Drosophilid collection in the Font Groga site, Barcelona (Spain)

During October 23rd and 24th and November 2012 we collected a sample of drosophilids at Font Groga (Barcelona). This site is located on the foothills of the Tibidabo mountain, which is located on the northwest edge of Barcelona and at approximately 400m above sea level. The vegetation is typical for the area, and it is mainly composed of a sparse pine forest (Pinus pinea) with some oaks (Quercus ilex) and Mediterranean brushwood. Flies were netted over 12 baits containing fermenting bananas. A large proportion of D. simulans males was found. The invasive species D. suzukii (Calabria et al. 2010; Cini et al. 2012) was detected in a non-negligible quantity. Taking into account the number of males and females, the estimated Ne for D. suzukii in the Font Groga sample was 33.70. A similar value was obtained for D. subobscura (34.97). Finally, in the study of species diversity the values obtained for H" (Shannon diversity index) and J (Shannon uniformity index) were 0.678 and 0.421, respectively. These estimates are very similar to those obtained in September 2009 in Montpellier by Calabria (2012), who reported H" = 0.679 and J = 0.422, but differ from those reported by the same author in a Font Groga sample of October 2007 (H" = 0.904 and J = 0.505).

Disease profiles of detainees in the Canton of Vaud in Switzerland: gender and age differences in substance abuse, mental health and chronic health conditions.

BACKGROUND: Literature on the disease profile of prisoners that differentiates by age and gender remains sparse. This study aimed to describe the health of correctional inmates in terms of substance abuse problems and mental and somatic health conditions, and compare it by gender and age. METHODS: This study examined cross-sectional data from the Canton of Vaud in Switzerland on the health conditions of detainees who were in prison on January 1, 2011 or entered prison in 2011. Health conditions validated by physician examination were reported using the International Classification of Diseases (ICD) version 10. The analyses were descriptive by groups of prisoners: the entire sample (All), Men, Older adults and Women. RESULTS: A total of 1,664 individuals were included in the analysis. Men comprised 91.5 % of the sample and had a mean age of 33 years. The other 8.5 % were women and had an average age of 39. Older adults (i.e., age 50 and older) represented 7 % of the total sample. Overall, 80 % of inmates were non-Swiss citizens, but the proportion of Swiss prisoners was higher among the older adults (51 %) and women (29 %). Overall, 41 % of inmates self-reported substance abuse problems. Of those, 27 % were being treated by psychiatrists for behavioral disorders related to substance abuse. Chronic infectious diseases were found in 9 % of the prison population. In addition, 27 % of detainees suffered from serious mental health conditions. Gender and age had an influence on the disease profile of this sample: compared to the entire prison population, the older inmates were less likely to misuse illegal drugs and to suffer from communicable infections but exhibited more problems with alcohol and a higher burden of chronic health conditions. Female prisoners were more disposed to mental health problems (including drug abuse) and infectious diseases. In terms of chronic diseases, women suffered from the same conditions as men, but the diseases were more prevalent in women. CONCLUSION: It is important to understand the different disease profiles of prisoners by gender and age, as it helps identify the needs of different groups and tailor age-and gender-specific interventions.

Mechanisms of Antifungal Drug Resistance.

Antifungal therapy is a central component of patient management for acute and chronic mycoses. Yet, treatment choices are restricted because of the sparse number of antifungal drug classes. Clinical management of fungal diseases is further compromised by the emergence of antifungal drug resistance, which eliminates available drug classes as treatment options. Once considered a rare occurrence, antifungal drug resistance is on the rise in many high-risk medical centers. Most concerning is the evolution of multidrug- resistant organisms refractory to several different classes of antifungal agents, especially among common Candida species. The mechanisms responsible are mostly shared by both resistant strains displaying inherently reduced susceptibility and those acquiring resistance during therapy. The molecular mechanisms include altered drug affinity and target abundance, reduced intracellular drug levels caused by efflux pumps, and formation of biofilms. New insights into genetic factors regulating these mechanisms, as well as cellular factors important for stress adaptation, provide a foundation to better understand the emergence of antifungal drug resistance.

