IL‐23/Th17 (IL‐17) axis plays a critical role in psoriasis. Rosmarinic acid (RA) was proved the inhibitory effect of T cell infiltration in the skin. However, whether and how RA has beneficial effects on psoriasis did not really know yet. So lipopolysaccharide (LPS)‐induced abnormal proliferation Hacat cell line and Imiquimod (IMQ)‐induced psoriasis‐like mouse dermatitis were used to assess the pharmacological effects and mechanisms of RA by Psoriasis Area Severity Index (PASI) score, histopathology, flow cytometry, reverse transcription‐polymerase chain reaction (RT‐PCR) and western blotting. The results showed that RA inhibited LPS‐induced aberrant expression of Hacat cell line, and significantly alleviated IMQ‐induced skin inflammation. Although RA had no obviously effect on the ratio of epidermal Langerhans cell (LC) and LC migration from the skin to the skin draining lymph nodes, RA inhibited the expression of IL‐23 in skin lesions, as well as reduced the differentiation of Th17 cells and producing of IL‐17A by down regulating the transcriptor factor RORγt and JAK2/Stat3 signal pathway, comparing to IMQ treated group. The findings suggest that RA inhibits psoriasis‐like skin inflammation in vivo and in vitro by reducing the expression of IL‐23, inhibiting Th17 dominated inflammation and down regulating the Jak2/Stat3 signal pathway.

No abstract

P-Glycoprotein (Pgp) is a main factor contributing to multidrug resistance and the consequent failure of chemotherapy. Overcoming Pgp efflux is a strategy to improve the efficacy of drugs. (+)-Borneol (BNL1) and (−)-borneol (BNL2) interfere and inhibit Pgp, and thus, the accumulation of drugs increases in cells. However, it is not clear yet how they play the inhibitory effect against Pgp. In this work, the effect and molecular mechanism of borneol enantiomers in reversing mitoxantrone (MTO) resistance against Pgp were explored by in vitro and in silico approaches. Chemosensitizing potential tests showed that BNLs could enhance the efficacy of MTO in MES-SA/MX2 cells, and BNL2 exhibited a stronger potential. The protein expression of Pgp was decreased to some extent by the administration of BNLs. Molecular docking revealed that BNLs could reduce the binding affinity between MTO and Pgp. The results were consistent with the chemosensitizing potential test and were supported by molecular dynamics (MD) simulations. Molecular docking also suggested that BNLs preferred to bind in the drug-binding pocket rather than the nucleotidebinding domain of inward-facing Pgp. The occupied space of BNLs had an evident distance from that of MTO, which was further verified by the conformational analysis after MD simulations. The decomposition of binding free energies revealed the key amino acid residues (GLN195, SER196, TRP232, PHE343, SER344, GLY346, and GLN347) for BNLs to reverse MTO resistance. The results provide an insight into the mechanism through which BNLs reduce the MTO resistance against inward-facing Pgp in the drug-binding pocket through noncompetitive inhibition.

Introduction: Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world. Up to now, many genes associated with HCC have not yet been identified. In this study, we screened the HCC-related genes through the integrated analysis of the TCGA database, of which the potential biomarkers were also further validated by clinical specimens. The discovery of potential biomarkers for HCC provides more opportunities for diagnostic indicators or gene-targeted therapies. Methods: Cancer-related genes in The Cancer Genome Atlas (TCGA) HCC database were screened by a random forest (RF) classifier based on the RF algorithm. Proteins encoded by the candidate genes and other associated proteins obtained via protein-protein interaction (PPI) analysis were subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The newly identified genes were further validated in the HCC cell lines and clinical tissue specimens by Western blotting, immunofluorescence, and immunohistochemistry (IHC). Survival analysis verified the clinical value of genes. Results: Ten genes with the best feature importance in the RF classifier were screened as candidate genes. By comprehensive analysis of PPI, GO and KEGG, these genes were confirmed to be closely related to HCC tumors. Representative NOX4 and FLVCR1 were selected for further validation by biochemical analysis which showed upregulation in both cancer cell lines and clinical tumor tissues. High expression of NOX4 or FLVCR1 in cancer cells predicts low survival. Conclusion: Herein, we report that NOX4 and FLVCR1 are promising biomarkers for HCC that may be used as diagnostic indicators or therapeutic targets.

