860 resultados para Development and learning


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Main purpose of this thesis is to introduce a new lossless compression algorithm for multispectral images. Proposed algorithm is based on reducing the band ordering problem to the problem of finding a minimum spanning tree in a weighted directed graph, where set of the graph vertices corresponds to multispectral image bands and the arcs’ weights have been computed using a newly invented adaptive linear prediction model. The adaptive prediction model is an extended unification of 2–and 4–neighbour pixel context linear prediction schemes. The algorithm provides individual prediction of each image band using the optimal prediction scheme, defined by the adaptive prediction model and the optimal predicting band suggested by minimum spanning tree. Its efficiency has been compared with respect to the best lossless compression algorithms for multispectral images. Three recently invented algorithms have been considered. Numerical results produced by these algorithms allow concluding that adaptive prediction based algorithm is the best one for lossless compression of multispectral images. Real multispectral data captured from an airplane have been used for the testing.

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A large part of the mammalian genome is transcribed into noncoding RNAs. Long noncoding RNAs (lncRNAs) have emerged as critical epigenetic regulators of gene expression. Distinct molecular mechanisms allow lncRNAs either to activate or to repress gene expression, thereby participating in the regulation of cellular and tissue function. LncRNAs, therefore, have important roles in healthy and diseased hearts, and might be targets for therapeutic intervention. In this Review, we summarize the current knowledge of the roles of lncRNAs in cardiac development and ageing. After describing the definition and classification of lncRNAs, we present an overview of the mechanisms by which lncRNAs regulate gene expression. We discuss the multiple roles of lncRNAs in the heart, and focus on the regulation of embryonic stem cell differentiation, cardiac cell fate and development, and cardiac ageing. We emphasize the importance of chromatin remodelling in this regulation. Finally, we discuss the therapeutic and biomarker potential of lncRNAs.

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The lymphatic system maintains tissue fluid balance, and dysfunction of lymphatic vessels and valves causes human lymphedema syndromes. Yet, our knowledge of the molecular mechanisms underlying lymphatic vessel development is still limited. Here, we show that cyclin-dependent kinase 5 (Cdk5) is an essential regulator of lymphatic vessel development. Endothelial-specific Cdk5 knockdown causes congenital lymphatic dysfunction and lymphedema due to defective lymphatic vessel patterning and valve formation. We identify the transcription factor Foxc2 as a key substrate of Cdk5 in the lymphatic vasculature, mechanistically linking Cdk5 to lymphatic development and valve morphogenesis. Collectively, our findings show that Cdk5-Foxc2 interaction represents a critical regulator of lymphatic vessel development and the transcriptional network underlying lymphatic vascular remodeling.

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The key information processing units within gene regulatory networks are enhancers. Enhancer activity is associated with the production of tissue-specific noncoding RNAs, yet the existence of such transcripts during cardiac development has not been established. Using an integrated genomic approach, we demonstrate that fetal cardiac enhancers generate long noncoding RNAs (lncRNAs) during cardiac differentiation and morphogenesis. Enhancer expression correlates with the emergence of active enhancer chromatin states, the initiation of RNA polymerase II at enhancer loci and expression of target genes. Orthologous human sequences are also transcribed in fetal human hearts and cardiac progenitor cells. Through a systematic bioinformatic analysis, we identified and characterized, for the first time, a catalog of lncRNAs that are expressed during embryonic stem cell differentiation into cardiomyocytes and associated with active cardiac enhancer sequences. RNA-sequencing demonstrates that many of these transcripts are polyadenylated, multi-exonic long noncoding RNAs. Moreover, knockdown of two enhancer-associated lncRNAs resulted in the specific downregulation of their predicted target genes. Interestingly, the reactivation of the fetal gene program, a hallmark of the stress response in the adult heart, is accompanied by increased expression of fetal cardiac enhancer transcripts. Altogether, these findings demonstrate that the activity of cardiac enhancers and expression of their target genes are associated with the production of enhancer-derived lncRNAs.

