Untersuchung der Serumkonzentrationen von secreted frizzled-related protein 5 bei Probanden mit Parodontitis in der Kieler FoCus-Kohorte

Ein Ungleichgewicht zwischen dem anti-inflammatorischen Adipozytokin secreted frizzled-related Protein 5 (sFRP5) und dem pro-inflammatorischen Glykoprotein wingless-type MMTV integration site family member 5a (Wnt5a) ist entscheidend in der Pathophysiologie verschiedener Entzündungsprozesse. Eine lokale Beteiligung des parainflammatorischen sFRP5/Wnt5a-Systems an der Pathogenese der bakteriell induzierten Parodontitis ist vorbeschrieben. Ziel dieser Arbeit war die Evaluation des Einflusses genetischer Alterationen und systemischer Serumkonzentrationen des Duos sFRP5/Wnt5a auf den Schweregrad der humanen Parodontitis. Dazu wurden 746 Probanden aus der Kieler Food Chain Plus (FoCus) Kohorte (http://www.focus.uni-kiel.de) rekrutiert. In diesen wurden aus venösem Nüchternblut sFRP5- und Wnt5a-Serumspiegel quantitativ mittels ELISA sowie sFRP5- und Wnt5a- Einzelnukleotid-Polymorphismen (SNPs) mittels Omni Express Exome Microarray bestimmt. In einer Case-Control-Studie wurden sFRP5- und Wnt5a-Serumspiegel sowie sFRP5- und Wnt5a-SNPs zwischen Patienten mit einer Parodontitis ohne Zahnverlust (n=245), Patienten mit einer Parodontitis und Zahnverlust (n=128) und gematchten (Geschlecht, Raucherstatus, Alter, Body Mass Index) Kontrollen (n=373) verglichen. In den 746 Fällen führte Homozygotie im sFRP5-SNP rs2039826 zu signifikant niedrigeren sFRP5-Serumkonzentrationen (p<0,05). sFRP5-Serumspiegel waren signifikant niedriger bei den Patienten mit Parodontitis und Zahnverlust 2,5 (0,0-10,4) im Vergleich zu Patienten mit Parodontitis ohne Zahnverlust 6,0 (2,5-15,8) ng/mL (p=0,04) und gematchten Kontrollen 7,0 (2,5-18,3) ng/mL (p=0,02). Zwischen Patienten mit Parodontitis ohne Zahnverlust 6,0 (2,5-15,8) ng/mL und gematchten Kontrollen 3,1 (0,0-10,6) ng/mL zeigte sich kein signifikanter Unterschied (p=0,06). Signifikante Assoziationen zwischen den untersuchten Gruppen bezogen auf Wnt5a-SNPs und -Serumspiegel zeigten sich nicht. Systemisches sFRP5 könnte eine entscheidende Rolle in der Pathogenese schwerer Parodontitiden spielen, gegebenenfalls sogar genetisch prädispositioniert. Weitere Studien zur Parodontitis müssen zeigen, ob sFRP5 als systemischer Biomarker gelten kann und eine Option zur Diagnostik sowie eine gezielte, kausale Behandlungsmöglichkeit durch die systematische und/oder lokale Gabe von rekombinantem sFRP5 darstellt

BERT WEAVER: Using WEight AVERaging to enable lifelong learning for transformer-based models in biomedical semantic search engines

Recent developments in transfer learning have boosted the advancements in natural language processing tasks. The performance is, however, dependent on high-quality, manually annotated training data. Especially in the biomedical domain, it has been shown that one training corpus is not enough to learn generic models that are able to efficiently predict on new data. Therefore, in order to be used in real world applications state-of-the-art models need the ability of lifelong learning to improve performance as soon as new data are available - without the need of re-training the whole model from scratch. We present WEAVER, a simple, yet efficient post-processing method that infuses old knowledge into the new model, thereby reducing catastrophic forgetting. We show that applying WEAVER in a sequential manner results in similar word embedding distributions as doing a combined training on all data at once, while being computationally more efficient. Because there is no need of data sharing, the presented method is also easily applicable to federated learning settings and can for example be beneficial for the mining of electronic health records from different clinics

