904 resultados para Network Analysis Methods
Resumo:
Based on the report for the unit “Foresight Analysis Methods” of the PhD program on Technology Assessment in 2013. This unit was supervised by Prof. António Moniz. The paper had meanwhile contributions from the supervisor and Dr. Douglas Robinson.
Resumo:
This work presents research conducted to understand the role of indicators in decisions of technology innovation. A gap was detected in the literature of innovation and technology assessment about the use and influence of indicators in this type of decision. It was important to address this gap because indicators are often frequent elements of innovation and technology assessment studies. The research was designed to determine the extent of the use and influence of indicators in decisions of technology innovation, to characterize the role of indicators in these decisions, and to understand how indicators are used in these decisions. The latter involved the test of four possible explanatory factors: the type and phase of decision, and the context and process of construction of evidence. Furthermore, it focused on three Portuguese innovation groups: public researchers, business R&D&I leaders and policymakers. The research used a combination of methods to collect quantitative and qualitative information, such as surveys, case studies and social network analysis. This research concluded that the use of indicators is different from their influence in decisions of technology innovation. In fact, there is a high use of indicators in these decisions, but lower and differentiated differences in their influence in each innovation group. This suggests that political-behavioural methods are also involved in the decisions to different degrees. The main social influences in the decisions came mostly from hierarchies, knowledge-based contacts and users. Furthermore, the research established that indicators played mostly symbolic roles in decisions of policymakers and business R&D&I leaders, although their role with researchers was more differentiated. Indicators were also described as helpful instruments to conduct a reasonable interpretation of data and to balance options in innovation and technology assessments studies, in particular when contextualised, described in detail and with discussion upon the options made. Results suggest that there are four main explanatory factors for the role of indicators in these decisions: First, the type of decision appears to be a factor to consider when explaining the role of indicators. In fact, each type of decision had different influences on the way indicators are used, and each type of decision used different types of indicators. Results for policy-making were particularly different from decisions of acquisition and development of products/technology. Second, the phase of the decision can help to understand the role indicators play in these decisions. Results distinguished between two phases detected in all decisions – before and after the decision – as well as two other phases that can be used to complement the decision process and where indicators can be involved. Third, the context of decision is an important factor to consider when explaining the way indicators are taken into consideration in policy decisions. In fact, the role of indicators can be influenced by the particular context of the decision maker, in which all types of evidence can be selected or downplayed. More importantly, the use of persuasive analytical evidence appears to be related with the dispute existent in the policy context. Fourth and last, the process of construction of evidence is a factor to consider when explaining the way indicators are involved in these decisions. In fact, indicators and other evidence were brought to the decision processes according to their availability and capacity to support the different arguments and interests of the actors and stakeholders. In one case, an indicator lost much persuasion strength with the controversies that it went through during the decision process. Therefore, it can be argued that the use of indicators is high but not very influential; their role is mostly symbolic to policymakers and business decisions, but varies among researchers. The role of indicators in these decisions depends on the type and phase of the decision and the context and process of construction of evidence. The latter two are related to the particular context of each decision maker, the existence of elements of dispute and controversies that influence the way indicators are introduced in the decision-making process.
Resumo:
Introduction: Non-invasive brain imaging techniques often contrast experimental conditions across a cohort of participants, obfuscating distinctions in individual performance and brain mechanisms that are better characterised by the inter-trial variability. To overcome such limitations, we developed topographic analysis methods for single-trial EEG data [1]. So far this was typically based on time-frequency analysis of single-electrode data or single independent components. The method's efficacy is demonstrated for event-related responses to environmental sounds, hitherto studied at an average event-related potential (ERP) level. Methods: Nine healthy subjects participated to the experiment. Auditory meaningful sounds of common objects were used for a target detection task [2]. On each block, subjects were asked to discriminate target sounds, which were living or man-made auditory objects. Continuous 64-channel EEG was acquired during the task. Two datasets were considered for each subject including single-trial of the two conditions, living and man-made. The analysis comprised two steps. In the first part, a mixture of Gaussians analysis [3] provided representative topographies for each subject. In the second step, conditional probabilities for each Gaussian provided statistical inference on the structure of these topographies across trials, time, and experimental conditions. Similar analysis was conducted at group-level. Results: Results show that the occurrence of each map is structured in time and consistent across trials both at the single-subject and at group level. Conducting separate analyses of ERPs at single-subject and group levels, we could quantify the consistency of identified topographies and their time course of activation within and across participants as well as experimental conditions. A general agreement was found with previous analysis at average ERP level. Conclusions: This novel approach to single-trial analysis promises to have impact on several domains. In clinical research, it gives the possibility to statistically evaluate single-subject data, an essential tool for analysing patients with specific deficits and impairments and their deviation from normative standards. In cognitive neuroscience, it provides a novel tool for understanding behaviour and brain activity interdependencies at both single-subject and at group levels. In basic neurophysiology, it provides a new representation of ERPs and promises to cast light on the mechanisms of its generation and inter-individual variability.
