Investigating the inter-individual variability of Astragali Radix against cisplatin-induced liver injury via 16S rRNA gene sequencing and LC/MS-based metabolomics.

BACKGROUND: Cisplatin (CDDP), one of the widely used chemotherapeutic drugs, can induce a series of side effects, such as hepatotoxicity and gastrointestinal toxicity. Astragali Radix (AR) is widely used as the tonic herbal medicine in traditional Chinese medicine (TCM). However, there was no report about the hepatoprotective effect of AR against the cisplatin-induced hepatic damage. PURPOSE: This study aimed to investigate the protective effect and potential mechanism of AR water extract against the cisplatin-induced liver injury. METHODS: Cisplatin was utilized to induce the liver injury using ICR mice, and the protective effect of AR was evaluated by serum biochemistry indices and liver histopathology. Then UHPLC Q-TOF-MS/MS-based untargeted serum metabolomics approach combined with 16S rRNA-based microbiota analysis was used to explore the underlying biomarkers and mechanism about the liver-protective effect of AR. RESULTS: AR could decrease the serum AST and ALT, ameliorate hepatic pathological damages caused by cisplatin. Serum metabolomics indicated AR could regulate the biosynthesis of unsaturated fatty acids, arachidonic acid metabolism, purine metabolism, and fatty acid biosynthesis. In addition, 16S rRNA gene sequencing analysis showed that AR could regulate cisplatin-induced gut microbiota disorder, especially the inflammation-related bacteria (p_Deferribacteres, g_Enterococcus, and g_Alistipes, etc.), and the short chain fatty acids (SCFAs)-producing bacteria (g_Alloprevotella, g_Intestinimoas, and g_Flavonifractor). Moreover, 7 mice (AR-7) showed better liver protective effect than the other 3 mice (AR-3), and their regulatory effect on the gut microbiota and serum metabolites were also different, indicating the presence of inter-individual variability for the liver protective effect of AR. CONCLUSIONS: This study revealed the protective effect and the potential mechanisms of AR against cisplatin-induced liver injury, and found that inter-individual variability of the liver protective effect of AR was related to the host microbiome and metabolome. These findings provided new insight into the health effect of dietary AR as a functional food for cisplatin-based chemotherapy.

Nomogram for Predicting Risk of Intestinal Complications After Colorectal Cancer Surgery.

BACKGROUND Intestinal complications are a major cause of morbidity after colorectal cancer surgery. This study aimed to develop an effective nomogram for predicting risk of intestinal complications following colorectal cancer surgery. MATERIAL AND METHODS We retrospectively analyzed 1876 patients who underwent colorectal cancer surgery at Yangpu and Zhuji hospitals from January 2013 to October 2018. Intestinal complications were defined as intestinal obstruction, leakage or bleeding, or peritonitis within 30 days after surgery. A logistic regression model was used to identify the risk factors associated with postoperative intestinal complications, and a nomogram for intestinal complications was established. The predictive accuracy of the nomogram was assessed using area under the receiver operating characteristic curve (AUC) and calibration plot. RESULTS A total of 164 patients (8.7%) developed intestinal complications after colorectal cancer surgery; 35 (21.3%) of whom died in the postoperative period. Multivariate logistic analysis showed that male gender, history of abdominal surgery, preoperative intestinal obstruction/perforation, metastatic cancer, and lower level of hemoglobin and prognostic nutrition index were independent risk factors (P<0.05 for all). A nomogram was then constructed, and it displayed good accuracy in predicting postoperative intestinal complications with an AUC of 0.76. The calibration plot also showed an excellent agreement between the predicted and observed probabilities. CONCLUSIONS We constructed a nomogram based on clinical variables, which could provide individual prediction of postoperative intestinal complications with good accuracy.