Objective. This study aimed to systematically review the efficacy and clinical safety of different courses and doses of tripterygium glycoside (TG) adjuvant methotrexate (MTX) therapy in the treatment of rheumatoid arthritis (RA). Methods. Randomized controlled trials (RCTs) of TG adjuvant MTX therapy in patients with RA were retrieved from SinoMed, China Network Knowledge Infrastructure, WanFang Data, PubMed, Cochrane Library, and Embase from inception to September 30, 2021. The effects and clinical safety evaluations were conducted using RevMan 5.3 software. Results. A total of 9 RCTs and 892 patients with RA were included in this study. In the meta-analysis, a total of 463 and 429 patients were enrolled into the TG adjuvant MTX therapy group and MTX monotherapy group, respectively. In comparison with MTX monotherapy, the results of the analyzed effects showed that the TG adjuvant MTX therapy can achieve 20%, 50%, and 70% improvements in American College of Rheumatology (ACR) criteria ACR20, ACR50, and ACR70 at P  = 0.005, P  = 0.0001, and P  = 0.004, respectively. Simultaneously, the efficacy of the TG adjuvant MTX therapy was improved at either 30 or 60 mg/day over a six-month course compared to MTX monotherapy ( P  < 0.0001). There was no statistical difference in the effects between the doses of 30 and 60 mg/day after three months ( P  = 0.82). TG adjuvant MTX also reduced the expression rate of the swollen joint count, tender joint count, erythrocyte sedimentation rate, rheumatoid factor, and C-reactive protein in subgroup analyses with different courses and doses. In terms of hepatic adverse effects ( P  = 0.28), leukopenia ( P  = 0.78), gastrointestinal adverse effects ( P  = 0.17), cutaneous adverse effects ( P  = 0.94), and irregular menstruation adverse effects ( P  = 0.29), there was no statistically significant difference with TG adjuvant MTX therapy and MTX monotherapy with different courses and doses. Conclusions. TG adjuvant MTX therapy is more effective than MTX monotherapy and is a safe strategy for RA treatment in doses of 30 or 60 mg/day over a treatment course of six months. However, high-quality multicenter RCT studies with large sample sizes are still needed to confirm the effects and clinical safety of different courses and doses of TG adjuvant MTX therapy.

Background Rheumatoid arthritis (RA) is a chronic and refractory autoimmune disease. Deficiency pattern (DP) and excess pattern (EP), as crucial types of Chinese medicine pattern diagnoses published by International Classification of Diseases 11th Revision (ICD-11), could provide new strategies for RA diagnosis. However, the biological basis of DP and EP of RA is not explicit. Methods 19 female RA DP patients, 41 female RA EP patients and 30 female healthy participants were included in the study. The serums of participants were collected and analyzed by metabolomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry to profile metabolic characteristics of RA DP and EP. Furthermore, bioinformatics analysis results were obtained by using Ingenuity Pathway Analysis (IPA) and statistical analysis was performed by SAS version 9.4 for further identification of potential biomarkers. Results Serum metabolic profiling revealed 25 and 24 differential metabolites in RA DP and EP respectively, and 19 metabolites were common to RA DP and EP. Compared with DP group, L-Homocysteic acid, LysoPE(P-16:0/0:0), N(omega)-Hydroxyarginine and LysoPC(16:0/0:0) decreased (P < 0.05), and Pyruvic acid, D-Ribose, Gamma-Glutamylserine, PE(22:0/24:1(15Z)), Inosinic acid increased (P < 0.05) in EP group. Menawhile, S-Nitrosoglutathione, 5-Thymidylic acid, SN38 glucuronide, PE(22:0/24:0), PC(24:0/24:1(15Z)) and Bisdiphosphoinositol tetrakisphosphate increased significantly in DP group compared to EP group (P < 0.05). For the unique metabolites, bioinformatics analysis results showed that 5-Methoxytryptamine involved in Melatonin Degradation II and Superpathway of Melatonin Degradation is the key metabolite to RA DP. Meanwhile, GABA is the key metabolite in EP group, which involved in Glutamate Dependent Acid Resistance, GABA Receptor Signaling, Glutamate Degradation III (via 4-aminobutyrate) and 4-aminobutyrate Degradation I. Bioinformatics analysis between unique metabolites of RA DP and EP groups with human target genes for RA showed that 5-methoxytryptamine and LysoPC(18:1(9Z)/0:0), the unique metabolites of RA DP, might participate in colorectal cancer metastasis signaling, tumor microenvironment pathway, apoptosis signaling, MYC mediated apoptosis signaling, erythropoietin signaling pathway and LXR/RXR activation. Simultaneously, GABA, LysoPA(18:1(9Z)/0:0) and L-Targinine, the unique metabolites of RA EP, might participate in neuroinflammation signaling pathway, osteoarthritis pathway, glucocorticoid receptor signaling, ILK signaling, IL-17 signaling and HIF1α signaling. Conclusions The study indicates that serum metabolomics preliminarily revealed the biological basis of RA DP and EP. 5-methoxytryptamine, LysoPC(18:1(9Z)/0:0) and GABA, LysoPA(18:1(9Z)/0:0), L-Targinine might be the predictors to distinguish the DP and EP of RA respectively. These interesting results provide thoughts for further study of traditional medicine patterns of ICD-11. It also contributes to provide strategy for personalized precision treatment of RA and further validation is needed.

Nauclea officinalis (N. officinalis), a medicinal plant of the genus Nauclea in the family Rubiaceae, is used in the treatment of fever, pneumonia, pharyngolaryngitis, and enteritis in China. Extracts of N. officinalis include alkaloids, phenolic acids, pentacyclic triterpenoids, and flavonoids, which exert all kinds of pharmacological effects, for instance anti-inflammatory, anti-tumor, antibacterial, and antiviral and therefore show good effectiveness. To gain a comprehensive and deep understanding, the medicinal chemistry and chemical biology of N. officinalis are summarized in this review to provide a theoretical basis. The pharmacological effects were reviewed to provide evidence or insights into potential opportunities for further studies and medicinal exploitation of N. officinalis.

Background Chinese herbal medicine is made up of hundreds of natural drug molecules and has played a major role in traditional Chinese medicine (TCM) for several thousand years. Therefore, it is of great significance to study the target of natural drug molecules for exploring the mechanism of treating diseases with TCM. However, it is very difficult to determine the targets of a fresh natural drug molecule due to the complexity of the interaction between drug molecules and targets. Compared with traditional biological experiments, the computational method has the advantages of less time and low cost for targets screening, but it remains many great challenges, especially for the molecules without social ties. Methods This study proposed a novel method based on the Cosine-correlation and Similarity-comparison of Local Network (CSLN) to perform the preliminary screening of targets for the fresh natural drug molecules and assign weights to them through a trained parameter. Results The performance of CSLN is superior to the popular drug-target-interaction (DTI) prediction model GRGMF on the gold standard data in the condition that is drug molecules are the objects for training and testing. Moreover, CSLN showed excellent ability in checking the targets screening performance for a fresh-natural-drug-molecule (scenario simulation) on the TCMSP (13 positive samples in top20), meanwhile, Western-Blot also further verified the accuracy of CSLN. Conclusions In summary, the results suggest that CSLN can be used as an alternative strategy for screening targets of fresh natural drug molecules.