Knowing who may progress along the disease pathway is critical for early diagnosis and intervention, improved treatment and better disease management, according to a team led by researchers from the Penn State College of Medicine that has developed a new method to predict the progression of autoimmune disease among those with preclinical symptoms. The team used artificial intelligence (AI) to analyze data from electronic health records and large genetic studies of people with autoimmune disease to come up with a risk prediction score. When compared to existing models, this methodology was between 25% and 1,000% more accurate in determining whose symptoms would move to advanced disease.

A new study found that 53.5 percent of surveyed US college students reported experiencing at least one harm caused by someone else’s drinking, ranging from verbal abuse and physical confrontations to academic disruptions and emotional distress. Students who identified as White, cisfemale, transgender, gender-nonconforming, or of higher socioeconomic status, as well as those living with roommates, attending four-year institutions, or participating in Greek life or intercollegiate athletics, were at greater risk.

A new study from the Keck School of Medicine of USC has tested a biomarker linked to vascular dementia across four separate groups and proposed an explanation for how cognitive impairment arises. The findings were just published in Alzheimer's & Dementia®: The Journal of the Alzheimer's Association.

Ebola virus, one of the deadliest pathogens, has a fatality rate of about 50%, posing a serious threat to global health and safety. To address this challenge, researchers at the University of Minnesota and the Midwest Antiviral Drug Discovery (AViDD) Center have developed the first nanobody-based inhibitors targeting the Ebola virus.