Background: Quantitative systems pharmacology (QSP) is an emerging discipline that integrates diverse data to quantitatively explore the interactions between drugs and multi-scale systems including small compounds, nucleic acids, proteins, pathways, cells, organs and disease processes. Results: Various computational methods such as ADME/T evaluation, molecular modeling, logical modeling, network modeling, pathway analysis, multi-scale systems pharmacology platforms and virtual patient for QSP have been developed. We reviewed the major progresses and broad applications in medical guidance, drug discovery and exploration of pharmacodynamic material basis and mechanism of traditional Chinese medicine. Conclusion: QSP has significant achievements in recent years and is a promising approach for quantitative evaluation of drug efficacy and systematic exploration of mechanisms of action of drugs.Author summary: Quantitative systems pharmacology (QSP) is an emerging discipline that integrates diverse data to quantitatively explore the interactions between drugs and multi-scale systems including small compounds, nucleic acids, proteins, pathways, cells, organs and disease processes. This review is an attempt to introduce the computational methods for QSP, including ADME/T (absorption, distribution, metabolism, excretion and toxicity) evaluation, molecular modeling, logical modeling, network modeling, pathway analysis, multi-scale systems pharmacology platforms and virtual patient as well as their applications in medical guidance, drug discovery and explorations of pharmacodynamics material basis and mechanism of traditional Chinese medicine.

Reduning Injection (RDNI) is a traditional Chinese medicine formula indicated for the treatment of inflammatory diseases. However, the molecular mechanism of RDNI is unclear. The information of RDNI ingredients was collected from previous studies. Targets of them were obtained by data mining and molecular docking. The information of targets and related pathways was collected in UniProt and KEGG. Networks were constructed and analyzed by Cytoscape to identify key compounds, targets, and pathways. Data mining and molecular docking identified 11 compounds, 84 targets, and 201 pathways that are related to the anti-inflammatory activity of RDNI. Network analysis identified two key compounds (caffeic acid and ferulic acid), five key targets (Bcl-2, eNOS, PTGS2, PPARA, and MMPs), and four key pathways (estrogen signaling pathway, PI3K-AKT signaling pathway, cGMP-PKG signaling pathway, and calcium signaling pathway) which would play critical roles in the treatment of inflammatory diseases by RDNI. The cross-talks among pathways provided a deeper understanding of anti-inflammatory effect of RDNI. RDNI is capable of regulating multiple biological processes and treating inflammation at a systems level. Network pharmacology is a practical approach to explore the therapeutic mechanism of TCM for complex disease.

No abstract

Background: Chronic obstructive pulmonary disease (COPD) has the characteristics of high incidence, mortality, disability rate, and heavy economic burden. Symptomatic measures such as anti-inflammatory, antispasmodic and anti-asthmatic are widely used in the treatment of COPD, and pulmonary rehabilitation has not been fully utilized. It is reported that up to 10 different kinds of Traditional Chinese exercises (TCEs) are often used for treating stable COPD. There are many randomized controlled trials (RCTs) and systematic reviews that have evaluated the efficacy of various TCEs for COPD. However, most of these studies were designed in comparison with conventional western medicine or health education. There are rarely studies to compare different TCEs head to head. Therefore, there remains uncertainty regarding the comparative efficacy among different TCEs. Thus, we plan to conduct a systematic review and Network meta-analysis (NMA) to compare the efficacy among 5 different TCEs and rank their benefits relative to each other. It is hoped that the findings of this study will facilitate the management and application of TCEs in the treatment of COPD. Methods: A systematic and comprehensive literature search will be performed from inception to April 2019 in both English and Chinese databases, involving Medline, Cochrane Library, Embase, China National Knowledge Infrastructure Database, Wanfang Database, China Biomedical Literature Database, and Chongqing VIP information. RCTs related to TCE in the treatment of COPD will be included. Quality of included trials will be assessed according to the risk of bias tool of Cochrane Handbook 5.1.0. The GRADE approach will be used to rate the certainty of the evidence of estimates derived from NMA. Data analysis will be conducted by using STATA 14.0. Results: This systematic review and NMA aims to summarize the direct and indirect evidence for different kinds of TCEs and to rank these TCEs. The findings of this NMA will be reported according to the PRISMA-NMA statement. The results of the NMA will be submitted to a peer-reviewed journal once completed. Conclusion: Using NMA, this study will provide an evidence profile which will be helpful to inform the selection of TCE for treating patients with COPD. The results will inform clinicians, bridge the evidence gaps, and identify promising TCE for future trials. PROSPERO registration number: PROSPERO CRD 42019132970.