An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

Ultra-high-resolution 3D imaging of atherosclerosis in mice with synchrotron differential phase contrast: a proof of concept study.

The goal of this study was to investigate the performance of 3D synchrotron differential phase contrast (DPC) imaging for the visualization of both macroscopic and microscopic aspects of atherosclerosis in the mouse vasculature ex vivo. The hearts and aortas of 2 atherosclerotic and 2 wild-type control mice were scanned with DPC imaging with an isotropic resolution of 15 μm. The coronary artery vessel walls were segmented in the DPC datasets to assess their thickness, and histological staining was performed at the level of atherosclerotic plaques. The DPC imaging allowed for the visualization of complex structures such as the coronary arteries and their branches, the thin fibrous cap of atherosclerotic plaques as well as the chordae tendineae. The coronary vessel wall thickness ranged from 37.4 ± 5.6 μm in proximal coronary arteries to 13.6 ± 3.3 μm in distal branches. No consistent differences in coronary vessel wall thickness were detected between the wild-type and atherosclerotic hearts in this proof-of-concept study, although the standard deviation in the atherosclerotic mice was higher in most segments, consistent with the observation of occasional focal vessel wall thickening. Overall, DPC imaging of the cardiovascular system of the mice allowed for a simultaneous detailed 3D morphological assessment of both large structures and microscopic details.

Improvement of allocentric spatial memory resolution in children from 2 to 4 years of age

Allocentric spatial memory, the memory for locations coded in relation to objects comprising our environment, is a fundamental component of episodic memory and is dependent on the integrity of the hippocampal formation in adulthood. Previous research from different laboratories reported that basic allocentric spatial memory abilities are reliably observed in children after 2 years of age. Based on work performed in monkeys and rats, we had proposed that the functional maturation of direct entorhinal cortex projections to the CA1 field of the hippocampus might underlie the emergence of basic allocentric spatial memory. We also proposed that the protracted development of the dentate gyrus and its projections to the CA3 field of the hippocampus might underlie the development of high-resolution allocentric spatial memory capacities, based on the essential contribution of these structures to the process known as pattern separation. Here, we present an experiment designed to assess the development of spatial pattern separation capacities and its impact on allocentric spatial memory performance in children from 18 to 48 months of age. We found that: (1) allocentric spatial memory performance improved with age, (2) as compared to younger children, a greater number of children older than 36 months advanced to the final stage requiring the highest degree of spatial resolution, and (3) children that failed at different stages exhibited difficulties in discriminating locations that required higher spatial resolution abilities. These results are consistent with the hypothesis that improvements in human spatial memory performance might be linked to improvements in pattern separation capacities.

Assessing the use of very high resolution data to predict species distribution in a mountain environment

