Effect of interleukin-6 receptor inhibition with tocilizumab in patients with rheumatoid arthritis (OPTION study): a double-blind, placebo-controlled, randomised trial.

BACKGROUND: Interleukin 6 is involved in the pathogenesis of rheumatoid arthritis via its broad effects on immune and inflammatory responses. Our aim was to assess the therapeutic effects of blocking interleukin 6 by inhibition of the interleukin-6 receptor with tocilizumab in patients with rheumatoid arthritis. METHODS: In this double-blind, randomised, placebo-controlled, parallel group phase III study, 623 patients with moderate to severe active rheumatoid arthritis were randomly assigned with an interactive voice response system, stratified by site with a randomisation list provided by the study sponsor, to receive tocilizumab 8 mg/kg (n=205), tocilizumab 4 mg/kg (214), or placebo (204) intravenously every 4 weeks, with methotrexate at stable pre-study doses (10-25 mg/week). Rescue therapy with tocilizumab 8 mg/kg was offered at week 16 to patients with less than 20% improvement in both swollen and tender joint counts. The primary endpoint was the proportion of patients with 20% improvement in signs and symptoms of rheumatoid arthritis according to American College of Rheumatology criteria (ACR20 response) at week 24. Analyses were by intention to treat. This trial is registered with ClinicalTrials.gov, number NCT00106548. FINDINGS: The intention-to-treat analysis population consisted of 622 patients: one patient in the 4 mg/kg group did not receive study treatment and was thus excluded. At 24 weeks, ACR20 responses were seen in more patients receiving tocilizumab than in those receiving placebo (120 [59%] patients in the 8 mg/kg group, 102 [48%] in the 4 mg/kg group, 54 [26%] in the placebo group; odds ratio 4.0 [95% CI 2.6-6.1], p<0.0001 for 8 mg/kg vs placebo; and 2.6 [1.7-3.9], p<0.0001 for 4 mg/kg vs placebo). More people receiving tocilizumab than those receiving placebo had at least one adverse event (143 [69%] in the 8 mg/kg group; 151 [71%] in the 4 mg/kg group; 129 [63%] in the placebo group). The most common serious adverse events were serious infections or infestations, reported by six patients in the 8 mg/kg group, three in the 4 mg/kg group, and two in the placebo group. INTERPRETATION: Tocilizumab could be an effective therapeutic approach in patients with moderate to severe active rheumatoid arthritis. FUNDING: F Hoffmann-La Roche, Chugai Pharmaceutical.

3-year follow-up results of bone mineral content and density after a school-based physical activity randomized intervention trial.

BACKGROUND: As an important modifiable lifestyle factor in osteoporosis prevention, physical activity has been shown to positively influence bone mass accrual during growth. We have previously shown that a nine month general school based physical activity intervention increased bone mineral content (BMC) and density (aBMD) in primary school children. From a public health perspective, a major key issue is whether these effects persist during adolescence. We therefore measured BMC and aBMD three years after cessation of the intervention to investigate whether the beneficial short-term effects persisted. METHODS: All children from 28 randomly selected first and fifth grade classes (intervention group (INT): 16 classes, n=297; control group (CON): 12 classes, n=205) who had participated in KISS (Kinder-und Jugendsportstudie) were contacted three years after cessation of the intervention program. The intervention included daily physical education with daily impact loading activities over nine months. Measurements included anthropometry, vigorous physical activity (VPA) by accelerometers, and BMC/aBMD for total body, femoral neck, total hip, and lumbar spine by dual-energy X-ray absorptiometry (DXA). Sex- and age-adjusted Z-scores of BMC or aBMD at follow-up were regressed on intervention (1 vs. 0), the respective Z-score at baseline, gender, follow-up height and weight, pubertal stage at follow-up, previous and current VPA, adjusting for clustering within schools. RESULTS: 377 of 502 (75%) children participated in baseline DXA measurements and of those, 214 (57%) participated to follow-up. At follow-up INT showed significantly higher Z-scores of BMC at total body (adjusted group difference: 0.157 units (0.031-0.283); p=0.015), femoral neck (0.205 (0.007-0.402); p=0.042) and at total hip (0.195 (0.036 to 0.353); p=0.016) and higher Z-scores of aBMD for total body (0.167 (0.016 to 0.317); p=0.030) compared to CON, representing 6-8% higher values for children in the INT. No differences could be found for the remaining bone parameters. For the subpopulation with baseline VPA (n=163), effect sizes became stronger after baseline VPA adjustment. After adjustment for baseline and current VPA (n=101), intervention effects were no longer significant, while effect sizes remained the same as without adjustment for VPA. CONCLUSION: Beneficial effects on BMC of a nine month general physical activity intervention appeared to persist over three years. Part of the maintained effects may be explained by current physical activity.

