992 resultados para Traffic signals
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In the healthy individuum lymphocyte traffic into the central nervous system (CNS) is very low and tightly controlled by the highly specialized blood-brain barrier (BBB). In contrast, under inflammatory conditions of the CNS such as in multiple sclerosis or in its animal model experimental autoimmune encephalomyelitis (EAE) circulating lymphocytes and monocytes/macrophages readily cross the BBB and gain access to the CNS leading to edema, inflammation and demyelination. Interaction of circulating leukocytes with the endothelium of the blood-spinal cord and blood-brain barrier therefore is a critical step in the pathogenesis of inflammatory diseases of the CNS. Leukocyte/endothelial interactions are mediated by adhesion molecules and chemokines and their respective chemokine receptors. We have developed a novel spinal cord window preparation, which enables us to directly visualize CNS white matter microcirculation by intravital fluorescence videomicroscopy. Applying this technique of intravital fluorescence videomicroscopy we could provide direct in vivo evidence that encephalitogenic T cell blasts interact with the spinal cord white matter microvasculature without rolling and that alpha4-integrin mediates the G-protein independent capture and subsequently the G-protein dependent adhesion strengthening of T cell blasts to microvascular VCAM-1. LFA-1 was found to neither mediate the G-protein independent capture nor the G- protein dependent initial adhesion strengthening of encephalitogenic T cell blasts within spinal cord microvessel, but was rather involved in T cell extravasation across the vascular wall into the spinal cord parenchyme. Our observation that G-protein mediated signalling is required to promote adhesion strengthening of encephalitogenic T cells on BBB endothelium in vivo suggested the involvement of chemokines in this process. We found functional expression of the lymphoid chemokines CCL19/ELC and CCL21/SLC in CNS venules surrounded by inflammatory cells in brain and spinal cord sections of mice afflicted with EAE suggesting that the lymphoid chemokines CCL19 and CCL21 besides regulating lymphocyte homing to secondary lymphoid tissue might be involved in T lymphocyte migration into the immuneprivileged CNS during immunosurveillance and chronic inflammation. Here, I summarize our current knowledge on the sequence of traffic signals involved in T lymphocyte recruitment across the healthy and inflamed blood-brain and blood-spinal cord barrier based on our in vitro and in vivo investigations.
Immune cell migration across the blood–brain barrier: molecular mechanisms and therapeutic targeting
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The endothelial blood–brain barrier (BBB) and the epithelial blood–cerebrospinal fluid barrier protect the CNS from the constantly changing milieu within the bloodstream. The BBB strictly controls immune cell entry into the CNS, which is rare under physiological conditions. During a variety of pathological conditions of the CNS, such as viral or bacterial infections, or during inflammatory diseases, such as multiple sclerosis, immunocompetent cells readily traverse the BBB and subsequently enter the CNS parenchyma. Most of the available information on immune cell entry into the CNS is derived from studying experimental autoimmune encephalomyelitis (EAE), an animal model for multiple sclerosis. Consequently, our current knowledge on traffic signals mediating immune cell entry across the BBB during immunosurveillance and disease results mainly from experimental data in the EAE model. Therefore, a large part of this review summarizes these findings. Similarly, the potential benefits and risks associated with therapeutic targeting of immune cell trafficking across the BBB will be discussed in the context of multiple sclerosis, since elucidation of the molecular mechanisms relevant to this disease have largely relied on the use of its in vivo model, EAE.
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This article presents a cartographic system to facilitate cooperative manoeuvres among autonomous vehicles in a well-known environment. The main objective is to design an extended cartographic system to help in the navigation of autonomous vehicles. This system has to allow the vehicles not only to access the reference points needed for navigation, but also noticeable information such as the location and type of traffic signals, the proximity to a crossing, the streets en route, etc. To do this, a hierarchical representation of the information has been chosen, where the information has been stored in two levels. The lower level contains the archives with the Universal Traverse Mercator (UTM) coordinates of the points that define the reference segments to follow. The upper level contains a directed graph with the relational database in which streets, crossings, roundabouts and other points of interest are represented. Using this new system it is possible to know when the vehicle approaches a crossing, what other paths arrive at that crossing, and, should there be other vehicles circulating on those paths and arriving at the crossing, which one has the highest priority. The data obtained from the cartographic system is used by the autonomous vehicles for cooperative manoeuvres.
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Sight distance plays an important role in road traffic safety. Two types of Digital Elevation Models (DEMs) are utilized for the estimation of available sight distance in roads: Digital Terrain Models (DTMs) and Digital Surface Models (DSMs). DTMs, which represent the bare ground surface, are commonly used to determine available sight distance at the design stage. Additionally, the use of DSMs provides further information about elements by the roadsides such as trees, buildings, walls or even traffic signals which may reduce available sight distance. This document analyses the influence of three classes of DEMs in available sight distance estimation. For this purpose, diverse roads within the Region of Madrid (Spain) have been studied using software based on geographic information systems. The study evidences the influence of using each DEM in the outcome as well as the pros and cons of using each model.
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Mode of access: Internet.
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Arizona Department of Transportation, Phoenix
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Federal Highway Administration, Office of Research, Washington, D.C.
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Texas Department of Transportation, Austin
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Federal Highway Administration, Office of Research, Washington, D.C.
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Federal Highway Administration, Traffic Systems Division, Washington, D.C.
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Federal Railroad Administration, Office of Research and Development, Washington, D.C.
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Federal Highway Administration, Washington, D.C.
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Federal Railroad Administration, Office of Research and Development, Washington, D.C.
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Texas Department of Transportation, Austin
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Federal Highway Administration, Washington, D.C.