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PURPOSE: The Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel (VCEP) was established by the International Society for Gastrointestinal Hereditary Tumours and the Clinical Genome Resource, who set out to develop recommendations for the interpretation of germline APC variants underlying Familial Adenomatous Polyposis, the most frequent hereditary polyposis syndrome. METHODS: Through a rigorous process of database analysis, literature review, and expert elicitation, the APC VCEP derived gene-specific modifications to the ACMG/AMP (American College of Medical Genetics and Genomics and Association for Molecular Pathology) variant classification guidelines and validated such criteria through the pilot classification of 58 variants. RESULTS: The APC-specific criteria represented gene- and disease-informed specifications, including a quantitative approach to allele frequency thresholds, a stepwise decision tool for truncating variants, and semiquantitative evaluations of experimental and clinical data. Using the APC-specific criteria, 47% (27/58) of pilot variants were reclassified including 14 previous variants of uncertain significance (VUS). CONCLUSION: The APC-specific ACMG/AMP criteria preserved the classification of well-characterized variants on ClinVar while substantially reducing the number of VUS by 56% (14/25). Moving forward, the APC VCEP will continue to interpret prioritized lists of VUS, the results of which will represent the most authoritative variant classification for widespread clinical use.

In the coming years, the number of electric vehicles (EVs) is going to increase, while the charging network might not be adequately expanded at the required time. It is very likely that there will be feedback effects within the power grid in form of capacity bottlenecks. This might result in reduced charging power for a higher number of electric vehicles in order to counteract fluctuations. In this paper, the authors describe a management system for electric vehicles that optimizes the allocation of charging processes on motorways. The designed system aims to optimize travel and charging times while reducing waiting times for electric vehicles in intercity transport. By considering respective charging capacities, it may be able to reduce feedback effects with the energy system. The management system uses data from the charging stations, electric vehicles and their planned route. This allows the system to forward relevant information regarding expected energy demand to the power grid. Consequently, vehicles periodically communicate their position, battery level and their remaining way to destination to the management system, which returns charging advice for the optimal charging station. By using an optimization algorithm, the scarce resource of the charging stations is efficiently allocated to the vehicles. In order to examine its efficiency, a model of the management system with reduced features is transferred into a simulation. The simulation study follows an academic approach and takes different penetration rates of electric vehicles into account. A heuristic approach led to a solution with reasonable complexity, i.e. polynomial running time. In comparison, an analytical solution was outlined which describes the optimal case. This simulation study shows that the proposed system manages the waiting times efficiently by smartly assigning the vehicles to the corresponding charging stations.