Highly parallel genetic approaches in Mendelian and complex diseases

The recent advance in high-throughput sequencing and genotyping protocols allows rapid investigation of Mendelian and complex diseases on a scale not previously been possible. In my thesis research I took advantage of these modern techniques to study retinitis pigmentosa (RP), a rare inherited disease characterized by progressive loss of photoreceptors and leading to blindness; and hypertension, a common condition affecting 30% of the adult population. Firstly, I compared the performance of different next generation sequencing (NGS) platforms in the sequencing of the RP-linked gene PRPF31. The gene contained a mutation in an intronic repetitive element, which presented difficulties for both classic sequencing methods and NGS. We showed that all NGS platforms are powerful tools to identify rare and common DNA variants, also in case of more complex sequences. Moreover, we evaluated the features of different NGS platforms that are important in re-sequencing projects. The main focus of my thesis was then to investigate the involvement of pre-mRNA splicing factors in autosomal dominant RP (adRP). I screened 5 candidate genes in a large cohort of patients by using long-range PCR as enrichment step, followed by NGS. We tested two different approaches: in one, all target PCRs from all patients were pooled and sequenced as a single DNA library; in the other, PCRs from each patient were separated within the pool by DNA barcodes. The first solution was more cost-effective, while the second one allowed obtaining faster and more accurate results, but overall they both proved to be effective strategies for gene screenings in many samples. We could in fact identify novel missense mutations in the SNRNP200 gene, encoding an essential RNA helicase for splicing catalysis. Interestingly, one of these mutations showed incomplete penetrance in one family with adRP. Thus, we started to study the possible molecular causes underlying phenotypic differences between asymptomatic and affected members of this family. For the study of hypertension, I joined a European consortium to perform genome-wide association studies (GWAS). Thanks to the use of very informative genotyping arrays and of phenotipically well-characterized cohorts, we could identify a novel susceptibility locus for hypertension in the promoter region of the endothelial nitric oxide synthase gene (NOS3). Moreover, we have proven the direct causality of the associated SNP using three different methods: 1) targeted resequencing, 2) luciferase assay, and 3) population study. - Le récent progrès dans le Séquençage à haut Débit et les protocoles de génotypage a permis une plus vaste et rapide étude des maladies mendéliennes et multifactorielles à une échelle encore jamais atteinte. Durant ma thèse de recherche, j'ai utilisé ces nouvelles techniques de séquençage afin d'étudier la retinite pigmentale (RP), une maladie héréditaire rare caractérisée par une perte progressive des photorécepteurs de l'oeil qui entraine la cécité; et l'hypertension, une maladie commune touchant 30% de la population adulte. Tout d'abord, j'ai effectué une comparaison des performances de différentes plateformes de séquençage NGS (Next Generation Sequencing) lors du séquençage de PRPF31, un gène lié à RP. Ce gène contenait une mutation dans un élément répétable intronique, qui présentait des difficultés de séquençage avec la méthode classique et les NGS. Nous avons montré que les plateformes de NGS analysées sont des outils très puissants pour identifier des variations de l'ADN rares ou communes et aussi dans le cas de séquences complexes. De plus, nous avons exploré les caractéristiques des différentes plateformes NGS qui sont importantes dans les projets de re-séquençage. L'objectif principal de ma thèse a été ensuite d'examiner l'effet des facteurs d'épissage de pre-ARNm dans une forme autosomale dominante de RP (adRP). Un screening de 5 gènes candidats issus d'une large cohorte de patients a été effectué en utilisant la long-range PCR comme étape d'enrichissement, suivie par séquençage avec NGS. Nous avons testé deux approches différentes : dans la première, toutes les cibles PCRs de tous les patients ont été regroupées et séquencées comme une bibliothèque d'ADN unique; dans la seconde, les PCRs de chaque patient ont été séparées par code barres d'ADN. La première solution a été la plus économique, tandis que la seconde a permis d'obtenir des résultats plus rapides et précis. Dans l'ensemble, ces deux stratégies se sont démontrées efficaces pour le screening de gènes issus de divers échantillons. Nous avons pu identifier des nouvelles mutations faux-sens dans le gène SNRNP200, une hélicase ayant une fonction essentielle dans l'épissage. Il est intéressant de noter qu'une des ces mutations montre une pénétrance incomplète dans une famille atteinte d'adRP. Ainsi, nous avons commencé une étude sur les causes moléculaires entrainant des différences phénotypiques entre membres affectés et asymptomatiques de cette famille. Lors de l'étude de l'hypertension, j'ai rejoint un consortium européen pour réaliser une étude d'association Pangénomique ou genome-wide association study Grâce à l'utilisation de tableaux de génotypage très informatifs et de cohortes extrêmement bien caractérisées au niveau phénotypique, un nouveau locus lié à l'hypertension a été identifié dans la région promotrice du gène endothélial nitric oxide sinthase (NOS3). Par ailleurs, nous avons prouvé la cause directe du SNP associé au moyen de trois méthodes différentes: i) en reséquençant la cible avec NGS, ii) avec des essais à la luciférase et iii) une étude de population.

