830 resultados para Gradient-based approaches
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FUS/TLS (fused in sarcoma/translocated in liposarcoma) is a ubiquitously expressed RNA-binding protein, that has been discovered as fused to transcription factors in several human sarcomas and found in protein aggregates in neurons of patients with an inherited form of Amyotrophic Lateral Sclerosis [1]. To date, FUS has been implicated in a variety of cellular processes such as gene expression control, transcriptional regulation, pre-mRNA splicing and miRNA processing [2]. In addition, some evidences link FUS to genome stability control and DNA damage response. In fact, mice lacking FUS are hypersensitive to ionizing radiation and show high levels of chromosome instability and in response to double-strand breaks, FUS gets phosphorylated by the protein kinase ATM [3, 4, 5]. Moreover, upon DNA damage stress, FUS mediates Ebp1 (ErbB3 receptor-binding protein) SUMOylation, a post-translational modification that is required for its onco-suppressive activity, by acting as SUMO E3 ligase [6]. The study aims to investigate the role of FUS in DNA damage response and SUMOylation, two cellular pathways tightly interconnected to each other. Moreover, we will exploit biochemical and mass spectrometry-based approaches in order to identify other potential substrates of the E3 SUMO ligase activity of FUS. Preliminary results of mass spectrometric identification of FUS interacting proteins, in HEK293 and SHSY5Y cells, highlighted the interaction of FUS with several proteins involved in DNA damage response and many of those have been described already as target of SUMOylation, such as XRCC5, DDX5, PARP1, Nucleophosmin, and others. These evidences strengthen the hypothesis that FUS might represent a link between these pathways, even thou its exact role still needs to be clearly addressed. [1] Vance C. et al. (2009) Science 323(5918): p. 1208-11 [2] Fiesel FC., Kahle PJ. (2011) FEBS J. 278(19): p. 3550-68 [3] Kuroda M. et al. (2000) Embo J. 19(3): p. 453-62 [4] Hicks GG. et al. (2000) Nat Genet. 24(2):p. 175-9 [5] Gardiner M. et al. (2008) Biochem J. 415(2): p. 297-307 [6] Oh SM. et al. (2010) Oncogene 29(7): p. 1017-30
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BackgroundConsensus-based approaches provide an alternative to evidence-based decision making, especially in situations where high-level evidence is limited. Our aim was to demonstrate a novel source of information, objective consensus based on recommendations in decision tree format from multiple sources.MethodsBased on nine sample recommendations in decision tree format a representative analysis was performed. The most common (mode) recommendations for each eventuality (each permutation of parameters) were determined. The same procedure was applied to real clinical recommendations for primary radiotherapy for prostate cancer. Data was collected from 16 radiation oncology centres, converted into decision tree format and analyzed in order to determine the objective consensus.ResultsBased on information from multiple sources in decision tree format, treatment recommendations can be assessed for every parameter combination. An objective consensus can be determined by means of mode recommendations without compromise or confrontation among the parties. In the clinical example involving prostate cancer therapy, three parameters were used with two cut-off values each (Gleason score, PSA, T-stage) resulting in a total of 27 possible combinations per decision tree. Despite significant variations among the recommendations, a mode recommendation could be found for specific combinations of parameters.ConclusionRecommendations represented as decision trees can serve as a basis for objective consensus among multiple parties.
