Federica Gilardi

The paper uses metabolomics to identify endocannabinoid system changes in adipose tissue during obesity-induced inflammation in mice.

This study uses activity-based proteome profiling to analyze serum serine hydrolases in infants with abusive head trauma, finding reduced enzyme activity compared to sudden infant death syndrome.

This paper develops a polygenic risk score (metaPRS) to predict sudden cardiac arrest in patients with coronary artery disease using genetic and clinical data from two cohorts.

The paper introduces dbnorm, an R package to visualize and correct signal drift in metabolomics data across batches, improving the detection of true biological variation.