Practical algorithms for multivariate rational approximation

17 USC 105 interim-entered record; under review.The article of record as published may be found at https://doi.org/10.1016/j.cpc.2020.107663We present two approaches for computing rational approximations to multivariate functions, motivated by their effectiveness as surrogate models for high-energy physics (HEP) applications. Our first approach builds on the Stieltjes process to efficiently and robustly compute the coefficients of the rational approximation. Our second approach is based on an optimization formulation that allows us to include structural constraints on the rational approximation (in particular, constraints demanding the absence of singularities), resulting in a semi-infinite optimization problem that we solve using an outer approximation approach. We present results for synthetic and real-life HEP data, and we compare the approximation quality of our approaches with that of traditional polynomial approximations.This work was supported by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research, under Contract DE-AC02-06CH11357. Support for this work was provided through the SciDAC program funded by U.S. Department of Energy, Office of Science, Advanced Scientific Computing Re search. This work was also supported by the U.S. Department of Energy through grant DE-FG02-05ER25694, and by Fermi Re search Alliance, LLC, United States of America under Contract No. DE-AC02-07CH11359 with the U.S. Department of Energy, Office of Science, Office of High Energy Physics. This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research and Office of Nuclear Physics, Scientific Discovery through Advanced Computing (SciDAC) program through the FASTMath Institute under Contract No. DE-AC02-05CH11231 at Lawrence Berkeley National Laboratory

Fracture strength test of digitally produced ceramic-filled and unfilled dental resin restorations via 3d printing : an in vitro study

Purpose of this study was to investigate the mechanical efficiency of 3D-printed permanent and provisional implant cemented fixed bridges produced via CAD/CAM technology using an interim and a permanent ceramic filled hybrid material. Two groups with t

Microbiological Characteristics and Surgical Management of Animal-Bite-Related Oral & Maxillofacial Injuries: A Single Center's Experience

The objective of the current study is to retrospectively evaluate animal-bite injuries and to gain insight into the epidemiology, accident consequences and treatment concept of these accidents in oral and maxillofacial surgery. Data of patients, who were admitted January 2015 and April 2021, were retrospectively evaluated regarding the patients' characteristics (age, gender), facial distribution of substance defects/partial amputations, duration of hospitalization, operation treatments and antibiotic treatments. Data of 75 patients were included. Patients were bitten by dogs (n = 69.92%), cats (n = 4) and horses (n = 2). Lower eyelid/cheek complex was the most affected region (n = 37, 32.74%). Most of the patients between 0 and 3 years had to be operated on under general anesthesia (p = 0.011), while most of the adults could be operated on under local anesthesia (p = 0.007). In the age group 0-12 years, 30 patients (68%) were operated on under general anesthesia. Ampicillin/Sulbactam (48%) was the antibiotic most used. Antibiotics were adjusted after wound swabs in case of wound infections or critical wound conditions. This means that resistant antibiotics were stopped, and sensitive antibiotics were used. Structured surgical and antibiotic management of animal-bite wounds in the maxillofacial region is the most important factor for medical care to avoid long-term aesthetic consequences. Public health actions and policies under the leadership of an interdisciplinary committee could improve primary wound management, healing outcome and information status in the general population

BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators

The parameters in Monte Carlo (MC) event generators are tuned on experimental measurements by evaluating the goodness of fit between the data and the MC predictions. The relative importance of each measurement is adjusted manually in an often time consuming, iterative process to meet different experimental needs. In this work, we introduce several optimization formulations and algorithms with new decision criteria for streamlining and automating this process. These algorithms are designed for two formulations: bilevel optimization and robust optimization. Both formulations are applied to the datasets used in the ATLAS A14 tune and to the dedicated hadronization datasets generated by the SHERPA generator, respectively. The corresponding tuned generator parameters are compared using three metrics. We compare the quality of our automatic tunes to the published ATLAS A14 tune. Moreover, we analyze the impact of a pre-processing step that excludes data that cannot be described by the physics models used in the MC event generators

Apprentice for Event Generator Tuning

Apprentice is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and likelihood evaluation. Apprentice also introduces algorithms to automate the selection of observable weights to minimize the effect of mis-modeling in the event generators. We illustrate our improvements for the task of MC-generator tuning and limit setting.Comment: 9 pages, 2 figures, submitted to the 25th International Conference on Computing in High-Energy and Nuclear Physic