Alcoholic liver disease (ALD) is a globally prevalent chronic liver disease caused by chronic or binge consumption of alcohol. The liver is the major organ that metabolizes alcohol; therefore, it is particularly sensitive to alcohol intake. Metabolites and byproducts generated during alcohol metabolism cause liver damage, leading to ALD via several mechanisms, such as impairing lipid metabolism, intensifying inflammatory reactions, and inducing fibrosis. Despite the severity of ALD, the development of novel treatments has been hampered by the lack of animal models that fully mimic human ALD. To overcome the current limitations of ALD studies and therapy development, it is necessary to understand the molecular mechanisms underlying alcohol-induced liver injury. Hence, to provide insights into the progression of ALD, this review examines previous studies conducted on alcohol metabolism in the liver. There is a particular focus on the occurrence of ALD caused by hepatotoxicity originating from alcohol metabolism.

Lee SE, et al. J Korean Med Sci. 2014 Oct;29(10):1333-1340. http://dx.doi.org/10.3346/jkms.2014.29.10.1333

Liver fibrosis is a common feature of chronic liver disease. Activated hepatic stellate cells (HSCs) are the main drivers of extracellular matrix accumulation in liver fibrosis. Hence, a strategy for regulating HSC activation is crucial in treating liver fibrosis. Mesenchymal stem cells (MSCs) are multipotent stem cells derived from various post-natal organs. Therapeutic approaches involving MSCs have been studied extensively in various diseases, including liver disease. MSCs modulate hepatic inflammation and fibrosis and/or differentiate into hepatocytes by interacting directly with immune cells, HSCs, and hepatocytes and secreting modulators, thereby contributing to reduced liver fibrosis. Cell-free therapy including MSC-released secretomes and extracellular vesicles has elicited extensive attention because they could overcome MSC transplantation limitations. Herein, we provide basic information on hepatic fibrogenesis and the therapeutic potential of MSCs. We also review findings presenting the effects of MSC itself and MSC-based cell-free treatments in liver fibrosis, focusing on HSC activation. Growing evidence supports the anti-fibrotic function of either MSC itself or MSC modulators, although the mechanism underpinning their effects on liver fibrosis has not been established. Further studies are required to investigate the detailed mechanism explaining their functions to expand MSC therapies using the cell itself and cell-free treatments for liver fibrosis.

To predict survival time of Korean hepatocellular carcinoma (HCC) patients using multi-center data as a foundation for the development of a predictive artificial intelligence model according to treatment methods based on machine learning. Data of patients who underwent treatment for HCC from 2008 to 2015 was provided by Korean Liver Cancer Study Group and Korea Central Cancer Registry. A total of 10,742 patients with HCC were divided into two groups, with Group I (2920 patients) confirmed on biopsy and Group II (5562 patients) diagnosed as HCC according to HCC diagnostic criteria as outlined in Korean Liver Cancer Association guidelines. The data were modeled according to features of patient clinical characteristics. Features effective in predicting survival rate were analyzed retrospectively. Various machine learning methods were used. Target was overall survival time, which divided into approximately 60 months (= /< 60 m, > 60 m). Target distribution in Group I (total 514 samples) was 28.8%: (148 samples) less than 60 months, 71.2% (366 samples) greater than 60 months, and in Group II (total 757 samples) was 66.6% (504 samples) less than 60 months, 33.4% (253 samples) greater than 60 months. Using NG Boost method, its accuracy was 83%, precision 84%, sensitivity 95%, and F1 score 89% for more than 60 months survival time in Group I with surgical resection. Moreover, its accuracy was 79%, precision 82%, sensitivity 87%, and F1 score 84% for less than 60 months survival time in Group II with TACE. The feature importance with gain criterion indicated that pathology, portal vein invasion, surgery, metastasis, and needle biopsy features could be explained as important factors for prediction in case of biopsy (Group I). By developing a predictive model using machine learning algorithms to predict prognosis of HCC patients, it is possible to project optimized treatment by case according to liver function and tumor status.

Background: Blood flow from the saphenofemoral junction(SFJ) tributaries may cause recurrence of varicose veins. Flush occlusion is defined as the total occlusion of the great saphenous vein(GSV) right to the saphenofemoral junction. The purpose of this study was to evaluate the efficacy and safety of flush endovenous thermal ablation with saphenofemoral junction tributary occlusion. Method: Between January 2019 and December 2022, 722 patients (total of 1273 limbs) were diagnosed with chronic vein insufficiency by one surgeon at a single center. Result: Of the 722 patients, 476 (65.9%) were female and 246 (34.1%) were male. Of the 1273 limbs, endovenous laser ablation(EVLA) was performed in 609 limbs and radiofrequency ablation(RFA) in 664 limbs. Of the 1273 limbs, the recurrence rate was 3.69% (n = 47), the development of endovenous heat-induced thromboembolism(EHIT) was 0.31% (n = 4), and neovascularization was 1.49% (n = 19). Conclusions: Flush endovenous thermal ablation was an effective method for decreasing recurrence without inducing endovenous heat-induced thromboembolism. Consecutive foam sclerotherapy for saphenofemoral junction tributaries may be feasible for reducing the recurrence of varicose veins.