Current Sheet Regulation of Solar Near-relativistic Electron Injection Histories

We present a sample of three large near-relativistic (>50 keV) electron events observed in 2001 by both the ACE and the Ulysses spacecraft, when Ulysses was at high-northern latitudes (>60◦) and close to 2 AU. Despite the large latitudinal distance between the two spacecraft, electrons injected near the Sun reached both heliospheric locations. All three events were associated with large solar flares, strong decametric type II radio bursts and accompanied by wide (>212◦) and fast (>1400 km s−1) coronal mass ejections (CMEs). We use advanced interplanetary transport simulations and make use of the directional intensities observed in situ by the spacecraft to infer the electron injection profile close to the Sun and the interplanetary transport conditions at both low and high latitudes. For the three selected events, we find similar interplanetary transport conditions at different heliolatitudes for a given event, with values of the mean free path ranging from 0.04 AU to 0.27 AU. We find differences in the injection profiles inferred for each spacecraft. We investigate the role that sector boundaries of the heliospheric current sheet (HCS) have on determining the characteristics of the electron injection profiles. Extended injection profiles, associated with coronal shocks, are found if the magnetic footpoints of the spacecraft lay in the same magnetic sector as the associated flare, while intermittent sparse injection episodes appear when the spacecraft footpoints are in the opposite sector or a wrap in the HCS bounded the CME structure.

Metabolic connectivity as index of verbal working memory.

Positron emission tomography (PET) data are commonly analyzed in terms of regional intensity, while covariant information is not taken into account. Here, we searched for network correlates of healthy cognitive function in resting state PET data. PET with [(18)F]-fluorodeoxyglucose and a test of verbal working memory (WM) were administered to 35 young healthy adults. Metabolic connectivity was modeled at a group level using sparse inverse covariance estimation. Among 13 WM-relevant Brodmann areas (BAs), 6 appeared to be robustly connected. Connectivity within this network was significantly stronger in subjects with above-median WM performance. In respect to regional intensity, i.e., metabolism, no difference between groups was found. The results encourage examination of covariant patterns in FDG-PET data from non-neurodegenerative populations.

Cognitive anatomy of the temporal lobe: Effect of personality in population with mild cognitive impairment & Functional specialization for memory systems in healthy individuals.

