Training in flexible intensive insulin therapy improves quality of life, decreases the risk of hypoglycaemia and ameliorates poor metabolic control in patients with type 1 diabetes.

AIM: Intensified insulin therapy has evolved to be the standard treatment of type 1 diabetes. However, it has been reported to increase significantly the risk of hypoglycaemia. We studied the effect of structured group teaching courses in flexible insulin therapy (FIT) on psychological and metabolic parameters in patients with type 1 diabetes. METHODS: We prospectively followed 45 type 1 diabetic patients of our outpatient clinic participating in 5 consecutive FIT teaching courses at the University Hospital of Basel. These courses consist of 7 weekly ambulatory evening group sessions. Patients were studied before and 1, 6, and 18 months after the course. Main outcome measures were glycated haemoglobin (HbA1c), severe hypoglycaemic events, quality of life (DQoL), diabetes self-control (IPC-9) and diabetes knowledge (DWT). RESULTS: Quality of life, self-control and diabetes knowledge improved after the FIT courses (all p<0.001). The frequency of severe hypoglycaemic events decreased ten-fold from 0.33 episodes/6 months at baseline to 0.03 episodes/6 months after 18 months (p<0.05). Baseline HbA1c was 7.2+/-1.1% and decreased in the subgroup with HbA1c > or = 8% from 8.4% to 7.8% (p<0.05). CONCLUSIONS: In an unselected, but relatively well-controlled population of type 1 diabetes, a structured, but not very time consuming FIT teaching programme in the outpatient setting improves psychological well-being and metabolic parameters.

IL28B polymorphisms leading to poor response to treatment are associated with low necroinflammatory activity and slow fibrosis progression in HCV genotype non-1-infected patients

Background and Aims: Genetic polymorphisms near IL28Bhave been associated with spontaneous and treatment-inducedclearance of hepatitis C virus (HCV). This is believed to proceed viathe appropriate activation of innate and adaptive immune responsestargeting infected hepatocytes. Intrahepatic inflammation is thereflection of the host cell immune response, but its relationshipwith IL28B polymorphisms has yet to be fully appreciated.Methods: We analyzed the association of IL28B polymorphismswith Metavir activity (≥1) and fibrosis scores (≥2) in 1114 HCVinfectedCaucasian patients enrolled in the Swiss Hepatitis C CohortStudy (629, 127, 268 and 110 infected with HCV genotype 1, 2, 3and 4, respectively). In a subgroup of 915 patients with an estimateddate of infection, the association between IL28B polymorphismsand fibrosis progression rate (FPR > median) was assessed. Singlenucleotide polymorphisms (SNPs) of interest were extracted froma dataset generated in a genome-wide association study and/orgenotyped by TaqMan assay. Associations of alleles with differentdegrees of activity and fibrosis were evaluated using an additivemodel of inheritance by multivariate logistic regression, accountingfor all relevant covariates.Results: The rare G allele at marker rs8099917 was associated withlower activity (P = 0.008) and fibrosis (P = 0.01), as well as slower FPR(P = 0.02). Most striking associations were observed among patientsinfected with non-1 genotypes (P = 0.002 for activity, P = 0.002 forfibrosis and P = 0.005 for FPR). In genotype 1-infected patients, theassociation with activity was observed only in the recessive model(P = 0.04), whereas other associations were not significant (P = 0.7for fibrosis and P = 0.4 for FPR).Conclusions: In chronic hepatitis C, IL28B polymorphisms linkedwith a poor virological response to therapy are also associated withreduced intrahepatic necroinflammation and slower liver diseaseprogression. These observations underscore the role played by thehost immune response in clearing HCV, especially in patients withHCV genotypes non-1.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

There and back again? Combining habitat suitability modelling and connectivity analyses to assess a potential return of the otter to Switzerland

After a steady decline in the early 20th century, several terrestrial carnivore species have recently recovered in Western Europe, either through reintroductions or natural recolonization. Because of the large space requirements of these species and potential conflicts with human activities, ensuring their recovery requires the implementation of conservation and management measures that address the environmental, landscape and social dimensions of the problem. Few examples exist of such integrated management. Taking the case of the otter (Lutra lutra) in Switzerland, we propose a multi-step approach that allows to (1) identify areas with potentially suitable habitat, (2) evaluate their connectivity, (3) verify the potentiality of the species recolonization from populations in neighbouring countries. We showed that even though suitable habitat is available for the species and the level of structural connectivity within Switzerland is satisfactory, the level of connectivity with neighbouring populations is crucial to prioritize strategies that favour the species recovery in the field. This research is the first example integrating habitat suitability and connectivity assessment at different scales with other factors in a multi-step assessment for species recovery.

