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Abstract Background Patient-specific aiming devices (PSAD) may improve precision and accuracy of glenoid component positioning in total shoulder arthroplasty, especially in degenerative glenoids. The aim of this study was to compare precision and accuracy of guide wire positioning into different glenoid models using a PSAD versus a standard guide. Methods Three experienced shoulder surgeons inserted 2.5 mm K-wires into polyurethane cast glenoid models of type Walch A, B and C (in total 180 models). Every surgeon placed guide wires into 10 glenoids of each type with a standard guide by DePuy Synthes in group (I) and with a PSAD in group (II). Deviation from planned version, inclination and entry point was measured, as well as investigation of a possible learning curve. Results Maximal deviation in version in B- and C-glenoids in (I) was 20.3° versus 4.8° in (II) (p

Abstract Static gene expression programs have been extensively characterized in stem cells and mature human cells. However, the dynamics of RNA isoform changes upon cell-state-transitions during cell differentiation, the determinants and functional consequences have largely remained unclear. Here, we established an improved model for human neurogenesis in vitro that is amenable for systems-wide analyses of gene expression. Our multi-omics analysis reveals that the pronounced alterations in cell morphology correlate strongly with widespread changes in RNA isoform expression. Our approach identifies thousands of new RNA isoforms that are expressed at distinct differentiation stages. RNA isoforms mainly arise from exon skipping and the alternative usage of transcription start and polyadenylation sites during human neurogenesis. The transcript isoform changes can remodel the identity and functions of protein isoforms. Finally, our study identifies a set of RNA binding proteins as a potential determinant of differentiation stage-specific global isoform changes. This work supports the view of regulated isoform changes that underlie state-transitions during neurogenesis.

This study endeavors to automate the assessment of competencies within the domain of entrepreneurship, specifically targeting the augmentation of entrepreneurial cognition and conduct within universities in German rural regions, like Lower Franconia. Employing methods, including literature analyses and expert interviews, we formulated and validated an entrepreneurship competence profile and accompanying self-assessment tool. The ensuing evaluative framework is poised for seamless integration into learning management systems, thereby facilitating intelligent competence monitoring within educational environments. Purpose: The aim of this thesis is to develop an automated competence assessment procedure in the field of entrepreneurship. This can be used in the university environment in the long term to promote and teach entrepreneurial thinking and behavior in order to sustainably improve the quality of learning outcomes and achieve targeted promotion of entrepreneurship. Methodology: Based on a relevant literature analysis, four guideline-based expert interviews were created and conducted. The results of the interviews were compiled and validated in a structured competence profile (entrepreneurship competence profile). Based on this competence catalog for entrepreneurs, an empirically valid self-test was created using standard psychometric questionnaire construction methods. Results: The entrepreneurship competence profile and a consequential empirically validated self-test for competence assessment were created. This test provides the basis for the long-term competence development of students and can further be embedded automatically into a learning management system (LMS) as part of intelligent competence monitoring, which allows for the recording of competencies for each student and the individual incorporation of gap closure into the curriculum. Originality/value: In previous research, there were no competence profiles or competence assessment procedures in the field of entrepreneurship that derived relevant competencies directly from actors within this environment. This work illustrates the development of a competence assessment procedure for entrepreneurs and shows which methods can be used to close prevailing research gaps in the field of intelligent competence monitoring.

Multiple peptide resistance factor (MprF) confers resistance to cationic antimicrobial peptides (AMPs) in several pathogens, thereby enabling evasion of the host immune response. The role of MprF in commensals remains, however, uncharacterized. To close this knowledge gap, we used a common gut commensal of animals, Lactiplantibacillus plantarum, and its natural host, the fruit fly Drosophila melanogaster, as an experimental model to investigate the role of MprF in commensal-host interactions. The L. plantarum ΔmprF mutant that we generated exhibited deficiency in the synthesis of lysyl-phosphatidylglycerol (Lys-PG), resulting in increased negative cell surface charge and increased susceptibility to AMPs. Susceptibility to AMPs had no effect on ΔmprF mutant's ability to colonize guts of uninfected flies. However, we observed significantly reduced abundance of the ΔmprF mutant after infection-induced inflammation in the guts of wild-type flies but not of flies lacking AMPs. Additionally, we found that the ΔmprF mutant compared to wild-type L. plantarum induces a stronger intestinal immune response in flies due to the increased release of immunostimulatory peptidoglycan fragments, indicating an important role of MprF in promoting host tolerance to commensals. Our further analysis suggests that MprF-mediated lipoteichoic acid modifications are involved in host immunomodulation. Overall, our results demonstrate that MprF, besides its well-characterized role in pathogen immune evasion and virulence, is also an important commensal resilience factor.

