Search results for "Method"
showing 10 items of 13253 documents
Neurofibromatosis type 2 tumor suppressor protein is expressed in oligodendrocytes and regulates cell proliferation and process formation.
2017
The neurofibromatosis type 2 (NF2) tumor suppressor protein Merlin functions as a negative regulator of cell growth and actin dynamics in different cell types amongst which Schwann cells have been extensively studied. In contrast, the presence and the role of Merlin in oligodendrocytes, the myelin forming cells within the CNS, have not been elucidated. In this work, we demonstrate that Merlin immunoreactivity was broadly distributed in the white matter throughout the central nervous system. Following Merlin expression during development in the cerebellum, Merlin could be detected in the cerebellar white matter tract at early postnatal stages as shown by its co-localization with Olig2-positi…
Progressive derivation of serially homologous neuroblast lineages in the gnathal CNS of Drosophila
2018
Along the anterior-posterior axis the central nervous system is subdivided into segmental units (neuromeres) the composition of which is adapted to their region-specific functional requirements. In Drosophila melanogaster each neuromere is formed by a specific set of identified neural stem cells (neuroblasts, NBs). In the thoracic and anterior abdominal region of the embryonic ventral nerve cord segmental sets of NBs resemble the ground state (2nd thoracic segment, which does not require input of homeotic genes), and serial (segmental) homologs generate similar types of lineages. The three gnathal head segments form a transitional zone between the brain and the ventral nerve cord. It has be…
Grey Matter Microstructural Integrity Alterations in Blepharospasm Are Partially Reversed by Botulinum Neurotoxin Therapy.
2016
OBJECTIVE Benign Essential Blepharospasm (BEB) and hemifacial spasm (HFS) are the most common hyperkinetic movement disorders of facial muscles. Although similar in clinical presentation different pathophysiological mechanisms are assumed. Botulinum Neurotoxin (BoNT) is a standard evidence-based treatment for both conditions. In this study we aimed to assess grey matter microstructural differences between these two groups of patients and compared them with healthy controls. In patients we furthermore tracked the longitudinal morphometric changes associated with BoNT therapy. We hypothesized microstructural differences between the groups at the time point of maximum symptoms representation a…
Disease–Genes Must Guide Data Source Integration in the Gene Prioritization Process
2019
One of the main issues in detecting the genes involved in the etiology of genetic human diseases is the integration of different types of available functional relationships between genes. Numerous approaches exploited the complementary evidence coded in heterogeneous sources of data to prioritize disease-genes, such as functional profiles or expression quantitative trait loci, but none of them to our knowledge posed the scarcity of known disease-genes as a feature of their integration methodology. Nevertheless, in contexts where data are unbalanced, that is, where one class is largely under-represented, imbalance-unaware approaches may suffer a strong decrease in performance. We claim that …
Cohesive Model for the Simulation of Crack Initiation and Propagation in Mixed-Mode I/II in Composite Materials
2019
A cohesive element able to connect and simulate crack growth between independently modeled finite element subdomains with non-matching meshes is proposed and validated. The approach is based on penalty constraints and has several advantages over conventional FE techniques in disconnecting two regions of a model during crack growth. The most important is the ability to release portion of the interface that are smaller than the local finite element length. Thus, the growth of delamination is not limited to advancing by releasing nodes of the FE model, which is a limitation common to the methods found in the literature. Furthermore, it is possible to vary the penalty parameter within the cohes…
Application of Graph Clustering and Visualisation Methods to Analysis of Biomolecular Data
2018
In this paper we present an approach based on integrated use of graph clustering and visualisation methods for semi-supervised discovery of biologically significant features in biomolecular data sets. We describe several clustering algorithms that have been custom designed for analysis of biomolecular data and feature an iterated two step approach involving initial computation of thresholds and other parameters used in clustering algorithms, which is followed by identification of connected graph components, and, if needed, by adjustment of clustering parameters for processing of individual subgraphs.
Next-generation sequencing: big data meets high performance computing
2017
The progress of next-generation sequencing has a major impact on medical and genomic research. This high-throughput technology can now produce billions of short DNA or RNA fragments in excess of a few terabytes of data in a single run. This leads to massive datasets used by a wide range of applications including personalized cancer treatment and precision medicine. In addition to the hugely increased throughput, the cost of using high-throughput technologies has been dramatically decreasing. A low sequencing cost of around US$1000 per genome has now rendered large population-scale projects feasible. However, to make effective use of the produced data, the design of big data algorithms and t…
Network-Wide Adaptive Burst Detection Depicts Neuronal Activity with Improved Accuracy
2017
Neuronal networks are often characterized by their spiking and bursting statistics. Previously, we introducedan adaptive burst analysis methodwhich enhances the analysis power for neuronal networks with highly varying firing dynamics. The adaptation is based on single channels analyzing each element of a network separately. Such kind of analysis was adequate for the assessment of local behavior, where the analysis focuses on the neuronal activity in the vicinity of a single electrode. However, the assessment of the whole network may be hampered, if parts of the network are analyzed using different rules. Here, we test how using multiple channels and measurement time points affect adaptive b…
Spectral entropy based neuronal network synchronization analysis based on microelectrode array measurements
2016
Synchrony and asynchrony are essential aspects of the functioning of interconnected neuronal cells and networks. New information on neuronal synchronization can be expected to aid in understanding these systems. Synchronization provides insight in the functional connectivity and the spatial distribution of the information processing in the networks. Synchronization is generally studied with time domain analysis of neuronal events, or using direct frequency spectrum analysis, e.g., in specific frequency bands. However, these methods have their pitfalls. Thus, we have previously proposed a method to analyze temporal changes in the complexity of the frequency of signals originating from differ…
Automatic detection of hemangiomas using unsupervised segmentation of regions of interest
2016
In this paper we compare the performances of three automatic methods of identifying hemangioma regions in images: 1) unsupervised segmentation using the Otsu method, 2) Fuzzy C-means clustering (FCM) and 3) an improved region growing algorithm based on FCM (RG-FCM). For each image, the starting point of the algorithms is a rectangular region of interest (ROI) containing the hemangioma. For computing the performances of each method, the ROIs had been manually labeled in 2 classes: pixels of hemangioma and pixels of non-hemangioma. The computed scores are given separately for each image, as well as global performances across all ROIs for both classes. The best classification of non-hemangioma…