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BackgroundBabao Dan (BBD) is a traditional Chinese medicine that has been widely used as a complementary and alternative medicine to treat chronic liver diseases. In this study, we aimed to observe the effect of BBD on the incidence of diethylnitrosamine (DEN)-initiated hepatocellular carcinoma formation in rats and explored its possible mechanism.MethodsTo verify this hypothesis, BBD was administrated to rats at a dose of 0.5g/kg body weight per two days from the 9th to 12th week in HCC-induced by DEN. Liver injury biomarkers and hepatic inflammatory parameters were evaluated by histopathology as well as serum and hepatic content analysis. We applied immunohistochemical analysis to investigate the expression of CK-19 and SOX-9 in liver tissues. The expression of TLR4 was determined by immunohistochemical, RT-PCR, and western blot analysis. Furthermore, we also detected the efficacy of BBD against primary HPCs neoplastic transformation induced by LPS.ResultsWe observed that DEN could induce hepatocarcinogenesis, and BBD could obviously decrease the incidence. The biochemical and histopathological examination results confirmed that BBD could protect against liver injury and decrease inflammatory infiltration. Immunohistochemistry staining results showed that BBD could effectively inhibit the ductal reaction and the expression of TLR4. The results showed that BBD-serumcould obviously inhibit primary HPCs neoplastic transformation induced by regulating the TLR4/Ras/ERK signaling pathway.ConclusionIn summary, our results indicate that BBD has potential applications in the prevention and treatment of HCC, which may be related to its effect on hepatic progenitor cells malignant transformation via inhibiting the TLR4/Ras/ERK signaling pathway.

BackgroundAbout 15% of lung cancers in men and 53% in women are not attributable to smoking worldwide. The aim was to develop and validate a simple and non-invasive model which could assess and stratify lung cancer risk in non-smokers in China.MethodsA large-sample size, population-based study was conducted under the framework of the Cancer Screening Program in Urban China (CanSPUC). Data on the lung cancer screening in Henan province, China, from October 2013 to October 2019 were used and randomly divided into the training and validation sets. Related risk factors were identified through multivariable Cox regression analysis, followed by establishment of risk prediction nomogram. Discrimination [area under the curve (AUC)] and calibration were further performed to assess the validation of risk prediction nomogram in the training set, and then validated by the validation set.ResultsA total of 214,764 eligible subjects were included, with a mean age of 55.19 years. Subjects were randomly divided into the training (107,382) and validation (107,382) sets. Elder age, being male, a low education level, family history of lung cancer, history of tuberculosis, and without a history of hyperlipidemia were the independent risk factors for lung cancer. Using these six variables, we plotted 1-year, 3-year, and 5-year lung cancer risk prediction nomogram. The AUC was 0.753, 0.752, and 0.755 for the 1-, 3- and 5-year lung cancer risk in the training set, respectively. In the validation set, the model showed a moderate predictive discrimination, with the AUC was 0.668, 0.678, and 0.685 for the 1-, 3- and 5-year lung cancer risk.ConclusionsWe developed and validated a simple and non-invasive lung cancer risk model in non-smokers. This model can be applied to identify and triage patients at high risk for developing lung cancers in non-smokers.