An optimized in vitro model of the respiratory tract wall to study particle cell interactions

As a part of the respiratory tissue barrier, lung epithelial cells play an important role against the penetration of the body by inhaled particulate foreign materials. In most cell culture models, which are designed to study particle-cell interactions, the cells are immersed in medium. This does not reflect the physiological condition of lung epithelial cells which are exposed to air, separated from it only by a very thin liquid lining layer with a surfactant film at the air-liquid interface. In this study, A549 epithelial cells were grown on microporous membranes in a two chamber system. After the formation of a confluent monolayer the cells were exposed to air. The morphology of the cells and the expression of tight junction proteins were studied with confocal laser scanning and transmission electron microscopy. Air-exposed cells maintained monolayer structure for 2 days, expressed tight junctions and developed transepithelial electrical resistance. Surfactant was produced and released at the apical side of the air-exposed epithelial cells. In order to study particle-cell interactions fluorescent 1 microm polystyrene particles were sprayed over the epithelial surface. After 4 h, 8.8% of particles were found inside the epithelium. This fraction increased to 38% after 24 h. During all observations, particles were always found in the cells but never between them. In this study, we present an in vitro model of the respiratory tract wall consisting of air-exposed lung epithelial cells covered by a liquid lining layer with a surfactant film to study particle-cell interactions.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

A BAYESIAN HIERARCHICAL FRAMEWORK FOR SPATIAL MODELING OF fMRI DATA

Functional neuroimaging techniques enable investigations into the neural basis of human cognition, emotions, and behaviors. In practice, applications of functional magnetic resonance imaging (fMRI) have provided novel insights into the neuropathophysiology of major psychiatric,neurological, and substance abuse disorders, as well as into the neural responses to their treatments. Modern activation studies often compare localized task-induced changes in brain activity between experimental groups. One may also extend voxel-level analyses by simultaneously considering the ensemble of voxels constituting an anatomically defined region of interest (ROI) or by considering means or quantiles of the ROI. In this work we present a Bayesian extension of voxel-level analyses that offers several notable benefits. First, it combines whole-brain voxel-by-voxel modeling and ROI analyses within a unified framework. Secondly, an unstructured variance/covariance for regional mean parameters allows for the study of inter-regional functional connectivity, provided enough subjects are available to allow for accurate estimation. Finally, an exchangeable correlation structure within regions allows for the consideration of intra-regional functional connectivity. We perform estimation for our model using Markov Chain Monte Carlo (MCMC) techniques implemented via Gibbs sampling which, despite the high throughput nature of the data, can be executed quickly (less than 30 minutes). We apply our Bayesian hierarchical model to two novel fMRI data sets: one considering inhibitory control in cocaine-dependent men and the second considering verbal memory in subjects at high risk for Alzheimer’s disease. The unifying hierarchical model presented in this manuscript is shown to enhance the interpretation content of these data sets.

BIVARIATE BINOMIAL SPATIAL MODELLING LOA loa PREVALENCE IN TROPICAL AFRICA

We present a state-of-the-art application of smoothing for dependent bivariate binomial spatial data to Loa loa prevalence mapping in West Africa. This application is special because it starts with the non-spatial calibration of survey instruments, continues with the spatial model building and assessment and ends with robust, tested software that will be used by the field scientists of the World Health Organization for online prevalence map updating. From a statistical perspective several important methodological issues were addressed: (a) building spatial models that are complex enough to capture the structure of the data but remain computationally usable; (b)reducing the computational burden in the handling of very large covariate data sets; (c) devising methods for comparing spatial prediction methods for a given exceedance policy threshold.

Endothelial survival factors and spatial completion, but not pericyte coverage of retinal capillaries determine vessel plasticity