Nowadays, Species Distribution Models (SDMs) are a widely used tool. Using different statistical approaches these models reconstruct the realized niche of a species using presence data and a set of variables, often topoclimatic. There utilization range is quite large from understanding single species requirements, to the creation of nature reserve based on species hotspots, or modeling of climate change impact, etc... Most of the time these models are using variables at a resolution of 50km x 50km or 1 km x 1 km. However in some cases these models are used with resolutions below the kilometer scale and thus called high resolution models (100 m x 100 m or 25 m x 25 m). Quite recently a new kind of data has emerged enabling precision up to lm x lm and thus allowing very high resolution modeling. However these new variables are very costly and need an important amount of time to be processed. This is especially the case when these variables are used in complex calculation like models projections over large areas. Moreover the importance of very high resolution data in SDMs has not been assessed yet and is not well understood. Some basic knowledge on what drive species presence-absences is still missing. Indeed, it is not clear whether in mountain areas like the Alps coarse topoclimatic gradients are driving species distributions or if fine scale temperature or topography are more important or if their importance can be neglected when balance to competition or stochasticity. In this thesis I investigated the importance of very high resolution data (2-5m) in species distribution models using either very high resolution topographic, climatic or edaphic variables over a 2000m elevation gradient in the Western Swiss Alps. I also investigated more local responses of these variables for a subset of species living in this area at two precise elvation belts. During this thesis I showed that high resolution data necessitates very good datasets (species and variables for the models) to produce satisfactory results. Indeed, in mountain areas, temperature is the most important factor driving species distribution and needs to be modeled at very fine resolution instead of being interpolated over large surface to produce satisfactory results. Despite the instinctive idea that topographic should be very important at high resolution, results are mitigated. However looking at the importance of variables over a large gradient buffers the importance of the variables. Indeed topographic factors have been shown to be highly important at the subalpine level but their importance decrease at lower elevations. Wether at the mountane level edaphic and land use factors are more important high resolution topographic data is more imporatant at the subalpine level. Finally the biggest improvement in the models happens when edaphic variables are added. Indeed, adding soil variables is of high importance and variables like pH are overpassing the usual topographic variables in SDMs in term of importance in the models. To conclude high resolution is very important in modeling but necessitate very good datasets. Only increasing the resolution of the usual topoclimatic predictors is not sufficient and the use of edaphic predictors has been highlighted as fundamental to produce significantly better models. This is of primary importance, especially if these models are used to reconstruct communities or as basis for biodiversity assessments. -- Ces dernières années, l'utilisation des modèles de distribution d'espèces (SDMs) a continuellement augmenté. Ces modèles utilisent différents outils statistiques afin de reconstruire la niche réalisée d'une espèce à l'aide de variables, notamment climatiques ou topographiques, et de données de présence récoltées sur le terrain. Leur utilisation couvre de nombreux domaines allant de l'étude de l'écologie d'une espèce à la reconstruction de communautés ou à l'impact du réchauffement climatique. La plupart du temps, ces modèles utilisent des occur-rences issues des bases de données mondiales à une résolution plutôt large (1 km ou même 50 km). Certaines bases de données permettent cependant de travailler à haute résolution, par conséquent de descendre en dessous de l'échelle du kilomètre et de travailler avec des résolutions de 100 m x 100 m ou de 25 m x 25 m. Récemment, une nouvelle génération de données à très haute résolution est apparue et permet de travailler à l'échelle du mètre. Les variables qui peuvent être générées sur la base de ces nouvelles données sont cependant très coûteuses et nécessitent un temps conséquent quant à leur traitement. En effet, tout calcul statistique complexe, comme des projections de distribution d'espèces sur de larges surfaces, demande des calculateurs puissants et beaucoup de temps. De plus, les facteurs régissant la distribution des espèces à fine échelle sont encore mal connus et l'importance de variables à haute résolution comme la microtopographie ou la température dans les modèles n'est pas certaine. D'autres facteurs comme la compétition ou la stochasticité naturelle pourraient avoir une influence toute aussi forte. C'est dans ce contexte que se situe mon travail de thèse. J'ai cherché à comprendre l'importance de la haute résolution dans les modèles de distribution d'espèces, que ce soit pour la température, la microtopographie ou les variables édaphiques le long d'un important gradient d'altitude dans les Préalpes vaudoises. J'ai également cherché à comprendre l'impact local de certaines variables potentiellement négligées en raison d'effets confondants le long du gradient altitudinal. Durant cette thèse, j'ai pu monter que les variables à haute résolution, qu'elles soient liées à la température ou à la microtopographie, ne permettent qu'une amélioration substantielle des modèles. Afin de distinguer une amélioration conséquente, il est nécessaire de travailler avec des jeux de données plus importants, tant au niveau des espèces que des variables utilisées. Par exemple, les couches climatiques habituellement interpolées doivent être remplacées par des couches de température modélisées à haute résolution sur la base de données de terrain. Le fait de travailler le long d'un gradient de température de 2000m rend naturellement la température très importante au niveau des modèles. L'importance de la microtopographie est négligeable par rapport à la topographie à une résolution de 25m. Cependant, lorsque l'on regarde à une échelle plus locale, la haute résolution est une variable extrêmement importante dans le milieu subalpin. À l'étage montagnard par contre, les variables liées aux sols et à l'utilisation du sol sont très importantes. Finalement, les modèles de distribution d'espèces ont été particulièrement améliorés par l'addition de variables édaphiques, principalement le pH, dont l'importance supplante ou égale les variables topographique lors de leur ajout aux modèles de distribution d'espèces habituels.