Regional deterministic characterization of fracture networks and its application to GIS-based rock fall risk assessment

The study investigates the possibility to incorporate fracture intensity and block geometry as spatially continuous parameters in GIS-based systems. For this purpose, a deterministic method has been implemented to estimate block size (Bloc3D) and joint frequency (COLTOP). In addition to measuring the block size, the Bloc3D Method provides a 3D representation of the shape of individual blocks. These two methods were applied using field measurements (joint set orientation and spacing) performed over a large field area, in the Swiss Alps. This area is characterized by a complex geology, a number of different rock masses and varying degrees of metamorphism. The spatial variability of the parameters was evaluated with regard to lithology and major faults. A model incorporating these measurements and observations into a GIS system to assess the risk associated with rock falls is proposed. The analysis concludes with a discussion on the feasibility of such an application in regularly and irregularly jointed rock masses, with persistent and impersistent discontinuities.

Roles of superantigens in microbial infections?

Superantigens have been defined in a variety of infectious particles such as bacteria and viruses. These superantigens have the capacity to stimulate a large percentage of the host T cells by interacting specifically with the T-cell receptor V beta chain which is shared by about 1-20% of mature T cells. The recent discovery that mammary tumour viruses express such superantigens enabled the analysis of the retroviral life cycle and led to questions about the role of superantigen in amplification of the infection.

Auditory cues support place navigation in rats when associated with a visual cue.

Rats, like other crepuscular animals, have excellent auditory capacities and they discriminate well between different sounds [Heffner HE, Heffner RS, Hearing in two cricetid rodents: wood rats (Neotoma floridana) and grasshopper mouse (Onychomys leucogaster). J Comp Psychol 1985;99(3):275-88]. However, most experimental literature concerning spatial orientation almost exclusively emphasizes the use of visual landmarks [Cressant A, Muller RU, Poucet B. Failure of centrally placed objects to control the firing fields of hippocampal place cells. J Neurosci 1997;17(7):2531-42; and Goodridge JP, Taube JS. Preferential use of the landmark navigational system by head direction cells in rats. Behav Neurosci 1995;109(1):49-61]. To address the important issue of whether rats are able to achieve a place navigation task relative to auditory beacons, we designed a place learning task in the water maze. We controlled cue availability by conducting the experiment in total darkness. Three auditory cues did not allow place navigation whereas three visual cues in the same positions did support place navigation. One auditory beacon directly associated with the goal location did not support taxon navigation (a beacon strategy allowing the animal to find the goal just by swimming toward the cue). Replacing the auditory beacons by one single visual beacon did support taxon navigation. A multimodal configuration of two auditory cues and one visual cue allowed correct place navigation. The deletion of the two auditory or of the one visual cue did disrupt the spatial performance. Thus rats can combine information from different sensory modalities to achieve a place navigation task. In particular, auditory cues support place navigation when associated with a visual one.

Surface assembly of poly(I:C) on PEGylated microspheres to shield from adverse interactions with fibroblasts.

By expressing an array of pattern recognition receptors (PRRs), fibroblasts play an important role in stimulating and modulating the response of the innate immune system. The TLR3 ligand polyriboinosinic acid-polyribocytidylic acid, poly(I:C), a mimic of viral dsRNA, is a vaccine adjuvant candidate to activate professional antigen presenting cells (APCs). However, owing to its ligation with extracellular TLR3 on fibroblasts, subcutaneously administered poly(I:C) bears danger towards autoimmunity. It is thus in the interest of its clinical safety to deliver poly(I:C) in such a way that its activation of professional APCs is as efficacious as possible, whereas its interference with non-immune cells such as fibroblasts is controlled or even avoided. Complementary to our previous work with monocyte-derived dendritic cells (MoDCs), here we sought to control the delivery of poly(I:C) surface-assembled on microspheres to human foreskin fibroblasts (HFFs). Negatively charged polystyrene (PS) microspheres were equipped with a poly(ethylene glycol) (PEG) corona through electrostatically driven coatings with a series of polycationic poly(L-lysine)-graft-poly(ethylene glycol) copolymers, PLL-g-PEG, of varying grafting ratios g from 2.2 up to 22.7. Stable surface assembly of poly(I:C) was achieved by incubation of polymer-coated microspheres with aqueous poly(I:C) solutions. Notably, recognition of both surface-assembled and free poly(I:C) by extracellular TLR3 on HFFs halted their phagocytic activity. Ligation of surface-assembled poly(I:C) with extracellular TLR3 on HFFs could be controlled by tuning the grafting ratio g and thus the chain density of the PEG corona. When assembled on PLL-5.7-PEG-coated microspheres, poly(I:C) was blocked from triggering class I MHC molecule expression on HFFs. Secretion of interleukin (IL)-6 by HFFs after exposure to surface-assembled poly(I:C) was distinctly lower as compared to free poly(I:C). Overall, surface assembly of poly(I:C) may have potential to contribute to the clinical safety of this vaccine adjuvant candidate.