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DNA triple helix based approaches to control and modulate cellular functions on the level of genomic DNA (antigene technology) suffered in the past from a stepmother like treatment in comparison to the flourishing field of oligonucleotide based control of translation (antisense technology). This was mostly due to lack of affinity of triplex forming oligonucleotides (TFOs) to their DNA target, to sequence restriciton constraints imposed by the triple helical recogniton motifs and by open questions to the accessibility of the target DNA. Recent developments in the area have brought about new bases that specifically recognize pyrimidine-purine inversion sites as well as sugar modifications, e.g. the 2'-aminoethoxy-oligonucleotides or oligonucleotides based on the locked nucleic acid (LNA) sugar unit, that greatly enhance triplex stability and alleviate in part the sequence restriction constraints. With this, sequence specific genomic DNA manipulation starts to become a useful tool in biotechnology
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BACKGROUND/AIMS Several countries are working to adapt clinical trial regulations to align the approval process to the level of risk for trial participants. The optimal framework to categorize clinical trials according to risk remains unclear, however. Switzerland is the first European country to adopt a risk-based categorization procedure in January 2014. We assessed how accurately and consistently clinical trials are categorized using two different approaches: an approach using criteria set forth in the new law (concept) or an intuitive approach (ad hoc). METHODS This was a randomized controlled trial with a method-comparison study nested in each arm. We used clinical trial protocols from eight Swiss ethics committees approved between 2010 and 2011. Protocols were randomly assigned to be categorized in one of three risk categories using the concept or the ad hoc approach. Each protocol was independently categorized by the trial's sponsor, a group of experts and the approving ethics committee. The primary outcome was the difference in categorization agreement between the expert group and sponsors across arms. Linear weighted kappa was used to quantify agreements, with the difference between kappas being the primary effect measure. RESULTS We included 142 of 231 protocols in the final analysis (concept = 78; ad hoc = 64). Raw agreement between the expert group and sponsors was 0.74 in the concept and 0.78 in the ad hoc arm. Chance-corrected agreement was higher in the ad hoc (kappa: 0.34 (95% confidence interval = 0.10-0.58)) than in the concept arm (0.27 (0.06-0.50)), but the difference was not significant (p = 0.67). LIMITATIONS The main limitation was the large number of protocols excluded from the analysis mostly because they did not fit with the clinical trial definition of the new law. CONCLUSION A structured risk categorization approach was not better than an ad hoc approach. Laws introducing risk-based approaches should provide guidelines, examples and templates to ensure correct application.
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A great number of debris flows occurred during the flood catastrophes of the summer of 1987 in the Swiss Alps. Aerial photography, field investigations and eyewitness accounts documented and analysed the events. As an example of the reconstructed major events, the large debris flow in the Varuna valley involved an estimated peak discharge between 400 and 800 m3/s and an event magnitude of 200,000 m3. Several single pulses were observed; the duration of each of them appeared to be not more than a few minutes. Apart from incision into weak bedrock, the maximum erosion depth seemed to depend on the channel gradient. Based on approximately 600 events, typical starting zones and rainfall conditions are discussed with regard to the triggering conditions. Existing and new empirical formulae are proposed to estimate the most important flow parameters. These values are compared to debris flow data from Canada and Japan.
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This chapter summarises the metabolomic strategies currently in force used in plant science and describes the methods used. The metabolite profiling and fingerprinting of plant tissues through MS- and/or NMR-based approaches and the subsequent identification of biomarkers is detailed. Strategies for the microisolation and de novo identification of unknown biomarkers are also discussed. The various approaches are illustrated by a metabolomic study of the maize response to herbivory. A review of recent metabolomic studies performed on seed and crop plant tissues involving various analytical strategies is provided.
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SOLUTIONS (2013 to 2018) is a European Union Seventh Framework Programme Project (EU-FP7). The project aims to deliver a conceptual framework to support the evidence-based development of environmental policies with regard to water quality. SOLUTIONS will develop the tools for the identification, prioritisation and assessment of those water contaminants that may pose a risk to ecosystems and human health. To this end, a new generation of chemical and effect-based monitoring tools is developed and integrated with a full set of exposure, effect and risk assessment models. SOLUTIONS attempts to address legacy, present and future contamination by integrating monitoring and modelling based approaches with scenarios on future developments in society, economy and technology and thus in contamination. The project follows a solutions-oriented approach by addressing major problems of water and chemicals management and by assessing abatement options. SOLUTIONS takes advantage of the access to the infrastructure necessary to investigate the large basins of the Danube and Rhine as well as relevant Mediterranean basins as case studies, and puts major efforts on stakeholder dialogue and support. Particularly, the EU Water Framework Directive (WFD) Common Implementation Strategy (CIS) working groups, International River Commissions, and water works associations are directly supported with consistent guidance for the early detection, identification, prioritisation, and abatement of chemicals in the water cycle. SOLUTIONS will give a specific emphasis on concepts and tools for the impact and risk assessment of complex mixtures of emerging pollutants, their metabolites and transformation products. Analytical and effect-based screening tools will be applied together with ecological assessment tools for the identification of toxicants and their impacts. The SOLUTIONS approach is expected to provide transparent and evidence-based candidates or River Basin Specific Pollutants in the case study basins and to assist future review of priority pollutants under the WFD as well as potential abatement options.