Résumé: L'impact de la maladie d'Alzheimer (MA) est dévastateur pour la vie quotidienne de la personne affectée, avec perte progressive de la mémoire et d'autres facultés cognitives jusqu'à la démence. Il n'existe toujours pas de traitement contre cette maladie et il y a aussi une grande incertitude sur le diagnostic des premiers stades de la MA. La signature anatomique de la MA, en particulier l'atrophie du lobe temporal moyen (LTM) mesurée avec la neuroimagerie, peut être utilisée comme un biomarqueur précoce, in vivo, des premiers stades de la MA. Toutefois, malgré le rôle évident du LMT dans les processus de la mémoire, nous savons que les modèles anatomiques prédictifs de la MA basés seulement sur des mesures d'atrophie du LTM n'expliquent pas tous les cas cliniques. Au cours de ma thèse, j'ai conduit trois projets pour comprendre l'anatomie et le fonctionnement du LMT dans (1) les processus de la maladie et dans (2) les processus de mémoire ainsi que (3) ceux de l'apprentissage. Je me suis intéressée à une population avec déficit cognitif léger (« Mild Cognitive Impairment », MCI), à risque pour la MA. Le but du premier projet était de tester l'hypothèse que des facteurs, autres que ceux cognitifs, tels que les traits de personnalité peuvent expliquer les différences interindividuelles dans le LTM. De plus, la diversité phénotypique des manifestations précliniques de la MA provient aussi d'une connaissance limitée des processus de mémoire et d'apprentissage dans le cerveau sain. L'objectif du deuxième projet porte sur l'investigation des sous-régions du LTM, et plus particulièrement de leur contribution dans différentes composantes de la mémoire de reconnaissance chez le sujet sain. Pour étudier cela, j'ai utilisé une nouvelle méthode multivariée ainsi que l'IRM à haute résolution pour tester la contribution de ces sous-régions dans les processus de familiarité (« ou Know ») et de remémoration (ou « Recollection »). Finalement, l'objectif du troisième projet était de tester la contribution du LTM en tant que système de mémoire dans l'apprentissage et l'interaction dynamique entre différents systèmes de mémoire durant l'apprentissage. Les résultats du premier projet montrent que, en plus du déficit cognitif observé dans une population avec MCI, les traits de personnalité peuvent expliquer les différences interindividuelles du LTM ; notamment avec une plus grande contribution du neuroticisme liée à une vulnérabilité au stress et à la dépression. Mon étude a permis d'identifier un pattern d'anormalité anatomique dans le LTM associé à la personnalité avec des mesures de volume et de diffusion moyenne du tissu. Ce pattern est caractérisé par une asymétrie droite-gauche du LTM et un gradient antéro-postérieur dans le LTM. J'ai interprété ce résultat par des propriétés tissulaires et neurochimiques différemment sensibles au stress. Les résultats de mon deuxième projet ont contribué au débat actuel sur la contribution des sous-régions du LTM dans les processus de familiarité et de remémoration. Utilisant une nouvelle méthode multivariée, les résultats supportent premièrement une dissociation des sous-régions associées aux différentes composantes de la mémoire. L'hippocampe est le plus associé à la mémoire de type remémoration et le cortex parahippocampique, à la mémoire de type familiarité. Deuxièmement, l'activation correspondant à la trace mnésique pour chaque type de mémoire est caractérisée par une distribution spatiale distincte. La représentation neuronale spécifique, « sparse-distributed», associée à la mémoire de remémoration dans l'hippocampe serait la meilleure manière d'encoder rapidement des souvenirs détaillés sans interférer les souvenirs précédemment stockés. Dans mon troisième projet, j'ai mis en place une tâche d'apprentissage en IRM fonctionnelle pour étudier les processus d'apprentissage d'associations probabilistes basé sur le feedback/récompense. Cette étude m'a permis de mettre en évidence le rôle du LTM dans l'apprentissage et l'interaction entre différents systèmes de mémoire comme la mémoire procédurale, perceptuelle ou d'amorçage et la mémoire de travail. Nous avons trouvé des activations dans le LTM correspondant à un processus de mémoire épisodique; les ganglions de la base (GB), à la mémoire procédurale et la récompense; le cortex occipito-temporal (OT), à la mémoire de représentation perceptive ou l'amorçage et le cortex préfrontal, à la mémoire de travail. Nous avons également observé que ces régions peuvent interagir; le type de relation entre le LTM et les GB a été interprété comme une compétition, ce qui a déjà été reporté dans des études récentes. De plus, avec un modèle dynamique causal, j'ai démontré l'existence d'une connectivité effective entre des régions. Elle se caractérise par une influence causale de type « top-down » venant de régions corticales associées avec des processus de plus haut niveau venant du cortex préfrontal sur des régions corticales plus primaires comme le OT cortex. Cette influence diminue au cours du de l'apprentissage; cela pourrait correspondre à un mécanisme de diminution de l'erreur de prédiction. Mon interprétation est que cela est à l'origine de la connaissance sémantique. J'ai également montré que les choix du sujet et l'activation cérébrale associée sont influencés par les traits de personnalité et des états affectifs négatifs. Les résultats de cette thèse m'ont amenée à proposer (1) un modèle expliquant les mécanismes possibles liés à l'influence de la personnalité sur le LTM dans une population avec MCI, (2) une dissociation des sous-régions du LTM dans différents types de mémoire et une représentation neuronale spécifique à ces régions. Cela pourrait être une piste pour résoudre les débats actuels sur la mémoire de reconnaissance. Finalement, (3) le LTM est aussi un système de mémoire impliqué dans l'apprentissage