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Heterozygous germline mutations in the zinc finger transcription factor GATA2 have recently been shown to underlie a range of clinical phenotypes, including Emberger syndrome, a disorder characterized by lymphedema and predisposition to myelodysplastic syndrome/acute myeloid leukemia (MDS/AML). Despite well-defined roles in hematopoiesis, the functions of GATA2 in the lymphatic vasculature and the mechanisms by which GATA2 mutations result in lymphedema have not been characterized. Here, we have provided a molecular explanation for lymphedema predisposition in a subset of patients with germline GATA2 mutations. Specifically, we demonstrated that Emberger-associated GATA2 missense mutations result in complete loss of GATA2 function, with respect to the capacity to regulate the transcription of genes that are important for lymphatic vessel valve development. We identified a putative enhancer element upstream of the key lymphatic transcriptional regulator PROX1 that is bound by GATA2, and the transcription factors FOXC2 and NFATC1. Emberger GATA2 missense mutants had a profoundly reduced capacity to bind this element. Conditional Gata2 deletion in mice revealed that GATA2 is required for both development and maintenance of lymphovenous and lymphatic vessel valves. Together, our data unveil essential roles for GATA2 in the lymphatic vasculature and explain why a select catalogue of human GATA2 mutations results in lymphedema.

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Terminal differentiation of B cells depends on two interconnected survival pathways, elicited by the B-cell receptor (BCR) and the BAFF receptor (BAFF-R), respectively. Loss of either signaling pathway arrests B-cell development. Although BCR-dependent survival depends mainly on the activation of the v-AKT murine thymoma viral oncogene homolog 1 (AKT)/PI3-kinase network, BAFF/BAFF-R-mediated survival engages non-canonical NF-κB signaling as well as MAPK/extracellular-signal regulated kinase and AKT/PI3-kinase modules to allow proper B-cell development. Plasma cell survival, however, is independent of BAFF-R and regulated by APRIL that signals NF-κB activation via alternative receptors, that is, transmembrane activator and CAML interactor (TACI) or B-cell maturation (BCMA). All these complex signaling events are believed to secure survival by increased expression of anti-apoptotic B-cell lymphoma 2 (Bcl2) family proteins in developing and mature B cells. Curiously, how lack of BAFF- or APRIL-mediated signaling triggers B-cell apoptosis remains largely unexplored. Here, we show that two pro-apoptotic members of the 'Bcl2 homology domain 3-only' subgroup of the Bcl2 family, Bcl2 interacting mediator of cell death (Bim) and Bcl2 modifying factor (Bmf), mediate apoptosis in the context of TACI-Ig overexpression that effectively neutralizes BAFF as well as APRIL. Surprisingly, although Bcl2 overexpression triggers B-cell hyperplasia exceeding the one observed in Bim(-/-)Bmf(-/-) mice, Bcl2 transgenic B cells remain susceptible to the effects of TACI-Ig expression in vivo, leading to ameliorated pathology in Vav-Bcl2 transgenic mice. Together, our findings shed new light on the molecular machinery restricting B-cell survival during development, normal homeostasis and under pathological conditions. Our data further suggest that Bcl2 antagonists might improve the potency of BAFF/APRIL-depletion strategies in B-cell-driven pathologies.

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We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.

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Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

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BACKGROUND: Developing and updating high-quality guidelines requires substantial time and resources. To reduce duplication of effort and enhance efficiency, we developed a process for guideline adaptation and assessed initial perceptions of its feasibility and usefulness. METHODS: Based on preliminary developments and empirical studies, a series of meetings with guideline experts were organised to define a process for guideline adaptation (ADAPTE) and to develop a manual and a toolkit made available on a website (http://www.adapte.org). Potential users, guideline developers and implementers, were invited to register and to complete a questionnaire evaluating their perception about the proposed process.

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Peatlands play a crucial role in Indonesia's economic development, and in its stated goal of reducing greenhouse gas emissions. Improved peatland management - including a national moratorium on the granting of any new conversion licenses - forms a cornerstone of Indonesia's climate change mitigation commitment. At the same time, rapid expansion of the plantation sector is driving wide-scale drainage and conversion of peat swamp ecosystems. The province of Riau, in central Sumatra, finds itself at the crossroads of these conflicting agendas. This essay presents a case study of three islands on Riau's east coast affected by industrial timber plantation concessions. It examines the divergent experiences, perceptions and responses of communities on the islands. A mix of dramatic protests, localised everyday actions and constructive dialogue has succeeded in delaying or perhaps halting one of the concessions, while negotiations and contestation with the other two continue. With the support of regional and national non-governmental organisations and local government, communities are pursuing alternative development strategies, including the cultivation of sago, which requires no peat drainage. While a powerful political economy of state and corporate actors shapes the contours of socio-environmental change, local social movements can alter trajectories of change, promoting incremental improvements and alternative pathways.