Pericyte loss and capillary regression are characteristic for incipient diabetic retinopathy. Pericyte recruitment is involved in vessel maturation, and ligand-receptor systems contributing to pericyte recruitment are survival factors for endothelial cells in pericyte-free in vitro systems. We studied pericyte recruitment in relation to the susceptibility toward hyperoxia-induced vascular remodeling using the pericyte reporter X-LacZ mouse and the mouse model of retinopathy of prematurity (ROP). Pericytes were found in close proximity to vessels, both during formation of the superficial and the deep capillary layers. When exposure of mice to the ROP was delayed by 24 h, i.e., after the deep retinal layer had formed [at postnatal (p) day 8], preretinal neovascularizations were substantially diminished at p18. Mice with a delayed ROP exposure had 50% reduced avascular zones. Formation of the deep capillary layers at p8 was associated with a combined up-regulation of angiopoietin-1 and PDGF-B, while VEGF was almost unchanged during the transition from a susceptible to a resistant capillary network. Inhibition of Tie-2 function either by soluble Tie-2 or by a sulindac analog, an inhibitor of Tie-2 phosphorylation, resensitized retinal vessels to neovascularizations due to a reduction of the deep capillary network. Inhibition of Tie-2 function had no effect on pericyte recruitment. Our data indicate that the final maturation of the retinal vasculature and its resistance to regressive signals such as hyperoxia depend on the completion of the multilayer structure, in particular the deep capillary layers, and are independent of the coverage by pericytes.

Fine-scale genetic structure and dispersal in the common vole (Microtus arvalis)

The genetic structure and demography of local populations is tightly linked to the rate and scale of dispersal. Dispersal parameters are notoriously difficult to determine in the field, and remain often completely unknown for smaller organisms. In this study, we investigate spatial and temporal genetic structure in relation to dispersal patterns among local populations of the probably most abundant European mammals, the common vole (Microtus arvalis). Voles were studied in six natural populations at distances of 0.4-2.5 km in three different seasons (fall, spring, summer) corresponding to different life-history stages. Field observations provided no direct evidence for movements of individuals between populations. The analysis of 10 microsatellite markers revealed a persistent overall genetic structure among populations of 2.9%, 2.5% and 3% FST in the respective season. Pairwise comparisons showed that even the closest populations were significantly differentiated from each other in each season, but there was no evidence for temporal differentiation within populations or isolation by distance among populations. Despite significant genetic structure, assignment analyses identified a relatively high proportion of individuals as being immigrants for the population where they were captured. The immigration rate was not significantly lower for females than for males. We suggest that a generally low and sex-dependent effective dispersal rate as the consequence of only few immigrants reproducing successfully in the new populations together with the social structure within populations may explain the maintenance of genetic differentiation among populations despite migration.

From Statistical Data to Spatial Knowledge - informing decision making in Vietnam

Vietnam has developed rapidly over the past 15 years. However, progress was not uniformly distributed across the country. Availability, adequate visualization and analysis of spatially explicit data on socio-economic and environmental aspects can support both research and policy towards sustainable development. Applying appropriate mapping techniques allows gleaning important information from tabular socio-economic data. Spatial analysis of socio-economic phenomena can yield insights into locally-specifi c patterns and processes that cannot be generated by non-spatial applications. This paper presents techniques and applications that develop and analyze spatially highly disaggregated socioeconomic datasets. A number of examples show how such information can support informed decisionmaking and research in Vietnam.

Optimized spectrally selective steady-state free precession sequences for cartilage imaging at ultra-high fields

OBJECT: Fat suppressed 3D steady-state free precession (SSFP) sequences are of special interest in cartilage imaging due to their short repetition time in combination with high signal-to-noise ratio. At low-to-high fields (1.5-3.0 T), spectral spatial (spsp) radio frequency (RF) pulses perform superiorly over conventional saturation of the fat signal (FATSAT pulses). However, ultra-high fields (7.0 T and more) may offer alternative fat suppression techniques as a result of the increased chemical shift. MATERIALS AND METHODS: Application of a single, frequency selective, RF pulse is compared to spsp excitation for water (or fat) selective imaging at 7.0 T. RESULTS: For SSFP, application of a single frequency selective RF pulse for selective water or fat excitation performs beneficially over the commonly applied spsp RF pulses. In addition to the overall improved fat suppression, the application of single RF pulses leads to decreased power depositions, still representing one of the major restrictions in the design and application of many pulse sequences at ultra-high fields. CONCLUSION: The ease of applicability and implementation of single frequency selective RF pulses at ultra-high-fields might be of great benefit for a vast number of applications where fat suppression is desirable or fat-water separation is needed for quantification purposes.

