Correlates of frailty, prediction of functional decline and preventative approaches - selected results from the lausanne cohort 65+ (lc65+) study (Switzerland) (Lausanne) and the longitudinal urban cohort ageing study (Lucas) (Germany)

Overall introduction.- Longitudinal studies have been designed to investigate prospectively, from their beginning, the pathway leading from health to frailty and to disability. Knowledge about determinants of healthy ageing and health behaviour (resources) as well as risks of functional decline is required to propose appropriate preventative interventions. The functional status in older people is important considering clinical outcome in general, healthcare need and mortality. Part I.- Results and interventions from lucas (longitudinal urban cohort ageing study). Authors.- J. Anders, U. Dapp, L. Neumann, F. Pröfener, C. Minder, S. Golgert, A. Daubmann, K. Wegscheider,. W. von Renteln-Kruse Methods.- The LUCAS core project is a longitudinal cohort of urban community-dwelling people 60 years and older, recruited in 2000/2001. Further LUCAS projects are cross-sectional comparative and interventional studies (RCT). Results.- The emphasis will be on geriatric medical care in a population-based approach, discussing different forms of access, too. (Dapp et al. BMC Geriatrics 2012, 12:35; http://www.biomedcentral.com/1471-2318/12/35): - longitudinal data from the LUCAS urban cohort (n = 3.326) will be presented covering 10 years of observation, including the prediction of functional decline, need of nursing care, and mortality by using a self-filling screening tool; - interventions to prevent functional decline do focus on first (pre-clinical) signs of pre-frailty before entering the frailty-cascade ("Active Health Promotion in Old Age", "geriatric mobility centre") or disability ("home visits"). Conclusions.- The LUCAS research consortium was established to study particular aspects of functional competence, its changes with ageing, to detect pre-clinical signs of functional decline, and to address questions on how to maintain functional competence and to prevent adverse outcome in different settings. The multidimensional data base allows the exploration of several further questions. Gait performance was exmined by GAITRite®-System. Supported by the Federal Ministry for Education and Research (BMBF Funding No. 01ET1002A). Part II.- Selected results from the lausanne cohort 65+ (Lc65 + ) Study (Switzerland). Authors.- Prof Santos-Eggimann Brigitte, Dr Seematter-Bagnoud Laurence, Prof Büla Christophe, Dr Rochat Stéphane. Methods.- The Lc65+ cohort was launched in 2004 with the random selection of 3054 eligible individuals aged 65 to 70 (birth year 1934-1938) in the non-institutionalized population of Lausanne (Switzerland). Results.- Information is collected about life course social and health-related events, socio-economics, medical and psychosocial dimensions, lifestyle habits, limitations in activities of daily living, mobility impairments, and falls. Gait performance are objectively measured using body-fixed sensors. Frailty is assessed using Fried's frailty phenotype. Follow-up consists in annual self-completed questionnaires, as well as physical examination and physical and mental performance tests every three years. - Lausanne cohort 65+ (Lc65 + ): design and longitudinal outcomes. The baseline data collection was completed among 1422 participants in 2004-2005 through self-completed questionnaires, face-to-face interviews, physical examination and tests of mental and physical performances. Information about institutionalization, self-reported health services utilization, and death is also assessed. An additional random sample (n = 1525) of 65-70 years old subjects was recruited in 2009 (birth year 1939-1943). - lecture no 4: alcohol intake and gait parameters: prevalent and longitudinal association in the Lc65+ study. The association between alcohol intake and gait performance was investigated.

Community Policing in Switzerland's Major Urban Areas: An Observational Study of the Implementation and Impact Using Geospatial Data Mining