et qui peut interagir avec les GB par une compétition. Nous avons aussi mis en évidence une interaction dynamique de type « top -down » et « bottom-up » entre le cortex préfrontal et le cortex OT. En conclusion, les résultats peuvent donner des indices afin de mieux comprendre certains dysfonctionnements de la mémoire liés à l'âge et la maladie d'Alzheimer ainsi qu'à améliorer le développement de traitement. Abstract: The impact of Alzheimer's disease is devastating for the daily life of the affected patients, with progressive loss of memory and other cognitive skills until dementia. We still lack disease modifying treatment and there is also a great amount of uncertainty regarding the accuracy of diagnostic classification in the early stages of AD. The anatomical signature of AD, in particular the medial temporal lobe (MTL) atrophy measured with neuroimaging, can be used as an early in vivo biomarker in early stages of AD. However, despite the evident role of MTL in memory, we know that the derived predictive anatomical model based only on measures of brain atrophy in MTL does not explain all clinical cases. Throughout my thesis, I have conducted three projects to understand the anatomy and the functioning of MTL on (1) disease's progression, (2) memory process and (3) learning process. I was interested in a population with mild cognitive impairment (MCI), at risk for AD. The objective of the first project was to test the hypothesis that factors, other than the cognitive ones, such as the personality traits, can explain inter-individual differences in the MTL. Moreover, the phenotypic diversity in the manifestations of preclinical AD arises also from the limited knowledge of memory and learning processes in healthy brain. The objective of the second project concerns the investigation of sub-regions of the MTL, and more particularly their contributions in the different components of recognition memory in healthy subjects. To study that, I have used a new multivariate method as well as MRI at high resolution to test the contribution of those sub-regions in the processes of familiarity and recollection. Finally, the objective of the third project was to test the contribution of the MTL as a memory system in learning and the dynamic interaction between memory systems during learning. The results of the first project show that, beyond cognitive state of impairment observed in the population with MCI, the personality traits can explain the inter-individual differences in the MTL; notably with a higher contribution of neuroticism linked to proneness to stress and depression. My study has allowed identifying a pattern of anatomical abnormality in the MTL related to personality with measures of volume and mean diffusion of the tissue. That pattern is characterized by right-left asymmetry in MTL and an anterior to posterior gradient within MTL. I have interpreted that result by tissue and neurochemical properties differently sensitive to stress. Results of my second project have contributed to the actual debate on the contribution of MTL sub-regions in the processes of familiarity and recollection. Using a new multivariate method, the results support firstly a dissociation of the subregions associated with different memory components. The hippocampus was mostly associated with recollection and the surrounding parahippocampal cortex, with familiarity type of memory. Secondly, the activation corresponding to the mensic trace for each type of memory is characterized by a distinct spatial distribution. The specific neuronal representation, "sparse-distributed", associated with recollection in the hippocampus would be the best way to rapidly encode detailed memories without overwriting previously stored memories. In the third project, I have created a learning task with functional MRI to sudy the processes of learning of probabilistic associations based on feedback/reward. That study allowed me to highlight the role of the MTL in learning and the interaction between different memory systems such as the procedural memory, the perceptual memory or priming and the working memory. We have found activations in the MTL corresponding to a process of episodic memory; the basal ganglia (BG), to a procedural memory and reward; the occipito-temporal (OT) cortex, to a perceptive memory or priming and the prefrontal cortex, to working memory. We have also observed that those regions can interact; the relation type between the MTL and the BG has been interpreted as a competition. In addition, with a dynamic causal model, I have demonstrated a "top-down" influence from cortical regions associated with high level cortical area such as the prefrontal cortex on lower level cortical regions such as the OT cortex. That influence decreases during learning; that could correspond to a mechanism linked to a diminution of prediction error. My interpretation is that this is at the origin of the semantic knowledge. I have also shown that the subject's choice and the associated brain activation are influenced by personality traits and negative affects. Overall results of this thesis have brought me to propose (1) a model explaining the possible mechanism linked to the influence of personality on the MTL in a population with MCI, (2) a dissociation of MTL sub-regions in different memory types and a neuronal representation specific to each region. This could be a cue to resolve the actual debates on recognition memory. Finally, (3) the MTL is also a system involved in learning and that can interact with the BG by a competition. We have also shown a dynamic interaction of « top -down » and « bottom-up » types between the pre-frontal cortex and the OT cortex. In conclusion, the results could give cues to better understand some memory dysfunctions in aging and Alzheimer's disease and to improve development of treatment.

