Reduning injection (RDNI) is a patented Traditional Chinese medicine that contains three Chinese herbal medicines, respectively are the dry aboveground part of Artemisia annua L., the flower of Lonicera japonica Thunb., and the fruit Gardenia jasminoides J.Ellis. RDNI has been recommended for treating Coronavirus Disease 2019 (COVID-19) in the “New Coronavirus Pneumonia Diagnosis and Treatment Plan". To elucidate and verify the underlying mechanisms of RDNI for the treatment of COVID-19. This study firstly performed anti-SARS-CoV-2 experiments in Vero E6 cells. Then, network pharmacology combined with molecular docking was adopted to explore the potential mechanisms of RDNI in the treatment for COVID-19. After that, western blot and a cytokine chip were used to validate the predictive results. We concluded that half toxic concentration of drug CC50 (dilution ratio) = 1:1280, CC50 = 2.031 mg crude drugs/mL (0.047 mg solid content/mL) and half effective concentration of drug (EC50) (diluted multiples) = 1:25140.3, EC50 = 103.420 μg crude drugs/mL (2.405 μg solid content/mL). We found that RDNI can mainly regulate targets like carbonic anhydrases (CAs), matrix metallopeptidases (MMPs) and pathways like PI3K/AKT, MAPK, Forkhead box O s and T cell receptor signaling pathways to reduce lung damage. We verified that RDNI could effectively inhibit the overexpression of MAPKs, PKC and p65 nuclear factor-κB. The injection could also affect cytokine levels, reduce inflammation and display antipyretic activity. RDNI can regulate ACE2, Mpro and PLP in COVID-19. The underlying mechanisms of RDNI in the treatment for COVID-19 may be related to the modulation of the cytokine levels and inflammation and its antipyretic activity by regulating the expression of MAPKs, PKC and p65 nuclear factor NF-κB.

Yinzhihuang granule (YZHG) has liver protective effect and can be used for clinical treatment of non-alcoholic fatty liver disease (NAFLD), but its material basis and mechanism need to be further clarified. This study aims to reveal the material basis and mechanism of YZHG treating NAFLD. Serum pharmacochemistry were employed to identify the components from YZHG. The potential targets of YZHG against NAFLD were predicted by system biology and then preliminarily verified by molecular docking. Furthermore, the functional mechanism of YZHG in NAFLD mice was elucidated by 16S rRNA sequencing and untargeted metabolomics. From YZHG, 52 compounds were identified, of which 42 were absorbed into the blood. Network pharmacology and molecular docking showed that YZHG treats NAFLD with multi-components and multi-targets. YZHG can improve the levels of blood lipids, liver enzymes, lipopolysaccharide (LPS), and inflammatory factors in NAFLD mice. YZHG can also significantly improve the diversity and richness of intestinal flora and regulate glycerophospholipid and sphingolipid metabolism. Moreover, Western Blot experiment showed that YZHG can regulate liver lipid metabolism and enhance intestinal barrier function. YZHG may treat NAFLD by improving the disruption of intestinal flora and enhancing the intestinal barrier. This will reduce the invasion of LPS into the liver subsequently regulate liver lipid metabolism and reduce liver inflammation.