Analysis, modelling and visualisation of spatiotemporal data for urban studies

The proportion of population living in or around cites is more important than ever. Urban sprawl and car dependence have taken over the pedestrian-friendly compact city. Environmental problems like air pollution, land waste or noise, and health problems are the result of this still continuing process. The urban planners have to find solutions to these complex problems, and at the same time insure the economic performance of the city and its surroundings. At the same time, an increasing quantity of socio-economic and environmental data is acquired. In order to get a better understanding of the processes and phenomena taking place in the complex urban environment, these data should be analysed. Numerous methods for modelling and simulating such a system exist and are still under development and can be exploited by the urban geographers for improving our understanding of the urban metabolism. Modern and innovative visualisation techniques help in communicating the results of such models and simulations. This thesis covers several methods for analysis, modelling, simulation and visualisation of problems related to urban geography. The analysis of high dimensional socio-economic data using artificial neural network techniques, especially self-organising maps, is showed using two examples at different scales. The problem of spatiotemporal modelling and data representation is treated and some possible solutions are shown. The simulation of urban dynamics and more specifically the traffic due to commuting to work is illustrated using multi-agent micro-simulation techniques. A section on visualisation methods presents cartograms for transforming the geographic space into a feature space, and the distance circle map, a centre-based map representation particularly useful for urban agglomerations. Some issues on the importance of scale in urban analysis and clustering of urban phenomena are exposed. A new approach on how to define urban areas at different scales is developed, and the link with percolation theory established. Fractal statistics, especially the lacunarity measure, and scale laws are used for characterising urban clusters. In a last section, the population evolution is modelled using a model close to the well-established gravity model. The work covers quite a wide range of methods useful in urban geography. Methods should still be developed further and at the same time find their way into the daily work and decision process of urban planners. La part de personnes vivant dans une région urbaine est plus élevé que jamais et continue à croître. L'étalement urbain et la dépendance automobile ont supplanté la ville compacte adaptée aux piétons. La pollution de l'air, le gaspillage du sol, le bruit, et des problèmes de santé pour les habitants en sont la conséquence. Les urbanistes doivent trouver, ensemble avec toute la société, des solutions à ces problèmes complexes. En même temps, il faut assurer la performance économique de la ville et de sa région. Actuellement, une quantité grandissante de données socio-économiques et environnementales est récoltée. Pour mieux comprendre les processus et phénomènes du système complexe "ville", ces données doivent être traitées et analysées. Des nombreuses méthodes pour modéliser et simuler un tel système existent et sont continuellement en développement. Elles peuvent être exploitées par le géographe urbain pour améliorer sa connaissance du métabolisme urbain. Des techniques modernes et innovatrices de visualisation aident dans la communication des résultats de tels modèles et simulations. Cette thèse décrit plusieurs méthodes permettant d'analyser, de modéliser, de simuler et de visualiser des phénomènes urbains. L'analyse de données socio-économiques à très haute dimension à l'aide de réseaux de neurones artificiels, notamment des cartes auto-organisatrices, est montré à travers deux exemples aux échelles différentes. Le problème de modélisation spatio-temporelle et de représentation des données est discuté et quelques ébauches de solutions esquissées. La simulation de la dynamique urbaine, et plus spécifiquement du trafic automobile engendré par les pendulaires est illustrée à l'aide d'une simulation multi-agents. Une section sur les méthodes de visualisation montre des cartes en anamorphoses permettant de transformer l'espace géographique en espace fonctionnel. Un autre type de carte, les cartes circulaires, est présenté. Ce type de carte est particulièrement utile pour les agglomérations urbaines. Quelques questions liées à l'importance de l'échelle dans l'analyse urbaine sont également discutées. Une nouvelle approche pour définir des clusters urbains à des échelles différentes est développée, et le lien avec la théorie de la percolation est établi. Des statistiques fractales, notamment la lacunarité, sont utilisées pour caractériser ces clusters urbains. L'évolution de la population est modélisée à l'aide d'un modèle proche du modèle gravitaire bien connu. Le travail couvre une large panoplie de méthodes utiles en géographie urbaine. Toutefois, il est toujours nécessaire de développer plus loin ces méthodes et en même temps, elles doivent trouver leur chemin dans la vie quotidienne des urbanistes et planificateurs.

hMMP9 as predictive factor for response and progression free survival in breast cancer patients treated with bevacizumab and pegylated liposomal doxorubicin (PLD)

