AI models have the potential not only to spot pancreatic cancer at an early stage, but also to predict the deadly disease’s prognosis, say scientists

A new study published in Nutrients offers new insight into omega-6 and whether it is truly the proinflammatory fatty acid many claim it to be.

Bronchiolitis obliterans syndrome (BOS) is a common complication in lung transplant patients. While molecular and pathological features have been well characterized, the influence of genetic factors on BOS development remains unexplored. Researchers from Pusan National University compared genetic variations in patient-derived lung tissues and found that the FCGBP gene is associated with BOS development and poor transplant outcomes, thereby, highlighting its role as a potential biomarker to predict transplant outcomes.

In a paper published in National Science Review, the team of Pro. Liu present an innovative computational framework, the sample-perturbed Gaussian graphical model (sPGGM), designed to analyse disease progression and identify pre-disease stages at the specific sample/cell level based on optimal transport theory and Gaussian graphical models. The proposed sPGGM provides a new single-sample way to identify the pre-disease state and discover signaling molecules leading to potential disease, which showcases exceptional effectiveness and robustness for both bulk and single-cell data analyses, offering a novel perspective for personalized disease prediction.