Integrative Review: Concepts And Methods Used In Nursing


Integrative review (IR) has an international reputation in nursing research and evidence-based practice. This IR aimed at identifying and analyzing the concepts and methods recommended to undertaking IR in nursing. Nine information resources,including electronic databases and grey literature were searched. Seventeen studies were included. The results indicate that: primary studies were mostly from USA; it is possible to have several research questions or hypotheses and include primary studies in the review from different theoretical and methodological approaches; it is a type of review that can go beyond the analysis and synthesis of findings from primary studies allowing exploiting other research dimensions, and that presents potentialities for the development of new theories and new problems for research. Conclusion: IR is understood as a very complex type of review and it is expected to be developed using standardized and systematic methods to ensure the required rigor of scientific research and therefore the legitimacy of the established evidence.


Towards increased productivity and quality in software development using agile, lean and collaborative approaches

Dagens programvaruindustri står inför alltmer komplicerade utmaningar i en värld där programvara är nästan allstädes närvarande i våra dagliga liv. Konsumenten vill ha produkter som är pålitliga, innovativa och rika i funktionalitet, men samtidigt också förmånliga. Utmaningen för oss inom IT-industrin är att skapa mer komplexa, innovativa lösningar till en lägre kostnad. Detta är en av orsakerna till att processförbättring som forskningsområde inte har minskat i betydelse. IT-proffs ställer sig frågan: “Hur håller vi våra löften till våra kunder, samtidigt som vi minimerar vår risk och ökar vår kvalitet och produktivitet?” Inom processförbättringsområdet finns det olika tillvägagångssätt. Traditionella processförbättringsmetoder för programvara som CMMI och SPICE fokuserar på kvalitets- och riskaspekten hos förbättringsprocessen. Mer lättviktiga metoder som t.ex. lättrörliga metoder (agile methods) och Lean-metoder fokuserar på att hålla löften och förbättra produktiviteten genom att minimera slöseri inom utvecklingsprocessen. Forskningen som presenteras i denna avhandling utfördes med ett specifikt mål framför ögonen: att förbättra kostnadseffektiviteten i arbetsmetoderna utan att kompromissa med kvaliteten. Den utmaningen attackerades från tre olika vinklar. För det första förbättras arbetsmetoderna genom att man introducerar lättrörliga metoder. För det andra bibehålls kvaliteten genom att man använder mätmetoder på produktnivå. För det tredje förbättras kunskapsspridningen inom stora företag genom metoder som sätter samarbete i centrum. Rörelsen bakom lättrörliga arbetsmetoder växte fram under 90-talet som en reaktion på de orealistiska krav som den tidigare förhärskande vattenfallsmetoden ställde på IT-branschen. Programutveckling är en kreativ process och skiljer sig från annan industri i det att den största delen av det dagliga arbetet går ut på att skapa något nytt som inte har funnits tidigare. Varje programutvecklare måste vara expert på sitt område och använder en stor del av sin arbetsdag till att skapa lösningar på problem som hon aldrig tidigare har löst. Trots att detta har varit ett välkänt faktum redan i många decennier, styrs ändå många programvaruprojekt som om de vore produktionslinjer i fabriker. Ett av målen för rörelsen bakom lättrörliga metoder är att lyfta fram just denna diskrepans mellan programutvecklingens innersta natur och sättet på vilket programvaruprojekt styrs. Lättrörliga arbetsmetoder har visat sig fungera väl i de sammanhang de skapades för, dvs. små, samlokaliserade team som jobbar i nära samarbete med en engagerad kund. I andra sammanhang, och speciellt i stora, geografiskt utspridda företag, är det mera utmanande att införa lättrörliga metoder. Vi har nalkats utmaningen genom att införa lättrörliga metoder med hjälp av pilotprojekt. Detta har två klara fördelar. För det första kan man inkrementellt samla kunskap om metoderna och deras samverkan med sammanhanget i fråga. På så sätt kan man lättare utveckla och anpassa metoderna till de specifika krav som sammanhanget ställer. För det andra kan man lättare överbrygga motstånd mot förändring genom att introducera kulturella förändringar varsamt och genom att målgruppen får direkt förstahandskontakt med de nya metoderna. Relevanta mätmetoder för produkter kan hjälpa programvaruutvecklingsteam att förbättra sina arbetsmetoder. När det gäller team som jobbar med lättrörliga och Lean-metoder kan en bra uppsättning mätmetoder vara avgörande för beslutsfattandet när man prioriterar listan över uppgifter som ska göras. Vårt fokus har legat på att stöda lättrörliga och Lean-team med interna produktmätmetoder för beslutsstöd gällande så kallad omfaktorering, dvs. kontinuerlig kvalitetsförbättring av programmets kod och design. Det kan vara svårt att ta ett beslut att omfaktorera, speciellt för lättrörliga och Lean-team, eftersom de förväntas kunna rättfärdiga sina prioriteter i termer av affärsvärde. Vi föreslår ett sätt att mäta designkvaliteten hos system som har utvecklats med hjälp av det så kallade modelldrivna paradigmet. Vi konstruerar även ett sätt att integrera denna mätmetod i lättrörliga och Lean-arbetsmetoder. En viktig del av alla processförbättringsinitiativ är att sprida kunskap om den nya programvaruprocessen. Detta gäller oavsett hurdan process man försöker introducera – vare sig processen är plandriven eller lättrörlig. Vi föreslår att metoder som baserar sig på samarbete när processen skapas och vidareutvecklas är ett bra sätt att stöda kunskapsspridning på. Vi ger en översikt över författarverktyg för processer på marknaden med det förslaget i åtanke.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Approaches to Supply Chain Risk Management: Identification, Analysis and Control