BackgroundCurrent standard treatment concepts in head and neck squamous cell carcinoma (HNSCC) are based on former studies using 2D and 3D treatment plans. However, modern radiation techniques allow for a more precise and individual dose application. Therefore, in a clearly defined patient population, de-intensified risk-adapted radiation is investigated.MethodsPatients with newly diagnosed HNSCC after surgery (with resection margins ≥1 mm and cM0) with the following tumor stages (TNM 7th Edition) were eligible for the study: oral cavity, oropharynx, or larynx: pT1–3, pN0–pN2b; hypopharynx: pT1–2, pN1. The patients should have either a low risk of local recurrence [≤pT2, resection margin ≥5 mm, no peritumoral lymphangiosis (L0), and no perineural invasion] or contralateral lymph node metastasis (≤3 ipsilateral lymph node metastases, in case of well-lateralized oropharyngeal or oral cavity cancer contralateral cN0, otherwise pN0). Patients were assigned to three different treatment regimes with reduction of the treated volume, radiation dose, or both, according to tumor stage and results of surgery performed. The primary objective was to show an LRR of

Abstract The gastroesophageal squamocolumnar junction (GE-SCJ) is a critical tissue interface between the esophagus and stomach, with significant relevance in the pathophysiology of gastrointestinal diseases. Despite this, the molecular mechanisms underlying GE-SCJ development remain unclear. Using single-cell transcriptomics, organoids, and spatial analysis, we examine the cellular heterogeneity and spatiotemporal dynamics of GE-SCJ development from embryonic to adult mice. We identify distinct transcriptional states and signaling pathways in the epithelial and mesenchymal compartments of the esophagus and stomach during development. Fibroblast-epithelial interactions are mediated by various signaling pathways, including WNT, BMP, TGF-β, FGF, EGF, and PDGF. Our results suggest that fibroblasts predominantly send FGF and TGF-β signals to the epithelia, while epithelial cells mainly send PDGF and EGF signals to fibroblasts. We observe differences in the ligands and receptors involved in cell-cell communication between the esophagus and stomach. Our findings provide insights into the molecular mechanisms underlying GE-SCJ development and fibroblast-epithelial crosstalk involved, paving the way to elucidate mechanisms during adaptive metaplasia development and carcinogenesis.

The current reconstructive surgical procedures implemented after the resection of extended bone segments are associated with high complication rates and long-term treatments. By transplanting an autologous, vascularized and stabilized bone segment, these challenges can be managed. Thus, we propose a novel procedure to expand the currently available autologous bone grafts to the dimensions of the recipient bone using an implantable device. The objective of the present study was to characterize the feasibility of developing an implant prototype for fibula expansion in an in vitro model using a porcine fibula. A balloon catheter, as the part of the implant responsible for expansion, was proven to expand while being periodically filled with sodium chloride. Therefore, the expansion of the balloon catheter was analyzed in an experimental test setup with a 3D-printed porcine fibula with a closure film simulating callus formation to simulate the in vivo situation. Our experimental testing proved the successful expansion of the porcine fibula by the balloon catheter. Hence, the feasibility of the concept for subsequent animal testing was confirmed.

Abstract Background Multimorbid and frail elderly patients often carry a high burden of treatment. Hospitalization due to the onset of an acute illness can disrupt the fragile balance, resulting in further readmissions after hospital discharge. Current models of care in Germany do not meet the needs of this patient group. Rather lack of coordination and integration of care combined with a lack of interdisciplinary approaches result in fragmented and inadequate care and increase the burden of treatment even more. Methods eliPfad is a randomized controlled trial conducted in 6 hospitals in Germany. Multimorbid elderly patients aged 55 or older are randomly assigned to the intervention or control group. Patients in the intervention group receive the eliPfad intervention additional to standard care. The core components of eliPfad are: Early assessment of patients’ individual treatment burden and support through a specially trained case manager Involvement of the patient’s general practitioner (GP) right from the beginning of the hospital stay Preparation of an individual, cross-sectoral treatment plan through the interdisciplinary hospital team with the involvement of the patient’s GP Establishment of a cross-sectoral electronic patient record (e-ePA) for documentation and cross-sectoral exchange Support/Promote patient adherence Tailored early rehabilitation during the hospital stay, which is continued at home Close-tele-monitoring of medically meaningful vital parameters through the use of tablets, digital devices, and personal contacts in the home environment The intervention period begins in the hospital and continues 6 weeks after discharge. Patients in the control group will be treated according to standard clinical care and discharged according to current discharge management. The primary aim is the prevention/reduction of readmissions in the first 6 months after discharge. In addition, the impact on health-related quality of life, the burden of treatment, survival, self-management, medication prescription, health literacy, patient-centered care, cost-effectiveness, and process evaluation will be examined. Nine hundred forty-eight patients will be randomized 1:1 to intervention and control group. Discussion If eliPfad leads to fewer readmissions, proves (cost-)effective, and lowers the treatment burden, it should be introduced as a new standard of care in the German healthcare system. Trial registration The trial was registered in the German Clinical Trials Registry (Deutsches Register Klinischer Studien (DRKS)) on 08/14/2023 under the ID DRKS00031500 .