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Only a minority ot excessive drinkers develop cirrhosis. The main cofactors implicated in the pathophysiology of alcoholic liver disease are obesity, diabetes or the metabolic syndrome. Several genetic polymorphisms have been associated with a higher risk of alcoholic cirrhosis. Recent data indicate that gut microbiota could play a role in the pathogenesis of alcoholic liver disease. The aim of this review is to summarize the factors that influence development and progression of alcoholic liver disease.

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Despite the development of novel typing methods based on whole genome sequencing, most laboratories still rely on classical molecular methods for outbreak investigation or surveillance. Reference methods for Clostridium difficile include ribotyping and pulsed-field gel electrophoresis, which are band-comparing methods often difficult to establish and which require reference strain collections. Here, we present the double locus sequence typing (DLST) scheme as a tool to analyse C. difficile isolates. Using a collection of clinical C. difficile isolates recovered during a 1-year period, we evaluated the performance of DLST and compared the results to multilocus sequence typing (MLST), a sequence-based method that has been used to study the structure of bacterial populations and highlight major clones. DLST had a higher discriminatory power compared to MLST (Simpson's index of diversity of 0.979 versus 0.965) and successfully identified all isolates of the study (100 % typeability). Previous studies showed that the discriminatory power of ribotyping was comparable to that of MLST; thus, DLST might be more discriminatory than ribotyping. DLST is easy to establish and provides several advantages, including absence of DNA extraction [polymerase chain reaction (PCR) is performed on colonies], no specific instrumentation, low cost and unambiguous definition of types. Moreover, the implementation of a DLST typing scheme on an Internet database, such as that previously done for Staphylococcus aureus and Pseudomonas aeruginosa ( http://www.dlst.org ), will allow users to easily obtain the DLST type by submitting directly sequencing files and will avoid problems associated with multiple databases.

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AIM: To develop and test the Parental PELICAN Questionnaire, an instrument to retrospectively assess parental experiences and needs during their child's end-of-life care. BACKGROUND: To offer appropriate care for dying children, healthcare professionals need to understand the illness experience from the family perspective. A questionnaire specific to the end-of-life experiences and needs of parents losing a child is needed to evaluate the perceived quality of paediatric end-of-life care. DESIGN: This is an instrument development study applying mixed methods based on recommendations for questionnaire design and validation. METHOD: The Parental PELICAN Questionnaire was developed in four phases between August 2012-March 2014: phase 1: item generation; phase 2: validity testing; phase 3: translation; phase 4: pilot testing. Psychometric properties were assessed after applying the Parental PELICAN Questionnaire in a sample of 224 bereaved parents in April 2014. Validity testing covered the evidence based on tests of content, internal structure and relations to other variables. RESULTS: The Parental PELICAN Questionnaire consists of approximately 90 items in four slightly different versions accounting for particularities of the four diagnostic groups. The questionnaire's items were structured according to six quality domains described in the literature. Evidence of initial validity and reliability could be demonstrated with the involvement of healthcare professionals and bereaved parents. CONCLUSION: The Parental PELICAN Questionnaire holds promise as a measure to assess parental experiences and needs and is applicable to a broad range of paediatric specialties and settings. Future validation is needed to evaluate its suitability in different cultures.

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OBJECTIVE: The aim of this article was to apply psychometric theory to develop and validate a visual grading scale for assessing the visual perception of digital image quality anteroposterior (AP) pelvis. METHODS: Psychometric theory was used to guide scale development. Seven phantom and seven cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images, and 184 volunteers scored cadaver images. Factor analysis and Cronbach's alpha were used to assess scale validity and reliability. RESULTS: A 24-item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good interitem correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α = 0.8 and 0.9, respectively). Factor analysis suggested that the scale is multidimensional (assessing multiple quality themes). CONCLUSION: This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. ADVANCES IN KNOWLEDGE: This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality.