Personalized Oncogenomics (POG) Program of British Columbia: Utilization of Genomic Analysis to Better Understand Tumour Heterogeneity and Evolution (NCT02155621).

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Epilepsy is one of the most common chronic neurological diseases. High-frequency oscillations (HFOs) have emerged as promising biomarkers for the epileptogenic zone. However, visual marking of HFOs is a time-consuming and laborious process. Several automated techniques have been proposed to detect HFOs, yet these are still far from being suitable for application in a clinical setting. Here, ripples and fast ripples from intracranial electroencephalograms were detected in six patients with intractable epilepsy using a convolutional neural network (CNN) method. This approach proved more accurate than using four other HFO detectors integrated in RIPPLELAB, providing a higher sensitivity (77.04% for ripples and 83.23% for fast ripples) and specificity (72.27% for ripples and 79.36% for fast ripples) for HFO detection. Furthermore, for one patient, the Cohen's kappa coefficients comparing automated detection and visual analysis results were 0.541 for ripples and 0.777 for fast ripples. Hence, our automated detector was capable of reliable estimates of ripples and fast ripples with higher sensitivity and specificity than four other HFO detectors. Our detector may be used to assist clinicians in locating epileptogenic zone in the future.

Aims:  To discover novel naturally occurring xylitol producing yeast species with potential for industrial applications. Methods and Results:  Exactly 274 strains were cultivated on both solid and liquid screening medium with xylose as the sole carbon resource. Five strains were selected on the basis of significant growth and high degree of xylose assimilation. Their phylogenetic position was confirmed by the PCR‐RFLP and sequence analysis of the D1/D2 domain of the 5′ end of the large subunit rDNA gene (5′‐LSU rDNA). Enzymatic analysis was conducted to compare xylose metabolism in each strain. Candida guilliermondii Xu280 and Candida maltosa Xu316 were found to have high xylose consumption rates and xylitol yields in the batch fermentation under micro‐aerobic condition. The effect of the different media with high initial xylose concentration on biosynthesis of xylitol by both strains was investigated. Conclusions:  We have identified Candida spp. strains, which exhibit high levels of xylitol production from xylose suggesting that these may have potential for industrial applications. Significance and Impacts of the Study:  Microbial species are of importance for xylitol production. Xylitol production involves complicated metabolic regulation including xylose transport, production of key enzymes and cofactor regeneration. Thus, screening of naturally occurring xylose‐utilizing micro‐organisms is a viable and effective mean to obtain xylitol producing organisms with industrial application. Moreover, the research on selected strains will contribute to a better understanding of regulatory properties of xylose metabolism in different yeasts.

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