Supply chain risk management has emerged as an increasingly important issue in logistics as disruptions in the supply chain have become critical issues for many companies. The scientific literature on the subject is developing and in many respects the understanding of it is still in its infancy. Thus, there is a need for more information in order for scholars and practitioners to understand the causalities and interrelations that characterise the phenomenon. The aim of this dissertation is to narrow this gap by exploring key aspects of supply chain risk management through two maritime supply chains in the immediate region of the Gulf of Finland. The study contributes to the field in three different ways. Firstly, it facilitates the identification of risks on different levels of the supply chain through a systematic analysis of the processes and actors, and of the cognitive barriers that limit the actors’ visibility and their understanding of the operations and the risks involved. There is a clear need to increase collaboration and information exchange in order to improve visibility in the chain. Risk management should be a collaborative effort among the individual actors, aimed at obtaining a holistic picture. Secondly, the study contributes to the literature on risk analysis through the use of systemic frameworks that illustrate the causalities and linkages in the system, thereby making it easier to perceive the vulnerabilities. Thirdly, the study enhances current knowledge of risk control in identifying actor roles, risk visibility and risk controllability as being among the key factors determining risk-management effectiveness against supply-chain vulnerability. This dissertation is divided into two parts. The first part gives a general overview of the relevant literature, the research design and the conclusions of the study, and the second part comprises six research publications. Case-study methodology with systematic combining approach is used, where in-depth interviews, questionnaires and expert panel sessions are the main data collection methods. The study illustrates the current state of risk management in multimodal maritime supply chains, and develops frameworks for further analysis. The results imply that there are major differences between organizations in their ability to execute supply chain risk management. Further collaboration should be considered in order to facilitate the development of systematic and effective management processes.

Reflexive model of research-based theatre – processing innovation at the crossroads of theatre, reflection and practice-based innovation activities

