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Brain damage is caused by loss or deterioration of brain cells and it is a prevalent type of injury that may be fatal, or may result in severe impairments, with devastating consequences on the quality of life of survivors. Loss of neural cells may lead to the formation of abnormal brain cavities (aBC), that are most often the result of stroke and traumatic brain injuries (TBI), but can also occur after surgical resection of tumors or abscesses. The chronic debilitating symptoms caused by neuronal damage are currently untreatable and largely depend on the degree and location of damage. In this work, we investigated the potential of neuromodulation as a treatment option, driven in a novel target - directly within the aBC wall, so as to alter aBC-related symptoms, and to improve behavioral outcome after neurological damage. We used a generic model for brain damage, developed in a rat model. A foldable electrode array was implanted against the aBC wall, in a motor cortical rat model. The electrode implant was used both to interact with neural populations as well as record their activity. Much of the current understanding about motor system function is based on correlations between brain and behavioral tasks. Thus, the general objective of this thesis was to develop algorithms that identify behavioral and neural signal features with multiple aims: (i) to validate the aBC wall as a target for recording meaningful brain activity, (ii) to better quantify motor impairments and (iii) to investigate how modulating brain activity can improve behavioral outcome. In a first step, we recorded electrical brain activity, as field potentials (FPs) on the surface of motor cortical aBC of freely moving rats. We showed that FPs are dominated by oscillatory activity in the theta range (4-9 Hz) and gamma range (30-100 Hz) and can be an informative biomarker for behavioral features, as it allowed us to discriminate between behavioral state: active versus resting. In a second step, we analyzed in detail impairment state. We developed an automated computer algorithm for analyzing reaching and grasping in impaired animals, subsequent to induction of a motor cortical aBC. The algorithm automatically tracks the movement of the rat's forelimb using image processing methods. We classified endpoint behavior, achieving accuracy rates of 86%-92%. With this extended analysis we captured perturbation of skill after a motor cortical lesion was induced. Kinematics of reaching revealed that rats developed individual strategies to achieve the task. In a third phase, we used the automatic algorithm to evaluate kinematics and endpoint outcome of skilled reaching during stimulation in different targets within the lesion wall. We stimulated either over the entire 16-electrode array (non-selective stimulation) or over subsets of electrodes (selective stimulation), proving that both strategies could alter kinematics of movement, with selective stimulation being at least as effective as non-selective stimulation. Neurostimulation has been proven effective in the past recent years in treating psychiatric disorders. Finally, we used a rat model of obsessive compulsive disorder (OCD) in which deep brain stimulation was used to diminish compulsive symptoms. We showed that responders to deep brain stimulation presented specific brain modulations in the frequency bands of delta (1- 4 Hz), theta (4-8 Hz), beta (12-30 Hz), and lower gamma (30-45 Hz) that were otherwise not present in the non-responders or in the control subjects. Our strategy is not limited by the cause of insult, be it ischemic stroke or traumatic brain injury, and allows direct interaction with the lesion wall via an invasive array of electrodes that can be used both for stimulation and for recording brain electrical activity. Access to neural activity allowed us to investigate neural mechanisms that may be relevant for impaired brain function, both in rat models of motor disability and psychiatric disorders. Finally, our strategy aims for an individual-focus treatment, that circumvents patient-dependent differences like severity and location of the brain damage.

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Over the past decades the prevalence of pollen allergy has increased. This trend is expected to continue due to ongoing urbanization, climate change and increasing air pollution. In order to mitigate urban heat and improve air quality in the city, urban green space has been promoted. Urban green spaces have been associated with numerous health benefits. Contact with the natural environment strengthens the human microbiome and immune system. Green spaces promote an active lifestyle and provide mental health benefits. By improving the air quality, green spaces can also contribute to better respiratory health. However, urban vegetation is also a source of airborne pollen.The literature provides contradicting results regarding the effects of green space on the health of pollen allergy patients. These contradictions stem from the complex interactions between environmental factors, as well as from a heterogeneity in approaches when it comes to exposure studies. To properly study the health effects from exposure to green space on the health of people with pollen allergy we need detailed spatial data on green space and the allergenic trees within these greenspaces. In addition, we need insights in the effects of local vegetation on local pollen composition. Until now, the majority of exposure studies relied on exposure within various buffers around the residence. Nevertheless, a significant share of exposure takes place outside the residential area and pollen and air pollutant concentrations vary in time and space. In order to define exposure more realistically there is need for a method that can account for the spatiotemporal aspect of personal exposure.Nevertheless, the first step towards an exposure analysis is the generation of a distribution model of potential allergenic trees. For Flanders a database with validated observations of vascular plants at a 1 km resolution is available (Florabank). The observations can be combined with environmental covariates (soil characteristics, land use, habitat type) in a species distribution model. We modelled habitat suitability for 13 wind-pollinated tree genera. Genus-specific thresholds were used to obtain presence-absence maps. By summing the 13 presence-absence maps we obtained a tree diversity map at genus-level. We find that summing binary maps does not result in an