Background: The anti-angiogenic drug, bevacizumab (Bv), is currently used in the treatment of different malignancies including breast cancer. Many angiogenesis-associated molecules are found in the circulation of cancer patients. Until now, there are no prognostic or predictive factors identified in breast cancer patients treated with Bv. We present here the first results of the prospective monitoring of 6 angiogenesis-related molecules in the peripheral blood of breast cancer patients treated with a combination of Bv and PLD in the phase II trial, SAKK 24/06. Methods: Patients were treated with PLD (20 mg/m2) and Bv (10 mg/kg) on days 1 and 15 of each 4-week cycle for a maximum of 6 cycles, followed by Bv monotherapy maintenance (10 mg/m2 q2 weeks) until progression or severe toxicity. Plasma and serum samples were collected at baseline, after 2 months of therapy, then every 3 months and at treatment discontinuation. Enzyme-linked immunosorbent assays (Quantikine, R&D Systems and Reliatech) were used to measure the expression levels of human vascular endothelial growth factor (hVEGF), placental growth factor (hPlGF), matrix metalloproteinase 9 (hMMP9) and soluble VEGF receptors hsVEGFR-1, hsVEGFR-2 and hsVEGFR-3. The log-transformed data (to reduce the skewness) for each marker was analyzed using an analysis of variance (ANOVA) model to determine if there was a difference between the mean of the subgroups of interest (where α = 0.05). The untransformed data was also analyzed in the same manner as a "sensitivity" check. Results: 132 blood samples were collected in 41 out of 43 enrolled patients. Baseline levels of the molecules were compared to disease status according to RECIST. There was a statistically significant difference in the mean of the log-transformed levels of hMMP9 between responders [CR+PR] versus the mean in patients with PD (p-value=0.0004, log fold change=0.7536), and between patients with disease control [CR+PR+SD] and those with PD (p-value=<0.0001, log fold change=0.81559), with the log-transformed level of hMMP9 being higher for the responder group. The mean of the log-transformed levels of hsVEGFR-1 was statistically significantly different between patients with disease control [CR+PR+SD] and those with PD (p-value=0.0068, log fold change=-0.6089), where the log-transformed level of hsVEGFR-1 was lower for the responder group. The log-transformed level of hMMP9 at baseline was identified as a significant prognostic factor in terms of progression free survival (PFS): p-value=0.0417, hazard ratio (HR)=0.574 with a corresponding 95% confidence interval (0.336 - 0.979)). No strong correlation was shown either between the log-transformed levels of hsVEGF, hPlGF, hsVEGFR-2 or hsVEGFR-3 and clinical response or the occurrence of severe toxicity, or between the levels of the different molecules. Conclusions: Our results suggest that baseline plasma level of the matrix metalloproteinase, hMMP9, could predict tumor response and PFS in patients treated with a combination of Bv and PLD. These data justify further investigation in breast cancer patients treated with anti-angiogenic therapy.

Socioeconomics status and quality of care in a population-based sample of swiss diabetic patients

Introduction: Low socioeconomic status (SES) is associated with higher prevalence of diabetes and worse outcomes; it has also been shown to be associated with worse quality of care. We aimed to explore the relationship between SES and quality of care in the Swiss context. Methods: We used data from a population-based survey including 519 adult diabetic patients living in the canton of Vaud. Self-reported data on patients' and diabetes characteristics, indicators of process and outcomes of care and quality of life were collected. Dependent variables included 6 processes of care (PoC) received during the last 12 months (HbA1C, lipid, microalbuminuria, fundoscopy, feet examination and influenza vaccination) and selected clinical outcomes (blood pressure, LDL, HbA1C, diabetes-specific (ADDQoL) and generic quality of life (SF-12)). Regression analyses were performed to assess the relationship between education and income, respectively, and quality of care as measured by PoC and clinical outcomes. Adjustment was made for age, gender and comorbidities. Results: Mean age was 64.5 years, 40% were women; 19%, 56% and 25% of the patients reported primary (I), secondary (II) and tertiary (III) education. Fundoscopy was the only PoC significantly associated with education, with III education patients more likely to get the exam than those with primary education (adjOR 1.8, 95% CI 1.0-3.3). Use of composite indicators of PoC showed that compared to patients with primary education, patients with III education were more likely to receive ≥5/6 PoC (adjOR 1.9, 95% CI 1.1-3.4), and that those with II or III education were more likely to receive 4/4 PoC (adjOR 1.9, 95% CI 1.0-3.3; adjOR 2.1, 95% CI 1.1-4.1, respectively). Quality of life was the only clinical outcome significantly associated with education, with II and III education patients reporting better quality of life compared to primary education patients, as measured by the ADDQoL (β 0.6, 95% CI 0.3-1.0, β 0.6, 95% CI 0.2-1.0, respectively) and the physical component score of the SF-12 (β 2.5, 95% CI 0.2-4.8, β 3.6, 95% CI 0.9-6.4, respectively). No associations were found between income and quality of care. Conclusion: Social inequalities have been demonstrated in Switzerland for global health indicators. Our results suggest that similar associations are found when considering quality of care measures in individuals with diabetes, but only for a few indicators.

