Giuseppe Pasculli

The most common primary liver cancer is hepatocellular carcinoma (HCC), and its mortality rate is increasing globally. The overall 5-year survival of patients with liver cancer is currently 10-20%. Moreover, because early diagnosis can significantly improve prognosis, which is highly correlated with tumor stage, early detection of HCC is critical. International guidelines advise using α-FP biomarker with/without ultrasonography for HCC surveillance in patients with advanced liver disease. However, traditional biomarkers are sub-optimal for risk stratification of HCC development in high-risk populations, early diagnosis, prognostication, and treatment response prediction. Since about 20% of HCCs do not produce α-FP due to its biological diversity, combining α-FP with novel biomarkers can enhance HCC detection sensitivity. There is a chance to offer promising cancer management methods in high-risk populations by utilizing HCC screening strategies derived from new tumor biomarkers and prognostic scores created by combining biomarkers with distinct clinical parameters. Despite numerous efforts to identify molecules as potential biomarkers, there is no single ideal marker in HCC. When combined with other clinical parameters, the detection of some biomarkers has higher sensitivity and specificity in comparison with a single biomarker. Therefore, newer biomarkers and models, such as the Lens culinaris agglutinin-reactive fraction of Alpha-fetoprotein (α-FP), α-FP-L3, Des-γ-carboxy-prothrombin (DCP or PIVKA-II), and the GALAD score, are being used more frequently in the diagnosis and prognosis of HCC. Notably, the GALAD algorithm was effective in HCC prevention, particularly for cirrhotic patients, regardless of the cause of their liver disease. Although the role of these biomarkers in surveillance is still being researched, they may provide a more practical alternative to traditional imaging-based surveillance. Finally, looking for new diagnostic/surveillance tools may help improve patients' survival. This review discusses the current roles of the most used biomarkers and prognostic scores that may aid in the clinical management of HCC patients.

Graph neural networks (GNNs) recursively propagate signals along the edges of an input graph, integrate node feature information with graph structure, and learn object representations. Like other deep neural network models, GNNs have notorious black box character. For GNNs, only few approaches are available to rationalize model decisions. We introduce EdgeSHAPer, a generally applicable method for explaining GNN-based models. The approach is devised to assess edge importance for predictions. Therefore, EdgeSHAPer makes use of the Shapley value concept from game theory. For proof-of-concept, EdgeSHAPer is applied to compound activity prediction, a central task in drug discovery. EdgeSHAPer's edge centricity is relevant for molecular graphs where edges represent chemical bonds. Combined with feature mapping, EdgeSHAPer produces intuitive explanations for compound activity predictions. Compared to a popular node-centric and another edge-centric GNN explanation method, EdgeSHAPer reveals higher resolution in differentiating features determining predictions and identifies minimal pertinent positive feature sets.

BACKGROUND: Hereditary haemorrhagic telangiectasia (HHT) is a systemic autosomal dominant vascular disease. Although the clinical picture is that of a chronic disabling disease, vascular malformations can suddenly lead to life-threatening conditions. AIM: To assess the frequency and type of emergency acute complications in HHT. DESIGN: Retrospective case-note review. METHODS: From August 2000 to December 2004, our specialized HHT centre saw 139 patients (74 males, 65 females, mean age 45.5 years, range 14-77) with a definite diagnosis of HHT. We reviewed their clinical files and recorded all visits for acute complications (massive nosebleeds, haematemesis, melaena, haematochezia, haemothorax, haemoptysis, TIA/ischaemic stroke, haemorrhagic stroke, brain abscess). RESULTS: Fifty patients (35.9%) had at least one acute complication. There were a total of 93 visits potentially involving the emergency department. Most commonly, patients sought urgent medical attention for nosebleeds and gastrointestinal bleeding (63.4%), but there were also disorders of the brain, lung, heart and liver. DISCUSSION: Acute complications of HHT are not uncommon and can be severe and wide-ranging. Physicians should be aware of HHT and its major complications, as a prompt diagnosis is essential to direct patients to the most appropriate therapies, and to suggest screening for visceral involvement in their relatives.