Resumo:
The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network.
Resumo:
In Alzheimer's disease (AD), synaptic alterations play a major role and are often correlated with cognitive changes. In order to better understand synaptic modifications, we compared alterations in NMDA receptors and postsynaptic protein PSD-95 expression in the entorhinal cortex (EC) and frontal cortex (FC; area 9) of AD and control brains. We combined immunohistochemical and image analysis methods to quantify on consecutive sections the distribution of PSD-95 and NMDA receptors GluN1, GluN2A and GluN2B in EC and FC from 25 AD and control cases. The density of stained receptors was analyzed using multivariate statistical methods to assess the effect of neurodegeneration. In both regions, the number of neuronal profiles immunostained for GluN1 receptors subunit and PSD-95 protein was significantly increased in AD compared to controls (3-6 fold), while the number of neuronal profiles stained for GluN2A and GluN2B receptors subunits was on the contrary decreased (3-4 fold). The increase in marked neuronal profiles was more prominent in a cortical band corresponding to layers 3 to 5 with large pyramidal cells. Neurons positive for GluN1 or PSD-95 staining were often found in the same localization on consecutive sections and they were also reactive for the anti-tau antibody AD2, indicating a neurodegenerative process. Differences in the density of immunoreactive puncta representing neuropile were not statistically significant. Altogether these data indicate that GluN1 and PSD-95 accumulate in the neuronal perikarya, but this is not the case for GluN2A and GluN2B, while the neuropile compartment is less subject to modifications. Thus, important variations in the pattern of distribution of the NMDA receptors subunits and PSD-95 represent a marker in AD and by impairing the neuronal network, contribute to functional deterioration.
Resumo:
Immune protection from infectious diseases and cancer is mediated by individual T cells of different clonal origin. Their functions are tightly regulated but not yet fully characterized. Understanding the contribution of each T cell will improve the prediction of immune protection based on laboratory assessment of T-cell responses. Here we developed techniques for simultaneous molecular and functional assessment of single CD8 T cells directly ex vivo. We studied two groups of patients with melanoma after vaccination with two closely related tumor antigenic peptides. Vaccination induced T cells with strong memory and effector functions, as found in virtually all T cells of the first patient group, and fractions of T cells in the second group. Interestingly, high functionality was not restricted to dominant clonotypes. Rather, dominant and nondominant clonotypes acquired equal functional competence. In parallel, this was also found for EBV- and CMV-specific T cells. Thus, the nondominant clonotypes may contribute similarly to immunity as their dominant counterparts.
Resumo:
INTRODUCTION The Rasch model is increasingly used in the field of rehabilitation because it improves the accuracy of measurements of patient status and their changes after therapy. OBJECTIVE To determine the long-term effectiveness of a holistic neuropsychological rehabilitation program for Spanish outpatients with acquired brain injury (ABI) using Rasch analysis. METHODS Eighteen patients (ten with long evolution - patients who started the program > 6 months after ABI- and eight with short evolution) and their relatives attended the program for 6 months. Patients' and relatives' answers to the European Brain Injury Questionnaire and the Frontal Systems Behavior Scale at 3 time points (pre-intervention. post-intervention and 12 month follow-up) were transformed into linear measures called logits. RESULTS The linear measures revealed significant improvements with large effects at the follow-up assessment on cognitive and executive functioning, social and emotional self-regulation, apathy and mood. At follow-up, the short evolution group achieved greater improvements in mood and cognitive functioning than the long evolution patients. CONCLUSIONS The program showed long-term effectiveness for most of the variables, and it was more effective for mood and cognitive functioning when patients were treated early. Relatives played a key role in the effectiveness of the rehabilitation program.
