1.Interleukin-20 targets podocytes and is upregulated in experimental murine diabetic nephropathy.
Yu Hsiang HSU ; Hsing Hui LI ; Junne Ming SUNG ; Wei Yu CHEN ; Ya Chin HOU ; Yun Han WENG ; Wei Ting LAI ; Chih Hsing WU ; Ming Shi CHANG
Experimental & Molecular Medicine 2017;49(3):e310-
Interleukin (IL)-20, a proinflammatory cytokine of the IL-10 family, is involved in acute and chronic renal failure. The aim of this study was to elucidate the role of IL-20 during diabetic nephropathy development. We found that IL-20 and its receptor IL-20R1 were upregulated in the kidneys of mice and rats with STZ-induced diabetes. In vitro, IL-20 induced MMP-9, MCP-1, TGF-β1 and VEGF expression in podocytes. IL-20 was upregulated by hydrogen peroxide, high-dose glucose and TGF-β1. In addition, IL-20 induced apoptosis in podocytes by activating caspase-8. In STZ-induced early diabetic nephropathy, IL-20R1-deficient mice had lower blood glucose and serum BUN levels and a smaller glomerular area than did wild-type controls. Anti-IL-20 monoclonal antibody (7E) treatment reduced blood glucose and the glomerular area and improved renal functions in mice in the early stage of STZ-induced diabetic nephropathy. ELISA showed that the serum IL-20 level was higher in patients with diabetes mellitus than in healthy controls. The findings of this study suggest that IL-20 induces cell apoptosis of podocytes and plays a role in the pathogenesis of early diabetic nephropathy.
Animals
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Apoptosis
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Blood Glucose
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Caspase 8
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Diabetes Mellitus
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Diabetic Nephropathies*
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Enzyme-Linked Immunosorbent Assay
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Glucose
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Humans
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Hydrogen Peroxide
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In Vitro Techniques
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Interleukin-10
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Interleukins
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Kidney
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Kidney Failure, Chronic
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Mice
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Podocytes*
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Rats
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Vascular Endothelial Growth Factor A
2.Conventional and machine learning-based risk scores for patients with early-stage hepatocellular carcinoma
Chun-Ting HO ; Elise Chia-Hui TAN ; Pei-Chang LEE ; Chi-Jen CHU ; Yi-Hsiang HUANG ; Teh-Ia HUO ; Yu-Hui SU ; Ming-Chih HOU ; Jaw-Ching WU ; Chien-Wei SU
Clinical and Molecular Hepatology 2024;30(3):406-420
Background/Aims:
The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC patients into distinct prognostic groups.
Methods:
The study retrospectively enrolled 1,411 consecutive treatment-naïve patients with the Barcelona Clinic Liver Cancer (BCLC) stage 0 to A HCC from 2012 to 2021. The patients were randomly divided into a training cohort (n=988) and validation cohort (n=423). Two risk scores (CATS-IF and CATS-INF) were developed to predict overall survival (OS) in the training cohort using the conventional methods (Cox proportional hazards model) and ML-based methods (LASSO Cox regression), respectively. They were then validated and compared in the validation cohort.
Results:
In the training cohort, factors for the CATS-IF score were selected by the conventional method, including age, curative treatment, single large HCC, serum creatinine and alpha-fetoprotein levels, fibrosis-4 score, lymphocyte-tomonocyte ratio, and albumin-bilirubin grade. The CATS-INF score, determined by ML-based methods, included the above factors and two additional ones (aspartate aminotransferase and prognostic nutritional index). In the validation cohort, both CATS-IF score and CATS-INF score outperformed other modern prognostic scores in predicting OS, with the CATSINF score having the lowest Akaike information criterion value. A calibration plot exhibited good correlation between predicted and observed outcomes for both scores.
Conclusions
Both the conventional Cox-based CATS-IF score and ML-based CATS-INF score effectively stratified patients with early-stage HCC into distinct prognostic groups, with the CATS-INF score showing slightly superior performance.
3.Taiwan Association for the Study of the Liver-Taiwan Society of Cardiology Taiwan position statement for the management of metabolic dysfunction- associated fatty liver disease and cardiovascular diseases
Pin-Nan CHENG ; Wen-Jone CHEN ; Charles Jia-Yin HOU ; Chih-Lin LIN ; Ming-Ling CHANG ; Chia-Chi WANG ; Wei-Ting CHANG ; Chao-Yung WANG ; Chun-Yen LIN ; Chung-Lieh HUNG ; Cheng-Yuan PENG ; Ming-Lung YU ; Ting-Hsing CHAO ; Jee-Fu HUANG ; Yi-Hsiang HUANG ; Chi-Yi CHEN ; Chern-En CHIANG ; Han-Chieh LIN ; Yi-Heng LI ; Tsung-Hsien LIN ; Jia-Horng KAO ; Tzung-Dau WANG ; Ping-Yen LIU ; Yen-Wen WU ; Chun-Jen LIU
Clinical and Molecular Hepatology 2024;30(1):16-36
Metabolic dysfunction-associated fatty liver disease (MAFLD) is an increasingly common liver disease worldwide. MAFLD is diagnosed based on the presence of steatosis on images, histological findings, or serum marker levels as well as the presence of at least one of the three metabolic features: overweight/obesity, type 2 diabetes mellitus, and metabolic risk factors. MAFLD is not only a liver disease but also a factor contributing to or related to cardiovascular diseases (CVD), which is the major etiology responsible for morbidity and mortality in patients with MAFLD. Hence, understanding the association between MAFLD and CVD, surveillance and risk stratification of MAFLD in patients with CVD, and assessment of the current status of MAFLD management are urgent requirements for both hepatologists and cardiologists. This Taiwan position statement reviews the literature and provides suggestions regarding the epidemiology, etiology, risk factors, risk stratification, nonpharmacological interventions, and potential drug treatments of MAFLD, focusing on its association with CVD.