Improving arterial stiffness prediction with machine learning utilizing hemodynamics and biomechanical features derived from phase contrast magnetic resonance imaging.

Arterial stiffness has emerged as a prominent marker of risk for cardiovascular diseases. Few studies are interested in predicting symptomatic or asymptomatic arterial stiffness from hemodynamics and biomechanics parameters. Machine learning models can be used as an intelligent tool for arterial stiffness detection based on hemodynamic and biomechanical parameters.

Evaluation of the antiviral activity of new dermaseptin analogs against Zika virus.

Zika virus represents the primary cause of infection during pregnancy and can lead to various neurological disorders such as microcephaly and Guillain-Barré syndrome affecting both children and adults. This infection is also associated with urological and nephrological problems. So far, evidence of mosquito-borne Zika virus infection has been reported in a total of 89 countries and territories.

Dermatological Conditions Seen in Kidney Transplant Recipients: Prevalence and Risk Factors.

Objectives: In kidney transplant, the use of immunosuppressive drugs, indispensable to avoid organ rejection, implies an increased risk of several infectious and neoplastic diseases. Cutaneous infections have a high incidence in kidney transplant recipients and are diagnosed in 55% to 97% of these patients. The objectives of this study were to identify the most frequent skin diseases and their clinical risk factors within a population of kidney transplant recipients.