Hémorragie intra-alvéolaire [Alveolar hemorrhage].

Diffuse alveolar hemorrhage (DAH) is defined by the presence of red blood cells originating from the lung capillaries or venules within the alveoli. The diagnosis is established on clinical features, radiological pattern, and especially bronchoalveolar lavage. Diffuse alveolar hemorrhage may have many immune or non-immune causes. Immune causes of DAH include vasculitides, connective tissue diseases, especially systemic lupus erythematosus, and antiglomerular basement membrane antibody disease (Goodpasture's syndrome). Treatment is both supportive and causal, often based on high dose corticosteroids and immunosuppressive therapy (especially intravenous cyclophosphamide). Plasma exchanges are performed in antiglomerular basement membrane antibody disease and systemic lupus erythematosus, and are considered in systemic vasculitis. Non-immune causes of DAH mainly include heart diseases, coagulation disorders, infections, drug toxicities and idiopathic DAH. Treatment of non-immune DAH is that of its cause. Whatever the cause, DAH is an emergency requiring prompt assessment and early treatment.

Intraoperative adverse events during laparoscopic colorectal resection-better laparoscopic treatment but unchanged incidence. Lessons learnt from a Swiss multi-institutional analysis of 3,928 patients.

PURPOSE: Intraoperative adverse events significantly influence morbidity and mortality of laparoscopic colorectal resections. Over an 11-year period, the changes of occurrence of such intraoperative adverse events were assessed in this study. METHODS: Analysis of 3,928 patients undergoing elective laparoscopic colorectal resection based on the prospective database of the Swiss Association of Laparoscopic and Thoracoscopic Surgery was performed. RESULTS: Overall, 377 intraoperative adverse events occurred in 329 patients (overall incidence of 8.4 %). Of 377 events, 163 (43 %) were surgical complications and 214 (57 %) were nonsurgical adverse events. Surgical complications were iatrogenic injury to solid organs (n = 63; incidence of 1.6 %), bleeding (n = 62; 1.6 %), lesion by puncture (n = 25; 0.6 %), and intraoperative anastomotic leakage (n = 13; 0.3 %). Of note, 11 % of intraoperative organ/puncture lesions requiring re-intervention were missed intraoperatively. Nonsurgical adverse events were problems with equipment (n = 127; 3.2 %), anesthetic problems (n = 30; 0.8 %), and various (n = 57; 1.5 %). Over time, the rate of intraoperative adverse events decreased, but not significantly. Bleeding complications significantly decreased (p = 0.015), and equipment problems increased (p = 0.036). However, the rate of adverse events requiring conversion significantly decreased with time (p < 0.001). Patients with an intraoperative adverse event had a significantly higher rate of postoperative local and general morbidity (41.2 and 32.9 % vs. 18.0 and 17.2 %, p < 0.001 and p < 0.001, respectively). CONCLUSIONS: Intraoperative surgical complications and adverse events in laparoscopic colorectal resections did not change significantly over time and are associated with an increased postoperative morbidity.