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Linkage disequilibrium (LD) is defined as the nonrandom association of alleles at two or more loci in a population and may be a useful tool in a diverse array of applications including disease gene mapping, elucidating the demographic history of populations, and testing hypotheses of human evolution. However, the successful application of LD-based approaches to pertinent genetic questions is hampered by a lack of understanding about the forces that mediate the genome-wide distribution of LD within and between human populations. Delineating the genomic patterns of LD is a complex task that will require interdisciplinary research that transcends traditional scientific boundaries. The research presented in this dissertation is predicated upon the need for interdisciplinary studies and both theoretical and experimental projects were pursued. In the theoretical studies, I have investigated the effect of genotyping errors and SNP identification strategies on estimates of LD. The primary importance of these two chapters is that they provide important insights and guidance for the design of future empirical LD studies. Furthermore, I analyzed the allele frequency distribution of 26,530 single nucleotide polymorphisms (SNPs) in three populations and generated the first-generation natural selection map of the human genome, which will be an important resource for explaining and understanding genomic patterns of LD. Finally, in the experimental study, I describe a novel and simple, low-cost, and high-throughput SNP genotyping method. The theoretical analyses and experimental tools developed in this dissertation will facilitate a more complete understanding of patterns of LD in human populations. ^
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Consumption choices assist in solving the problem of how to convey and recognize religious identities. In the communication of an identity, individuals use the knowledge embedded in consumption norms, which restrict the range of choices to a smaller set and abbreviate the required knowledge for encoding and decoding messages. Using this knowledge as a shared framework for understanding, individuals with religious beliefs can choose consumption items that would not only strengthen their beliefs but also help them express the intensity of their commitments to these beliefs. Because individuals and societies have different beliefs, norms, commitments, and expressive needs, consumption choice can help to express these differences. Our explanation contrasts with incentive-based approaches that view religious consumption norms as solutions to free-rider problem inherent in clubs.
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To identify genetic susceptibility loci for severe diabetic retinopathy, 286 Mexican-Americans with type 2 diabetes from Starr County, Texas completed detailed physical and ophthalmologic examinations including fundus photography for diabetic retinopathy grading. 103 individuals with moderate-to-severe non-proliferative diabetic retinopathy or proliferative diabetic retinopathy were defined as cases for this study. DNA samples extracted from study subjects were genotyped using the Affymetrix GeneChip® Human Mapping 100K Set, which includes 116,204 single nucleotide polymorphisms (SNPs) across the whole genome. Single-marker allelic tests and 2- to 8-SNP sliding-window Haplotype Trend Regression implemented in HelixTreeTM were first performed with these direct genotypes to identify genes/regions contributing to the risk of severe diabetic retinopathy. An additional 1,885,781 HapMap Phase II SNPs were imputed from the direct genotypes to expand the genomic coverage for a more detailed exploration of genetic susceptibility to diabetic retinopathy. The average estimated allelic dosage and imputed genotypes with the highest posterior probabilities were subsequently analyzed for associations using logistic regression and Fisher's Exact allelic tests, respectively. To move beyond these SNP-based approaches, 104,572 directly genotyped and 333,375 well-imputed SNPs were used to construct genetic distance matrices based on 262 retinopathy candidate genes and their 112 related biological pathways. Multivariate distance matrix regression was then used to test hypotheses with genes and pathways as the units of inference in the context of susceptibility to diabetic retinopathy. This study provides a framework for genome-wide association analyses, and implicated several genes involved in the regulation of oxidative stress, inflammatory processes, histidine metabolism, and pancreatic cancer pathways associated with severe diabetic retinopathy. Many of these loci have not previously been implicated in either diabetic retinopathy or diabetes. In summary, CDC73, IL12RB2, and SULF1 had the best evidence as candidates to influence diabetic retinopathy, possibly through novel biological mechanisms related to VEGF-mediated signaling pathway or inflammatory processes. While this study uncovered some genes for diabetic retinopathy, a comprehensive picture of the genetic architecture of diabetic retinopathy has not yet been achieved. Once fully understood, the genetics and biology of diabetic retinopathy will contribute to better strategies for diagnosis, treatment and prevention of this disease.^
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Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^