Contemporary organisations have to embrace the notion of doing ‘more with less’. This challenges knowledge production within companies and public organisations, forcing them to reorganise their structures and rethink what knowledge production actually means in the context of innovation and how knowledge is actually produced among various professional groups within the organisation in their everyday actions. Innovations are vital for organisational survival, and ‘ordinary’ employees and customers are central but too-often ignored producers of knowledge for contemporary organisations. Broader levels of participation and reflexive practices are needed. This dissertation discusses the missing links between innovation research conducted in the context of industrial management, arts, and culture; applied drama and theatre practices (specifically post-Boalian approaches); and learning – especially organising reflection – in organisational settings. This dissertation (1) explores and extends the role of research-based theatre to organising reflection and reflexive practices in the context of practice-based innovation, (2) develops a reflexive model of RBT for investigating and developing practice-based organisational process innovations in order to contribute to the development of a tool for innovation management and analysis, and (3) operationalises this model within private- and publicsector organisations. The proposed novel reflexive model of research-based theatre for investigating and developing practice-based organisational process innovations extends existing methods and offers a different way of organising reflection and reflexive practices in the context of general innovation management. The model was developed through five participatory action research processes conducted in four different organisations. The results provide learning steps – a reflection path – for understanding complex organisational life, people, and relations amid renewal and change actions. The proposed model provides a new approach to organising and cultivating reflexivity in practice-based innovation activities via research-based theatre. The results can be utilised as a guideline when processing practice-based innovation within private or public organisations. The model helps innovation managers to construct, together with their employees, temporary communities where they can learn together through reflecting on their own and each others’ experiences and to break down assumptions related to their own perspectives. The results include recommendations for practical development steps applicable in various organisations with regard to (i) application of research-based theatre and (ii) related general innovation management. The dissertation thus contributes to the development of novel learning approaches in knowledge production. Keywords: practice-based innovation, research-based theatre, learning, reflection, mode 2b knowledge production

Research framework for the connection between environmental collaboration and firm performance

This thesis focuses on collaborative activities with regard to environmental issues both within the firm and outside the firm with the key suppliers and customers, i.e. internal and external environmental collaboration. Integrating environmental thinking into supply chain management has received increasing interest in recent years. The relational view and the natural resource-based-view together suggest that environmental capabilities can be built jointly with supply chain partners and used to gain sustained competitive advantage. Several studies have been undertaken to analyse the connection between environmental activities and firm performance but most studies have taken only economic performance into account. This study pays attention also to two other dimensions of firm performance, intra-firm supply chain performance and environmental performance, and aims at presenting the linkages between them and environmental collaboration. This thesis creates a research framework for the connections between environmental collaboration and firm performance and suggests approaches to analyse these. In order to find out the key concepts and their relationship, an extensive literature review is conducted. The research framework proposes a positive connection between internal and external environmental collaboration and all three dimensions of firm performance. In addition, environmental performance and intra-firm supply chain performance are expected to contribute positively to economic performance. Hence, firms are suggested to benefit from environmental collaboration both within the firm and outside the firm. Empirical testing of the developed research framework is out of the scope of this study. However, this thesis proposes using a mixed methods research approach, including survey research and multiple case studies. Finland State of Logistics 2012 survey commissioned by the Finnish Ministry of Transport and Communications and conducted by Turku School of Economics is used as an example of data for the quantitative phase. The applicability of these two methods is discussed at a general level and with regard to analysing the research framework developed in the thesis. Future research will aim at the development of the research framework and the methods in order to confirm the connection between environmental collaboration and firm performance.

Identification of research trends in the field of separation processes. Application of epidemiological model, citation analysis, text mining, and technical analysis of the financial markets

Choice of industrial development options and the relevant allocation of the research funds become more and more difficult because of the increasing R&D costs and pressure for shorter development period. Forecast of the research progress is based on the analysis of the publications activity in the field of interest as well as on the dynamics of its change. Moreover, allocation of funds is hindered by exponential growth in the number of publications and patents. Thematic clusters become more and more difficult to identify, and their evolution hard to follow. The existing approaches of research field structuring and identification of its development are very limited. They do not identify the thematic clusters with adequate precision while the identified trends are often ambiguous. Therefore, there is a clear need to develop methods and tools, which are able to identify developing fields of research. The main objective of this Thesis is to develop tools and methods helping in the identification of the promising research topics in the field of separation processes. Two structuring methods as well as three approaches for identification of the development trends have been proposed. The proposed methods have been applied to the analysis of the research on distillation and filtration. The results show that the developed methods are universal and could be used to study of the various fields of research. The identified thematic clusters and the forecasted trends of their development have been confirmed in almost all tested cases. It proves the universality of the proposed methods. The results allow for identification of the fast-growing scientific fields as well as the topics characterized by stagnant or diminishing research activity.

