelity of cell aggregates and somatic embryos at various stages of in vitro development of O. catharinensis was investigated using RAPD and AFLP markers. Both analyses confirmed the absence of genetic variation in all developmental stages of O. catharinensis embryogenic cultures, verifying that the in vitro system is genetically stable. The cultures were also analyzed for their methylation profiles at 5`-CCGG-3` sites by identifying methylation-sensitive amplification polymorphisms. Some of these markers differentiated cell aggregates from embryo bodies. The sequencing of ten MSAP markers revealed that four sequences showed significant similarity to genes encoding plant proteins. Particularly, the predicted amino acid sequence of the fragment designated as OcEaggHMttc155 was similar to the enzyme 1-aminocyclopropane-1-carboxylate oxidase (ACO), which is involved in the biosynthesis of ethylene, and its expression was reported to occur from the beginning to the intermediate stages of plant embryo development. Here, we suggest that this enzyme is possibly involved in the control of the earliest stages of somatic embryogenesis of O. catharinensis, and an approach to study ACO expression during somatic embryogenesis is proposed.

Frequency of concurrent autoimmune disorders in patients with autoimmune hepatitis - Effect of age, gender, and genetic background

Background: Concurrent autoimmune disorders (CAIDs) have been shown to occur in 22% to 34% of the patients with autoimmune hepatitis (AIH). Their presence has been linked to female gender, older age, and to certain HLA antigens, namely HLA-A11. DRB1*04, and DRB4*01. Aims: To assess the frequency and nature of CAID in Brazilian patients with AIH types 1 (AIH-1) and 2 (AIH-2) and to investigate the influence of age, gender, and genetic background in their occurrence. Patients and Methods: The presence and nature of CAID was studied in 143 patients [117 females, median age 11 (1.3 to 69)] with AIH-1 (n = 125) and AIH-2 (n = 28). HLA typing and tumor necrosis factor a gene promoter and exon I cytotoxic T lymphocyte associated antigen 4 (CTLA-4) gene polymorphisms were determined by polymerase chain reaction-based techniques. Results: The frequency of CAID was similar in patients with AIH-1 (14%) and AIH-2 (18%), but their nature was shown to vary. Arthritis was seen in half of the patients (n = 8) with CAID and AIH-1 and in none of those with AIH-2. Subjects with AIH-1 and CAID were shown to be older [24 (1.3 to 6 1) vs. 11 (1.3 to 69) y P = 0.02] and to have more often circulating antinuclear antibody (76% vs. 40%, P = 0.008) and less frequently antiactin antibodies (33% vs. 75%, P = 0.008) when compared with their counterparts without CAID. No particular HLA-DR and DQ alleles, as well as tumor necrosis factor a and CTLA-4 genotypes, were associated with CAID. Conclusions: The nature, but not the frequency, of CAID was shown to vary in AIH-1 and AIH-2. In subjects with AIH-1, CAID was linked to older subjects and to the presence of antinuclear antibody. No predisposition to CAID was associated to HLA-DRB1*04 or DDB4*01 alleles. The observed lower frequency of CAID could be attributed to the lower age of disease onset in Brazilians and to differences in HLA-encoded susceptibility to AIH-1 observed in South America.

Specification, refinement and verification of concurrent systems - An integration of Object-Z and CSP

This paper presents a method of formally specifying, refining and verifying concurrent systems which uses the object-oriented state-based specification language Object-Z together with the process algebra CSP. Object-Z provides a convenient way of modelling complex data structures needed to define the component processes of such systems, and CSP enables the concise specification of process interactions. The basis of the integration is a semantics of Object-Z classes identical to that of CSP processes. This allows classes specified in Object-Z to he used directly within the CSP part of the specification. In addition to specification, we also discuss refinement and verification in this model. The common semantic basis enables a unified method of refinement to be used, based upon CSP refinement. To enable state-based techniques to be used fur the Object-Z components of a specification we develop state-based refinement relations which are sound and complete with respect to CSP refinement. In addition, a verification method for static and dynamic properties is presented. The method allows us to verify properties of the CSP system specification in terms of its component Object-Z classes by using the laws of the the CSP operators together with the logic for Object-Z.

