Background: The diagnosis of hepatocellular carcinoma (HCC) is dependent on the histologic and immunohistochemical analysis of biopsy and resection specimens. The distinction of HCC from metastatic neoplasms is pertinent for treatment and prognostic purposes. Arginase-1 (Arg-1), a marker of hepatocellular differentiation, has shown superior sensitivity and specificity when compared to other immunohistochemical markers of detection of HCC such as hepatocyte paraffin antigen (HepPar-1). Studies have shown that poorly differentiated HCC can lose arginase expression, however well differentiated HCC are rarely ever arginase negative.
Methods: In this study Arg-1 expression was detected using immunohistochemical staining on tissue specimens from 40 confirmed cases of well differentiated HCC specimens using a highly specific monoclonal antibody for Arg-1. Specificity of the Arg-1 antibody was evaluated by immunostaining of 24 non-HCC tumors in the liver and 200 non-liver neoplasms using paraffin block and tissue micro-array (TMA) based immunohistochemistry.
Results: Four well differentiated HCC cases were found to be completely negative for Arg-1 and similarly all 224 non-HCC tumors did not express Arg-1. The arginase negative well differentiated tumors were positive for other hepatocellular markers such as HepPar-1 and polyclonal carcinoembryonic antigen (pCEA). Of the four tumors, only one recurred at 28 months. All patients are currently stable with a mean survival of 43 months.
Conclusions: Arg-1 negative well differentiated HCC can be a clinical dilemma which can lead to misdiagnosis. Confirmation with other hepatocellular markers such as HepPar1 and pCEA is essential in making the correct diagnosis. The clinicopathologic outcomes of arginase negative well differentiated HCC has been poorly characterized, thus our findings are of utmost importance in understanding the clinical behavior of these tumors. This may have a potential role in understanding the mechanism of the use of targeted therapy in HCC tumors.
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http://dx.doi.org/10.21037/tgh.2019.08.01 | DOI Listing |
JMIR Med Inform
January 2025
Department of Science and Education, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, China.
Background: Large language models (LLMs) have been proposed as valuable tools in medical education and practice. The Chinese National Nursing Licensing Examination (CNNLE) presents unique challenges for LLMs due to its requirement for both deep domain-specific nursing knowledge and the ability to make complex clinical decisions, which differentiates it from more general medical examinations. However, their potential application in the CNNLE remains unexplored.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Prosthodontics, Faculty of Dentistry, University of the Western Cape, Cape Town, South Africa.
Objective: To explore the interventions for change in oral health behaviour that are effective in improving oral health behaviours in 8 to 18-year-old children during oral health promotion.
Methods: The Joanna Briggs Institute framework of evidence synthesis for conducting a scoping review was implemented for the methodology. Included studies related to the objective, measured clinical or non-clinical outcomes, were in English, 2011-2023, and were experimental, observational or reviews.
J Craniofac Surg
January 2025
State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, Key Laboratory of Oral Biomedicine Ministry of Education, Hubei Key Laboratory of Stomatology, School & Hospital of Stomatology, Wuhan University.
Lipomas are benign soft tissue tumors composed of mature adipocytes, commonly found in subcutaneous tissues. Despite their prevalence in various body regions, they are relatively rare in the oral and maxillofacial regions. This study retrospectively analyzed the clinical and imaging characteristics, as well as the treatment outcomes of 57 patients diagnosed with lipoma.
View Article and Find Full Text PDFEnviron Microbiol
January 2025
Institute of Microbiology and Dahlem Centre of Plant Sciences, Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Berlin, Germany.
The leaf surface, known as the phylloplane, presents an oligotrophic and heterogeneous environment due to its topography and uneven distribution of resources. Although it is a challenging environment, leaves support abundant bacterial communities that are spatially structured. However, the factors influencing these spatial distribution patterns are not well understood.
View Article and Find Full Text PDFBreast Cancer Res Treat
January 2025
Department of Oncology, University of Torino, Via Nizza 44, 10126, Turin, Italy.
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