Proteins and their interacting partners: an introduction to protein–ligand binding site prediction methods

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein–ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein–ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein–ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

Participatory crop improvement: the challenges of and opportunities for institutionalisation in the Indian public research sector

This thesis considers Participatory Crop Improvement (PCI) methodologies and examines the reasons behind their continued contestation and limited mainstreaming in conventional modes of crop improvement research within National Agricultural Research Systems (NARS). In particular, it traces the experiences of a long-established research network with over 20 years of experience in developing and implementing PCI methods across South Asia, and specifically considers its engagement with the Indian NARS and associated state-level agricultural research systems. In order to address the issues surrounding PCI institutionalisation processes, a novel conceptual framework was derived from a synthesis of the literatures on Strategic Niche Management (SNM) and Learning-based Development Approaches (LBDA) to analyse the socio-technical processes and structures which constitute the PCI ‘niche’ and NARS ‘regime’. In examining the niche and regime according to their socio-technical characteristics, the framework provides explanatory power for understanding the nature of their interactions and the opportunities and barriers that exist with respect to the translation of lessons and ideas between niche and regime organisations. The research shows that in trying to institutionalise PCI methods and principles within NARS in the Indian context, PCI proponents have encountered a number of constraints related to the rigid and hierarchical structure of the regime organisations; the contractual mode of most conventional research, which inhibits collaboration with a wider group of stakeholders; and the time-limited nature of PCI projects themselves, which limits investment and hinders scaling up of the innovations. It also reveals that while the niche projects may be able to induce a ‘weak’ form of PCI institutionalisation within the Indian NARS by helping to alter their institutional culture to be more supportive of participatory plant breeding approaches and future collaboration with PCI researchers, a ‘strong’ form of PCI institutionalisation, in which NARS organisations adopt participatory methodologies to address all their crop improvement agenda, is likely to remain outside of the capacity of PCI development projects to deliver.

The Brazilian Research Consortium on Obsessive-Compulsive Spectrum Disorders: recruitment, assessment instruments, methods for the development of multicenter collaborative studies and preliminary results

OBJETIVO: Descrever o recrutamento de pacientes, instrumentos de avaliação, métodos para o desenvolvimento de estudos colaborativos multicêntricos e os resultados preliminares do Consórcio Brasileiro de Pesquisa em Transtornos do Espectro Obsessivo-Compulsivo, que inclui sete centros universitários. MÉTODO: Este estudo transversal incluiu entrevistas semi-estruturadas (dados sociodemográficos, histórico médico e psiquiátrico, curso da doença e diagnósticos psiquiátricos comórbidos) e instrumentos que avaliam os sintomas do transtorno obsessivo-compulsivo (Escala para Sintomas Obsessivo-Compulsivos de Yale-Brown e Escala Dimensional para Sintomas Obsessivo-Compulsivos de Yale-Brown), sintomas depressivos (Inventário de Depressão de Beck), sintomas ansiosos (Inventário de Ansiedade de Beck), fenômenos sensoriais (Escala de Fenômenos Sensoriais da Universidade de São Paulo), juízo crítico (Escala de Avaliação de Crenças de Brown), tiques (Escala de Gravidade Global de Tiques de Yale) e qualidade de vida (questionário genérico de avaliação de qualidade de vida, Medical Outcome Quality of Life Scale Short-form-36 e Escala de Avaliação Social). O treinamento dos avaliadores consistiu em assistir cinco entrevistas filmadas e entrevistar cinco pacientes junto com um pesquisador mais experiente, antes de entrevistar pacientes sozinhos. A confiabilidade entre todos os líderes de grupo para os instrumentos mais importantes (Structured Clinical Interview for DSM-IV, Dimensional Yale-Brown Obsessive-Compulsive Scale, Universidade de São Paulo Sensory Phenomena Scale ) foi medida após seis entrevistas completas. RESULTADOS: A confiabilidade entre avaliadores foi de 96%. Até março de 2008, 630 pacientes com transtorno obsessivo-compulsivo tinham sido sistematicamente avaliados. A média de idade (±SE) foi de 34,7 (±0,51), 56,3% eram do sexo feminino e 84,6% caucasianos. Os sintomas obsessivo-compulsivos mais prevalentes foram os de simetria e os de contaminação. As comorbidades psiquiátricas mais comuns foram depressão maior, ansiedade generalizada e transtorno de ansiedade social. O transtorno de controle de impulsos mais comum foi escoriação neurótica. CONCLUSÃO: Este consórcio de pesquisa, pioneiro no Brasil, permitiu delinear o perfil sociodemográfico, clínico e terapêutico do paciente com transtorno obsessivo-compulsivo em uma grande amostra clínica de pacientes. O Consórcio Brasileiro de Pesquisa em Transtornos do Espectro Obsessivo-Compulsivo estabeleceu uma importante rede de colaboração de investigação clínica padronizada sobre o transtorno obsessivo-compulsivo e pode abrir o caminho para projetos semelhantes destinados a integrar outros grupos de pesquisa no Brasil e em todo o mundo.