Pancreatic cancer is a common malignancy worldwide due to its poor prognosis and high mortality rate. It is clinically proven that the combination of chemotherapeutic drugs and Traditional Chinese Medicine injections (TCMIs) significantly improves the therapeutic effect. To evaluate the efficacy and clinical benefits of TCMIs in combination with chemotherapy in the treatment of pancreatic cancer and to explore the mechanism of clinical advantage of Aidi injection. Randomized controlled trials (RCTs) were searched in databases by NMA before December 29, 2020. WinBUGS 1.4, Stata 14.0, and R 4.0.4 software were used for calculations. All results were expressed as odds ratios and 95% credible intervals. Through the network pharmacology method, the chemical components and their targets, as well as the disease targets were further analyzed. And then, biological experiments were integrated to verify the results of network pharmacology analysis. (PROSPERO ID: CRD42021283559). A total of 33 RCTs with 8 TCMIs and 2011 patients were included. The results of NMA showed that Aidi injection can significantly improve the clinical efficacy (OR = 0.34, 95%CI: 0.16-0.74), and the clinical advantage was that it can significantly alleviate the leukopenia and thrombocytopenia caused by chemotherapy (OR = 5.65, 95%CI: 1.18-28.13). A total of 23 chemical compounds and 280 potential targets for Aidi injection were obtained from the online databases. Among them, there were 22 compounds, 50 targets and 211 signaling pathways closely related to leukopenia. Five genes were predicted to be core targets of ADI in alleviating leukopenia, and 2 of them (TP53 and VEGFA) were confirmed by biological experiments as regulatory targets of ADI in the treatment of PC. In conclusion, TCMIs in combination with chemotherapy, can improve clinical efficacy and safety in the treatment of pancreatic cancer. However, the overall evidence base is low, and large samples with multi-center RCTs are still needed to support further research findings. Aidi injection can alleviate leukopenia mainly by intervening in oxidative stress, regulating cell proliferation and apoptosis, and regulating the inflammatory response. The combined application of NMA, network pharmacology, and biological experiments provides a reference for clinical evaluation and mechanism of action exploration of other drugs.

Coronary artery disease (CAD) is a cardiovascular disease characterized by atherosclerosis, angiogenesis, thrombogenesis, inflammation, etc. Xintong granule (XTG) is considered a practical therapeutic strategy in China for CAD. Although its therapeutic role in CAD has been reported, the molecular mechanisms of XTG in CAD have not yet been explored. A network pharmacology approach including drug-likeness (DL) evaluation, oral bioavailability (OB) prediction, protein-protein interaction (PPI) network construction and analysis, and Gene Ontology term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses was used to predict the active ingredients, potential targets, and molecular mechanisms of XTG associated with the treatment of CAD. Molecular docking analysis was performed to investigate the interactions between the active compounds and the underlying targets. Fifty-one active ingredients of XTG and 294 CAD-related targets were screened for analysis. Gene Ontology enrichment analysis showed that the therapeutic targets of XTG in CAD are mainly involved in blood circulation and vascular regulation. KEGG pathway analysis indicated that XTG intervenes in CAD mainly through the regulation of fluid shear stress and atherosclerosis, the AGE-RAGE signaling pathway in diabetic complications, and the relaxin signaling pathway. Molecular docking analysis showed that each key active ingredient (quercetin, luteolin, kaempferol, stigmasterol, resveratrol, fisetin, gamma-sitosterol, and beta-sitosterol) of XTG can bind to the core targets of CAD (AKT1, JUN, RELA, MAPK8, NFKB1, EDN1, and NOS3). The present study revealed the CAD treatment-related active ingredients, underlying targets, and potential molecular mechanisms of XTG acting by regulating fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, and relaxin signaling pathway.

Gas chromatography–mass spectrometry (GC–MS) is widely used to separate, identify, and semi-quantify volatile and derivatizable semi-volatile constituents (mono-/sesqui-terpenoids, phenylpropanoids, fatty-acid derivatives) that carry the discriminatory chemical information needed for authentication and quality control of traditional Chinese medicinal materials (TCMMs). To frame the methodological landscape rather than merely list components, this synthesis draws on peer-reviewed GC–MS / HS‑SPME works mainly indexed in PubMed, Web of Science, and Scopus (focusing on the last decade), using searches built around keyword clusters (GC–MS, volatile oil, TCM authentication/QC, processing) and prioritizing studies that report separation conditions, pretreatment rationale, identification confidence (spectral match + retention index), and chemometric discrimination. The covered evidence shows GC–MS reliability depends less on instrument prestige than on upstream choices: pretreatment selectivity and thermal bias govern which labile markers survive; co-elution and matrix effects require explicit deconvolution/alignment; and identification confidence needs RI anchoring and, where possible, standard cross-checks, while inconsistent validation reporting and GC's intrinsic inaccessibility of strongly polar non-volatiles remain the main bottlenecks. When framed as a separation-first workflow—integrating optimized pretreatment (distillation/SPME/SFE), derivatization strategies, and multivariate modelling—GC–MS delivers verifiable chemical fingerprints to track geographical, batch, and processing-induced changes, supporting more comparable, regulation-ready QC protocols for TCMMs.