The anammox case - A new experimental manifesto for microbiological eco-physiology

The anaerobic ammonium oxidation process is a new process for ammonia removal from wastewater. It is also a new microbial physiology that was previously believed to be impossible. The identification of Candidatus Brocadia anammoxidans and its relatives as the responsible bacteria was only possible with the development of a new experimental approach. That approach is the focus of this paper. The approach is a modernisation of the Winogradsky/Beyerinck strategy of selective enrichment and is based on the introduction of the molecular toolbox and modern bioreactor engineering to microbial ecology. It consists of five steps: (1) postulation of an ecological niche based on thermodynamic considerations and macro-ecological field data; (2) engineering of this niche into a laboratory bioreactor for enrichment culture; (3) black-box physiological characterisation of the enrichment culture as a whole; (4) phylogenetic characterisation of the enriched community using molecular tools; (5) physical separation of the dominant members of the enrichment culture using gradient centrifugation and the identification of the species of interest in accordance with Koch's postulates; (6) verification of the in situ importance of these species in the actual ecosystems. The power of this approach is illustrated with a case study: the identification of the planctomycetes responsible for anaerobic ammonium oxidation. We argue that this was impossible using molecular ecology or conventional 'cultivation based techniques' alone. We suggest that the approach might also be used for the microbiological study of many interesting microbes such as anaerobic methane oxidisers.

Rastreio neonatal dos défices do ciclo da ureia em Portugal

Os défices do ciclo da ureia são um grupo de doenças hereditárias do metabolismo caracterizadas fundamentalmente por uma acumulação de amónia. Clinicamente o espectro é muito alargado, com formas de apresentação no período neonatal até situações mais moderadas de apresentação tardia em adultos. O tratamento é fundamentalmente de base nutricional e traduz-se numa redução significativa da mortalidade e morbilidade. Com a introdução da espectrometria de massa nos laboratórios de rastreio neonatal em meados dos anos 90, passou a ser possível quantificar alguns intermediários do ciclo, o que associado à existência de um intervalo livre e um tratamento eficaz, permitiu o rastreio de algumas das doenças deste grupo. Em 2004 iniciou-se em Portugal o rastreio dos défices do ciclo da ureia, tendo-se rastreado até ao presente, 988 687 recém-nascidos e identificado 19 casos positivos. Recentes desenvolvimentos técnicos vieram possibilitar a quantificação de novos marcadores, mais concretamente do ácido orótico, o que abre a possibilidade de rastrear o défice em ornitina transcarbamilase, o défice do ciclo da ureia mais frequente. Os autores apresentam a situação atual do rastreio dos défices do ciclo da ureia e as perspetivas em virtude dos novos desenvolvimentos técnicos.

Fungal and microbial volatile organic compounds exposure assessment in a waste sorting plant

In the management of solid waste, pollutants over a wide range are released with different routes of exposure for workers. The potential for synergism among the pollutants raises concerns about potential adverse health effects, and there are still many uncertainties involved in exposure assessment. In this study, conventional (culture-based) and molecular real-time polymerase chain reaction (RTPCR) methodologies were used to assess fungal air contamination in a waste-sorting plant which focused on the presence of three potential pathogenic/toxigenic fungal species: Aspergillus flavus, A. fumigatus, and Stachybotrys chartarum. In addition, microbial volatile organic compounds (MVOC) were measured by photoionization detection. For all analysis, samplings were performed at five different workstations inside the facilities and also outdoors as a reference. Penicillium sp. were the most common species found at all plant locations. Pathogenic/toxigenic species (A. fumigatus and S. chartarum) were detected at two different workstations by RTPCR but not by culture-based techniques. MVOC concentration indoors ranged between 0 and 8.9 ppm (average 5.3 ± 3.16 ppm). Our results illustrated the advantage of combining both conventional and molecular methodologies in fungal exposure assessment. Together with MVOC analyses in indoor air, data obtained allow for a more precise evaluation of potential health risks associated with bioaerosol exposure. Consequently, with this knowledge, strategies may be developed for effective protection of the workers.

