Artemisinin and its derivatives belong to a family of drugs approved for the treatment of malaria with known clinical safety and efficacy. In addition to its anti-malarial effect, artemisinin displays anti-viral, anti-inflammatory, and anti-cancer effects in vivo and in vitro. Recently, much attention has been paid to the therapeutic role of artemisinin in liver diseases. Several studies suggest that artemisinin and its derivatives can protect the liver through different mechanisms, such as those pertaining to inflammation, proliferation, invasion, metastasis, and induction of apoptosis and autophagy. In this review, we provide a comprehensive discussion of the underlying molecular mechanisms and signaling pathways of artemisinin and its derivatives in treating liver diseases. Further pharmacological research will aid in determining whether artemisinin and its derivatives may serve as promising medicines for the treatment of liver diseases in the future.

We aim to determine the impact of an artificial liver support system (ALSS) treatment before liver transplantation (LT), and identify the prognostic factors and evaluate the predictive values of the current commonly used ACLF prognostic models for short-term prognosis after LT. Data from 166 patients who underwent LT with acute-on-chronic liver failure (ACLF) were retrospectively collected from January 2011 to December 2018 from the First Affiliated Hospital of Zhejiang University School of Medicine. Patients were divided into two groups depending on whether they received ALSS treatment pre-LT. In the observation group, liver function tests and prognostic scores were significantly lower after ALSS treatment, and the waiting time for a donor liver was significantly longer than that of the control group. Both intraoperative blood loss and period of postoperative ICU care were significantly lower; however, there were no significant differences between groups in terms of total postoperative hospital stays. Postoperative 4-week and 12-week survival rates in the observation group were significantly higher than those of the control group. Similar trends were also observed at 48 and 96 weeks, however, without significant difference. Multivariate Cox regression analysis of the risk factors related to prognosis showed that preoperative ALSS treatment, neutrophil–lymphocyte ratio, and intraoperative blood loss were independent predicting factors for 4-week survival rate after transplantation. ALSS treatment combined with LT in patients with HBV-related ACLF improved short-term survival. ALSS treatment pre-LT is an independent protective factor affecting the 4-week survival rate after LT.

Objective:To evaluate the effect of postoperative adjuvant chemotherapy on survival after complete resection of stage III-N2 non-small-cell lung cancer. Methods: From Jan. 1999 to Dec. 2003, one-hundred and fifty patients, who were diagnosed as stage III-N2 non-small cell lung cancer after operation, were randomly devided into chemotherapy group and control group. The former received four cycles of chemotherapy with NVB (25 mg/m 2 , D1, D5)/paclitaxel (175 mg/m 2 , D1) and Carboplatin (AUC=5, D1). Results: In chemotherapy group, 75.8% (68/79) of patients had finished the 4 cycles of chemotherapy and no one died of toxic effects of chemotherapy. Twenty-five percent of the patients had grade 3−4 neutropenia and 2% had febrile neutropenia. The median survival for the entire 150 patients was 879 d, with 1-year survival rate of 81%, 2-year survival rate of 59% and 3-year survival rate of 43%. There was no significant difference in median survival between chemotherapy and control group (897 d vs 821 d, P=0.0527), but there was significant difference in the 1-year and 2-year overall survival (94.71%, 76.28% vs 512 d, P=0.122), but there was significant difference in the 2-year survival rate between two groups with brain metastases (66.7% vs 37.6% P<0.05). The median survival after brain metastasis appeared was 190 days. Conclusion: Postoperative adjuvant chemotherapy does not significantly improve median survival among patients with completely resected stage II-N2 non-small-cell lung cancer, but significantly improves the 1-year and 2-year overall survival. It neither decreases the incidence of brain metastasis but put off the time of brain metastasis.

Objective. Disease prediction is crucial to treatment success. The aim of this study was to accurately and explicably predict, based on the first laboratory measurements, medications, and demographic information, the risk of death in patients with hypertensive chronic kidney disease within 1 and 3 years after admission to the Intensive Care Unit (ICU). Methods. Patients with hypertensive chronic kidney disease who had been registered in the Medical Information Mart for Intensive Care (MIMIC-III) database of critical care medicine were set as the subject of study, which was randomly divided into a training set and a validation set in a ratio of 7 : 3. Univariate Cox regression analysis and stepwise Cox regression analysis were applied in the training set to identify the predictive factors of prognosis of patients with hypertensive chronic kidney disease in ICU, and the predictive nomogram based on Cox regression model was constructed. We internally validated the model in the training set and externally validated that in the validation model. The efficacy was assessed primarily through area under the receiver operating characteristic (ROC) curve, clinical decision curves, and calibration curves. Results. A total of 1762 patients with hypertensive chronic kidney disease were finally included. During the 3-year follow-up, 667 patients (37.85%) died, with a median follow-up time of 220 days (1-1090). The data set were randomly divided into a training set ( n = 1231 ) and a validation set ( n = 531 ). It was identified in the training set that insurance, albumin, alkaline phosphatase, the mean corpuscular hemoglobin concentration, mean corpuscular volume, history of coronary angiogram, hyperlipemia, medication of digoxin, acute renal failure, and history of renal surgery were the most relevant features. Taking 1 year and 3 years as the cut-off points, the AUC of participants were 0.736 and 0.744, respectively, in the internal validation and were 0.775 and 0.769, respectively, in the external validation, suggesting that the model is of favorable predictive efficacy. Conclusion. We trained and validated a model using data from a large multicenter cohort, which has considerable predictive performance on an individual scale and could be used to improve treatment strategies.

Background Acute-on-chronic liver failure (ACLF) is a critical illness with high mortality. Herein, we developed and validated a new and simple prognostic nomogram to predict 90-day mortality in hepatitis B virus-related ACLF (HBV-ACLF) patients. Methods This single-center retrospective study collected data from 181 HBV-ACLF patients treated between June 2018 and March 2020. The correlation between clinical data and 90-day mortality in patients with HBV-ACLF was assessed using univariate and multivariate logistic regression analyses. Results Multivariate logistic regression analysis showed that age (p = 0.011), hepatic encephalopathy (p = 0.001), total bilirubin (p = 0.007), international normalized ratio (p = 0.006), and high-density lipoprotein cholesterol (p = 0.011) were independent predictors of 90-day mortality in HBV-ACLF patients. A nomogram was created to predict 90-day mortality using these risk factors. The C-index for the prognostic nomogram was calculated as 0.866, and confirmed to be 0.854 via bootstrapping verification. The area under the curve was 0.870 in the external validation cohort. The predictive value of the nomogram was similar to that of the Chinese Group on the Study of Severe Hepatitis B score, and exceeded the performance of other prognostic scores. Conclusion The prognostic nomogram constructed using the factors identified in multivariate regression analysis might serve as a beneficial tool to predict 90-day mortality in HBV-ACLF patients.