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BACKGROUND: Polygoni Cuspidati Rhizoma et Radix (PCRR), a well-known traditional Chinese medicine (TCM), inhibits inflammation associated with various human diseases. However, the anti-inflammatory effects of PCRR in acute lung injury (ALI) and the underlying mechanisms of action remain unclear. AIM: To determine the ingredients related to PCRR for treatment of ALI using multiple databases to obtain potential targets for fishing. METHODS: Recognized and candidate active compounds for PCRR were obtained from Traditional Chinese Medicine Systems Pharmacology, STITCH, and PubMed databases. Target ALI databases were built using the Therapeutic Target, DrugBank, DisGeNET, Online Mendelian Inheritance in Man, and Genetic Association databases. Network pharmacology includes network construction, target prediction, topological feature analysis, and enrichment analysis. Bioinformatics resources from the Database for Annotation, Visualization and Integrated Discovery were utilized for gene ontology biological process and Kyoto Encyclopedia of Genes and Genomes network pathway enrichment analysis, and molecular docking techniques were adopted to verify the combination of major active ingredients and core targets. RESULTS: Thirteen bioactive compounds corresponding to the 433 PCRR targets were identified. In addition, 128 genes were closely associated with ALI, 60 of which overlapped with PCRR targets and were considered therapeutically relevant. Functional enrichment analysis suggested that PCRR exerted its pharmacological effects in ALI by modulating multiple pathways, including the cell cycle, cell apoptosis, drug metabolism, inflammation, and immune modulation. Molecular docking results revealed a strong associative relationship between the active ingredient and core target. CONCLUSION: PCRR alleviates ALI symptoms via molecular mechanisms predicted by network pharmacology. This study proposes a strategy to elucidate the mechanisms of TCM at the network pharmacology level.
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Background: Rarity limits the breadth of study on clear cell sarcoma of the kidney (CCSK). There is currently no predictive model that quantifies the overall survival (OS) of CCSK and a few large sample-based analysis of relapse-related factors. Methods: Patients were collected both from the Surveillance, Epidemiology, and End Results (SEER) database and case report articles extracted from the global online document database to form 2 groups. The first was the OS group, which was used to build and verify the nomogram for predicting the OS of CCSK. Independent predictors of OS were screened by Cox regression analysis to develop the nomogram. Nomogram accuracy was assessed by C-index, receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA) curves. In addition, the difference in OS between receiving radiotherapy or not in stage I patients was analyzed by the Chi-square test. The second was the relapse group, which was used to analyze the relapse-related factors by Cox regression analysis and the Kaplan-Meier method with the log-rank test. Result: 256 patients were included in the OS group. The stage, chemotherapy, and radiotherapy were independent OS-related factors of CCSK, and the nomogram for predicting the OS of CCSK was established based on them. The results of the C-index, ROC, calibration, and DCA curves showed that the nomogram has good discrimination, accuracy, and clinical profitability. The Chi-squared test showed no significant difference in OS with receiving radiotherapy or not in stage I patients. The relapse group included 153 patients, of which 60 relapsed. The univariate Cox regression analysis showed no correlation between radiotherapy and relapse. The multivariate Cox regression analysis showed that stage and surgery/chemotherapy sequence were the independent factors for relapse. The log-rank test of seven chemotherapeutic drugs showed that etoposide (E), cyclophosphamide (C), vincristine (V), and doxorubicin (D) (all P < 0.05) had significant differences in preventing relapse, and then drew the relapse-free survival curves of these four drugs. Conclusion: Our nomogram accurately quantified the OS of CCSK. There was no significant difference in OS between receiving radiotherapy or not in stage I patients. Stage, surgery/chemotherapy sequence, and the use of ECVD were relapse-related factors. Radiotherapy had no significant contribution to preventing relapse.