Resumo:
Recurrent breast cancer occurring after the initial treatment is associated with poor outcome. A bimodal relapse pattern after surgery for primary tumor has been described with peaks of early and late recurrence occurring at about 2 and 5 years, respectively. Although several clinical and pathological features have been used to discriminate between low- and high-risk patients, the identification of molecular biomarkers with prognostic value remains an unmet need in the current management of breast cancer. Using microarray-based technology, we have performed a microRNA expression analysis in 71 primary breast tumors from patients that either remained disease-free at 5 years post-surgery (group A) or developed early (group B) or late (group C) recurrence. Unsupervised hierarchical clustering of microRNA expression data segregated tumors in two groups, mainly corresponding to patients with early recurrence and those with no recurrence. Microarray data analysis and RT-qPCR validation led to the identification of a set of 5 microRNAs (the 5-miRNA signature) differentially expressed between these two groups: miR-149, miR-10a, miR-20b, miR-30a-3p and miR-342-5p. All five microRNAs were down-regulated in tumors from patients with early recurrence. We show here that the 5-miRNA signature defines a high-risk group of patients with shorter relapse-free survival and has predictive value to discriminate non-relapsing versus early-relapsing patients (AUC = 0.993, p-value<0.05). Network analysis based on miRNA-target interactions curated by public databases suggests that down-regulation of the 5-miRNA signature in the subset of early-relapsing tumors would result in an overall increased proliferative and angiogenic capacity. In summary, we have identified a set of recurrence-related microRNAs with potential prognostic value to identify patients who will likely develop metastasis early after primary breast surgery.
Resumo:
MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. From the resulting tremendous amount of data that is going to be accumulated soon, we discuss what new challenges must be tackled in terms of methods for advanced network analysis and visualization, as well data organization and distribution. This new framework is well suited to investigate key questions on brain complexity and we try to foresee what fields will most benefit from these approaches.
Resumo:
Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions. Geneset analysis methods have been described previously to analyze the expression values of several genes related by known biological criteria (metabolic pathway, pathology signature, co-regulation by a common factor, etc.) at the same time and the cost of these methods allows for the use of more values to help discover the underlying biological mechanisms. Results: As several methods assume different null hypotheses, we propose to reformulate the main question that biologists seek to answer. To determine which genesets are associated with expression values that differ between two experiments, we focused on three ad hoc criteria: expression levels, the direction of individual gene expression changes (up or down regulation), and correlations between genes. We introduce the FAERI methodology, tailored from a two-way ANOVA to examine these criteria. The significance of the results was evaluated according to the self-contained null hypothesis, using label sampling or by inferring the null distribution from normally distributed random data. Evaluations performed on simulated data revealed that FAERI outperforms currently available methods for each type of set tested. We then applied the FAERI method to analyze three real-world datasets on hypoxia response. FAERI was able to detect more genesets than other methodologies, and the genesets selected were coherent with current knowledge of cellular response to hypoxia. Moreover, the genesets selected by FAERI were confirmed when the analysis was repeated on two additional related datasets. Conclusions: The expression values of genesets are associated with several biological effects. The underlying mathematical structure of the genesets allows for analysis of data from several genes at the same time. Focusing on expression levels, the direction of the expression changes, and correlations, we showed that two-step data reduction allowed us to significantly improve the performance of geneset analysis using a modified two-way ANOVA procedure, and to detect genesets that current methods fail to detect.
