Gaussian Process-based prediction of memory performance and biomarker status in ageing and Alzheimer's disease-A systematic model evaluation.

Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as genetic covariates, biomarkers, vascular risk factors, neuropsychological tests etc.) might provide useful predictions of clinical outcomes during the progression towards Alzheimer's disease (AD). The use of multiple features in predictive frameworks for clinical outcomes has become increasingly prevalent in AD research. However, many studies do not focus on systematically and accurately evaluating combinations of multiple input features. Hence, the aim of the present work is to explore and assess optimal combinations of various features for MR-based prediction of (1) cognitive status and (2) biomarker positivity with a multi-kernel learning Gaussian process framework. The explored features and parameters included (A) combinations of brain tissues, modulation, smoothing, and image resolution; (B) incorporating demographics & clinical covariates; (C) the impact of the size of the training data set; (D) the influence of dimensionality reduction and the choice of kernel types. The approach was tested in a large German cohort including 959 subjects from the multicentric longitudinal study of cognitive impairment and dementia (DELCODE). Our evaluation suggests the best prediction of memory performance was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF biomarkers explaining 57% of outcome variance in out-of-sample predictions. The highest performance for Aß42/40 status classification was achieved for a combination of demographics, ApoE4, and a memory score while usage of structural MRI further improved the classification of individual patient's pTau status.

Identification of Desulfobacterales as primary hydrogenotrophs in a complex microbial mat community.

Hypersaline microbial mats have been shown to produce significant quantities of H2 under dark, anoxic conditions via cyanobacterial fermentation. This flux of a widely accessible microbial substrate has potential to significantly influence the ecology of the mat, and any consumption will affect the net efflux of H2 that might otherwise be captured as a resource. Here, we focus on H2 consumption in a microbial mat from Elkhorn Slough, California, USA, for which H2 production has been previously characterized. Active biologic H2 consumption in this mat is indicated by a significant time-dependent decrease in added H2 compared with a killed control. Inhibition of sulfate reduction, as indicated by a decrease in hydrogen sulfide production relative to controls, resulted in a significant increase in H2 efflux, suggesting that sulfate-reducing bacteria (SRB) are important hydrogenotrophs. Low methane efflux under these same conditions indicated that methanogens are likely not important hydrogenotrophs. Analyses of genes and transcripts that encode for rRNA or dissimilatory sulfite reductase, using both PCR-dependent and PCR-independent metatranscriptomic sequencing methods, demonstrated that Desulfobacterales are the dominant, active SRB in the upper, H2-producing layer of the mat (0-2 mm). This hypothesis was further supported by the identification of transcripts encoding hydrogenases derived from Desulfobacterales capable of H2 oxidation. Analysis of molecular data provided no evidence for the activity of hydrogenotrophic methanogens. The combined biogeochemical and molecular data strongly indicate that SRB belonging to the Desulfobacterales are the quantitatively important hydrogenotrophs in the Elkhorn Slough mat.

A lack of predatory interaction between rumen ciliate protozoa and Shiga-toxin producing Escherichia coli.

AIMS: To investigate interactions between rumen protozoa and Shiga toxin-producing Escherichia coli (STEC) and to ascertain whether it is likely that rumen protozoa act as ruminant hosts for STEC. METHODS AND RESULTS: The presence of stx genes in different microbial fractions recovered from cattle and sheep rumen contents and faeces was examined using PCR. In animals shedding faecal STEC, stx genes were not detected in the rumen bacterial or rumen protozoal fractions. Direct interactions between ruminal protozoa and STEC were investigated by in vitro co-incubation. Rumen protozoa did not appear to ingest STEC, a STEC lysogen or non-STEC E. coli populations when co-incubated. CONCLUSIONS: The ruminal environment is unlikely to be a preferred habitat for STEC. Bacterial grazing by rumen protozoa appears to have little, if any, effect on STEC populations. SIGNIFICANCE AND IMPACT OF THE STUDY: This study indicates that ruminal protozoa are unlikely to be a major factor in the survival of STEC in ruminants. They appear as neither a host that protects STEC from the ruminal environment nor a predator that might reduce STEC numbers.