Programmed death ligand 1 expression and tumor-infiltrating lymphocytes in glioblastoma.

BACKGROUND: Immune checkpoint inhibitors targeting programmed cell death 1 (PD1) or its ligand (PD-L1) showed activity in several cancer types. METHODS: We performed immunohistochemistry for CD3, CD8, CD20, HLA-DR, phosphatase and tensin homolog (PTEN), PD-1, and PD-L1 and pyrosequencing for assessment of the O6-methylguanine-methyltransferase (MGMT) promoter methylation status in 135 glioblastoma specimens (117 initial resection, 18 first local recurrence). PD-L1 gene expression was analyzed in 446 cases from The Cancer Genome Atlas. RESULTS: Diffuse/fibrillary PD-L1 expression of variable extent, with or without interspersed epithelioid tumor cells with membranous PD-L1 expression, was observed in 103 of 117 (88.0%) newly diagnosed and 13 of 18 (72.2%) recurrent glioblastoma specimens. Sparse-to-moderate density of tumor-infiltrating lymphocytes (TILs) was found in 85 of 117 (72.6%) specimens (CD3+ 78/117, 66.7%; CD8+ 52/117, 44.4%; CD20+ 27/117, 23.1%; PD1+ 34/117, 29.1%). PD1+ TIL density correlated positively with CD3+ (P < .001), CD8+ (P < .001), CD20+ TIL density (P < .001), and PTEN expression (P = .035). Enrichment of specimens with low PD-L1 gene expression levels was observed in the proneural and G-CIMP glioblastoma subtypes and in specimens with high PD-L1 gene expression in the mesenchymal subtype (P = 5.966e-10). No significant differences in PD-L1 expression or TIL density between initial and recurrent glioblastoma specimens or correlation of PD-L1 expression or TIL density with patient age or outcome were evident. CONCLUSION: TILs and PD-L1 expression are detectable in the majority of glioblastoma samples but are not related to outcome. Because the target is present, a clinical study with specific immune checkpoint inhibitors seems to be warranted in glioblastoma.

Structured sparsity through reweighting and application to diffusion MRI

We consider the problem of multiple correlated sparse signals reconstruction and propose a new implementation of structured sparsity through a reweighting scheme. We present a particular application for diffusion Magnetic Resonance Imaging data and show how this procedure can be used for fibre orientation reconstruction in the white matter of the brain. In that framework, our structured sparsity prior can be used to exploit the fundamental coherence between fibre directions in neighbour voxels. Our method approaches the ℓ0 minimisation through a reweighted ℓ1-minimisation scheme. The weights are here defined in such a way to promote correlated sparsity between neighbour signals.

Association between resistin levels and cardiovascular disease events in older adults: The health, aging and body composition study.

OBJECTIVE: Prospective data on the association between resistin levels and cardiovascular disease (CVD) events are sparse with conflicting results. METHODS: We studied 3044 aged 70-79 years from the Health, Aging, and Body Composition Study. CVD events were defined as coronary heart disease (CHD) or stroke events. «Hard » CHD events were defined as CHD death or myocardial infarction. We estimated hazard ratio (HR) and 95% confidence intervals (CI) according to the quartiles of serum resistin concentrations and adjusted for clinical variables, and then further adjusted for metabolic disease (body mass index, fasting plasma glucose, abdominal visceral and subcutaneous adipose tissue, leptin, adiponectin, insulin) and inflammation (C-reactive protein, interleukin-6, tumor necrosis factors-α). RESULTS: During a median follow-up of 10.1 years, 559 patients had « hard » CHD events, 884 CHD events and 1106 CVD Events. Unadjusted incidence rate for CVD events was 36.6 (95% CI 32.1-41.1) per 1000 persons-year in the lowest quartile and 54.0 per 1000 persons-year in the highest quartile (95% CI 48.2-59.8, P for trend < 0.001). In the multivariate models adjusted for clinical variables, HRs for the highest vs. lowest quartile of resistin was 1.52 (95% CI 1.20-1.93, P < 0.001) for « Hard » CHD events, 1.41 (95% CI 1.16-1.70, P = 0.001) for CHD events and 1.35 (95% CI 1.14-1.59, P = 0.002) for CVD events. Further adjustment for metabolic disease slightly reduced the associations while adjustment for inflammation markedly reduced the associations. CONCLUSIONS: In older adults, higher resistin levels are associated with CVD events independently of clinical risk factors and metabolic disease markers, but markedly attenuated by inflammation.