Very high-resolution digital elevation models: are multi-scale-derived variables ecologically relevant?

1. Digital elevation models (DEMs) are often used in landscape ecology to retrieve elevation or first derivative terrain attributes such as slope or aspect in the context of species distribution modelling. However, DEM-derived variables are scale-dependent and, given the increasing availability of very high-resolution (VHR) DEMs, their ecological relevancemust be assessed for different spatial resolutions. 2. In a study area located in the Swiss Western Alps, we computed VHR DEMs-derived variables related to morphometry, hydrology and solar radiation. Based on an original spatial resolution of 0.5 m, we generated DEM-derived variables at 1, 2 and 4 mspatial resolutions, applying a Gaussian Pyramid. Their associations with local climatic factors, measured by sensors (direct and ambient air temperature, air humidity and soil moisture) as well as ecological indicators derived fromspecies composition, were assessed with multivariate generalized linearmodels (GLM) andmixed models (GLMM). 3. Specific VHR DEM-derived variables showed significant associations with climatic factors. In addition to slope, aspect and curvature, the underused wetness and ruggedness indices modelledmeasured ambient humidity and soilmoisture, respectively. Remarkably, spatial resolution of VHR DEM-derived variables had a significant influence on models' strength, with coefficients of determination decreasing with coarser resolutions or showing a local optimumwith a 2 mresolution, depending on the variable considered. 4. These results support the relevance of using multi-scale DEM variables to provide surrogates for important climatic variables such as humidity, moisture and temperature, offering suitable alternatives to direct measurements for evolutionary ecology studies at a local scale.

Predicting richness and composition in mountain insect communities at high resolution: a new test of the SESAM framework

Aim The aim of this study was to test different modelling approaches, including a new framework, for predicting the spatial distribution of richness and composition of two insect groups. Location The western Swiss Alps. Methods We compared two community modelling approaches: the classical method of stacking binary prediction obtained fromindividual species distribution models (binary stacked species distribution models, bS-SDMs), and various implementations of a recent framework (spatially explicit species assemblage modelling, SESAM) based on four steps that integrate the different drivers of the assembly process in a unique modelling procedure. We used: (1) five methods to create bS-SDM predictions; (2) two approaches for predicting species richness, by summing individual SDM probabilities or by modelling the number of species (i.e. richness) directly; and (3) five different biotic rules based either on ranking probabilities from SDMs or on community co-occurrence patterns. Combining these various options resulted in 47 implementations for each taxon. Results Species richness of the two taxonomic groups was predicted with good accuracy overall, and in most cases bS-SDM did not produce a biased prediction exceeding the actual number of species in each unit. In the prediction of community composition bS-SDM often also yielded the best evaluation score. In the case of poor performance of bS-SDM (i.e. when bS-SDM overestimated the prediction of richness) the SESAM framework improved predictions of species composition. Main conclusions Our results differed from previous findings using community-level models. First, we show that overprediction of richness by bS-SDM is not a general rule, thus highlighting the relevance of producing good individual SDMs to capture the ecological filters that are important for the assembly process. Second, we confirm the potential of SESAM when richness is overpredicted by bS-SDM; limiting the number of species for each unit and applying biotic rules (here using the ranking of SDM probabilities) can improve predictions of species composition

Précarité et problèmes cutanés [Skin problems associated with poor living conditions].

Les personnes vivant dans une situation de précarité sont susceptibles de développer un large éventail de problèmes médicaux et les atteintes cutanées sont très fréquentes. Nous présentons quatre situations cliniques de problèmes cutanés fréquemment retrouvés au sein des populations précaires. Leurs diagnostic et prise en charge précoces sont essentiels pour en prévenir l'ultérieure dissémination dans des contextes de promiscuité. People living in poor conditions are at high risk of developing different medical diseases of which dermatological diseases are very common. We present 4 clinical cases of skin diseases, which are the most prevalent amongst the majority of socially and economically vulnerable patients. Early diagnosis and appropriate treatment are of paramount importance, in order to avoid their spread in close- knit communities where these patients often live.

