The study showed that children with beta thalassemia major had delayed physical growth possibly secondary to iron overload. Effective and early iron chelation is needed for preventing growth failure in transfusion-dependent beta thalassemia.

Pancreatic cancer is a highly lethal disease associated with significant morbidity and mortality. In the United States (US), the overall 5-year relative survival rate for pancreatic cancer during the 2012–2018 period was 11.5%. However, the cancer stage at diagnosis strongly influences relative survival in these patients. Per the National Cancer Institute (NCI) statistics for 2012–2018, the 5-year relative survival rate for patients with localized disease was 43.9%, while it was 3.1% for patients with distant metastasis. The poor survival rates are primarily due to the late development of clinical signs and symptoms. Hence, early diagnosis is critical in improving treatment outcomes. In recent years, artificial intelligence (AI) has gained immense popularity in gastroenterology. AI-assisted endoscopic ultrasound (EUS) models have been touted as a breakthrough in the early detection of pancreatic cancer. These models may also accurately differentiate pancreatic cancer from chronic pancreatitis and autoimmune pancreatitis, which mimics pancreatic cancer on radiological imaging. In this review, we detail the application of AI-assisted EUS models for pancreatic cancer detection. We also highlight the utility of AI-assisted EUS models in differentiating pancreatic cancer from radiological mimickers. Furthermore, we discuss the current limitations and future applications of AI technology in EUS for pancreatic cancers.

Atrial fibrillation (AF) and nonalcoholic fatty liver disease (NAFLD) share common risk factors and appear to have an association. Independently, the incidence and prevalence of both diseases are on the rise. Epidemiological evidence, experimental studies and various randomized clinical trials suggest a link between the 2 entities, delineating cumulative risks and clinical strategies to improve outcomes. Dyslipidemia, insulin resistance, inflammatory milieu, and activation of the renin-angiotensin system are likely common pathophysiological mechanisms linking AF and NAFLD. In this article we review the known pathways and pathophysiology that link the 2 conditions. This review also discusses therapies that target both NAFLD and AF, such as angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, statins, metformin, and vitamin E. We further discuss other potential medications that have shown effects in NAFLD or AF through anti-inflammatory, antidiabetic, lipid-lowering, or renin-angiotensin system inhibiting effects. Future epidemiological studies are needed to establish a direct causal relationship between NAFLD and AF.