Hepatic fibrosis is the critical pathological stage in the progression of chronic liver disease to cirrhosis and hepatocellular carcinoma (HCC). However, no approved anti-hepatic fibrosis drugs are available currently. Qijia Rougan Formula (QRF) is a traditional Chinese medicine (TCM) with significant clinical efficacy on hepatic fibrosis. It was derived from Sanjiasan, a famous decoction documented in the Book of Treatise on the Pestilence in the Ming Dynasty of China. However, the underlying regulatory mechanisms remain elusive. This study further confirmed the therapeutic effects of QRF on hepatic fibrosis and dissected its underlying molecular mechanisms from the perspective of macrophage M2 polarization, one of the critical events in hepatic fibrosis. Experimentally, QRF significantly improved extracellular matrix (ECM) deposition and fibrosis in the liver of model rats. QRF diminished the proportion of M2 macrophages, decreased the levels of TGF-β, PDGFB and IL-10, and regulated the expression of p-JAK1, p-STAT6, JAK1 and microRNA-23a both in vitro and in vivo. Collectively, it was confirmed that QRF effectively improves liver function and hepatocyte damage, and reduces ECM deposition. QRF ameliorates hepatic fibrosis by regulating JAK1/STAT6-microRNA-23a negative feedback loop to inhibit macrophage M2 polarization and thus reduce ECM deposition. Our study illustrates the potential of QRF for hepatic fibrosis therapy, suggesting that QRF is a promising anti-hepatic fibrosis drug candidate.

Cholestatic liver disease (CLD) is a range of conditions caused by the accumulation of bile acids (BAs) or disruptions in bile flow, which can harm the liver and bile ducts. To investigate its pathogenesis and treatment, it is essential to establish and assess experimental models of cholestasis, which have significant clinical value. However, owing to the complex pathogenesis of cholestasis, a single modelling method can merely reflect one or a few pathological mechanisms, and each method has its adaptability and limitations. We summarize the existing experimental models of cholestasis, including animal models, gene-knockout models, cell models, and organoid models. We also describe the main types of cholestatic disease simulated clinically. This review provides an overview of targeted therapy used for treating cholestasis based on the current research status of cholestasis models. In addition, we discuss the respective advantages and disadvantages of different models of cholestasis to help establish experimental models that resemble clinical disease conditions. In sum, this review not only outlines the current research with cholestasis models but also projects prospects for clinical treatment, thereby bridging basic research and practical therapeutic applications.

Stomachache is not only disease name of Traditional Chinese medicine (TCM) but also the clinical symptom. It is a common and multiple diseases. TCM has its particular advantage in clinical treatment of stomachache. Syndrome differentiation is an important concept in TCM practice. The therapeutic process is virtually a nonlinear mapping process from clinical symptom to syndrome diagnosis with processing and seeking rules from mass data. Artificial neutral network has strong learning ability for nonlinear relationship. Artificial neutral network has been widely used to TCM area where the multiple factors, multilevel, nonlinear problem accompanied by a large number of optimization exist. We present an original experimental method to apply the improved third-order convergence LM algorithm to intelligent syndrome differentiation for the first time, and compare the predicted ability of Levenberg-Marquardt (LM) algorithm and the improved third-order convergence LM algorithm in syndrome differentiation. In this study, 2436 cases of stomachache electronic medical data from hospital information system, and then the real world data were normalized and standardized. Afterwards, LM algorithm and the improved third-order convergence LM algorithm were used to build the Back Propagation (BP) neural network model for intelligent syndrome differentiation of stomachache on Matlab, respectively. Finally, the differentiation performance of the 2 models was tested and analyzed. The testing results showed that the improved third-order convergence LM algorithm model has better average prediction and diagnosis accuracy, especially in predicting “liver-stomach disharmony” and “stomach yang deficiency”, is above 95%. By effectively using the self-learning and auto-update ability of the BP neural network, the intelligent syndrome differentiation model of TCM can fully approach the real side of syndrome differentiation, and shows excellent predicted ability of syndrome differentiation.

Background: Human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) immunological nonresponders (HIV/AIDS-INRs) whose CD4⁺ cell counts do not rebound after highly active antiretroviral therapy (HAART) treatment usually experience severely impaired immune function and high mortality. Traditional Chinese medicine (TCM) has many advantages in the field of AIDS, especially its promotion of patients’ immune reconstitution. Accurate differentiation of TCM syndromes is a prerequisite for guiding an effective TCM prescription. However, the objective and biological evidence for identification of the TCM syndromes in HIV/AIDS-INRs remains lacking. Lung and spleen deficiency (LSD) syndrome, a typical HIV/AIDS-INR syndrome, was examined on in this study. Methods: We first performed a proteomic study of LSD syndrome in INRs (INRs-LSD) using tandem mass tag combined with liquid chromatography-tandem mass spectrometry (TMT-LC-MS/MS) and screened them against the healthy and undocumented identifiable groups. The TCM syndrome-specific proteins were subsequently validated based on bioinformatics analysis and enzyme-linked immunosorbent assay (ELISA). Results: A total of 22 differentially expressed proteins (DEPs) were screened in INRs-LSD compared to the healthy group. Based on bioinformatic analysis, these DEPs were found to be mainly associated with the immunoglobin A (IgA)-generated intestinal immune network. In addition, we examined the TCM syndrome-specific proteins alpha-2-macroglobulin (A2M) and human selectin L (SELL) with ELISA and found that they were both upregulated, which was consistent with the proteomic screening results. Conclusions: A2M and SELL were finally identified as potential biomarkers for INRs-LSD, providing a scientific and biological basis for identifying typical TCM syndromes in HIV/AIDS-INRs and an opportunity to build a more effective TCM treatment system for HIV/AIDS-INRs.

Increasing interest is aroused by traditional Chinese medicine (TCM) treatment of chronic hepatitis B (CHB) based on specific TCM syndrome. As the most common CHB syndromes, spleen‐stomach dampness‐heat (SSDH) syndrome and liver‐gallbladder dampness‐heat (LGDH) syndrome are still apt to be confused in TCM diagnosis, greatly hindering the stable exertion of TCM effectiveness. It is urgently needed to provide objective and biological evidences for differentiation and identification of the two significant syndromes. In this study, microRNA (miRNA) microarray analyses coupled with bioinformatics were employed for comparative miRNA profiling of SSDH and LGDH patients. It was found that the two syndromes had both the same and different significantly differentially expressed miRNAs (SDE‐miRNAs). Commonness and specificity were also both found between their SDE‐miRNA‐based bioinformatics analyses, including Hierarchical Clustering, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and miRNA‐GO/pathway networks. Furthermore, syndrome‐specific SDE‐miRNAs were identified as the potential biomarkers, including hsa‐miR‐1273g‐3p and hsa‐miR‐4419b for SSDH as well as hsa‐miR‐129‐1‐3p and hsa‐miR‐129‐2‐3p for LGDH. All these laid biological and clinical bases for classification and diagnosis of the two significant CHB dampness‐heat syndromes including SSDH and LGDH, providing more opportunities for better application of TCM efficacy and superiority in CHB treatment.