Autoimmune pancreatitis (AIP) is a special type of chronic pancreatitis with clinical symptoms of obstructive jaundice and abdominal discomfort; this condition is caused by autoimmunity and marked by pancreatic fibrosis and dysfunction. Previous studies have revealed a close relationship between early pancreatic atrophy and the incidence rate of diabetes in type 1 AIP patients receiving steroid treatment. Shimada performed a long-term follow-up study and reported that the pancreatic volume (PV) of these patients initially exponentially decreased but then slowly decreased, which was considered to be an important factor related to diabetes; moreover, serum IgG4 levels were positively correlated with PV during follow-up. In this letter, regarding the original study presented by Shimada , we present our insights and discuss how multimodal medical imaging and artificial intelligence can be used to better assess the relationship between pancreatic morphological changes and diabetes in patients with AIP.
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http://dx.doi.org/10.4329/wjr.v16.i11.703 | DOI Listing |
Front Immunol
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Section of Immunology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
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Department of Gastroenterology, The Affiliated Hospital of Qingdao University, Qingdao, China.
CCL2, a pivotal cytokine within the chemokine family, functions by binding to its receptor CCR2. The CCL2/CCR2 signaling pathway plays a crucial role in the development of fibrosis across multiple organ systems by modulating the recruitment and activation of immune cells, which in turn influences the progression of fibrotic diseases in the liver, intestines, pancreas, heart, lungs, kidneys, and other organs. This paper introduces the biological functions of CCL2 and CCR2, highlighting their similarities and differences concerning fibrotic disorders in various organ systems, and reviews recent progress in the diagnosis and treatment of clinical fibrotic diseases linked to the CCL2/CCR2 signaling pathway.
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School of Medicine, Department of Health Promotion, Mother and Child Care, Internal Medicine and Medical Specialties (Promise), University of Palermo, Palermo, Italy.
Front Oncol
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Department of Minimally Invasive Spine Surgery, Affiliated Hospital of Chengde Medical University, Chengde, Hebei, China.
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Materials And Methods: Using traditional machine learning methods, including random-effects meta-analysis and forward-search optimization, we developed a robust signature validated across 14 publicly available datasets, achieving a summary AUC of 0.99 in training datasets and 0.
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