La présente étude est à la fois une évaluation du processus de la mise en oeuvre et des impacts de la police de proximité dans les cinq plus grandes zones urbaines de Suisse - Bâle, Berne, Genève, Lausanne et Zurich. La police de proximité (community policing) est à la fois une philosophie et une stratégie organisationnelle qui favorise un partenariat renouvelé entre la police et les communautés locales dans le but de résoudre les problèmes relatifs à la sécurité et à l'ordre public. L'évaluation de processus a analysé des données relatives aux réformes internes de la police qui ont été obtenues par l'intermédiaire d'entretiens semi-structurés avec des administrateurs clés des cinq départements de police, ainsi que dans des documents écrits de la police et d'autres sources publiques. L'évaluation des impacts, quant à elle, s'est basée sur des variables contextuelles telles que des statistiques policières et des données de recensement, ainsi que sur des indicateurs d'impacts construit à partir des données du Swiss Crime Survey (SCS) relatives au sentiment d'insécurité, à la perception du désordre public et à la satisfaction de la population à l'égard de la police. Le SCS est un sondage régulier qui a permis d'interroger des habitants des cinq grandes zones urbaines à plusieurs reprises depuis le milieu des années 1980. L'évaluation de processus a abouti à un « Calendrier des activités » visant à créer des données de panel permettant de mesurer les progrès réalisés dans la mise en oeuvre de la police de proximité à l'aide d'une grille d'évaluation à six dimensions à des intervalles de cinq ans entre 1990 et 2010. L'évaluation des impacts, effectuée ex post facto, a utilisé un concept de recherche non-expérimental (observational design) dans le but d'analyser les impacts de différents modèles de police de proximité dans des zones comparables à travers les cinq villes étudiées. Les quartiers urbains, délimités par zone de code postal, ont ainsi été regroupés par l'intermédiaire d'une typologie réalisée à l'aide d'algorithmes d'apprentissage automatique (machine learning). Des algorithmes supervisés et non supervisés ont été utilisés sur les données à haute dimensionnalité relatives à la criminalité, à la structure socio-économique et démographique et au cadre bâti dans le but de regrouper les quartiers urbains les plus similaires dans des clusters. D'abord, les cartes auto-organisatrices (self-organizing maps) ont été utilisées dans le but de réduire la variance intra-cluster des variables contextuelles et de maximiser simultanément la variance inter-cluster des réponses au sondage. Ensuite, l'algorithme des forêts d'arbres décisionnels (random forests) a permis à la fois d'évaluer la pertinence de la typologie de quartier élaborée et de sélectionner les variables contextuelles clés afin de construire un modèle parcimonieux faisant un minimum d'erreurs de classification. Enfin, pour l'analyse des impacts, la méthode des appariements des coefficients de propension (propensity score matching) a été utilisée pour équilibrer les échantillons prétest-posttest en termes d'âge, de sexe et de niveau d'éducation des répondants au sein de chaque type de quartier ainsi identifié dans chacune des villes, avant d'effectuer un test statistique de la différence observée dans les indicateurs d'impacts. De plus, tous les résultats statistiquement significatifs ont été soumis à une analyse de sensibilité (sensitivity analysis) afin d'évaluer leur robustesse face à un biais potentiel dû à des covariables non observées. L'étude relève qu'au cours des quinze dernières années, les cinq services de police ont entamé des réformes majeures de leur organisation ainsi que de leurs stratégies opérationnelles et qu'ils ont noué des partenariats stratégiques afin de mettre en oeuvre la police de proximité. La typologie de quartier développée a abouti à une réduction de la variance intra-cluster des variables contextuelles et permet d'expliquer une partie significative de la variance inter-cluster des indicateurs d'impacts avant la mise en oeuvre du traitement. Ceci semble suggérer que les méthodes de géocomputation aident à équilibrer les covariables observées et donc à réduire les menaces relatives à la validité interne d'un concept de recherche non-expérimental. Enfin, l'analyse des impacts a révélé que le sentiment d'insécurité a diminué de manière significative pendant la période 2000-2005 dans les quartiers se trouvant à l'intérieur et autour des centres-villes de Berne et de Zurich. Ces améliorations sont assez robustes face à des biais dus à des covariables inobservées et covarient dans le temps et l'espace avec la mise en oeuvre de la police de proximité. L'hypothèse alternative envisageant que les diminutions observées dans le sentiment d'insécurité soient, partiellement, un résultat des interventions policières de proximité semble donc être aussi plausible que l'hypothèse nulle considérant l'absence absolue d'effet. Ceci, même si le concept de recherche non-expérimental mis en oeuvre ne peut pas complètement exclure la sélection et la régression à la moyenne comme explications alternatives. The current research project is both a process and impact evaluation of community policing in Switzerland's five major urban areas - Basel, Bern, Geneva, Lausanne, and Zurich. Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The process evaluation data on police internal reforms were obtained through semi-structured interviews with key administrators from the five police departments as well as from police internal documents and additional public sources. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey (SCS) data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures. The SCS is a standing survey instrument that has polled residents of the five urban areas repeatedly since the mid-1980s. The process evaluation produced a "Calendar of Action" to create panel data to measure community policing implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that analyzes the impact of the different community policing models between matched comparison areas across the five cities. Using ZIP code districts as proxies for urban neighborhoods, geospatial data mining algorithms serve to develop a neighborhood typology in order to match the comparison areas. To this end, both unsupervised and supervised algorithms are used to analyze high-dimensional data on crime, the socio-economic and demographic structure, and the built environment in order to classify urban neighborhoods into clusters of similar type. In a first step, self-organizing maps serve as tools to develop a clustering algorithm that reduces the within-cluster variance in the contextual variables and simultaneously maximizes the between-cluster variance in survey responses. The random forests algorithm then serves to assess the appropriateness of the resulting neighborhood typology and to select the key contextual variables in order to build a parsimonious model that makes a minimum of classification errors. Finally, for the impact analysis, propensity score matching methods are used to match the survey respondents of the pretest and posttest samples on age, gender, and their level of education for each neighborhood type identified within each city, before conducting a statistical test of the observed difference in the outcome measures. Moreover, all significant results were subjected to a sensitivity analysis to assess the robustness of these findings in the face of potential bias due to some unobserved covariates. The study finds that over the last fifteen years, all five police departments have undertaken major reforms of their internal organization and operating strategies and forged strategic partnerships in order to implement community policing. The resulting neighborhood typology reduced the within-cluster variance of the contextual variables and accounted for a significant share of the between-cluster variance in the outcome measures prior to treatment, suggesting that geocomputational methods help to balance the observed covariates and hence to reduce threats to the internal validity of an observational design. Finally, the impact analysis revealed that fear of crime dropped significantly over the 2000-2005 period in the neighborhoods in and around the urban centers of Bern and Zurich. These improvements are fairly robust in the face of bias due to some unobserved covariate and covary temporally and spatially with the implementation of community policing. The alternative hypothesis that the observed reductions in fear of crime were at least in part a result of community policing interventions thus appears at least as plausible as the null hypothesis of absolutely no effect, even if the observational design cannot completely rule out selection and regression to the mean as alternative explanations.