Lack of MRI neurohypophyseal bright signal in a child with congenital nephrogenic diabetes insipidus

Congenital nephrogenic diabetes insipidus (CNDI) is a rare disease characterized by the inability of the kidney to respond to arginine vasopressin (AVP). The absence of the neurohypophyseal 'bright signal' on T1 sequence magnetic resonance imaging (MRI) is considered as an argument in favour of the diagnosis of central diabetes insipidus (CDI). This observation is challenged as we hereby present a case of a child diagnosed with CNDI and who did not present MRI pituitary bright signal. A 6-month-old male presented with failure to thrive, polyuria and polydypsia. Family history revealed that the mother, 35 years of age, had been presenting polydypsia and polyuria, and she was investigated at the age of 6 years with no concluding diagnosis. The patient's physical exam showed a weight of 5215 g (−3 DS) and clinical signs of dehydration. The patient's plasma sodium level was 155 mmol/L, osmolality 305 mOsm/kg and urine osmolality 150 mOsm/kg. Brain MRI showed in T1 sequences the absence of the posterior pituitary bright signal suggesting the diagnosis of CDI (Figure 1). The child was treated with synthetic AVP analogue 1-desamino-8-d-arginine vasopressin (DDAVP) without improvement, which led to the consideration of CNDI. The diagnosis was confirmed by an elevated serum level of AVP of 214 pmol/L (reference value ≤4.34 pmol/L) and by genetic analysis demonstrating and T106C mutation in the V2R (X-linked CNDI). The child was treated with thiazide diuretic and increased fluids with restricted sodium intake. This resulted in catch-up growth and improved neurological development. A follow-up MRI was performed 6 months after the start of therapy with the same technique. At that time, the child's weight had improved to 9310 g (−1.5 DS) corresponding to a gain of 22 g per day, and he did not present any clinical signs of dehydration and had a normal plasma level of sodium (140 mmol/L). MRI showed that the bright signal was still absent.

Electrical stimulation induces propagated colonic contractions in an experimental model.

BACKGROUND: Direct colonic electrical stimulation may prove to be a treatment option for specific motility disorders such as chronic constipation. The aim of this study was to provoke colonic contractions using electrical stimulation delivered from a battery-operated device. METHODS: Electrodes were inserted into the caecal seromuscular layer of eight anaesthetized pigs. Contractions were induced by a neurostimulator (Medtronic 3625). Caecal motility was measured simultaneously by video image analysis, manometry and a technique assessing colonic transit. RESULTS: Caecal contractions were generated using 8-10 V amplitude, 1000 micros pulse width, 120 Hz frequency for 10-30 s, with an intensity of 7-15 mA. The maximal contraction strength was observed after 20-25 s. Electrical stimulation was followed by a relaxation phase of 1.5-2 min during which contractions propagated orally and aborally over at least 10 cm. Spontaneous and stimulated caecal motility values were significantly different for both intraluminal pressure (mean(s.d.) 332(124) and 463(187) mmHg respectively; P < 0.001, 42 experiments) and movement of contents (1.6(0.9) and 3.9(2.8) mm; P < 0.001, 40 experiments). CONCLUSION: Electrical stimulation modulated caecal motility, and provoked localized and propagated colonic contractions.

Magmatic fluids in the Breccia-hosted epithermal Au-Ag deposit of Rosia Montana, Romania