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As many as 2.5 million adolescent women seek abortion each year, and nearly 70,000 women die from complications related to unsafe abortion, of which almost half are women under the age of 25. A further 5 million women suffer disability due to unsafe abortion yearly. In most developing countries, abortion is legally restricted or highly inaccessible, which leads young women to seek services from unskilled practitioners often leading to incomplete, septic abortions and massive bleeding, which can result in permanent injury, infertility, and death. Based on our deeply held belief that all people, including adolescents, have a right to sexual and reproductive health services and the importance of addressing adolescent needs within Postabortion Care (PAC) services, Pathfinder used private funds to initiate a Youth-Friendly Postabortion Care (YFPAC) program in eight sub-Saharan African countries. Implemented between June 2007 and May 2008, the YFPAC program offered an opportunity to apply the PAC Consortium’s Technical Guidance on Youth-Friendly PAC, generating promising approaches and lessons learned. The goal of the YFPAC initiative was to increase access to PAC services that are responsive to adolescent needs in sub-Saharan Africa. While outcomes varied according to the country, the overall outcomes included: Increased community support for services and activities that prevent unwanted pregnancy, decreased stigma around abortion, and awareness of the issue of unsafe abortion among adolescent women: 311 peer educators reached almost 17,487 youth and other community members; 171 stakeholders (e.g., religious and traditional leaders, health officials, and local government officials) were sensitized on YFPAC, resulting in a positive shift in communities’ attitudes toward youth in need of PAC services. 125 service providers were trained to deliver YFPAC services and three doctors in Ghana were provided with a technical update on YFPAC. YFPAC services are available in Angola, Ghana, Nigeria, Mozambique, Tanzania, Uganda, Ethiopia, and Kenya. Pathfinder introduced YFPAC services into 25 facilities (in 27 service delivery points), and provided more than 3,800 clients with YFPAC services throughout the eight countries. The number of adolescent PAC clients seen at the project facilities increased— 710 clients were seen in the first quarter, 1,144 were seen in the fourth. The number of adolescent PAC clients who adopt a contraceptive method to prevent future unintended pregnancies has increased. Statistics show an average postabortion contraceptive acceptance of 69%, with the highest acceptance being 83% and the lowest being 44%. Evidence-based approaches, tools, and lessons learned are being disseminated and used for scale-up or replication of YFPAC interventions.
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Coral reefs represent major accumulations of calcium carbonate (CaCO3). The particularly labyrinthine network of reefs in Torres Strait, north of the Great Barrier Reef (GBR), has been examined in order to estimate their gross CaCO3 productivity. The approach involved a two-step procedure, first characterising and classifying the morphology of reefs based on a classification scheme widely employed on the GBR and then estimating gross CaCO3 productivity rates across the region using a regional census-based approach. This was undertaken by independently verifying published rates of coral reef community gross production for use in Torres Strait, based on site-specific ecological and morphological data. A total of 606 reef platforms were mapped and classified using classification trees. Despite the complexity of the maze of reefs in Torres Strait, there are broad morphological similarities with reefs in the GBR. The spatial distribution and dimensions of reef types across both regions are underpinned by similar geological processes, sea-level history in the Holocene and exposure to the same wind/wave energetic regime, resulting in comparable geomorphic zonation. However, the presence of strong tidal currents flowing through Torres Strait and the relatively shallow and narrow dimensions of the shelf exert a control on local morphology and spatial distribution of the reef platforms. A total amount of 8.7 million tonnes of CaCO3 per year, at an average rate of 3.7 kg CaCO3 m-2 yr-1 (G), were estimated for the studied area. Extrapolated production rates based on detailed and regional census-based approaches for geomorphic zones across Torres Strait were comparable to those reported elsewhere, particularly values for the GBR based on alkalinity-reduction methods. However, differences in mapping methodologies and the impact of reduced calcification due to global trends in coral reef ecological decline and changing oceanic physical conditions warrant further research. The novel method proposed in this study to characterise the geomorphology of reef types based on classification trees provides an objective and repeatable data-driven approach that combined with regional census-based approaches has the potential to be adapted and transferred to different coral reef regions, depicting a more accurate picture of interactions between reef ecology and geomorphology.
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This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators
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Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.