Correlative microscopy.

In recent years correlative microscopy, combining the power and advantages of different imaging system, e.g., light, electrons, X-ray, NMR, etc., has become an important tool for biomedical research. Among all the possible combinations of techniques, light and electron microscopy, have made an especially big step forward and are being implemented in more and more research labs. Electron microscopy profits from the high spatial resolution, the direct recognition of the cellular ultrastructure and identification of the organelles. It, however, has two severe limitations: the restricted field of view and the fact that no live imaging can be done. On the other hand light microscopy has the advantage of live imaging, following a fluorescently tagged molecule in real time and at lower magnifications the large field of view facilitates the identification and location of sparse individual cells in a large context, e.g., tissue. The combination of these two imaging techniques appears to be a valuable approach to dissect biological events at a submicrometer level. Light microscopy can be used to follow a labelled protein of interest, or a visible organelle such as mitochondria, in time, then the sample is fixed and the exactly same region is investigated by electron microscopy. The time resolution is dependent on the speed of penetration and fixation when chemical fixatives are used and on the reaction time of the operator for cryo-fixation. Light microscopy can also be used to identify cells of interest, e.g., a special cell type in tissue or cells that have been modified by either transfections or RNAi, in a large population of non-modified cells. A further application is to find fluorescence labels in cells on a large section to reduce searching time in the electron microscope. Multiple fluorescence labelling of a series of sections can be correlated with the ultrastructure of the individual sections to get 3D information of the distribution of the marked proteins: array tomography. More and more efforts are put in either converting a fluorescence label into an electron dense product or preserving the fluorescence throughout preparation for the electron microscopy. Here, we will review successful protocols and where possible try to extract common features to better understand the importance of the individual steps in the preparation. Further the new instruments and software, intended to ease correlative light and electron microscopy, are discussed. Last but not least we will detail the approach we have chosen for correlative microscopy.

Current Sheet Regulation of Solar Near-Relativistic Electron Injection Histories

We present a sample of three large near-relativistic (>50 keV) electron events observed in 2001 by both the ACE and the Ulysses spacecraft, when Ulysses was at high-northern latitudes (>60°) and close to 2 AU. Despite the large latitudinal distance between the two spacecraft, electrons injected near the Sun reached both heliospheric locations. All three events were associated with large solar flares, strong decametric type II radio bursts and accompanied by wide (>212°) and fast (>1400 km s-1) coronal mass ejections (CMEs). We use advanced interplanetary transport simulations and make use of the directional intensities observed in situ by the spacecraft to infer the electron injection profile close to the Sun and the interplanetary transport conditions at both low and high latitudes. For the three selected events, we find similar interplanetary transport conditions at different heliolatitudes for a given event, with values of the mean free path ranging from 0.04 AU to 0.27 AU. We find differences in the injection profiles inferred for each spacecraft. We investigate the role that sector boundaries of the heliospheric current sheet (HCS) have on determining the characteristics of the electron injection profiles. Extended injection profiles, associated with coronal shocks, are found if the magnetic footpoints of the spacecraft lay in the same magnetic sector as the associated flare, while intermittent sparse injection episodes appear when the spacecraft footpoints are in the opposite sector or a wrap in the HCS bounded the CME structure.

Landslide detection and monitoring capability of boat-based mobile laser scanning along Dieppe coastal cliffs, Normandy