Resumo:
Through the history of Electrical Engineering education, vectorial and phasorial diagrams have been used as a fundamental learning tool. At present, computational power has replaced them by long data lists, the result of solving equation systems by means of numerical methods. In this sense, diagrams have been shifted to an academic background and although theoretically explained, they are not used in a practical way within specific examples. This fact may be against the understanding of the complex behavior of the electrical power systems by students. This article proposes a modification of the classical Perrine-Baum diagram construction to allowing both a more practical representation and a better understanding of the behavior of a high-voltage electric line under different levels of load. This modification allows, at the same time, the forecast of the obsolescence of this behavior and line’s loading capacity. Complementary, we evaluate the impact of this tool in the learning process showing comparative undergraduate results during three academic years
Resumo:
Powdery mildew is an important disease of wheat caused by the obligate biotrophic fungus Blumeria graminis f. sp. tritici. This pathogen invades exclusively epidermal cells after penetrating directly through the cell wall. Because powdery mildew colonizes exclusively epidermal cells, it is of importance not only to identify genes which are activated, but also to monitor tissue specificity of gene activation. Acquired resistance of wheat to powdery mildew can be induced by a previous inoculation with the non-host pathogen B. graminis f. sp. hordei, the causal agent of barley powdery mildew. The establishment of the resistant state is accompanied by the activation of genes. Here we report the tissue-specific cDNA-AFLP analysis and cloning of transcripts accumulating 6 and 24 h after the resistance-inducing inoculation with B. graminis f. sp. hordei. A total of 25,000 fragments estimated to represent about 17,000 transcripts were displayed. Out of these, 141 transcripts, were found to accumulate after Bgh inoculation using microarray hybridization analysis. Forty-four accumulated predominantly in the epidermis whereas 76 transcripts accumulated mostly in mesophyll tissue.
Resumo:
In this paper we analyse the decline of the Swiss corporate network between 1980 and 2000. We address the theoretical and methodological challenge of this transformation by the use of a combination of network analysis and multiple correspondence analysis (MCA). Based on a sample of top managers of the 110 largest Swiss companies in 1980 and 2000 we show that, beyond an adjustment to structural pressure, an explanation of the decline of the network has to include the strategies of the fractions of the business elites. We reveal that three factors contribute crucially to the decline of the Swiss corporate network: the managerialization of industrial leaders, the marginalization of law degree holders and the influx of hardly connected foreign managers.
Resumo:
Abstract OBJECTIVE Evaluating the evidence of hypertension prevalence among indigenous populations in Brazil through a systematic review and meta-analysis. METHODS A search was performed by two reviewers, with no restriction of date or language in the databases of PubMed, LILACS, SciELO, Virtual Health Library and Capes Journal Portal. Also, a meta-regression model was designed in which the last collection year of each study was used as a moderating variable. RESULTS 23 articles were included in the review. No hypertension was found in indigenous populations in 10 studies, and its prevalence was increasing and varied, reaching levels of up to 29.7%. Combined hypertension prevalence in Indigenous from the period of 1970 to 2014 was 6.2% (95% CI, 3.1% - 10.3%). In the regression, the value of the odds ratio was 1.12 (95% CI, 1.07 - 1.18; p <0.0001), indicating a 12% increase every year in the probability of an indigenous person presenting hypertension. CONCLUSION There has been a constant increase in prevalence despite the absence of hypertension in about half of the studies, probably due to changes in cultural, economic and lifestyle habits, resulting from indigenous interaction with non-indigenous society.
Resumo:
INTRODUCTION: Interindividual variations in regional structural properties covary across the brain, thus forming networks that change as a result of aging and accompanying neurological conditions. The alterations of superficial white matter (SWM) in Alzheimer's disease (AD) are of special interest, since they follow the AD-specific pattern characterized by the strongest neurodegeneration of the medial temporal lobe and association cortices. METHODS: Here, we present an SWM network analysis in comparison with SWM topography based on the myelin content quantified with magnetization transfer ratio (MTR) for 39 areas in each hemisphere in 15 AD patients and 15 controls. The networks are represented by graphs, in which nodes correspond to the areas, and edges denote statistical associations between them. RESULTS: In both groups, the networks were characterized by asymmetrically distributed edges (predominantly in the left hemisphere). The AD-related differences were also leftward. The edges lost due to AD tended to connect nodes in the temporal lobe to other lobes or nodes within or between the latter lobes. The newly gained edges were mostly confined to the temporal and paralimbic regions, which manifest demyelination of SWM already in mild AD. CONCLUSION: This pattern suggests that the AD pathological process coordinates SWM demyelination in the temporal and paralimbic regions, but not elsewhere. A comparison of the MTR maps with MTR-based networks shows that although, in general, the changes in network architecture in AD recapitulate the topography of (de)myelination, some aspects of structural covariance (including the interhemispheric asymmetry of networks) have no immediate reflection in the myelination pattern.