@article{JiangOronClarketal.2016, author = {Jiang, Yuxiang and Oron, Tal Ronnen and Clark, Wyatt T. and Bankapur, Asma R. and D'Andrea, Daniel and Lepore, Rosalba and Funk, Christopher S. and Kahanda, Indika and Verspoor, Karin M. and Ben-Hur, Asa and Koo, Da Chen Emily and Penfold-Brown, Duncan and Shasha, Dennis and Youngs, Noah and Bonneau, Richard and Lin, Alexandra and Sahraeian, Sayed M. E. and Martelli, Pier Luigi and Profiti, Giuseppe and Casadio, Rita and Cao, Renzhi and Zhong, Zhaolong and Cheng, Jianlin and Altenhoff, Adrian and Skunca, Nives and Dessimoz, Christophe and Dogan, Tunca and Hakala, Kai and Kaewphan, Suwisa and Mehryary, Farrokh and Salakoski, Tapio and Ginter, Filip and Fang, Hai and Smithers, Ben and Oates, Matt and Gough, Julian and T{\"o}r{\"o}nen, Petri and Koskinen, Patrik and Holm, Liisa and Chen, Ching-Tai and Hsu, Wen-Lian and Bryson, Kevin and Cozzetto, Domenico and Minneci, Federico and Jones, David T. and Chapman, Samuel and BKC, Dukka and Khan, Ishita K. and Kihara, Daisuke and Ofer, Dan and Rappoport, Nadav and Stern, Amos and Cibrian-Uhalte, Elena and Denny, Paul and Foulger, Rebecca E. and Hieta, Reija and Legge, Duncan and Lovering, Ruth C. and Magrane, Michele and Melidoni, Anna N. and Mutowo-Meullenet, Prudence and Pichler, Klemens and Shypitsyna, Aleksandra and Li, Biao and Zakeri, Pooya and ElShal, Sarah and Tranchevent, L{\´e}on-Charles and Das, Sayoni and Dawson, Natalie L. and Lee, David and Lees, Jonathan G. and Sillitoe, Ian and Bhat, Prajwal and Nepusz, Tam{\´a}s and Romero, Alfonso E. and Sasidharan, Rajkumar and Yang, Haixuan and Paccanaro, Alberto and Gillis, Jesse and Sede{\~n}o-Cort{\´e}s, Adriana E. and Pavlidis, Paul and Feng, Shou and Cejuela, Juan M. and Goldberg, Tatyana and Hamp, Tobias and Richter, Lothar and Salamov, Asaf and Gabaldon, Toni and Marcet-Houben, Marina and Supek, Fran and Gong, Qingtian and Ning, Wei and Zhou, Yuanpeng and Tian, Weidong and Falda, Marco and Fontana, Paolo and Lavezzo, Enrico and Toppo, Stefano and Ferrari, Carlo and Giollo, Manuel and Piovesan, Damiano and Tosatto, Silvio C. E. and del Pozo, Angela and Fern{\´a}ndez, Jos{\´e} M. and Maietta, Paolo and Valencia, Alfonso and Tress, Michael L. and Benso, Alfredo and Di Carlo, Stefano and Politano, Gianfranco and Savino, Alessandro and Rehman, Hafeez Ur and Re, Matteo and Mesiti, Marco and Valentini, Giorgio and Bargsten, Joachim W. and van Dijk, Aalt D. J. and Gemovic, Branislava and Glisic, Sanja and Perovic, Vladmir and Veljkovic, Veljko and Almeida-e-Silva, Danillo C. and Vencio, Ricardo Z. N. and Sharan, Malvika and Vogel, J{\"o}rg and Kansakar, Lakesh and Zhang, Shanshan and Vucetic, Slobodan and Wang, Zheng and Sternberg, Michael J. E. and Wass, Mark N. and Huntley, Rachael P. and Martin, Maria J. and O'Donovan, Claire and Robinson, Peter N. and Moreau, Yves and Tramontano, Anna and Babbitt, Patricia C. and Brenner, Steven E. and Linial, Michal and Orengo, Christine A. and Rost, Burkhard and Greene, Casey S. and Mooney, Sean D. and Friedberg, Iddo and Radivojac, Predrag and Veljkovic, Nevena}, title = {An expanded evaluation of protein function prediction methods shows an improvement in accuracy}, series = {Genome Biology}, volume = {17}, journal = {Genome Biology}, number = {184}, doi = {10.1186/s13059-016-1037-6}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-166293}, year = {2016}, abstract = {Background A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.}, language = {en} } @article{FlemmingHankirErnestusetal.2020, author = {Flemming, S. and Hankir, M. and Ernestus, R.-I. and Seyfried, F. and Germer, C.-T. and Meybohm, P. and Wurmb, T. and Vogel, U. and Wiegering, A.}, title = {Surgery in times of COVID-19 — recommendations for hospital and patient management}, series = {Langenbeck's Archives of Surgery}, volume = {405}, journal = {Langenbeck's Archives of Surgery}, issn = {1435-2443}, doi = {10.1007/s00423-020-01888-x}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-231766}, pages = {359-364}, year = {2020}, abstract = {Background The novel coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2), has escalated rapidly to a global pandemic stretching healthcare systems worldwide to their limits. Surgeonshave had to immediately react to this unprecedented clinical challenge by systematically repurposing surgical wards. Purpose To provide a detailed set of guidelines developed in a surgical ward at University Hospital Wuerzburg to safelyaccommodate the exponentially rising cases of SARS-CoV-2 infected patients without compromising the care of emergencysurgery and oncological patients or jeopardizing the well-being of hospital staff. Conclusions The dynamic prioritization of SARS-CoV-2 infected and surgical patient groups is key to preserving life whilemaintaining high surgical standards. Strictly segregating patient groups in emergency rooms, non-intensive care wards andoperating areas prevents viral spread while adequately training and carefully selecting hospital staff allow them to confidentlyand successfully undertake their respective clinical duties.}, language = {en} } @article{VogelRueckertGreineretal.2023, author = {Vogel, P. and R{\"u}ckert, M. A. and Greiner, C. and G{\"u}nther, J. and Reichl, T. and Kampf, T. and Bley, T. A. and Behr, V. C. and Herz, S.}, title = {iMPI: portable human-sized magnetic particle imaging scanner for real-time endovascular interventions}, series = {Scientific Reports}, volume = {13}, journal = {Scientific Reports}, doi = {10.1038/s41598-023-37351-2}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-357794}, year = {2023}, abstract = {Minimally invasive endovascular interventions have become an important tool for the treatment of cardiovascular diseases such as ischemic heart disease, peripheral artery disease, and stroke. X-ray fluoroscopy and digital subtraction angiography are used to precisely guide these procedures, but they are associated with radiation exposure for patients and clinical staff. Magnetic Particle Imaging (MPI) is an emerging imaging technology using time-varying magnetic fields combined with magnetic nanoparticle tracers for fast and highly sensitive imaging. In recent years, basic experiments have shown that MPI has great potential for cardiovascular applications. However, commercially available MPI scanners were too large and expensive and had a small field of view (FOV) designed for rodents, which limited further translational research. The first human-sized MPI scanner designed specifically for brain imaging showed promising results but had limitations in gradient strength, acquisition time and portability. Here, we present a portable interventional MPI (iMPI) system dedicated for real-time endovascular interventions free of ionizing radiation. It uses a novel field generator approach with a very large FOV and an application-oriented open design enabling hybrid approaches with conventional X-ray-based angiography. The feasibility of a real-time iMPI-guided percutaneous transluminal angioplasty (PTA) is shown in a realistic dynamic human-sized leg model.}, language = {en} }