Hybrid constraint programming and metaheuristic methods for large scale optimization problems

This work presents hybrid Constraint Programming (CP) and metaheuristic methods for the solution of Large Scale Optimization Problems; it aims at integrating concepts and mechanisms from the metaheuristic methods to a CP-based tree search environment in order to exploit the advantages of both approaches. The modeling and solution of large scale combinatorial optimization problem is a topic which has arisen the interest of many researcherers in the Operations Research field; combinatorial optimization problems are widely spread in everyday life and the need of solving difficult problems is more and more urgent. Metaheuristic techniques have been developed in the last decades to effectively handle the approximate solution of combinatorial optimization problems; we will examine metaheuristics in detail, focusing on the common aspects of different techniques. Each metaheuristic approach possesses its own peculiarities in designing and guiding the solution process; our work aims at recognizing components which can be extracted from metaheuristic methods and re-used in different contexts. In particular we focus on the possibility of porting metaheuristic elements to constraint programming based environments, as constraint programming is able to deal with feasibility issues of optimization problems in a very effective manner. Moreover, CP offers a general paradigm which allows to easily model any type of problem and solve it with a problem-independent framework, differently from local search and metaheuristic methods which are highly problem specific. In this work we describe the implementation of the Local Branching framework, originally developed for Mixed Integer Programming, in a CP-based environment. Constraint programming specific features are used to ease the search process, still mantaining an absolute generality of the approach. We also propose a search strategy called Sliced Neighborhood Search, SNS, that iteratively explores slices of large neighborhoods of an incumbent solution by performing CP-based tree search and encloses concepts from metaheuristic techniques. SNS can be used as a stand alone search strategy, but it can alternatively be embedded in existing strategies as intensification and diversification mechanism. In particular we show its integration within the CP-based local branching. We provide an extensive experimental evaluation of the proposed approaches on instances of the Asymmetric Traveling Salesman Problem and of the Asymmetric Traveling Salesman Problem with Time Windows. The proposed approaches achieve good results on practical size problem, thus demonstrating the benefit of integrating metaheuristic concepts in CP-based frameworks.

The COLOSS BEEBOOK Volume II, Standard methods for Apis mellifera pest and pathogen research: Introduction

The COLOSS BEEBOOK is a practical manual compiling standard methods in all fields of research on the western honey bee, Apis mellifera. The COLOSS network was founded in 2008 as a consequence of the heavy and frequent losses of managed honey bee colonies experienced in many regions of the world (Neumann and Carreck, 2010). As many of the world’s honey bee research teams began to address the problem, it soon became obvious that a lack of standardized research methods was seriously hindering scientists’ ability to harmonize and compare the data on colony losses obtained internationally. In its second year of activity, during a COLOSS meeting held in Bern, Switzerland, the idea of a manual of standardized honey bee research methods emerged. The manual, to be called the COLOSS BEEBOOK, was inspired by publications with similar purposes for fruit fly research (Lindsley and Grell, 1968; Ashburner, 1989; Roberts, 1998; Greenspan, 2004).

Performance tiers: Implementing comparative effectiveness analysis in the health care setting through operations research and spatial methods

This dissertation develops and tests a comparative effectiveness methodology utilizing a novel approach to the application of Data Envelopment Analysis (DEA) in health studies. The concept of performance tiers (PerT) is introduced as terminology to express a relative risk class for individuals within a peer group and the PerT calculation is implemented with operations research (DEA) and spatial algorithms. The analysis results in the discrimination of the individual data observations into a relative risk classification by the DEA-PerT methodology. The performance of two distance measures, kNN (k-nearest neighbor) and Mahalanobis, was subsequently tested to classify new entrants into the appropriate tier. The methods were applied to subject data for the 14 year old cohort in the Project HeartBeat! study.^ The concepts presented herein represent a paradigm shift in the potential for public health applications to identify and respond to individual health status. The resultant classification scheme provides descriptive, and potentially prescriptive, guidance to assess and implement treatments and strategies to improve the delivery and performance of health systems. ^