Zusammenfassung

Geführte Akustische Wellen (GAW) haben sich im Themengebiet des Structural Health Monitoring (SHM) etabliert. Neben ihren Vorteilen bei der Überwachung von Objekten und Detektion von Fehlstellen, gibt es jedoch auch einige Herausforderungen. Zu diesen zählt die dispersive Natur der häufig eingesetzten Lambwellen. Dispersion führt zu Signalverzerrung und reduziert dadurch die räumliche Auflösung und erschwert die Erkennung von schwach reflektierenden Fehlstellen. In diesem Beitrag wird der Einsatz eines Phased-Array-Systems zur Delaminationserkennung bei einem Mehrschichtsystem demonstriert, bei dem dispersive Lambwellen zum Einsatz kommen. Durch das Kompensieren der Dispersionseffekte kann die Sign Coherence Factor (SCF) Erweiterung des Total Focusing Method (TFM) Algorithmus eingesetzt und so auch schwach reflektierende Fehlstellen erkannt werden. Des Weiteren wird auf das Entstehen von Modenüberlagerungen bei Mehrschichtsystemen eingegangen, die bei der Auswahl der Arbeitsfrequenz und Sendesignallänge des Phased-Array-Systems berücksichtigt werden müssen.

Guided Acoustic Waves (GAW) are well established in the field of Structural Health Monitoring (SHM). However, in addition to their advantages in monitoring objects and detecting defects, there are also several challenges. These include the dispersive nature of the commonly used Lamb waves. Dispersion leads to signal distortion that reduces spatial resolution and makes it difficult to detect weakly reflecting defects. This paper demonstrates the use of a phased array system for delamination detection in a multilayer system using dispersive Lamb waves. By compensating for the dispersion effects, the Sign Coherence Factor (SCF) extension of the Total Focusing Method (TFM) algorithm can be used to detect even weakly reflective defects. Furthermore, the occurrence of mode superposition in multilayer systems is discussed, which must be taken into account when selecting the operating frequency and transmit signal length of the phased array system.

Post-COVID syndrome affects at least 10% of individuals recovering from COVID-19. Currently, there is no causal treatment. This retrospective cohort study aimed to evaluate the potential of traditional Chinese medicine (TCM) in treating post-COVID symptoms. TCM physicians in Germany and Austria completed online questionnaires to retrospectively record symptoms, treatment approaches, and outcomes for patients diagnosed with post-COVID. Nine physicians collected data from 79 patients (65% female, 47 ± 16 SD). The most common TCM treatments for post-COVID were acupuncture (n = 66; 85%), Chinese pharmacological therapy (n = 61; 77%), and Chinese dietary counseling (n = 32; 41%). After an average of 7 ± 4 TCM consultations, physicians rated global symptom improvement as 62% ± 29%. Significant alleviation from the start of TCM treatment was observed in major symptoms, such as fatigue (P < .001), impaired physical performance (P < .001), and exertional dyspnea (P < .001). TCM treatment was associated with significant improvements in post-COVID symptoms, warranting further evaluation through randomized controlled studies.

BACKGROUND: Alterations in pre-mRNA splicing are crucial to the pathophysiology of various diseases. However, the effects of alternative splicing of mRNA on podocytes in hypertensive nephropathy are still unknown. The Sys_CARE project aimed to identify alternative splicing events involved in the development and progression of glomerular hypertension. METHODS: Murine podocytes were exposed to mechanical stretch, after which proteins and mRNA were analyzed by proteomics, RNA sequencing and several bioinformatic alternative splicing tools. RESULTS: Using transcriptomic and proteomic analysis, we identified significant changes in gene expression and protein abundance due to mechanical stretch. RNA-Seq identified over 3,000 alternative spliced genes after mechanical stretch, including all types of alternative splicing events. Among these, 17 genes exhibited an alternative splicing event across four different splicing analysis tools. From this group, we focused on Myl6, a component of the myosin protein complex, and Shroom3, an actin-binding protein essential for podocyte function. We identified two Shroom3 isoforms with significant expression changes under mechanical stretch, which was validated by qRT-PCR and in situ hybridization. Additionally, we observed an expression switch of two Myl6 isoforms after mechanical stretch, accompanied by an alteration in the C-terminal amino acid sequence. CONCLUSIONS: A comprehensive RNA-Seq analysis of mechanically stretched podocytes identified novel potential podocyte-specific biomarkers and highlighted significant alternative splicing events, notably in the mRNA of Shroom3 and Myl6.

