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.

Hintergrund: Bis dato befassen sich die meisten Forschungsvorhaben im Bereich der KB mit Wirkungsforschung, wobei Nachweise von Wirkungen durch KB aufgrund von komplexen und auch multikausalen Wirkzusammenhängen nicht vorbehaltlos zu erbringen sind. Forschung im Bereich der Kulturellen Bildung (KB), die dazu beiträgt, den Begriff KB, die zugrundeliegende Theorie, den Praxisbereich und auch die Angebote von KB zu verstehen und einzuordnen, ist hingegen eher rar. Die Potenziale der KB unterstreichen jedoch den Bedarf der Weiterentwicklung und theoretisch-methodischen Fundierung der KB. Es wird also Forschung gebraucht, die einen Beitrag zur evidenzbasierten Qualitätsverbesserung und -sicherung leistet. Mit der vorliegenden Erhebung bei wichtigen Akteur:innen der KB soll das Verständnis von KB in der Europäischen Metropolregion Nürnberg (EMN) abgebildet werden.

Methodik: Es wurde eine quantitative Querschnittsstudie in Form einer Online-Befragung durchgeführt, und es bestand die Möglichkeit der Beantwortung der Fragen via paper+pencil. Es wurden vorrangig quantitative Daten erhoben, in geringem Ausmaß auch qualitative Daten in Form von Antwortmöglichkeiten unter Sonstiges und Freitextfragen. Eine Orientierung bezüglich zentraler inhaltlicher Aussagen und daraus entwickelter Kategorien gab eine qualitative Vorstudie (siehe: Hamani et al. 2023).

Ergebnisse: Die Stichprobe bestand aus 73 Akteur:innen im Bereich der KB in der EMN. Die Ergebnisse wurden deskriptivstatistisch ausgewertet. Die qualitativen Antworten in den Feldern Sonstiges und zu den Freitextfragen wurden in induktiv gebildete Kategorien eingeordnet. Auch wurden explorative Analysen durchgeführt.

Diskussion und Fazit: Die vielschichtigen Erkenntnisse aus der Befragung unterstreichen die Komplexität von KB und verdichten sich bezüglich mancher Handlungs- und Inhaltsdimensionen. Hierfür hat die Studie Kategorisierungsmöglichkeiten entwickelt und durch handelnde Akteur:innen gewichten lassen.

Functional revascularization is key to stroke recovery and requires remodeling and regeneration of blood vessels around which is located the brain’s only stromal compartment. Stromal progenitor cells (SPCs) are critical for tissue regeneration following injury in many organs, yet their identity in the brain remains elusive. Here we show that the perivascular niche of brain SPCs includes pericytes, venular smooth muscle cells and perivascular fibroblasts that together help cerebral microvasculature regenerate following experimental stroke. Ischemic injury triggers amplification of pericytes and perivascular fibroblasts in the infarct region where they associate with endothelial cells inside a reactive astrocyte border. Fate-tracking of Hic1+ SPCs uncovered a transient functional and transcriptional phenotype of stroke-activated pericytes and perivascular fibroblasts. Both populations of these cells remained segregated, displaying distinct angiogenic and fibrogenic profiles. Therefore, pericytes and perivascular fibroblasts are distinct subpopulations of SPCs in the adult brain that coordinate revascularization and scar formation after injury.

Purpose Federated training is often challenging on heterogeneous datasets due to divergent data storage options, inconsistent naming schemes, varied annotation procedures, and disparities in label quality. This is particularly evident in the emerging multi-modal learning paradigms, where dataset harmonization including a uniform data representation and filtering options are of paramount importance.Methods DICOM-structured reports enable the standardized linkage of arbitrary information beyond the imaging domain and can be used within Python deep learning pipelines with highdicom. Building on this, we developed an open platform for data integration with interactive filtering capabilities, thereby simplifying the process of creation of patient cohorts over several sites with consistent multi-modal data.Results In this study, we extend our prior work by showing its applicability to more and divergent data types, as well as streamlining datasets for federated training within an established consortium of eight university hospitals in Germany. We prove its concurrent filtering ability by creating harmonized multi-modal datasets across all locations for predicting the outcome after minimally invasive heart valve replacement. The data include imaging and waveform data (i.e., computed tomography images, electrocardiography scans) as well as annotations (i.e., calcification segmentations, and pointsets), and metadata (i.e., prostheses and pacemaker dependency).Conclusion Structured reports bridge the traditional gap between imaging systems and information systems. Utilizing the inherent DICOM reference system arbitrary data types can be queried concurrently to create meaningful cohorts for multi-centric data analysis. The graphical interface as well as example structured report templates are available at https://github.com/Cardio-AI/fl-multi-modal-dataset-creation .