Predicting cell type-specific epigenomic profiles accounting for distal genetic effects.

Understanding how genetic variants affect the epigenome is key to interpreting GWAS, yet profiling these effects across the non-coding genome remains challenging due to experimental scalability. This necessitates accurate computational models. Existing machine learning approaches, while progressively improving, are confined to the cell types they were trained on, limiting their applicability.

Towards user-centered design of medical devices for SUDEP prediction and prevention: Insights from persons with epilepsy and caregivers.

Objectives: As epilepsy management medical devices emerge as potential technological solutions for prediction and prevention of sudden death in epilepsy (SUDEP), there is a gap in understanding the features and priorities that should be included in the design of these devices. This study aims to bridge the gap between current technology and emerging needs by leveraging insights from persons with epilepsy (PWE) and caregivers (CG) on current epilepsy management devices and understanding how SUDEP awareness influences preferences and design considerations for potential future solutions.

Methods: Two cross-sectional surveys were designed to survey PWE and CG on medical device design features, SUDEP awareness, and participation in medical device research.

Plasma microRNA Environment Linked to Tissue Factor Pathway and Cancer-Associated Thrombosis: Prognostic Significance in Ovarian Cancer.

Ovarian cancer (OC) is a leading cause of death among gynaecological malignancies. The haemostatic system, which controls blood flow and prevents clotting disorders, paradoxically drives OC progression while increasing the risk of venous thromboembolism (VTE). MicroRNAs (miRNAs) have emerged as crucial in understanding VTE pathogenesis.

Haemostatic Gene Expression in Cancer-Related Immunothrombosis: Contribution for Venous Thromboembolism and Ovarian Tumour Behaviour.

Ovarian cancer (OC) is the deadliest gynaecological malignancy. Identifying new prognostic biomarkers is an important research field. Haemostatic components together with leukocytes can drive cancer progression while increasing the susceptibility to venous thromboembolism (VTE) through immunothrombosis.