National urine drug testing data showed increasing xylazine detection despite declining urinary concentrations in fentanyl-positive samples, suggesting complementary measures of changes in the illicit drug supply.
Researchers reported that an artificial intelligence workflow maintained high interpretive accuracy while reducing urine drug test sign-out time in a supervised clinical laboratory setting.
A machine-learning model distinguished samples collected following 1 night of total sleep deprivation from control and sleep-restriction conditions in a randomized crossover study of healthy young men.