ABSTRACT
Ulcerative colitis (UC) is a cryptogenic inflammatory bowel disease, and there is an urgent need to elucidate its pathogenesis. ACE2 and TMPRSS2, the entry molecules of SARS-CoV-2, are reportedly associated with the disease; however, no consensus has been reached yet. In this study, we examined the expression of ACE2 and TMPRSS2 in colon and rectal specimens of UC. We collected colorectal specimens from 60 patients (30 patients with UC and 30 controls from 2018 to 2021) and analyzed the proportion and intensity of ACE2 and TMPRSS2 using immunohistochemistry. The results revealed a significant increase in the proportion of ACE2 expression and the intensity of TMPRSS2 expression in patients with UC. ACE2 and TMPRSS2 expression in UC remained unaffected by the COVID-19 pandemic. We demonstrated that ACE2 and TMPRSS2 are likely involved in the pathogenesis of UC.
Subject(s)
COVID-19 , Colitis, Ulcerative , Humans , Angiotensin-Converting Enzyme 2 , Pandemics , SARS-CoV-2 , Serine EndopeptidasesABSTRACT
SARS-CoV-2 vaccines have been administered in many countries after the COVID-19 pandemic. Lymphadenopathy is a side effect of SARS-CoV-2 vaccine. We report a rare example of Kikuchi disease in the cervical lymph nodes after SARS-CoV-2 vaccination. A 41-year-old man complained of a swollen neck and fever 9 days after the first dose of SARS-CoV-2 mRNA-1273 vaccine. Computed tomography revealed enlarged cervical lymph nodes. Fine needle aspiration and resection were performed, and the clinicopathological diagnosis was consistent with Kikuchi disease. Histologically, the resected lymph nodes lost their polarity, and many histiocytes were aggregated with karyorrhectic nuclear debris and apoptosis. SARS-CoV-2 positive cells were small lymphocytes detected by immunohistochemistry. This is the first report that demonstrated SARS-CoV-2 expression in Kikuchi disease post-SARS-CoV-2 vaccination.
ABSTRACT
Ulcerative colitis (UC) is an intractable disease that affects young adults. Histological findings are essential for its diagnosis; however, the number of diagnostic pathologists is limited. Herein, we used a no-code artificial intelligence (AI) platform "Teachable Machine" to train a model that could distinguish between histological images of UC, non-UC coloproctitis, adenocarcinoma, and control. A total of 5100 histological images for training and 900 histological images for testing were prepared by pathologists. Our model showed accuracies of 0.99, 1.00, 0.99, and 0.99, for UC, non-UC coloproctitis, adenocarcinoma, and control, respectively. This is the first report in which a no-code easy AI platform has been able to comprehensively recognize the distinctive histologic patterns of UC.
ABSTRACT
Ulcerative colitis (UC) and Crohn disease (CD) are cryptogenic inflammatory bowel diseases that are suggestive of aberrant mucin (MUC) expression; however, their relationship remains unclear. Here, we examined aberrant MUC expression in intestinal samples from UC and CD patients in comparison to samples from patients with ischemic colitis and control groups. To study the expression of MUC1 , MUC5AC , and MUC6 in different patient groups, we reviewed the slides stained with hematoxylin and eosin and performed immunohistochemistry. The results revealed that MUC1 was expressed more in the UC group and MUC6 in the CD group. No significant changes were observed in MUC expression in the ischemic colitis group. Overall, we demonstrated changes in MUC expression in UC and CD, which can help in the diagnosis and early clinical management of UC and CD.