Abstract This paper presents an innovative approach to decentralized data management in the German energy market, focusing on the use of decentralized data management with the help of Data Spaces to facilitate the automated change of energy suppliers within 24 h. The central focus of this research is the MakoMaker Space, a demonstrator project that employs the Connector from the Eclipse Data Space Components. The MakoMaker project demonstrates the successful automation of energy supplier changes, emphasizing the preservation of customer data sovereignty. It shows an alternative approach to the process, putting the customer into the center. Customers retain control of their data, which is accessible to providers as needed. While the paper discusses the potential for further enhancements, such as the integration of an identity provider and the development of a sustainable business model for service coordination, the primary focus is on the demonstrator’s successful application in a pilot setting.

A vast multitude of tasks in histopathology could potentially benefit from the support of artificial intelligence (AI). Many examples have been shown in the literature and first commercial products with FDA or CE-IVDR clearance are available. However, two key challenges remain: (1) a scarcity of thoroughly annotated images, respectively the laboriousness of this task, and (2) the creation of robust models that can cope with the data heterogeneity in the field (domain generalization). In this work, we investigate how the combination of prototypical few-shot classification models and data augmentation can address both of these challenges. Based on annotated data sets that include multiple centers, multiple scanners, and two tumor entities, we examine the robustness and the adaptability of few-shot classifiers in multiple scenarios. We demonstrate that data from one scanner and one site are sufficient to train robust few-shot classification models by applying domain-specific data augmentation. The models achieved classification performance of around 90% on a multiscanner and multicenter database, which is on par with the accuracy achieved on the primary single-center single-scanner data. Various convolutional neural network (CNN) architectures can be used for feature extraction in the few-shot model. A comparison of nine state-of-the-art architectures yielded that EfficientNet B0 provides the best trade-off between accuracy and inference time. The classification of prototypical few-shot models directly relies on class prototypes derived from example images of each class. Therefore, we investigated the influence of prototypes originating from images from different scanners and evaluated their performance also on the multiscanner database. Again, our few-shot model showed a stable performance with an average absolute deviation in accuracy compared to the primary prototypes of 1.8% points. Finally, we examined the adaptability to a new tumor entity: classification of tissue sections containing urothelial carcinoma into normal, tumor, and necrotic regions. Only three annotations per subclass (e.g., muscle and adipose tissue are subclasses of normal tissue) were provided to adapt the few-shot model, which obtained an overall accuracy of 93.6%. These results demonstrate that prototypical few-shot classification is an ideal technology for realizing an interactive AI authoring system as it only requires few annotations and can be adapted to new tasks without involving retraining of the underlying feature extraction CNN, which would in turn require a selection of hyper-parameters based on data science expert knowledge. Similarly, it can be regarded as a guided annotation system. To this end, we realized a workflow and user interface that targets non-technical users.

Animals continuously detect information via multiple sensory channels, like vision and hearing, and integrate these signals to realise faster and more accurate decisions; a fundamental neural computation known as multisensory integration. A widespread view of this process is that multimodal neurons linearly fuse information across sensory channels. However, does linear fusion generalise beyond the classical tasks used to explore multisensory integration? Here, we develop novel multisensory tasks, which focus on the underlying statistical relationships between channels, and deploy models at three levels of abstraction: from probabilistic ideal observers to artificial and spiking neural networks. Using these models, we demonstrate that when the information provided by different channels is not independent, linear fusion performs sub-optimally and even fails in extreme cases. This leads us to propose a simple nonlinear algorithm for multisensory integration which is compatible with our current knowledge of multimodal circuits, excels in naturalistic settings and is optimal for a wide class of multisensory tasks. Thus, our work emphasises the role of nonlinear fusion in multisensory integration, and provides testable hypotheses for the field to explore at multiple levels: from single neurons to behaviour.