overestimation of diversity when the study area is urbanized (Flanders) and the spatial resolution is coarse (1 km). The obtained diversity map can be used to determine exposure to biodiversity in health studies.In a second step, we studied the effects of local vegetation on the pollen composition. Although pollen can travel long distances, local vegetation contributes to local peak concentrations of pollen. Standardized pollen monitoring takes place at roof top level and measures a background level of pollen. Possible local peaks remain undetected, yet contribute to human pollen exposure. By mounting passive samplers at 2 m above the ground in 13 locations in Flanders we aimed to measure local pollen compositions during the tree pollen season (February-May) of 2017. The passive samplers successfully measured local pollen compositions characterized by 12 taxa. We used Non-metric Multidimensional Scaling (NMDS) to characterize each sampling site by its pollen composition. Then we use an indirect gradient analysis to associate the pollen composition with the land cover within a 20, 200, 500, 1000, 2000 and 5000 m radius around the sampling site. We found an urban-rural and wet-dry gradient associated with the first and second NMDS axis. Most of the associations were found for the land cover in a 1000-5000 m radius. This local scale effect is of importance for urban green management: urban forests at the edge of the city contribute to the pollen concentration within the city. In addition, we understand that environmental health studies require sufficiently large exposure radii.Thus, in the residential exposure study we determined garden cover, grassland cover and forest cover within a 1, 2 and 5 km radius around the residence of 157 adults with a tree pollen allergy. The density of allergenic trees (alder, hazel and birch) was derived from the regional forest inventories. We used a generalized linear models with a Poisson distribution to associate residential exposure to mental well-being (standardized questionnaires) and respiratory health (average symptom severity reported in a smartphone application). All green space types were protective for mental well-being, yet a risk factor for symptom severity. The density of allergenic trees in forests was a risk factor for mental well-being as well as symptom severity. We found that green space effects on health became smaller as the exposure radius increased.In an attempt to determine personal exposure more realistically, we used GPS data gathered by a smartphone application. We compared exposure between case-days with severe allergy symptoms and control-days without symptoms. We determined exposure by extracting green space cover, allergenic tree density, birch pollen levels and pollutant levels at the GPS point locations. For each day we could determine the average exposure taking into account spatiotemporal variability. Grassland cover, forest cover, alder density and hazel density protected against severe allergy symptoms. Birch density and birch pollen as well as pollutants (nitrogen dioxide (NO2), ozone (O3), and particulate matter < 10 µm (PM10)) were risk factors for severe allergy symptoms. For GPS tracks that were entirely within Flanders, we could calculate exposure to the tree diversity model at genus level. We found no associations between severe allergy symptoms and alpha-diversity of tree genera.This manuscript shows that adults with a tree pollen allergy experience mental and respiratory health benefits from exposure to green space, given that density of allergenic trees (birch) is low. GPS tracking allowed for a more realistic approximation of personal exposure. Although we did not identify a diversity effect, we do promote biodiverse urban green spaces in order to prevent domination of allergenic vegetation.

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Micro-aggregates have several unique properties that make them suitable for tissue engineering: they are associated with increased cell viability, they enhance multilineage differentiation and they secrete trophic factors with an anti-inflammatory effect. In addition, micro-aggregates have the ability to fuse into one larger structure when brought into close contact. Hence, they are of great interest in bottom-up tissue engineering, in which large heterotypic tissues that mimic the native organisational tissue structure are gradually built up by using small units as building blocks. An important step for the application of micro-aggregates in tissue engineering is a complete understanding of their formation. During this formation, a change in cell morphology, determined by cell contractility and cortical tension, is required. These factors are both determined by the structure and functionality of the cytoskeleton. Therefore, the importance of different components of the cytoskeleton during the aggregation of hPDCs was studied by adding different inhibitors to the medium. In this thesis, Y-27632, a ROCK-inhibitor, and (S)-nitroblebbistatin, an inhibitor of MYH ATPase, were evaluated for their effect on aggregate formation. Two different aggregate sizes were tested since cell number might influence cell aggregation by affecting contact opportunities between cells and cell survival. The dynamics of the aggregation behaviour were captured using time-lapse microscopy. Area and circularity of the aggregates were extracted from the images and analysed using a data-based modelling approach. It is demonstrated that ROCK-inhibitor reduces compaction and slows down the formation of micro-aggregates compared to control conditions. Moreover, the effect of Y-27632 is found to be depended on aggregate size. Experiments with (S)-nitroblebbistatin were not coherent. Consequently, no conclusions concerning the contribution of myosin II to cellular aggregation could be made. In addition to time-lapse microscopy, aggregates treated with ROCK-inhibitor were imaged in confocal microscopy in order to quantify cell viability and visualise the actin network as well as the nucleus. Although this analysis did not reveal any statistically significant results, some clear trends are observed. First of all, it is stated that cells at the boundary have a higher volume compared to central cells. Secondly, it is seen that boundary cells have a tendency to become more spherical as the concentration of Y-27632 is increased. It is believed that a more complete insight in aggregate formation is the first step towards a better process control and thus would enhance the performance of the final engineered tissue.