The breccia-hosted epithermal Au-Ag deposit of Rosia Montana is located 7 kin northeast of Abrud, in the northern part of the South Apuseni Mountains, Romania. Estimated total reserves of 214.91 million metric toils (Mt) of ore at 1.46 g/t An and 6.9 g/t Ag (10.1 Moz of An and 47.6 Moz of Ag) make Rosia Montana one of the largest gold deposits in Europe. At this location, Miocene calc-alkaline magmatic and hydrothermal activity was associated with local extensional tectonics within a strike-slip regime related to the indentation of the Adriatic microplate into the European plate during the Carpathian orogenesis. The host rocks of the magmatic complex consist of pre-Mesozoic metamorphosed continental crust covered by Cretaceous turbiditic sediment (flysch). Magmatic activity at Rosia Montana and its surroundings occurred in several pulses and lasted about 7 m.y, Rosia Montana is a breccia-hosted epithermal system related to strong phreatomagmatic activity due to the shallow emplacement of the Montana dacite. The Montana dacite intruded Miocene volcaniclastic material (volcaniclastic breccias) and crops out at Cetate and Carnic Hills. Current mining is focused primarily on the Cetate open pit, which was mapped in detail, leading to the recognition of three distinct breccia bodies: the dacite breccia with a dominantly hydrothermal matrix, the gray polymict breccia with a greater proportion of sand-sized matrix support, and the black polymict breccia, which reached to the surface, contains carbonized tree trunks and has a dominantly barren elastic matrix. The hydrothermal alteration is pervasive. Adularia alteration with a phyllic overprint is ubiquitous; silicification and argillic alteration occur locally. Mineralization consists of quartz, adularia, carbonates (commonly Mn-rich), pyrite, Fe-poor sphalerite, galena, chalcopyrite, tetrahedrite, and native gold and occurs as disseminations, as well as in veins and filling vugs within the Montana dacite and the different breccias. The age of mineralization (12.85 +/- 0.07 Ma) was determined by Ar-40- Ar-39 dating on hydrothermal adularia crystals from vugs in the dacite breccia in the Cetate open pit. Microthermometric measurements of fluid inclusions in quartz phenocrysts from the Montana dacite revealed two fluid types that are absent from the hydrothermal breccia and must have been trapped at depth prior to dacite dome emplacement: brine inclusions (32-55 -wt % NaCl equiv, homogenizing at T-h > 460 degrees C) and intermediate density fluids (4.9-15.6 wt % NaCl equiv, T, between 345 degrees-430 degrees C). Secondary aqueous fluid inclusion assemblages in the phenocrysts have salinities of 0.2 to 2.2 wt percent NaCl equiv and T-h of 200 degrees to 280 degrees C. Fluid inclusion assemblages in hydrothermal quartz from breccias and veins have salinities of 0.2 to 3.4 wt percent NaCl equiv and T-h, from 200 degrees to 270 degrees C. The oxygen isotope composition of several zones of an ore-related epithermal quartz crystal indicate a very constant delta O-18 of 4.5 to 5.0 per mil for the mineralizing fluid, despite significant salinity and temperature variation over time. Following microthermometry, selected fluid inclusion assemblages were analyzed by laser ablation-inductively coupled-plasma mass spectrometry (LA-ICMS). Despite systematic differences in salinity between phenocryst-hosted fluids trapped at depth and fluids from quartz in the epithermal breccias, all fluids have overlapping major and trace cation ratios, including identical Na/K/Rb/Sr/Cs/Ba. Consistent with the constant near-magmatic oxygen isotope composition of the hydrothermal fluids, these data strongly indicate a common magmatic component of these chemically conservative solutes in all fluids. Cu, Pb, Zn, and Mn show variations in concentration relative to the relatively non-reactive alkalis, reflecting the precipitation of sulfide minerals together with An in the epithermal breccia, and possibly of Cu in an inferred subjacent porphyry environment. The magmatic-hydrothermal processes responsible for epithermal Au-Ag mineralization at Rosia Montana are, however, not directly related to the formation of the spatially associated porphyry Cu-Au deposit of Rosia Poieni, which occurred lout 3 m.y. later.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Development of pharmaceutical care services in nursing homes: practice and research in a Swiss canton.

OBJECTIVE: The aim of this study was to assess the implementation process and economic impact of a new pharmaceutical care service provided since 2002 by pharmacists in Swiss nursing homes. SETTING: The setting was 42 nursing homes located in the canton of Fribourg, Switzerland under the responsibility of 22 pharmacists. METHOD: We developed different facilitators, such as a monitoring system, a coaching program, and a research project, to help pharmacists change their practice and to improve implementation of this new service. We evaluated the implementation rate of the service delivered in nursing homes. We assessed the economic impact of the service since its start in 2002 using statistical evaluation (Chow test) with retrospective analysis of the annual drug costs per resident over an 8-year period (1998-2005). MAIN OUTCOME MEASURES: The description of the facilitators and their implications in implementation of the service; the economic impact of the service since its start in 2002. RESULTS: In 2005, after a 4-year implementation period supported by the introduction of facilitators of practice change, all 42 nursing homes (2,214 residents) had implemented the pharmaceutical care service. The annual drug costs per resident decreased by about 16.4% between 2002 and 2005; this change proved to be highly significant. The performance of the pharmacists continuously improved using a specific coaching program including an annual expert comparative report, working groups, interdisciplinary continuing education symposia, and individual feedback. This research project also determined priorities to develop practice guidelines to prevent drug-related problems in nursing homes, especially in relation to the use of psychotropic drugs. CONCLUSION: The pharmaceutical care service was fully and successfully implemented in Fribourg's nursing homes within a period of 4 years. These findings highlight the importance of facilitators designed to assist pharmacists in the implementation of practice changes. The economic impact was confirmed on a large scale, and priorities for clinical and pharmacoeconomic research were identified in order to continue to improve the quality of integrated care for the elderly.