Identifying the Mechanism of Polygoni Cuspidati Rhizoma et Radix in Treating Acute Liver Failure Based on Network Pharmacology and Molecular Docking.

Materials and Methods: The potential bioactive compounds of PCRR and their targets were collected from TCMSP, TCMID, and BATMAN-TCM databases with absorption, distribution, metabolism, and excretion protocols (oral bioavailability ≥30% and drug-likeness ≥0.18). The ALF-related target genes were identified using the GeneCards and OMIM databases. A protein-protein interaction (PPI) network among these targets was constructed using the Cytoscape software to obtain the core targets. The genes associated with ALF were analyzed via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to identify the signaling pathways related to the therapeutic effect of PCRR in ALF. Results: In total, 10 bioactive compounds of PCRR and 200 targets related to them were obtained, and 2913 ALF-related target genes were identified. PPI network analysis pinpointed 15 core targets, namely, TP53, AKT1, JUN, HSP90AA1, MAPK1, RELA, TNF, ESR1, IL6, MYC, MAPK14, FOS, RB1, CDKN1A, and EGFR. GO enrichment and KEGG pathway analyses revealed that the therapeutic mechanisms of PCRR in ALF are related to cell metabolism, oxidative stress, inflammation, and hepatocyte apoptosis. Conclusion: This is the first study to explore the therapeutic mechanisms of PCRR in ALF via network pharmacology and molecular docking. This study provides a research platform with candidate ALF-related targets of PRCC for the development of therapeutics against ALF.

Long non-coding RNA UCA1 is a predictive biomarker of cancer.

Human urothelial carcinoma associated 1 (UCA1) is a long noncoding RNA that is putatively oncogenic in solid tumors. This meta-analysis investigated an association between UCA1 levels and survival times of cancer patients. The primary endpoints were overall survival (OS) and progression-free survival (PFS). A comprehensive, computerized literature search was conducted of the databases PubMed, EMBASE, Chinese National Knowledge Infrastructure (CNKI), and Wanfang. The strength of association between UCA1 and cancer prognosis was assessed by computing the hazard ratio (HR) with its corresponding 95% confidence interval (CI). Twelve studies comprising 954 cancer patients met the criteria for this meta-analysis. Overall, a significant negative association was found between UCA1 levels and OS time (HR1.81, 95% CI1.52-2.17), including the following cancers analyzed independently: colorectal (HR2.61, 95% CI1.56-4.37), non-small cell lung (HR1.49, 95% CI1.16-1.90), gastric (HR2.19, 95% CI1.36-3.51), and ovarian (HR1.89, 95% CI1.14-3.12). There was also a significant negative association between UCA1 levels and PFS time (HR2.59, 95% CI1.61-4.16). In conclusion, this meta-analysis indicated that higher levels of UCA1 correlate with shorter PFS and OS times in cancers.

Effect of oxygen-driven nebulization at different oxygen flows in acute exacerbation of chronic obstructive pulmonary disease patients.

OBJECTIVES: The aim of this study was to study the effect of oxygen-driven nebulization (ODN) at different oxygen flows on heart rate, respiratory rate, SpO2, SaO2, PaO2, PaCO2 and pH of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) patients. METHODS: According to random number table, 9 AECOPD patients were randomly divided into 3 groups, numbered A, B and C and treated with ODN. Oxygen flow of groups A, B and C was 4-5, 6-7 and 8-9 L/min, respectively. Heart rate, respiratory rate, SpO2, SaO2, PaO2, PaCO2 and pH were recorded before ODN and 30 minutes after ODN. Statistical differences of data before or after ODN were analyzed by analysis of variance and F-test, whereas data before and after ODN were tested by paired t test. RESULTS: There was no significant difference of heart rate, respiratory rate, SpO2, PaO2, PaCO2, SaO2 and pH among 3 groups before ODN or after ODN. The heart rate was increased in all groups after ODN. But significant increase was only present in groups A and C but not in group B. SaO2 was significantly increased in group C after ODN but no statistical difference was observed between before and after ODN in groups A and B. There was no significant change in respiratory rate, SpO2, PaO2, PaCO2, SaO2 and pH between before and after ODN in all groups. CONCLUSIONS: Optimal oxygen flow in ODN-treating AECOPD patients may be 6-7 L/min.