New insight in the relationship between regional patterns of knee cartilage thickness, osteoarthritis disease severity, and gait mechanics.

To test if the relationship between knee kinetics during walking and regional patterns of cartilage thickness is influenced by disease severity we tested the following hypotheses in a cross-sectional study of medial compartment osteoarthritis (OA) subjects: (1) the peak knee flexion (KFM) and adduction moments (KAM) during walking are associated with regional cartilage thickness and medial-to-lateral cartilage thickness ratios, and (2) the associations between knee moments and cartilage thickness data are dependent on disease severity. Seventy individuals with medial compartment knee OA were studied. Gait analysis was used to determine the knee moments and cartilage thickness was measured from magnetic resonance imaging. Multiple linear regression analyses tested for associations between cartilage thickness and knee kinetics. Medial cartilage thickness and medial-to-lateral cartilage thickness ratios were lower in subjects with greater KAM for specific regions of the femoral condyle and tibial plateau with no associations for KFM in patients of all disease severities. When separated by severity, the association between KAM and cartilage thickness was found only in patients with more severe OA, and KFM was significantly associated with cartilage thickness only for the less severe OA subjects for specific tibial plateau regions. The results support the idea that the KAM is larger in patients with more severe disease and the KFM has greater influence early in the disease process, which may lessen as pain increases with disease severity. Each component influences different regions of cartilage. Thus the relative contributions of both KAM and KFM should be considered when evaluating gait mechanics and the influence of any intervention for knee OA.

Regional differences of physical activity and sedentary behaviour in Swiss children are not explained by socio-demographics or the built environment.

OBJECTIVE: We evaluated whether regional differences in physical activity (PA) and sedentary behaviour (SB) existed along language boundaries within Switzerland and whether potential differences would be explained by socio-demographics or environmental characteristics. METHODS: We combined data of 611 children aged 4 to 7 years from four regional studies. PA and SB were assessed by accelerometers. Information about the socio-demographic background was obtained by questionnaires. Objective neighbourhood attributes could be linked to home addresses. Multivariate regression models were used to test associations between PA and SB and socio-demographic characteristics and neighbourhood attributes. RESULTS: Children from the German compared to the French-speaking region were more physically active and less sedentary (by 10-15 %, p < 0.01). Although German-speaking children lived in a more favourable environment and a higher socioeconomic neighbourhood (differences p < 0.001), these characteristics did not explain the differences in PA behaviour between French and German speaking. CONCLUSIONS: Factors related to the language region, which might be culturally rooted were among the strongest correlates of PA and SB among Swiss children, independent of individual, social and environmental factors.

The composition of airborne and grain-dust fungal communities is shaped at regional scale by plant genotypes and farming practices

Chronic exposure to airborne fungi has been associated with different respiratory symptoms and pathologies in occupational populations, such as grain workers. However, the homogeneity in the fungal species composition of these bioaerosols on a large geographical scale and the different drivers that shape these fungal communities remain unclear. In this study, the diversity of fungi in grain dust and in the aerosols released during harvesting was determined across 96 sites at a geographical scale of 560 km(2) along an elevation gradient of 500 m by tag-encoded 454-pyrosequencing of the internal transcribed spacer (ITS) sequences. Associations between the structure of fungal communities in the grain dust and different abiotic (farming system, soil characteristics, geographic and climatic parameters) and biotic (wheat cultivar, previous crop culture) factors were explored. These analyses revealed a strong relationship between the airborne and grain dust fungal communities and showed the presence of allergenic and mycotoxigenic species in most samples, which highlights the potential contribution of these fungal species to work-related respiratory symptoms of grain workers. The farming system was the major driver of the alpha and beta phylogenetic diversity of fungal communities. In addition, elevation and soil CaCO3 concentrations shaped the alpha diversity whereas wheat cultivar, cropping history and the number of freezing days per year shaped the taxonomic beta diversity of these communities.

Predicted decrease in global climate suitability masks regional complexity of invasive fruit fly species response to climate change

Climate change affects the rate of insect invasions as well as the abundance, distribution and impacts of such invasions on a global scale. Among the principal analytical approaches to predicting and understanding future impacts of biological invasions are Species Distribution Models (SDMs), typically in the form of correlative Ecological Niche Models (ENMs). An underlying assumption of ENMs is that species-environment relationships remain preserved during extrapolations in space and time, although this is widely criticised. The semi-mechanistic modelling platform, CLIMEX, employs a top-down approach using species ecophysiological traits and is able to avoid some of the issues of extrapolation, making it highly applicable to investigating biological invasions in the context of climate change. The tephritid fruit flies (Diptera: Tephritidae) comprise some of the most successful invasive species and serious economic pests around the world. Here we project 12 tephritid species CLIMEX models into future climate scenarios to examine overall patterns of climate suitability and forecast potential distributional changes for this group. We further compare the aggregate response of the group against species-specific responses. We then consider additional drivers of biological invasions to examine how invasion potential is influenced by climate, fruit production and trade indices. Considering the group of tephritid species examined here, climate change is predicted to decrease global climate suitability and to shift the cumulative distribution poleward. However, when examining species-level patterns, the predominant directionality of range shifts for 11 of the 12 species is eastward. Most notably, management will need to consider regional changes in fruit fly species invasion potential where high fruit production, trade indices and predicted distributions of these flies overlap.

From Regional Landslide Detection to Site-Specific Slope Deformation Monitoring and Modelling Based on Active Remote Sensors

Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales. At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale. At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures. To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses.