The Behavioral and Psychological Symptoms of Dementia in Down Syndrome (BPSD-DS) Scale:Comprehensive Assessment of Psychopathology in Down Syndrome

People with Down syndrome (DS) are prone to develop Alzheimer's disease (AD). Behavioral and psychological symptoms of dementia (BPSD) are core features, but have not been comprehensively evaluated in DS. In a European multidisciplinary study, the novel Behavioral and Psychological Symptoms of Dementia in Down Syndrome (BPSD-DS) scale was developed to identify frequency and severity of behavioral changes taking account of life-long characteristic behavior. 83 behavioral items in 12 clinically defined sections were evaluated. The central aim was to identify items that change in relation to the dementia status, and thus may differentiate between diagnostic groups. Structured interviews were conducted with informants of persons with DS without dementia (DS, n = 149), with questionable dementia (DS+Q, n = 65), and with diagnosed dementia (DS+AD, n = 67). First exploratory data suggest promising interrater, test-retest, and internal consistency reliability measures. Concerning item relevance, group comparisons revealed pronounced increases in frequency and severity in items of anxiety, sleep disturbances, agitation & stereotypical behavior, aggression, apathy, depressive symptoms, and eating/drinking behavior. The proportion of individuals presenting an increase was highest in DS+AD, intermediate in DS+Q, and lowest in DS. Interestingly, among DS+Q individuals, a substantial proportion already presented increased anxiety, sleep disturbances, apathy, and depressive symptoms, suggesting that these changes occur early in the course of AD. Future efforts should optimize the scale based on current results and clinical experiences, and further study applicability, reliability, and validity. Future application of the scale in daily care may aid caregivers to understand changes, and contribute to timely interventions and adaptation of caregiving

Erratum:The behavioral and psychological symptoms of dementia in down syndrome scale (BPSD-DS II): Optimization and further validation

BACKGROUND: People with Down syndrome (DS) are at high risk to develop Alzheimer's disease dementia (AD). Behavioral and psychological symptoms of dementia (BPSD) are common and may also serve as early signals for dementia. However, comprehensive evaluation scales for BPSD, adapted to DS, are lacking. Therefore, we previously developed the BPSD-DS scale to identify behavioral changes between the last six months and pre-existing life-long characteristic behavior. OBJECTIVE: To optimize and further study the scale (discriminative ability and reliability) in a large representative DS study population. METHODS: Optimization was based on item irrelevance and clinical experiences obtained in the initial study. Using the shortened and refined BPSD-DS II, informant interviews were conducted to evaluate 524 DS individuals, grouped according to dementia status: no dementia (DS, N = 292), questionable dementia (DS + Q, N = 119), and clinically diagnosed dementia (DS + AD, N = 113). RESULTS: Comparing item change scores between groups revealed prominent changes in frequency and severity for anxious, sleep-related, irritable, restless/stereotypic, apathetic, depressive, and eating/drinking behavior. For most items, the proportion of individuals displaying an increased frequency was highest in DS + AD, intermediate in DS + Q, and lowest in DS. For various items within sections about anxious, sleep-related, irritable, apathetic, and depressive behaviors, the proportion of individuals showing an increased frequency was already substantial in DS + Q, suggesting that these changes may serve as early signals of AD in DS. Reliability data were promising. CONCLUSION: The optimized scale yields largely similar results as obtained with the initial version. Systematically evaluating BPSD in DS may increase understanding of changes among caregivers and (timely) adaptation of care/treatment

Plague Circulation and Population Genetics of the Reservoir Rattus rattus: The Influence of Topographic Relief on the Distribution of the Disease within the Madagascan Focus.

International audienceBACKGROUND: Landscape may affect the distribution of infectious diseases by influencing the population density and dispersal of hosts and vectors. Plague (Yersinia pestis infection) is a highly virulent, re-emerging disease, the ecology of which has been scarcely studied in Africa. Human seroprevalence data for the major plague focus of Madagascar suggest that plague spreads heterogeneously across the landscape as a function of the relief. Plague is primarily a disease of rodents. We therefore investigated the relationship between disease distribution and the population genetic structure of the black rat, Rattus rattus, the main reservoir of plague in Madagascar. METHODOLOGYPRINCIPAL FINDINGS: We conducted a comparative study of plague seroprevalence and genetic structure (15 microsatellite markers) in rat populations from four geographic areas differing in topology, each covering about 150-200 km(2) within the Madagascan plague focus. The seroprevalence levels in the rat populations mimicked those previously reported for humans. As expected, rat populations clearly displayed a more marked genetic structure with increasing relief. However, the relationship between seroprevalence data and genetic structure differs between areas, suggesting that plague distribution is not related everywhere to the effective dispersal of rats. CONCLUSIONSSIGNIFICANCE: Genetic diversity estimates suggested that plague epizootics had only a weak impact on rat population sizes. In the highlands of Madagascar, plague dissemination cannot be accounted for solely by the effective dispersal of the reservoir. Human social activities may also be involved in spreading the disease in rat and human populations

Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks

peer reviewedaudience: researcher, professionalVarious approaches exist to relate saturated hydraulic conductivity (Ks) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods, i.e.multiple linear regression and artificial neural networks, that use the entire grain-size distribution data as input for Ks prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalized likelihood uncertainty estimation (GLUE) approach to predict Ks from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from literature demonstrates the importance of site specific calibration. The dataset used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size -Ks pairs. Finally, an application with the optimized models is presented for a borehole lacking Ks data

The behavioral and psychological symptoms of dementia in down syndrome (BPSD-DS) scale:comprehensive assessment of psychopathology in down syndrome

Behavioral and psychological symptoms of dementia (BPSD) have not been comprehensively studied in people with Down syndrome, despite their high risk on dementia. A novel evaluation scale was developed to identify the nature, frequency and severity of behavioral changes (83 behavioral items in 12 clinically defined sections). Central aim was to identify items that change in relation to the dementia status. Structured interviews were conducted with informants of people with Down syndrome without dementia (DS, N = 149), with questionable dementia (DS + TD, N = 65) and with diagnosed dementia (DS + AD, N = 67). Group comparisons showed a pronounced increase in frequency and severity of items about anxiety, sleep disturbances, agitation & stereotypical behavior, aggression, apathy, depressive symptoms, and, eating/drinking behavior. The proportion of individuals presenting an increase was highest in the DS + AD group and lowest in the DS group. Interestingly, among DS + TD individuals, a substantial proportion already presented increased anxiety, sleep disturbances, apathy and depressive symptoms, suggesting that these changes may be early alarm signals of dementia. The scale may contribute to a better understanding of the changes, adapting daily care/support, and providing suitable therapies to people with Down syndrome. The scale needs to be optimized based on the results and experiences. The applicability, reliability and validity require further study

Insights into the Complex Associations Between MHC Class II DRB Polymorphism and Multiple Gastrointestinal Parasite Infestations in the Striped Mouse

Differences in host susceptibility to different parasite types are largely based on the degree of matching between immune genes and parasite antigens. Specifically the variable genes of the major histocompatibility complex (MHC) play a major role in the defence of parasites. However, underlying genetic mechanisms in wild populations are still not well understood because there is a lack of studies which deal with multiple parasite infections and their competition within. To gain insights into these complex associations, we implemented the full record of gastrointestinal nematodes from 439 genotyped individuals of the striped mouse, Rhabdomys pumilio. We used two different multivariate approaches to test for associations between MHC class II DRB genotype and multiple nematodes with regard to the main pathogen-driven selection hypotheses maintaining MHC diversity and parasite species-specific co-evolutionary effects. The former includes investigations of a ‘heterozygote advantage’, or its specific form a ‘divergent-allele advantage’ caused by highly dissimilar alleles as well as possible effects of specific MHC-alleles selected by a ‘rare allele advantage’ ( = negative ‘frequency-dependent selection’). A combination of generalized linear mixed models (GLMMs) and co-inertia (COIA) analyses made it possible to consider multiple parasite species despite the risk of type I errors on the population and on the individual level. We could not find any evidence for a ‘heterozygote’ advantage but support for ‘divergent-allele’ advantage and infection intensity. In addition, both approaches demonstrated high concordance of positive as well as negative associations between specific MHC alleles and certain parasite species. Furthermore, certain MHC alleles were associated with more than one parasite species, suggesting a many-to-many gene-parasite co-evolution. The most frequent allele Rhpu-DRB*38 revealed a pleiotropic effect, involving three nematode species. Our study demonstrates the co-existence of specialist and generalist MHC alleles in terms of parasite detection which may be an important feature in the maintenance of MHC polymorphism