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.

Virtual Reality (VR) has paved its way into experimental psychology due to its capacity to realistically simulate real-world experiences in a controlled way. Theoretically, this technology opens the possibility to conduct experiments anywhere in the world using consumer hardware (e.g. mobile-VR). This would allow researchers to access large scale, heterogeneous samples and to conduct experiments in the field in cases where social distancing is required – e.g. during the COVID-19 pandemic. Here, we investigate the feasibility of carrying VR experiments in the field using mobile-VR through a stress inductive (public speaking task) and a relaxation (nature) task and contrast them with results in the laboratory (HTC Vive and mobile-VR). The first experiment employed a 2 (device: HTC Vive Pro (HMD) versus Wearality Sky VR smartphone adapter) x 3 (audience: ‘none’, ‘attentive’, ‘inattentive’) between-subjects design. Thirty-four participants took part in the experiment and completed a public speaking task. No significant difference was detected in participants’ sense of presence, cybersickness, or stress levels. In the second experiment, using an inexpensive Google Cardboard smartphone adapter a 3 (between: device setting) x 2 (within: task) mixed-design was employed. Sixty participants joined the experiment, and completed a public speaking and a nature observation task. No significant difference in participants’ sense of presence, cybersickness, perceived stress and relaxation were detected. Taken together, our results provide initial evidence supporting the feasibility and validity of using mobile VR in specific psychological field experiments, such as stress induction and relaxation tasks, conducted in the field. We discuss challenges and concrete recommendations for using VR in field experiments. Future research is needed to evaluate its applicability across a broader range of experimental paradigms.

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.

Virtual reality (VR) technologies are increasingly used in neuropsychological assessment of various cognitive functions. Compared to traditional laboratory studies, VR allows for a more natural environment and more complex task-related movements with a high degree of control over the environment. However, there are still few studies that transfer well-established paradigms for measuring attentional distraction by novel sounds in laboratory settings to virtual environments and sports activities. In this study, the oddball paradigm, which is well established in laboratory settings for studying attention, is transferred to table tennis in a virtual environment. While 33 subjects played virtual table tennis, they were presented with a task-irrelevant sequence of frequent standard sounds and infrequent novel sounds. Trials in which an unexpected novel sound preceded the ball’s appearance resulted in a delayed racket movement compared to trials in which a standard sound was presented. This distraction effect was observed in the first part of the experiment but disappeared with increasing exposure. The results suggest that unexpected and task-irrelevant novel sounds can initially distract attention and impair performance on a complex movement task in a rich environment. The results demonstrate that versions of the well-established oddball distraction paradigm can be used to study attentional distraction, its dynamics, and its effects on complex movements in naturalistic environments.