Diseases and Causes of Death in European Bats: Dynamics in Disease Susceptibility and Infection Rates

Bats receive increasing attention in infectious disease studies, because of their well recognized status as reservoir species for various infectious agents. This is even more important, as bats with their capability of long distance dispersal and complex social structures are unique in the way microbes could be spread by these mammalian species. Nevertheless, infection studies in bats are predominantly limited to the identification of specific pathogens presenting a potential health threat to humans. But the impact of infectious agents on the individual host and their importance on bat mortality is largely unknown and has been neglected in most studies published to date.) were collected in different geographic regions in Germany. Most animals represented individual cases that have been incidentally found close to roosting sites or near human habitation in urban and urban-like environments. The bat carcasses were subjected to a post-mortem examination and investigated histo-pathologically, bacteriologically and virologically. Trauma and disease represented the most important causes of death in these bats. Comparative analysis of pathological findings and microbiological results show that microbial agents indeed have an impact on bats succumbing to infectious diseases, with fatal bacterial, viral and parasitic infections found in at least 12% of the bats investigated.Our data demonstrate the importance of diseases and infectious agents as cause of death in European bat species. The clear seasonal and individual variations in disease prevalence and infection rates indicate that maternity colonies are more susceptible to infectious agents, underlining the possible important role of host physiology, immunity and roosting behavior as risk factors for infection of bats

Learning Biomarker Models for Progression Estimation of Alzheimer’s Disease

Being able to estimate a patient’s progress in the course of Alzheimer’s disease and predicting future progression based on a number of observed biomarker values is of great interest for patients, clinicians and researchers alike. In this work, an approach for disease progress estimation is presented. Based on a set of subjects that convert to a more severe disease stage during the study, models that describe typical trajectories of biomarker values in the course of disease are learned using quantile regression. A novel probabilistic method is then derived to estimate the current disease progress as well as the rate of progression of an individual by fitting acquired biomarkers to the models. A particular strength of the method is its ability to naturally handle missing data. This means, it is applicable even if individual biomarker measurements are missing for a subject without requiring a retraining of the model. The functionality of the presented method is demonstrated using synthetic and—employing cognitive scores and image-based biomarkers—real data from the ADNI study. Further, three possible applications for progress estimation are demonstrated to underline the versatility of the approach: classification, construction of a spatio-temporal disease progression atlas and prediction of future disease progression

Virus occurrence in private and public wells in a fractured dolostone aquifer in Canada

Groundwater samples from 22 wells completed in a regional fractured dolostone aquifer in the Guelph region of southern Ontario, Canada, were collected over an 8-month period and analyzed for viruses and Campylobacter jejuni. Only 8% of the 118 samples exhibited viruses at extremely low concentrations, but of the 22 wells sampled, 10 (45%) were positive for human enteric viruses (polyomavirus, adenovirus A, and GII norovirus) including 5 of the 8 public supply wells (62.5%) and 5 of the 11 private wells (45%). Each virus-positive well had only one virus occurrence with six sampling events during the 8-month sampling campaign and only one virus type was detected in each well. The probability of virus detection was positively associated with well open-interval length. Virus concentration (in the wells that were virus-positive) was negatively associated with well depth and open-interval length and positively associated with overburden thickness (ie, the thickness of unconsolidated materials overlying bedrock facies) and the amount of precipitation 8–14 and 15–21 days prior to the sampling date. The ephemeral nature of the virus detections and the low detection rate on a per sample basis were consistent with previous studies. The percentage of virus-positive wells, however, was much higher than previous studies, but consistent with the fact that the hydrogeologic conditions of fractured bedrock aquifers create wide capture zones and short groundwater travel times to wells making them more vulnerable to contamination occurrence but at very low concentrations