Search results for "bepress|Social and Behavioral Sciences|Communication|Social Media"
showing 10 items of 9925 documents
CNS-localized myeloid cells capture living invading T cells during neuroinflammation
2020
Using an in vivo real-time approach, the authors show that local myeloid cells remove early CNS-invading T cells via an engulfment pathway that is dependent on N-acetyl-D-glucosamine (GlcNAc) and lectin. These results reveal a novel capacity of myeloid cells to counteract neuroinflammation.
NG2/CSPG4 and progranulin in the posttraumatic glial scar.
2018
Traumatic injury of the central nervous system is one of the leading causes of death and disability in young adults. Failure of regeneration is caused by autonomous neuronal obstacles and by formation of the glial scar, which is essential to seal the injury but also constitutes a barrier for regrowing axons. The scar center is highly inflammatory and populated by NG2+ glia, whereas astrocytes form the sealing border and trap regrowing axons, suggesting that the non-permissive environment of activated astrocytes and extracellular matrix components is one of the reasons for the regenerative failure. Particularly, secreted chondroitin-sulfate proteoglycans, CSPGs, of the lectican family hinder…
Enabling openness of valuable information resources: Curbing data subtractability and exclusion
2019
In this paper we investigate how data openness can be made possible in communal settings. We adopt a utility perspective that foregrounds the use value of data, conceptualizing them as “goods.” On the basis of this conceptualization we explore 2 key goods' attributes: subtractability and exclusion. Our theoretical basis is built upon concepts from the theory of the commons, power theorizing, and notions related to data and information. Empirically, we investigate openness in the genetics domain through a longitudinal study of the evolving communal infrastructure for data related to 2 genes influencing women's susceptibility to breast and ovarian cancer (BRCA1 and BRCA2). We follow the conti…
Twitter as a tool for teaching and communicating microbiology: the #micromoocsem initiative
2016
López-Goñi, Ignacio et al.
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…
Dynamic large-scale network synchronization from perception to action
2018
Sensory-guided actions entail the processing of sensory information, generation of perceptual decisions, and the generation of appropriate actions. Neuronal activity underlying these processes is distributed into sensory, fronto-parietal, and motor brain areas, respectively. How the neuronal processing is coordinated across these brain areas to support functions from perception to action remains unknown. We investigated whether phase synchronization in large-scale networks coordinate these processes. We recorded human cortical activity with magnetoencephalography (MEG) during a task in which weak somatosensory stimuli remained unperceived or were perceived. We then assessed dynamic evolutio…
A REST-based framework to support non-invasive and early coeliac disease diagnosis
2019
The health sector has traditionally been one of the early adopters of databases, from the most simple Electronic Health Record (formerly Computer-Based Patient Record) systems in use in general practice, hospitals and intensive care units to big data, multidata based systems used to support diagnosis and care decisions. In this paper we present a framework to support non-invasive and early diagnosis of coeliac disease. The proposed framework makes use of well-known technologies and techniques, both hardware and software, put together in a novel way. The main goals of our framework are: (1) providing users with a reliable and fast repository of a large amount of data; (2) to make such reposi…
On a Planar Dynamical System Arising in the Network Control Theory
2016
We study the structure of attractors in the two-dimensional dynamical system that appears in the network control theory. We provide description of the attracting set and follow changes this set suffers under the changes of positive parameters µ and Θ.
Discovering Differential Equations from Earth Observation Data
2020
Modeling and understanding the Earth system is a constant and challenging scientific endeavour. When a clear mechanistic model is unavailable, complex or uncertain, learning from data can be an alternative. While machine learning has provided excellent methods for detection and retrieval, understanding the governing equations of the system from observational data seems an elusive problem. In this paper we introduce sparse regression to uncover a set of governing equations in the form of a system of ordinary differential equations (ODEs). The presented method is used to explicitly describe variable relations by identifying the most expressive and simplest ODEs explaining data to model releva…