Background: Parkinson’s disease (PD) has transitioned from a rare condition in 1817 to the fastest-growing neurological disorder globally. The significant increase in cases from 2.5 million in 1990 to 6.1 million in 2016, coupled with predictions of a further doubling by 2040, underscores an impending healthcare challenge. This escalation aligns with global demographic shifts, including rising life expectancy and a growing global population. The economic impact, notably in the U.S., reached $51.9 billion in 2017, with projections suggesting a 46% increase by 2037, emphasizing the substantial socio-economic implications for both patients and caregivers. Coupled with a worldwide demand for health workers that is expected to rise to 80 million by 2030, we have fertile ground for a pandemic. Methods: Our transdisciplinary research focused on early PD detection through running speech and continuous handwriting analysis, incorporating medical, biomedical engineering, AI, and linguistic expertise. The cohort comprised 30 participants, including 20 PD patients at stages 1–4 on the Hoehn and Yahr scale and 10 healthy controls. We employed advanced AI techniques to analyze correlation plots generated from speech and handwriting features, aiming to identify prodromal PD biomarkers. Results: The study revealed distinct speech and handwriting patterns in PD patients compared to controls. Our ParkinsonNet model demonstrated high predictive accuracy, with F1 scores of 95.74% for speech and 96.72% for handwriting analyses. These findings highlight the potential of speech and handwriting as effective early biomarkers for PD. Conclusions: The integration of AI as a decision support system in analyzing speech and handwriting presents a promising approach for early PD detection. This methodology not only offers a novel diagnostic tool but also contributes to the broader understanding of PD’s early manifestations. Further research is required to validate these findings in larger, diverse cohorts and to integrate these tools into clinical practice for timely PD pre-diagnosis and management.

Media linguistics, an interdisciplinary research field, extensively engages in the analysis of language in the media and its impact on society. An interesting application case in media linguistics concerns the analysis of headlines in online press. Headlines in the media play a crucial role in information dissemination and significantly influence public opinion formation. When it comes to political events or international developments, headlines serve as powerful tools to shape the perception of the news and thus steer readers’ attitudes in a desired direction. In this article, I refer to the Austrian, German and Romanian online press regarding Romania’s accession to the Schengen Area. It is noticeable that the coverage in German media often appears more distant, while Austrian media adopt a critical tone in their headlines. This particularity could be linked to Austria’s geo graphical proximity to Romania, raising interesting questions about media linguistics and the cultural imprint on media coverage. In addition, the analysis also employs a pragmalinguistic perspective, which explores how linguistic elements in headlines are used within specific communicative contexts to convey meaning and achieve pragmatic goals.