Background-Access-site and access-related vascular injury (ASARVI) is still a major limiting factor in transcatheter aortic valve implantation and affects the outcome of patients. Management strategies for ASARVI include manual compression, stent grafts, and vascular surgery. We hypothesized that the standard use of a self-expanding stent graft for the management of ASARVI is feasible and safe. Methods and Results-Of 407 patients treated by transfemoral transcatheter aortic valve implantation, 110 experienced ASARVI (27.0%). Of these, 96 (87.3%) were managed by the implantation of a self-expanding nitinol stent graft. In the majority of patients, minor vascular complications triggered the implantation of a stent graft (86.5%), mainly because of bleeding (90.6%) and dissection (5.2%) of the common femoral artery with high rates of primary treatment success (97.9%

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In the last chapter of 1 Timothy there is one passage arguing passionately and polemically against diff erently minded teachers. It calls on its readers to beware of the diff erent teaching (1 Tim 6:3-12). Th is New Testament text brings forward a train of thought that shows far reaching parallels to the Cynic Philosophy of the 1st and 2nd centuries A.D. Th e criticism which 1 Timothy passes on its opponents corresponds to the criticism of the contemporary Cynics against their adversaries. It mainly concerns the hypocritical motivations that lead the diff erently minded teachers to preach their message: according to the view of their critics they only aim to make money out of their teachings. In this reasoning polemical and paraenetical components unite. Th e careful consideration of this New Testament passage's similarity to the cynic world of thought also faciliates the description of the specifi c character in the intention of 1 Timothy against the cynic background, i.e. the christological accentuation of the favoured good teaching and lifestyle.

Exploring new ways to represent and discover organic molecules is critical to the development of new therapies. Fingerprinting algorithms are used to encode or machine-read organic molecules. Molecular encodings facilitate the computation of distance and similarity measurements to support tasks such as similarity search or virtual screening. Motivated by the ubiquity of carbon and the emerging structured patterns, we propose a parametric approach for molecular encodings using carbon-based multilevel atomic neighborhoods. It implements a walk along the carbon chain of a molecule to compute different representations of the neighborhoods in the form of a binary or numerical array that can later be exported into an image. Applied to the task of binary peptide classification, the evaluation was performed by using forty-nine encodings of twenty-nine data sets from various biomedical fields, resulting in well over 1421 machine learning models. By design, the parametric approach is domain- and task-agnostic and scopes all organic molecules including unnatural and exotic amino acids as well as cyclic peptides. Applied to peptide classification, our results point to a number of promising applications and extensions. The parametric approach was developed as a Python package (cmangoes), the source code and documentation of which can be found at https://github.com/ghattab/cmangoes and https://doi.org/10.5281/zenodo.7483771.

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