One of the main effects of pro-inflammatory cytokines is the induction of chemokines and the expression of adhesive molecules that regulate the migration of immune cells to the center of the damage. Chemoattractant gradient also provides a physiological delivery of cells to tissues and lymphatic organs under normal circumstances. Chemokines are chemotactic cytokines that form a very large and diverse group of secreted proteins that have many functions both in processes that maintain homeostasis but also in inflammatory states. Production of some chemokines also has a major effect on graft rejection. Further understanding of the mechanisms involved in the acute rejection chemokine could contribute to improving treatment steps in transplantology. In this diploma thesis, serum chemokine levels were monitored in renal transplant patients, but these measurements did not show significant dynamics. Furthermore, the effect of pro- inflammatory cytokines on the release of chemokines from renal epithelial cells and monocytes was studied. Experiments were performed to monitor the levels of individual chemokines such as ENA-78, IL-8, MCP-1, MIP-1β, RANTES, GRO-α, THP-1 (monocyte/macrophage cell line), RPTEC (renal epithelial cells of proximal tubules) and RA (renal cell tumor lines). TNF-α had an effect on the...

Background Quantifying joint deformity in people with rheumatoid arthritis (RA) and psoriatic arthritis (PsA), using high resolution peripheral quantitative computed tomography (HR-pQCT), remains problematic because it is difficult to estimate where the healthy joint surface would have been. Methods The second metacarpophalangeal of RA, PsA and healthy subjects were imaged with HR-pQCT. Using the bone surfaces of the healthy cohort as a reference, the method predicted the healthy surface of each individual diseased bone surface. Quantifiable outcomes were measured based on differences between the predicted healthy surface and the actual diseased surface. Sensitivity studies were conducted to measure precision, and the algorithm was validated against artificially created deformities with known geometries. Results Subjects with PsA and RA had significantly greater occurrences of erosion based surface outcomes than the healthy cohort. Sensitivity analyses revealed precision errors of up to 0.26 mm. Validating the algorithm showed an average accuracy error of 0.12 mm (4%) for detecting erosions and 0.27 mm (20%) for detecting periosteal bone growths. Conclusions The new method allows for visualization and quantification of surface changes within the affected joint by identifying areas of erosion and periosteal bone formation. Surface based outcomes are a novel way to interpret and further quantify articular bone changes affected by PsA and RA.

Cette recherche est basée sur une étude numérique de performances thermiques d'un habitat bioclimatique. Dans cette étude, nous avons considérés deux habitats bioclimatiques, l'un concernant un habitat classique de toiture en tôles d'aluminium, de faux plafond en laine de bois et le second, un habitat intégrant du panneau de MCP qui sépare la toiture en tuiles transparentes de l'enceinte parallélépipédique. Les équations de transfert de chaleur dans l'habitat sont basées sur la méthode nodale et sont déduites d'un bilan thermique établi pour les différents composants de l'habitat. Les transferts de chaleur dans l'unité de stockage sont axées sur la méthode enthalpique et purement conductif. Elles sont résolues par une méthode implicite aux différences finies et les algorithmes de Gauss et de Thomas. Nous avons analysé l'influence de certains paramètres tels que : le flux solaire, l'épaisseur du mur, la température maximale et minimale, et le taux de renouvellement d'air sur les distributions de températures des composants de l'habitat et de l'unité de stockage, les efficacités thermiques de stockage et de déstockage de l'unité de stockage. Une modélisation des phénomènes de transfert de chaleur dans l'habitat et dans l'unité de stockage est présentée, complétée par une simulation du fonctionnement du système basée sur les notions de journée type à travers les données météorologiques de la région de Ouagadougou et terminé par une analyse technico-économique. / This research is based on a numerical study of thermal performances of a bioclimatic habitat. In this study, we considered two bioclimatic habitats, one concerning a conventional aluminum roofing habitat, wood-wool false ceilings, and the second, a habitat incorporating a MCP panel that separates the roof into tiles transparent parallelepipedic enclosure. The heat transfer equations in the habitat are based on the nodal method and are deduced from a heat balance established for the different components of the habitat. The heat transfers in the storage unit are focused on the enthalpy and purely conductive method. They are solved by an implicit finite difference method and the Gauss and Thomas algorithms. We analyzed the influence of certain parameters such as: solar flux, wall thickness, maximum and minimum temperature, and the rate of air exchange on the temperature distributions of the components of the habitat and water. Storage unit, the thermal efficiencies of storage and retrieval of the storage unit. A modeling of the heat transfer phenomena in the habitat and in the storage unit is presented, completed by a simulation of the functioning of the system based on the notions of typical day through the meteorological data of the region of Ouagadougou and ended by a technical and economic analysis.

Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores. Energia. Faculdade de Engenharia. Universidade do Porto. 2010

Previous studies demonstrated that intravenous administration of human umbilical cord blood (HUCB) cells could improve behavioral and neurological recovery of stroked animals following middle cerebral artery occlusion (MCAO). In addition, HUCB cell recipients had less of an inflammatory response with less leukocyte infiltration. In these studies we explored how HUCB cells change the inflammatory response of neurons, astrocytes, and microglia to hypoxia/ischemia. Initiation of the inflammatory response occurs with the expression of chemokines. We determined that monocyte chemoattractant protein-1 (MCP-1) and macrophage inflammatory protein 1alph (MIP-1a), which are upregulated in the brain early after a stroke, induce migration of HUCB cells to the site of injury. Neutralizing these chemokines with antibodies prevented migration in an in vitro migration assay. We next explored the interaction of the whole HUCB mononuclear cell fraction, as well as subpopulations from within the mononuclear fraction (T cell alone, B cell alone, and monocytes/macrophage alone) with cultures of enriched neurons, astrocytes or microglia exposed to hypoxia in an oxygen, glucose deprivation paradigm. We showed that HUCB cells increased the cell viability of neurons and astrocytes, while decreasing cell viability of microglia. There was also a change in the cytokine secretion profile from the cells exposed to HUCB cells under hypoxic conditions. These results suggested that chemokines, MCP-1 and MIP-1a increased in stroked brain, and they played an important role in recruitment of HUCB into the CNS after intravenous administration. Once inside the brain, HUCB could suppress the immune response by promoting microglial death and modulating the function of astrocytes. In addition, HUCB cells provide neuron protection against the injury caused by stroke. However, it is unlikely to contribute the effect of HUCB to a single population of HUCB.

Electronic cigarettes have grown in popularity across the U.S. and concerns have been raised about their abuse liability. The purpose of the current study was to evaluate and compare the abuse liability of an electronic cigarette with and without nicotine to a nicotine inhaler (the Nicotrol inhaler) and participants’ own brand of cigarettes. A total of 24 smokers attended four sessions in which the abuse liability of each product was examined using the Multiple-Choice Procedure (MCP), nicotine delivery, nicotine abstinence symptom suppression, and subjective reinforcing effects. Results revealed that the nicotine containing and non-nicotine containing electronic cigarette had a higher reinforcing efficacy on the MCP than the nicotine inhaler, but on average had a lower reinforcing efficacy than participants own brand of cigarettes. The nicotine containing electronic cigarette delivered nicotine to participants in amounts that did not differ significantly from participants’ own brand of cigarettes. The electronic cigarette with nicotine reduced nicotine abstinence symptoms to a greater degree than the electronic cigarette without nicotine, and both electronic cigarettes were rated as subjectively more reinforcing than the inhaler but less reinforcing than participants’ own brand of cigarettes. In sum, the results from this study suggest that the electronic cigarette examined had a moderate level of abuse liability that was higher than an FDA-approved nicotine inhaler but lower than traditional cigarettes. Furthermore, findings also suggest that electronic cigarette abuse liability may extend beyond factors related to nicotine delivery.

Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.

No description available.

AEGIS (Antimatter Experiment, Gravity, Interferometry and Spectroscopy) isan experiment under development at CERN which will measure earth's gravitationalforce on antimatter. This will be done by creating a horizontal pulsedbeam of low energy antihydrogen, an atom consisting of an antiproton anda positron. The experiment will measure the vertical de ection of the beamthrough which it is possible to calculate the gravitational constant for antimatter.To characterise the production process in the current state of the experimentit is necessary to develop an imaging detector for single excited hydrogenatoms. This thesis covers the design phase of that detector and includes studiesand tests of detector components. Following literature studies, tests and havingdiscarded several potential designs, a baseline design was chosen. The suggesteddetector will contain a set of ionising rings followed by an electron multiplyingmicrochannel plate, a light emitting phosphor screen, a lens system and nallya CCD camera for readout. The detector will be able to detect single hydrogenatoms, measure their time of ight as well as being able to image electronplasmas and measure the time of ight of the initial particles in such a plasma.Tests were made to determine the behaviour of microchannel plates at the lowtemperatures used in the experiment. Especially, the resistance and multiplicationfactor of the microchannel plates have been measured at temperaturesdown to 14 K. / AEGIS

Under deregulated electric market, electricity price is no longer set by the monopoly utility company rather it responds to the market and operating conditions. Offering the right amount of electricity at the right time with the right bidding price has become the key for utility companies pursuing maximum profits under deregulated electricity market. Therefore, electricity market clearing price (MCP) forecasting became essential for decision making, scheduling and bidding strategy planning purposes. However, forecasting electricity MCP is a very difficult problem due to uncertainties associated with input variables.<p> Neural network based approach promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. Although there are several techniques available for short-term MCP forecasting, very little has been done to do mid-term MCP forecasting. Two new artificial neural networks have been proposed and reported in this thesis that can be utilized to forecast mid-term daily peak and mid-term hourly electricity MCP. The proposed neural networks can simulate the electricity MCP with electricity hourly demand, electricity daily peak demand, natural gas price and precipitation as input variables. Two situations have been considered; electricity MCP forecasting under real deregulated electric market and electricity MCP forecasting under deregulated electric market with perfect competition. The PJM interconnect system has been utilized for numerical results. Techniques have been developed to overcome difficulties in training the neural network and improve the training results.