Ground-mounted photovoltaic facilities in open spaces have been common in Germany for many years. However, according to the legislation, these are only supported by the government on poorer quality soils, former military training areas, or along traffic routes. Nevertheless, also on high quality soils it is not forbidden to install ground-mounted photovoltaic facilities. In recent years, Germany has started implementing agrivoltaics, which is an alternative land use concept that combines agriculture and renewable energy production. This opens the possibility to use land of higher soil quality for energy generation without necessarily creating land-use conflicts and being subsidized by the government. This study aims to provide a comprehensive overview of existing and planned agrivoltaic facilities in Germany analyzing them based on various parameters. The data for this study was collected through a community questionnaire and supplemented with data from state institutions. The results indicate that as of March 2023, 21 agrivoltaic facilities with a total capacity of 81.67 MWp have been installed. A strong increase of the installed capacity is expected in 2023 and 2024, reaching approximately 382.59 MWP by the end of 2024. The market development of agrivoltaics is mainly driven by changes in the legal environment which present opportunities for further market ramp-up of agrivoltaics. The adoption of agrivoltaics shows a notable spatial diversity in Germany which appears to be influenced by the interaction between regulatory environments and agricultural structures.

BackgroundImmunotherapeutic approaches, including immune checkpoint inhibitor (ICI) therapy, are increasingly recognized for their potential. Despite notable successes, patient responses to these treatments vary significantly. The absence of reliable predictive and prognostic biomarkers hampers the ability to foresee outcomes. This meta-analysis aims to evaluate the predictive significance of circulating myeloid-derived suppressor cells (MDSC) in patients with solid tumors undergoing ICI therapy, focusing on progression-free survival (PFS) and overall survival (OS).MethodsA comprehensive literature search was performed across PubMed and EMBASE from January 2007 to November 2023, utilizing keywords related to MDSC and ICI. We extracted hazard ratios (HRs) and 95% confidence intervals (CIs) directly from the publications or calculated them based on the reported data. A hazard ratio greater than 1 indicated a beneficial effect of low MDSC levels. We assessed heterogeneity and effect size through subgroup analyses.ResultsOur search yielded 4,023 articles, of which 17 studies involving 1,035 patients were included. The analysis revealed that patients with lower levels of circulating MDSC experienced significantly improved OS (HR=2.13 [95% CI 1.51–2.99]) and PFS (HR=1.87 [95% CI 1.29–2.72]) in response to ICI therapy. Notably, heterogeneity across these outcomes was primarily attributed to differences in polymorphonuclear MDSC (PMN-MDSC) subpopulations and varying cutoff methodologies used in the studies. The monocytic MDSC (M-MDSC) subpopulation emerged as a consistent and significant prognostic marker across various subgroup analyses, including ethnicity, tumor type, ICI target, sample size, and cutoff methodology.ConclusionsOur findings suggest that standardized assessment of MDSC, particularly M-MDSC, should be integral to ICI therapy strategies. These cells hold the promise of identifying patients at risk of poor response to ICI therapy, enabling tailored treatment approaches. Further research focusing on the standardization of markers and validation of cutoff methods is crucial for integrating MDSC into clinical practice.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023420095, identifier CRD42023420095.

Abstract The market approval of Tazemetostat (TAZVERIK) for the treatment of follicular lymphoma and epithelioid sarcoma has established “enhancer of zeste homolog 2” (EZH2) as therapeutic target in oncology. Despite their structural similarities and common mode of inhibition, Tazemetostat and other EZH2 inhibitors display differentiated pharmacological profiles based on their target residence time. Here we established high throughput screening methods based on time-resolved fluorescence energy transfer, scintillation proximity and high content analysis microscopy to quantify the biochemical and cellular binding of a chemically diverse collection of EZH2 inhibitors. These assays allowed to further characterize the interplay between EZH2 allosteric modulation by methylated histone tails (H3K27me3) and inhibitor binding, and to evaluate the impact of EZH2’s clinically relevant mutant Y641N on drug target residence times. While all compounds in this study exhibited slower off-rates, those with clinical candidate status display significantly slower target residence times in wild type EZH2 and disease-related mutants. These inhibitors interact in a more entropy-driven fashion and show the most persistent effects in cellular washout and antiproliferative efficacy experiments. Our work provides mechanistic insights for the largest cohort of EZH2 inhibitors reported to date, demonstrating that—among several other binding parameters—target residence time is the best predictor of cellular efficacy.

Abstract During the SARS-CoV-2 pandemic, the German healthcare system faced challenges of efficiently allocating testing resources. To address this, we developed an open-source personalized recommendation system (PRS) called “CovApp”. The PRS utilized a questionnaire to estimate the risk of infection, provided personalized recommendations such as testing, self-isolation, or quarantine, and featured QR code data transmission to electronic health records. The PRS served up to 2.5 million monthly users and received 67,000 backlinks from 1800 domains. We clinically evaluated the PRS at the SARS-CoV-2 testing facility at Charité and observed a 21.7% increase in patient throughput per hour and a 22.5% increase in patients per day. Patients using the PRS were twice as likely to belong to the High Risk group eligible for testing (18.6% vs. 8.9%, p