Publications by authors named "Yunmi Ko"

Background/aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD.

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Background & Aims: Various hepatocellular carcinoma (HCC) prediction models have been proposed for patients with chronic hepatitis B (CHB) using clinical variables. We aimed to develop an artificial intelligence (AI)-based HCC prediction model by incorporating imaging biomarkers derived from abdominal computed tomography (CT) images along with clinical variables.

Methods: An AI prediction model employing a gradient-boosting machine algorithm was developed utilizing imaging biomarkers extracted by DeepFore, a deep learning-based CT auto-segmentation software.

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CD47 is expressed on cell surfaces and acts as a "don't eat me" signal by interacting with signal-regulatory protein-α on the macrophage surface. Some cancer cells express CD47 protein and can evade macrophage phagocytosis. Herein, we evaluated the feasibility of targeting CD47 for osteosarcoma by analyzing its expression patterns, clinicopathological correlations, and immunotherapeutic potential.

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Article Synopsis
  • * Researchers analyzed data from nearly 4,800 patients and found that their model, named PLAN-B-CURE, outperformed existing prediction models significantly in various metrics.
  • * The results indicate that the PLAN-B-CURE model can be utilized for personalized monitoring of patients post-HBsAg seroclearance, improving long-term health management.
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Background & Aims: The association between hepatitis B envelope antigen (HBeAg) seroclearance during long-term nucleos(t)ide analogue (NA) treatment and the risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) remains unclear. Here, we aimed to investigate the association of HBeAg seroclearance during potent NA treatment with the development of HCC and decompensated cirrhosis.

Methods: Using a multicenter historical cohort including 2,392 non-cirrhotic adult patients with HBeAg-positive CHB who initiated NA treatment with tenofovir or entecavir, the risk of HCC and decompensated cirrhosis was compared between patients who achieved HBeAg seroclearance within 36 months of NA treatment (the HBeAg-loss group) and those who did not (the HBeAg-maintained group), using inverse probability of treatment weighting.

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Article Synopsis
  • - This study investigated the metabolic effects of different antiviral treatments for chronic hepatitis B (specifically focusing on tenofovir alafenamide [TAF]) using a 15-year cohort of patients in Korea, separated into two groups: those on a single antiviral and those who switched antivirals.
  • - After applying statistical methods, the findings revealed significant changes in cholesterol levels among groups, with TAF causing an increase in total cholesterol and a notable rise in atherosclerotic cardiovascular disease (ASCVD) risk compared to other treatments.
  • - In patients who switched from tenofovir disoproxil fumarate (TDF) to TAF, there was a significant increase in total cholesterol post-switch, highlighting the potential metabolic
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Aim: Antiviral treatment reduces the risk of developing hepatocellular carcinoma (HCC) in patients with chronic hepatitis B. However, there is a lack of high-quality evidence regarding the preventive effects of tenofovir alafenamide (TAF) on HCC. We evaluated the impact of TAF use after curative treatment on HCC recurrence.

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Background/aim: Atezolizumab plus bevacizumab and lenvatinib are currently available as first-line therapy for the treatment of unresectable hepatocellular carcinoma (HCC). However, comparative efficacy studies are still limited. This study aimed to investigate the effectiveness of these treatments in HCC patients with portal vein tumor thrombosis (PVTT).

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Immunotherapy is an attractive therapeutic strategy for the treatment of osteosarcoma (OS). The unique features of γδ T cells have made them popular for cancer immunotherapy. Here, we expanded γδ T cells using human peripheral blood mononuclear cells (PBMCs) and investigated their therapeutic potential against OS cells.

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Background/aim: Osteosarcoma is the most common type of bone cancer, but current therapeutic interventions remain largely insufficient. The development of new treatment strategies is needed, and moreover, optimal rodent models are necessary for testing the efficacy of new treatment modalities of osteosarcoma. Humanized mice carry human hematopoietic and immune systems, and are considered an ideal tool to study human diseases including cancer immunology.

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Purpose: Patients with unresectable, relapsed, or refractory osteosarcoma need a novel therapeutic agent. Metformin is a biguanide derivative used in the treatment of type II diabetes, and is recently gaining attention in cancer research.

Methods: We evaluated the effect of metformin against human osteosarcoma.

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Background: Humanized mouse models are still under development, and various protocols exist to improve human cell engraftment and function.

Methods: Fourteen NOD/SCID/IL-2Rγnull (NSG) mice (4‒5 wk old) were conditioned with busulfan and injected with human umbilical cord blood (hUCB)-derived CD34(+) hematopoietic stem cells (HSC) via retro-orbital sinuses. The bone marrow (BM), spleen, and peripheral blood (PB) were analyzed 8 and 12 weeks after HSC transplantation.

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Purpose: Features of epidermal growth factor receptor (EGFR) expression in osteosarcoma and in vitro efficacies of EGFR inhibitors against osteosarcoma cells were evaluated.

Materials And Methods: Thirty biopsy samples of osteosarcoma patients were retrospectively analyzed for EGFR protein expression by immunohistochemistry. Relationships between EGFR expression and clinicopathologic characteristics and treatment outcomes were evaluated.

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XPF and ERCC1 exist as a heterodimer to be stable and active in cells and catalyze DNA cleavage on the 5'-side of a lesion during nucleotide excision repair. To characterize the specific interaction between XPF and ERCC1, we expressed the human ERCC1 binding domain of XPF (XPF-EB) and the XPF binding domain of ERCC1 (ERCC1-FB) in Escherichia coli. Milligram quantities of a heterodimer were characterized with gel filtration chromatography, an Ni(2+)-NTA binding assay, and analytical ultracentrifugation.

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Synopsis of recent research by authors named "Yunmi Ko"

  • - Recent research by Yunmi Ko predominantly focuses on viral hepatitis and its complications, particularly chronic hepatitis B (CHB). Studies include the development of machine learning models to predict liver-related outcomes following hepatitis B surface antigen seroclearance and evaluating the impact of antiviral treatments on hepatocellular carcinoma (HCC) risk.
  • - Ko's work highlights the metabolic effects of various antiviral treatments, specifically the significance of tenofovir alafenamide (TAF) in managing dyslipidemia among patients with chronic hepatitis B, while investigating differences in outcomes when switching from other antiviral therapies.
  • - In addition to hepatitis research, Ko has explored cancer immunotherapy, specifically the therapeutic potential of γδ T cells against osteosarcoma, demonstrating the versatility of her research interests in the fields of virology and oncology.

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