Landscape and forest structure at moose mortality sites on Isle Royale National Park. A LiDAR based assessment

Landscape structure and heterogeneity play a potentially important, but little understood role in predator-prey interactions and behaviourally-mediated habitat selection. For example, habitat complexity may either reduce or enhance the efficiency of a predator's efforts to search, track, capture, kill and consume prey. For prey, structural heterogeneity may affect predator detection, avoidance and defense, escape tactics, and the ability to exploit refuges. This study, investigates whether and how vegetation and topographic structure influence the spatial patterns and distribution of moose (Alces alces) mortality due to predation and malnutrition at the local and landscape levels on Isle Royale National Park. 230 locations where wolves (Canis lupus) killed moose during the winters between 2002 and 2010, and 182 moose starvation death sites for the period 1996-2010, were selected from the extensive Isle Royale Wolf-Moose Project carcass database. A variety of LiDAR-derived metrics were generated and used in an algorithm model (Random Forest) to identify, characterize, and classify three-dimensional variables significant to each of the mortality classes. Furthermore, spatial models to predict and assess the likelihood at the landscape scale of moose mortality were developed. This research found that the patterns of moose mortality by predation and malnutrition across the landscape are non-random, have a high degree of spatial variability, and that both mechanisms operate in contexts of comparable physiographic and vegetation structure. Wolf winter hunting locations on Isle Royale are more likely to be a result of its prey habitat selection, although they seem to prioritize the overall areas with higher moose density in the winter. Furthermore, the findings suggest that the distribution of moose mortality by predation is habitat-specific to moose, and not to wolves. In addition, moose sex, age, and health condition also affect mortality site selection, as revealed by subtle differences between sites in vegetation heights, vegetation density, and topography. Vegetation density in particular appears to differentiate mortality locations for distinct classes of moose. The results also emphasize the significance of fine-scale landscape and habitat features when addressing predator-prey interactions. These finer scale findings would be easily missed if analyses were limited to the broader landscape scale alone.

INVESTIGATING THE IMPACTS OF STREAMBED HABITAT HETEROGENEITY ON ECOSYSTEM STRUCTURE AND PROCESSES USING BASIC AND APPLIED PERSPECTIVES

Stream restoration often focuses on increasing habitat heterogeneity to reverse ecosystem degradation. However, the connection between heterogeneity and ecosystem structure and processes is poorly understood. We looked to investigate this interaction from both applied and basic science perspectives. For the applied study, we examined two culvert replacements designed to mimic natural stream channels, to see if they were better at maintaining ecosystem processes within as well as upstream and downstream of culverts compared to non-replaced culverts. We measured three ecosystem processes (nutrient uptake, hydrologic characteristics, and coarse particulate organic matter retention) and found that stream simulation culvert restoration improved organic matter retention within culverts, and that there were no differences in processes measured upstream and downstream of both restoration designs. Our results suggest that measurements of ecosystem processes are more likely to show a response to restoration if they match the scale of the restoration activity. For the basic science study, we quantified the longitudinal spatial heterogeneity of physical and biofilm characteristics at microhabitat to segment scales on streams with different streambed variability. We found that all physical characteristics and biofilm characteristics were spatially independent at the macro-habitat scale and greater. Together, these studies demonstrate the importance of scale in ecological interactions and the value of incorporating considerations of scale into restoration activities.