Direct multisearch for multiobjective optimization

In practical applications of optimization it is common to have several conflicting objective functions to optimize. Frequently, these functions are subject to noise or can be of black-box type, preventing the use of derivative-based techniques. We propose a novel multiobjective derivative-free methodology, calling it direct multisearch (DMS), which does not aggregate any of the objective functions. Our framework is inspired by the search/poll paradigm of direct-search methods of directional type and uses the concept of Pareto dominance to maintain a list of nondominated points (from which the new iterates or poll centers are chosen). The aim of our method is to generate as many points in the Pareto front as possible from the polling procedure itself, while keeping the whole framework general enough to accommodate other disseminating strategies, in particular, when using the (here also) optional search step. DMS generalizes to multiobjective optimization (MOO) all direct-search methods of directional type. We prove under the common assumptions used in direct search for single objective optimization that at least one limit point of the sequence of iterates generated by DMS lies in (a stationary form of) the Pareto front. However, extensive computational experience has shown that our methodology has an impressive capability of generating the whole Pareto front, even without using a search step. Two by-products of this paper are (i) the development of a collection of test problems for MOO and (ii) the extension of performance and data profiles to MOO, allowing a comparison of several solvers on a large set of test problems, in terms of their efficiency and robustness to determine Pareto fronts.

Multiple sequence alignment correction using constraints

Trabalho apresentado no âmbito do European Master in Computational Logics, como requisito parcial para obtenção do grau de Mestre em Computational Logics

New analytical methodologies for doping control – detection of anabolic androgenic steroids in human urine

Dissertation submitted to Faculdade de Ciências e Tecnologia - Universidade Nova de Lisboa in fulfilment of the requirements for the degree of Doctor of Philosophy (Biochemistry - Biotechnology)

Automatic syllabification for danish text-to-speech systems

In this paper, a rule-based automatic syllabifier for Danish is described using the Maximal Onset Principle. Prior success rates of rule-based methods applied to Portuguese and Catalan syllabification modules were on the basis of this work. The system was implemented and tested using a very small set of rules. The results gave rise to 96.9% and 98.7% of word accuracy rate, contrary to our initial expectations, being Danish a language with a complex syllabic structure and thus difficult to be rule-driven. Comparison with data-driven syllabification system using artificial neural networks showed a higher accuracy rate of the former system.

Gold nanoprobes for assessing expression of critical genes in the infection pathway of MRSA

Staphylococcus aureus is an important opportunistic pathogen that can cause a wide variety of diseases from mild to life-threatening conditions. S. aureus can colonize many parts of the human body but the anterior nares are the primary ecological niche. Its clinical importance is due to its ability to resist almost all classes of antibiotics available together with its large number of virulence factores. MRSA (Methicillin-Resistant S. aureus) strains are particularly important in the hospital settings, being the major cause of nosocomial infections worldwide. MRSA resistance to β-lactam antibiotics involves the acquisition of the exogenous mecA gene, part of the SCCmec cassette. Fast and reliable diagnostic techniques are needed to reduce the mortality and morbidity associated with MRSA infections, through the early identification of MRSA strains. The current identification techniques are time-consuming as they usually involves culturing steps, taking up to five days to determine the antibiotic resistance profile. Several amplification-based techniques have been developed to accelerate the diagnosis. The aim of this project was to develop an even faster methodology that bypasses the DNA amplification step. Gold-nanoprobes were developed and used to detect the presence of mecA gene in S. aureus genome, associated with resistance traits, for colorimetric assays based on non-crosslinking method. Our results showed that the mecA and mecA_V2 gold-nanoprobes were sensitive enough to discriminate the presence of mecA gene in PCR products and genomic DNA (gDNA) samples for target concentrations of 10 ng/μL and 20 ng/μL, respectively. As our main objective was to avoid the amplification step, we concluded that the best strategy for the early identification of MRSA infection relies on colorimetric assays based on non-crosslinking method with gDNA samples that can be extracted directly from blood samples.

Combining data mining and evolutionary computation for multi-criteria optimization of earthworks

Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.

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The use of the Internet now has a specific purpose: to find information. Unfortunately, the amount of data available on the Internet is growing exponentially, creating what can be considered a nearly infinite and ever-evolving network with no discernable structure. This rapid growth has raised the question of how to find the most relevant information. Many different techniques have been introduced to address the information overload, including search engines, Semantic Web, and recommender systems, among others. Recommender systems are computer-based techniques that are used to reduce information overload and recommend products likely to interest a user when given some information about the user's profile. This technique is mainly used in e-Commerce to suggest items that fit a customer's purchasing tendencies. The use of recommender systems for e-Government is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on e-Government services. More specifically, e-Democracy aims to increase citizens' participation in democratic processes through the use of information and communication technologies. In this chapter, an architecture of a recommender system that uses fuzzy clustering methods for e-Elections is introduced. In addition, a comparison with the smartvote system, a Web-based Voting Assistance Application (VAA) used to aid voters in finding the party or candidate that is most in line with their preferences, is presented.