Microbiome and environment explain the absence of correlations between consumers and their diet in Bornean microsnails

Classical ecological theory posits that species partition resources such that each species occupies a unique resource niche. In general, the availability of more resources allows more species to co‐occur. Thus, a strong relationship between communities of consumers and their resources is expected. However, correlations may be influenced by other layers in the food web, or by the environment. Here we show, by studying the relationship between communities of consumers (land snails) and individual diets (from seed plants), that there is in fact no direct, or at most a weak but negative, relationship. However, we found that the diversity of the individual microbiome positively correlates with both consumer community diversity and individual diet diversity in three target species. Moreover, these correlations were affected by various environmental variables, such as anthropogenic activity, habitat island size, and a possibly important nutrient source, guano runoff from nearby caves. Our results suggest that the microbiome and the environment explain the absence of correlations between diet and consumer community diversity. Hence, we advocate that microbiome inventories are routinely added to any community dietary analysis, which our study shows can be done with relatively little extra effort. Our approach presents the tools to quickly obtain an overview of the relationships between consumers and their resources. We anticipate our approach to be useful for ecologists and environmentalist studying different communities in a local food web

Use of fuzzy edge single-photon emission computed tomography analysis in definite Alzheimer's disease - a retrospective study

<p>Abstract</p> <p>Background</p> <p>Definite Alzheimer's disease (AD) requires neuropathological confirmation. Single-photon emission computed tomography (SPECT) may enhance diagnostic accuracy, but due to restricted sensitivity and specificity, the role of SPECT is largely limited with regard to this purpose.</p> <p>Methods</p> <p>We propose a new method of SPECT data analysis. The method is based on a combination of parietal lobe selection (as regions-of-interest (ROI)), 3D fuzzy edge detection, and 3D watershed transformation. We applied the algorithm to three-dimensional SPECT images of human brains and compared the number of watershed regions inside the ROI between AD patients and controls. The Student's two-sample t-test was used for testing domain number equity in both groups.</p> <p>Results</p> <p>AD patients had a significantly reduced number of watershed regions compared to controls (<it>p </it>< 0.01). A sensitivity of 94.1% and specificity of 80% was obtained with a threshold value of 57.11 for the watershed domain number. The narrowing of the SPECT analysis to parietal regions leads to a substantial increase in both sensitivity and specificity.</p> <p>Conclusions</p> <p>Our non-invasive, relatively low-cost, and easy method can contribute to a more precise diagnosis of AD.</p