Integrated in a wide research assessing destabilizing and triggering factors to model cliff dynamic along the Dieppe's shoreline in High Normandy, this study aims at testing boat-based mobile LiDAR capabilities by scanning 3D point clouds of the unstable coastal cliffs. Two acquisition campaigns were performed in September 2012 and September 2013, scanning (1) a 30-km-long shoreline and (2) the same test cliffs in different environmental conditions and device settings. The potentials of collected data for 3D modelling, change detection and landslide monitoring were afterward assessed. By scanning during favourable meteorological and marine conditions and close to the coast, mobile LiDAR devices are able to quickly scan a long shoreline with median point spacing up to 10cm. The acquired data are then sufficiently detailed to map geomorphological features smaller than 0.5m2. Furthermore, our capability to detect rockfalls and erosion deposits (>m3) is confirmed, since using the classical approach of computing differences between sequential acquisitions reveals many cliff collapses between Pourville and Quiberville and only sparse changes between Dieppe and Belleville-sur-Mer. These different change rates result from different rockfall susceptibilities. Finally, we also confirmed the capability of the boat-based mobile LiDAR technique to monitor single large changes, characterizing the Dieppe landslide geometry with two main active scarps, retrogression up to 40m and about 100,000m3 of eroded materials.

Disease profiles of detainees in the Canton of Vaud in Switzerland: gender and age differences in substance abuse, mental health and chronic health conditions.

BACKGROUND: Literature on the disease profile of prisoners that differentiates by age and gender remains sparse. This study aimed to describe the health of correctional inmates in terms of substance abuse problems and mental and somatic health conditions, and compare it by gender and age. METHODS: This study examined cross-sectional data from the Canton of Vaud in Switzerland on the health conditions of detainees who were in prison on January 1, 2011 or entered prison in 2011. Health conditions validated by physician examination were reported using the International Classification of Diseases (ICD) version 10. The analyses were descriptive by groups of prisoners: the entire sample (All), Men, Older adults and Women. RESULTS: A total of 1,664 individuals were included in the analysis. Men comprised 91.5 % of the sample and had a mean age of 33 years. The other 8.5 % were women and had an average age of 39. Older adults (i.e., age 50 and older) represented 7 % of the total sample. Overall, 80 % of inmates were non-Swiss citizens, but the proportion of Swiss prisoners was higher among the older adults (51 %) and women (29 %). Overall, 41 % of inmates self-reported substance abuse problems. Of those, 27 % were being treated by psychiatrists for behavioral disorders related to substance abuse. Chronic infectious diseases were found in 9 % of the prison population. In addition, 27 % of detainees suffered from serious mental health conditions. Gender and age had an influence on the disease profile of this sample: compared to the entire prison population, the older inmates were less likely to misuse illegal drugs and to suffer from communicable infections but exhibited more problems with alcohol and a higher burden of chronic health conditions. Female prisoners were more disposed to mental health problems (including drug abuse) and infectious diseases. In terms of chronic diseases, women suffered from the same conditions as men, but the diseases were more prevalent in women. CONCLUSION: It is important to understand the different disease profiles of prisoners by gender and age, as it helps identify the needs of different groups and tailor age-and gender-specific interventions.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Inversion and assimilation methods with applications in geophysical remote sensing

Stratospheric ozone can be measured accurately using a limb scatter remote sensing technique at the UV-visible spectral region of solar light. The advantages of this technique includes a good vertical resolution and a good daytime coverage of the measurements. In addition to ozone, UV-visible limb scatter measurements contain information about NO2, NO3, OClO, BrO and aerosols. There are currently several satellite instruments continuously scanning the atmosphere and measuring the UVvisible region of the spectrum, e.g., the Optical Spectrograph and Infrared Imager System (OSIRIS) launched on the Odin satellite in February 2001, and the Scanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) launched on Envisat in March 2002. Envisat also carries the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument, which also measures limb-scattered sunlight under bright limb occultation conditions. These conditions occur during daytime occultation measurements. The global coverage of the satellite measurements is far better than any other ozone measurement technique, but still the measurements are sparse in the spatial domain. Measurements are also repeated relatively rarely over a certain area, and the composition of the Earth’s atmosphere changes dynamically. Assimilation methods are therefore needed in order to combine the information of the measurements with the atmospheric model. In recent years, the focus of assimilation algorithm research has turned towards filtering methods. The traditional Extended Kalman filter (EKF) method takes into account not only the uncertainty of the measurements, but also the uncertainty of the evolution model of the system. However, the computational cost of full blown EKF increases rapidly as the number of the model parameters increases. Therefore the EKF method cannot be applied directly to the stratospheric ozone assimilation problem. The work in this thesis is devoted to the development of inversion methods for satellite instruments and the development of assimilation methods used with atmospheric models.