Spatial and temporal patterns in ungulate-ecosystem interactions

Ungulates are important components of a variety of ecosystems worldwide. This dissertation integrates aspects of ungulate and forest ecology to increase our understanding of how they work together in ways that are of interest to natural resource managers, educators, and those who are simply curious about nature. Although animal ecology and ecosystem ecology are often studied separately, one of the general goals of this dissertation is to examine how they interact across spatial and temporal scales. Forest ecosystems are heterogeneous across a range of scales. Spatial and temporal habitat use patterns of forest ungulates tend to be congregated in patches where food and/or cover are readily available. Ungulates interact with ecosystem processes by selectively foraging on plants and excreting waste products in concentrated patches. Positive feedbacks may develop where these activities increase the value of habitat through soil fertilization or the alteration of plant chemistry and architecture. Heterogeneity in ecosystem processes and plant community structure, observed at both stand and local scales, may be the integrated outcome of feedbacks between ungulate behavior and abiotic resource gradients. The first chapter of this dissertation briefly discusses pertinent background information on ungulate ecology, with a focus on white-tailed deer (Odocoileus virginianus) in the Upper Great Lakes region and moose (Alces acles) in Isle Royale National Park, Michigan, USA. The second chapter demonstrates why ecological context is important for studying ungulate ecology in forest ecosystems. Excluding deer from eastern hemlock (Tsuga canadensis) stands, which deer use primarily as winter cover, resulted in less spatial complexity in soil reactive nitrogen and greater complexity in diffuse light compared to unfenced stands. The spatial patterning of herbaceous-layer cover was more similar to nitrogen where deer were present, and was a combination of nitrogen and light within deer exclosures. This relationship depends on the seasonal timing of deer habitat use because deer fertilize the soil during winter, but leave during the growing season. The third chapter draws upon an eight-year, 39-stand data set of deer fecal pellet counts in hemlock stands to estimate the amount of nitrogen that deer are depositing in hemlock stands each winter. In stands of high winter deer use, deer-excreted nitrogen inputs consistently exceeded those of atmospheric deposition at the stand scale. At the neighborhood scale, deer-excreted nitrogen was often in excess of atmospheric deposition due to the patchy distribution of deer habitat use. Spatial patterns in habitat use were consistent over the eight-year study at both stand and neighborhood scales. The fourth chapter explores how foraging selectivity by moose interacts with an abiotic resource gradient to influence forest structure and composition. Soil depth on Isle Royale varies from east to west according to glacial history. Fir saplings growing in deeper soils on the west side are generally more palatable forage for moose (lower foliar C:N) than those growing in shallower soils on the east side. Therefore, saplings growing in better conditions are less likely to reach the canopy due to moose browsing, and fir is a smaller overstory component on the west side. Lastly, chapter five focuses on issues surrounding eastern hemlock regeneration failure, which is a habitat type that is important to many wildlife species. Increasing hemlock on the landscape is complicated by several factors including disturbance regime and climate change, in addition to the influence of deer.

Looking left with left neglect: the role of spatial attention when active vision selects local image features for fixation

When we actively explore the visual environment, our gaze preferentially selects regions characterized by high contrast and high density of edges, suggesting that the guidance of eye movements during visual exploration is driven to a significant degree by perceptual characteristics of a scene. Converging findings suggest that the selection of the visual target for the upcoming saccade critically depends on a covert shift of spatial attention. However, it is unclear whether attention selects the location of the next fixation uniquely on the basis of global scene structure or additionally on local perceptual information. To investigate the role of spatial attention in scene processing, we examined eye fixation patterns of patients with spatial neglect during unconstrained exploration of natural images and compared these to healthy and brain-injured control participants. We computed luminance, colour, contrast, and edge information contained in image patches surrounding each fixation and evaluated whether they differed from randomly selected image patches. At the global level, neglect patients showed the characteristic ipsilesional shift of the distribution of their fixations. At the local level, patients with neglect and control participants fixated image regions in ipsilesional space that were closely similar with respect to their local feature content. In contrast, when directing their gaze to contralesional (impaired) space neglect patients fixated regions of significantly higher local luminance and lower edge content than controls. These results suggest that intact spatial attention is necessary for the active sampling of local feature content during scene perception.

Potentials and limitations of coordinated spatial and non-spatial information

Information management and geoinformation systems (GIS) have become indispensable in a large majority of protected areas all over the world. These tools are used for management purposes as well as for research and in recent years have become even more important for visitor information, education and communication. This study is divided into two parts: the first part provides a general overview of GIS and information management in a selected number of national park organizations. The second part lists and evaluates the needs of evolving large protected areas in Switzerland. The results show a wide use of GIS and information management tools in well established protected areas. The more isolated use of singular GIS tools has increasingly been replaced by an integrated geoinformation management. However, interview partners pointed out that human resources for GIS in most parks are limited. The interviews also highlight uneven access to national geodata. The view of integrated geoinformation management is not yet fully developed in the park projects in Switzerland. Short-term needs, such as software and data availability, motivate a large number of responses collected within an exhaustive questionnaire. Nevertheless, the need for coordinated action has been identified and should be followed up. The park organizations in North America show how an effective coordination and cooperation might be organized.

Development of a novel material flow simulation model for the integration of spatial and process relevant information

Simulation techniques are almost indispensable in the analysis of complex systems. Materials- and related information flow processes in logistics often possess such complexity. Further problem arise as the processes change over time and pose a Big Data problem as well. To cope with these issues adaptive simulations are more and more frequently used. This paper presents a few relevant advanced simulation models and intro-duces a novel model structure, which unifies modelling of geometrical relations and time processes. This way the process structure and their geometric relations can be handled in a well understandable and transparent way. Capabilities and applicability of the model is also presented via a demonstrational example.