Life-course socioeconomic environment and health risk behaviours: a multilevel small-area analysis of young-old persons in an urban neighbourhood in Lausanne, Switzerland

With a life expectancy at the age of 65 of around 20 years, damaging health risk behaviours of young-old adults have become a target for preventive actions. Such risk factors necessitate an accurate understanding of the present and past socioeconomic conditions associated with health risk behaviours. The aim of our study is to assess the impact of certain life events as well as economic and environmental factors on health risk behaviours. We included 1309 participants of the Lausanne Cohort Lc65+ aged 65-70 years and employed logistic regression analyses, with individuals nested within areas. The results illustrate the influences of socioeconomic factors from childhood to young-old age. Life experiences in adulthood and economic resources in young-old age are both associated with unfavourable health behaviours. Neighbourhood is a modest determinant as well, particularly regarding alcohol consumption. Therefore, prevention against health risk behaviours should focus on population subgroups defined on the basis of their socioeconomic and living contexts.

Endocytic and secretory traffic in Arabidopsis merge in the trans-Golgi network/early endosome, an independent and highly dynamic organelle.

Plants constantly adjust their repertoire of plasma membrane proteins that mediates transduction of environmental and developmental signals as well as transport of ions, nutrients, and hormones. The importance of regulated secretory and endocytic trafficking is becoming increasingly clear; however, our knowledge of the compartments and molecular machinery involved is still fragmentary. We used immunogold electron microscopy and confocal laser scanning microscopy to trace the route of cargo molecules, including the BRASSINOSTEROID INSENSITIVE1 receptor and the REQUIRES HIGH BORON1 boron exporter, throughout the plant endomembrane system. Our results provide evidence that both endocytic and secretory cargo pass through the trans-Golgi network/early endosome (TGN/EE) and demonstrate that cargo in late endosomes/multivesicular bodies is destined for vacuolar degradation. Moreover, using spinning disc microscopy, we show that TGN/EEs move independently and are only transiently associated with an individual Golgi stack.

Psychiatric co-morbidities and cardiovascular risk factors in people with lifetime history of epilepsy of an urban community.

OBJECTIVES: Depression has been consistently reported in people with epilepsy. Several studies also suggest a higher burden of cardiovascular diseases. We therefore analysed psychosocial co-morbidity and cardiovascular risk factors in patients with a lifetime history of epilepsy in the PsyCoLaus study, a Swiss urban population-based assessment of mental health and cardiovascular risk factors in adults aged between 35 and 66 years. PATIENTS AND METHODS: Among 3719 participants in the PsyCoLaus study, we retrospectively identified those reporting at least 2 unprovoked seizures, defined as epilepsy. These subjects were compared to all others regarding psychiatric, social, and cardiovascular risk factors data using uni- and multivariable assessments. RESULTS: A significant higher need for social help (p<0.001) represented the only independent difference between 43 subjects with a history of epilepsy and 3676 controls, while a higher prevalence of psychiatric co-morbidities (p=0.015) and a lower prevalent marital status (p=0.01) were only significant on univariate analyses. Depression and cardio-vascular risk factors, as well as educational level and employment, were similar among the groups. CONCLUSIONS: This analysis confirms an increased prevalence of psychosocial burden in subjects with a lifetime history of epilepsy; conversely, we did not find a higher cardiovascular risk. The specific urban and geographical location of our cohort and the age span of the studied population may account for the differences from previous studies.

Classification of urban multi-angular image sequences by aligning their manifolds

When dealing with multi-angular image sequences, problems of reflectance changes due either to illumination and acquisition geometry, or to interactions with the atmosphere, naturally arise. These phenomena interplay with the scene and lead to a modification of the measured radiance: for example, according to the angle of acquisition, tall objects may be seen from top or from the side and different light scatterings may affect the surfaces. This results in shifts in the acquired radiance, that make the problem of multi-angular classification harder and might lead to catastrophic results, since surfaces with the same reflectance return significantly different signals. In this paper, rather than performing atmospheric or bi-directional reflection distribution function (BRDF) correction, a non-linear manifold learning approach is used to align data structures. This method maximizes the similarity between the different acquisitions by deforming their manifold, thus enhancing the transferability of classification models among the images of the sequence.