Delirium in the elderly: Current problems with increasing geriatric age.

Delirium is an acute disorder of attention and cognition seen relatively commonly in people aged 65 yr or older. The prevalence is estimated to be between 11 and 42 per cent for elderly patients on medical wards. The prevalence is also high in nursing homes and long term care (LTC) facilities. The consequences of delirium could be significant such as an increase in mortality in the hospital, long-term cognitive decline, loss of autonomy and increased risk to be institutionalized. Despite being a common condition, it remains under-recognised, poorly understood and not adequately managed. Advanced age and dementia are the most important risk factors. Pain, dehydration, infections, stroke and metabolic disturbances, and surgery are the most common triggering factors. Delirium is preventable in a large proportion of cases and therefore, it is also important from a public health perspective for interventions to reduce further complications and the substantial costs associated with these. Since the aetiology is, in most cases, multfactorial, it is important to consider a multi-component approach to management, both pharmacological and non-pharmacological. Detection and treatment of triggering causes must have high priority in case of delirium. The aim of this review is to highlight the importance of delirium in the elderly population, given the increasing numbers of ageing people as well as increasing geriatric age.

Imaging the time-integrated cerebral metabolic activity with subcellular resolution through nanometer-scale detection of biosynthetic products deriving from (13)C-glucose.

Glucose is the primary source of energy for the brain but also an important source of building blocks for proteins, lipids, and nucleic acids. Little is known about the use of glucose for biosynthesis in tissues at the cellular level. We demonstrate that local cerebral metabolic activity can be mapped in mouse brain tissue by quantitatively imaging the biosynthetic products deriving from [U-(13)C]glucose metabolism using a combination of in situ electron microscopy and secondary ion mass-spectroscopy (NanoSIMS). Images of the (13)C-label incorporated into cerebral ultrastructure with ca. 100nm resolution allowed us to determine the timescale on which the metabolic products of glucose are incorporated into different cells, their sub-compartments and organelles. These were mapped in astrocytes and neurons in the different layers of the motor cortex. We see evidence for high metabolic activity in neurons via the nucleus (13)C enrichment. We observe that in all the major cell compartments, such as e.g. nucleus and Golgi apparatus, neurons incorporate substantially higher concentrations of (13)C-label than astrocytes.

Latent Class Analysis of Gambling Activities in a Sample of Young Swiss Men : Association with Gambling Problems, Substance Use Outcomes, Personality Traits and Coping Strategies.

The study aimed to identify different patterns of gambling activities (PGAs) and to investigate how PGAs differed in gambling problems, substance use outcomes, personality traits and coping strategies. A representative sample of 4989 young Swiss males completed a questionnaire assessing seven distinct gambling activities, gambling problems, substance use outcomes, personality traits and coping strategies. PGAs were identified using latent class analysis (LCA). Differences between PGAs in gambling and substance use outcomes, personality traits and coping strategies were tested. LCA identified six different PGAs. With regard to gambling and substance use outcomes, the three most problematic PGAs were extensive gamblers, followed by private gamblers, and electronic lottery and casino gamblers, respectively. By contrast, the three least detrimental PGAs were rare or non-gamblers, lottery only gamblers and casino gamblers. With regard to personality traits, compared with rare or non-gamblers, private and casino gamblers reported higher levels of sensation seeking. Electronic lottery and casino gamblers, private gamblers and extensive gamblers had higher levels of aggression-hostility. Extensive and casino gamblers reported higher levels of sociability, whereas casino gamblers reported lower levels of anxiety-neuroticism. Extensive gamblers used more maladaptive and less adaptive coping strategies than other groups. Results suggest that gambling is not a homogeneous activity since different types of gamblers exist according to the PGA they are engaged in. Extensive gamblers, electronic and casino gamblers and private gamblers may have the most problematic PGAs. Personality traits and coping skills may predispose individuals to PGAs associated with more or less negative outcomes.