Background/Objectives: The prediction of cancer types is primarily reliant on driver genes and their specific mutations. The advancement in novel omics technologies has led to the acquisition of additional genetic data. When integrated with artificial intelligence models, there is considerable potential for this to enhance the accuracy of cancer diagnosis. As mutational signatures can provide insights into repair mechanism malfunctions, they also have the potential for more accurate cancer diagnosis. Methods: First, we compared unsupervised and supervised machine learning approaches to predict cancer types. We employed deep and artificial neural network architectures with an explainable component like layerwise relevance propagation to extract the most relevant features for the cancer-type prediction. Ten-fold cross-validation and an extensive grid search were used to optimize the neural network architecture using driver gene mutations, mutational signatures and topological mutation information as input. The PCAWG dataset was used as input to discriminate between 17 primary sites and 24 cancer types. Results: Overall, our approach showed that the most relevant mutation information to discriminate between cancer types is increased by >10% using the whole genome or intergenic and intronic genome regions instead of exome information. Furthermore, the most relevant features for most cancer types, except for two, are in the mutational signatures and not the topological mutation information. Conclusions: Informative mutational signatures outperformed the prediction of cancer types in comparison to driver gene mutations and added a new layer of diagnostic information. As the degree of information within the mutational signatures is not solely based on the frequency of occurrence, it is even possible to separate cancer types from the same primary site by the different relevant mutations. Furthermore, the comparison of informative mutational signatures allowed the cancer-type assignment of specific impaired repair mechanisms.

Estimating the magnitude of placebo responses across pharmacological and nonpharmacological trials is important for understanding their influence on trial outcomes. Yet, the extent to which more intense placebo interventions like sham acupuncture yield larger analgesic responses than placebo pills, and the factors predicting these responses, remain unclear. This meta-analysis investigated the magnitude and predictors of placebo analgesia responses in pharmacological vs acupuncture trials. Analyses included individual patient data from the placebo arm of 11 randomized controlled trials (RCTs): 9 pharmacological RCTs using placebo pills (N = 2021) and 2 acupuncture RCTs using sham acupuncture (N = 747). All trials were conducted in patients with chronic nociceptive pain (osteoarthritis, N = 2068; low back pain, N = 700). The placebo response was calculated as the change in pain intensity (0-100) between baseline and week 12. A random effects model demonstrated that placebo pills and patients with osteoarthritis exhibited smaller placebo responses than sham acupuncture and patients with low back pain (both P < 0.001, marginal effects). A mixed effects model showed that route of administration interacted significantly with baseline pain, premature termination, and the presence of adverse events. Together, predictors explained 20% to 25% of the individual variance in placebo responses, whereas 75% to 80% remained unaccounted for. In summary, sham acupuncture accounted for slightly larger placebo responses than placebo pills. Since basic trial and patient parameters explained only a small portion of this variability, we might need to start considering the patient's perception of the treatment—including cognition and emotions—to better predict placebo analgesia responses.

The increasing consumption of news online in the 21st century coincided with increased publication of disinformation, biased reporting, hate speech and other unwanted Web content.

We describe BiasScanner, an application that aims to strengthen democracy by supporting news consumers with scrutinizing news articles they are reading online. BiasScanner contains a server-side pre-trained large language model to identify biased sentences of news articles and a front-end Web browser plug-in. BiasScanner can identify and classify more than two dozen types of media bias at the sentence level, making it the most fine-grained model and only automatic application deployed as a browser plug-in. One special feature is the high-quality, LLM-generated explanations of the model’s decisions.

While prior research has addressed news bias detection, we are not aware of any automatic work that resulted in a deployed browser plug-in (c.f. also biasscanner.org for a Web demo).

The textual realm and the geographic/spatial realm intersect when we use human language to talk about geographic space. Various terms have been used to talk about this intersection (“geoparsing”, “georeferencing”, “toponym resolution”, “spatial grounding” etc.) and related applications such as geographic information retrieval. In this keynote, I will review some things that the community has accomplished since 2003, what occupies people’s minds at the moment, and I will raise a few research questions that would be interesting to answer, or that would unlock the potential for new kinds of applications. I conclude with some personal conjectures about how one version of the future might look like.