Biochemical Sensors for Personalized Therapy in Parkinson's Disease: Where We Stand.

Since its first introduction, levodopa has remained the cornerstone treatment for Parkinson's disease. However, as the disease advances, the therapeutic window for levodopa narrows, leading to motor complications like fluctuations and dyskinesias. Clinicians face challenges in optimizing daily therapeutic regimens, particularly in advanced stages, due to the lack of quantitative biomarkers for continuous motor monitoring.

Real-world safety profile of direct oral anticoagulants (DOACs): Disproportionality analysis of major bleeding events.

Background: Direct Oral Anticoagulants (DOACs) have revolutionized the management of thrombotic conditions, providing more predictable and manageable anticoagulation compared to traditional vitamin K antagonists. Despite their success, major bleeding events remain a significant concern. This study aims to assess and compare the haemorrhagic risks associated with various DOACs using data from the FDA's Adverse Event Reporting System (FAERS).

Machine learning and wearable sensors for automated Parkinson's disease diagnosis aid: a systematic review.

Background: The diagnosis of Parkinson's disease is currently based on clinical evaluation. Despite clinical hallmarks, unfortunately, the error rate is still significant. Low in-vivo diagnostic accuracy of clinical evaluation mainly relies on the lack of quantitative biomarkers for an objective motor performance assessment.

Smoking exposure and Parkinson's disease: A UK Brain Bank pathology-validated case-control study.

Introduction: Epidemiological studies have consistently shown an inverse association between cigarette smoking and Parkinson's disease. Literature indicates that both current and former smokers have a reduced risk of developing PD compared to non-smokers. If smoking protects against Parkinson's disease risk or, conversely, smoking habit is abated due to the disease itself, according to the reverse causation, is still an unsolved question.

Unlocking the Potential of Stroke Blood Biomarkers: Early Diagnosis, Ischemic vs. Haemorrhagic Differentiation and Haemorrhagic Transformation Risk: A Comprehensive Review.

Stroke, a complex and heterogeneous disease, is a leading cause of morbidity and mortality worldwide. The timely therapeutic intervention significantly impacts patient outcomes, but early stroke diagnosis is challenging due to the lack of specific diagnostic biomarkers. This review critically examines the literature for potential biomarkers that may aid in early diagnosis, differentiation between ischemic and hemorrhagic stroke, and prediction of hemorrhagic transformation in ischemic stroke.