Machine learning for refining interpretation of magnetic resonance imaging scans in the management of multiple sclerosis: a narrative review.

Multiple sclerosis (MS) is an autoimmune disease of the brain and spinal cord with both inflammatory and neurodegenerative features. Although advances in imaging techniques, particularly magnetic resonance imaging (MRI), have improved the process of diagnosis, its cause is unknown, a cure remains elusive and the evidence base to guide treatment is lacking. Computational techniques like machine learning (ML) have started to be used to understand MS.

Novel digital droplet inverse PCR assay shows that natural clearance of hepatitis B infection is associated with fewer viral integrations.

Hepatitis B virus (HBV) DNA integration into the host cell genome is reportedly a major cause of liver cancer, and a source of hepatitis B surface antigen (HBsAg). High HBsAg levels can alter immune responses which therefore contributes to the progression of HBV-related disease. However, to what extent integration leads to the persistent circulating HBsAg is unclear.

Reducing DNA extraction costs through factorial design for the DNAdvance Kit.

Objective: Extracting DNA is essential in wildlife genetic studies, and numerous methods are available. However, the process is costly and time-consuming for non-model organisms, including most wildlife species. Therefore, we optimized a cost-efficient protocol to extract DNA from the muscle tissue of White-tailed Deer using the DNAdvance kit (Beckman Coulter), a magnetic-bead-based approach.