Lentivector immunization induces tumor antigen-specific B and T cell responses in vivo.

Expression of the cancer/germ-line antigen NY-ESO-1 by tumors elicits spontaneous humoral and cellular immune responses in some cancer patients. Development of vaccines capable of stimulating such comprehensive immune responses is desirable. We have produced recombinant lentivectors directing the intracellular synthesis of NY-ESO-1 (rLV/ESO) and have analyzed the in vivo immune response elicited by this vector. Single injection of rLV/ESO into HLA-A2-transgenic mice elicited long-lasting B and T cell responses against NY-ESO-1. CD8+ T cells against the HLA-A2-restricted peptide NY-ESO-1(157-165) were readily detectable ex vivo and showed restricted TCR Vbeta usage. Moreover, rLV/ESO elicited a far greater anti-NY-ESO-1(157-165) CD8+ T cell response than peptide- or protein-based vaccines. Anti-NY-ESO-1 antibodies were rapidly induced after immunization and their detection preceded that of the antigen-specific CD8+ T cells. The rLV/ESO also induced CD4+ T cells. These cells played an essential role as their depletion completely abrogated B cell and CD8+ T cell responses against NY-ESO-1. The induced CD4+ T cells were primarily directed against a single NY-ESO-1 epitope spanning amino acids 81-100. Altogether, our study shows that rLV/ESO induces potent and comprehensive immune responses in vivo.

Safety and effectiveness of amphotericin B deoxycholate for the treatment of visceral leishmaniasis in Uganda

Between September 2003 and April 2004, the supply of antimonial drugs to Amudat Hospital, in north-eastern Uganda, was interrupted and all cases of visceral leishmaniasis presenting at the hospital could only be treated with amphotericin B deoxycholate (AmB). This allowed the safety and effectiveness of the AmB to be evaluated, in comparison with an historical cohort of patients treated, at the same hospital, with meglumine antimoniate (Sb-V). Demographic and clinical data were collected before and after treatment. Adverse effects were recorded passively in all the subjects, and actively, using a standardized questionnaire, in a sub-group of the patients given AmB. The in-hospital case-fatality 'rates' were 4.8% [95% confidence interval (CI) =2.4%-8.8%] among the 210 patients treated with AmB and 3.7% (CI=1.4%-7.9%) among the 161 patients treated with Sb-V (P>0.20). Adverse effects requiring treatment interruption were rare in both cohorts. Treatment failures (i.e. non-responses or relapses) were observed in 2.9% (CI= 1.2%-6.4%) of the patients treated with AmB and 1.2% (CI=0.1%-4.4%) of the patients treated with Sb-V (P>0.20). For the treatment of visceral leishmaniasis in Uganda, AmB therefore had a similar effectiveness and safety profile to that of meglumine antimoniate.

The activity of S.pombe DSC-1-like factor is cell cycle regulated and dependent on the activity of p34cdc2.

In the eukaryotic cell cycle, there are major control points in late G2 to determine the timing of the initiation of mitosis, and in late G1, regulating entry into S phase. In yeasts, this latter control is called start. Traverse of the start control and progression to S phase is accompanied by an increase in the expression of some of the genes whose products are required for DNA synthesis. In Saccharomyces cerevisiae, the coordinate expression of these genes in late G1 is dependent on a cis-acting sequence element called the MluI cell cycle box (MCB). A transcription factor called DSC-1 binds these elements and mediates cell cycle regulated transcription, though it is unclear whether this is by cell cycle-dependent changes in its activity. A DSC-1-like factor has also been identified in the fission yeast S.pombe. This is composed of at least the products of the cdc10 and sct1/res1 genes, and binds to the promoters of genes whose expression increases prior to S phase. We demonstrate that p85cdc10 is a nuclear protein and that the activity of the S.pombe DSC-1 factor varies through the cell cycle; it is high in cells that have passed start, decreases at the time of anaphase, remains low during the pre-start phase of G1 and increases at the time of the next S phase. We also show that the reactivation in late G1 is dependent on the G1 form of p34cdc2.

Myc's other life: stem cells and beyond.

Over the last three decades genetic and biochemical studies have revealed the pleiotropic effects of the Myc oncoprotein. While cell line studies have defined the intracellular processes regulated by Myc such as proliferation, differentiation, and metabolic growth, in vivo studies have confirmed these functions, and revealed roles in acquisition and maintenance of stem cell properties. These roles may be partially mediated by Myc's capacity to modify the chromatin landscape on a global scale. Myc also regulates numerous protein-coding transcripts, and many noncoding RNAs (rRNAs, tRNAs, and miRNAs). As Myc activity directly correlates with protein expression, further complexity is provided by post-translational modifications that regulate Myc in normal stem cells or deregulate it in malignant stem cells.