Metabolic-associated fatty liver disease (MAFLD) is a prevalent chronic liver condition globally, characterized by suboptimal treatment outcomes. Traditional therapies often fail to address the multifaceted pathogenesis of MAFLD, which involves lipid metabolism, inflammation, and gut-liver axis dysregulation. JiGuCao Capsule formula (JCF), a patented Chinese medicine, has demonstrated clinical efficacy in liver disease treatment, indicating its potential as a new therapeutic option for MAFLD. This study aimed to investigate the therapeutic effects and underlying mechanisms of JCF in treating MAFLD, particularly focusing on its impact on liver pathology, intestinal health, and gut microbiota composition. A MAFLD mouse model was developed by administering a high-fat diet and 5% fructose water for 16 weeks. At week 8, mice exhibited significant steatosis, inflammation, and insulin resistance. Fifty mice were allocated into two groups: the normal diet (ND) group with 19 mice and the high-fat feed diet (HFD) group with 31 mice. Seven mice from each group were sacrificed at week 8 for serological and histopathological assessments. The remaining mice were allocated into ND (n = 6), HFD (n = 6), HFD + JCFL (human equivalent dose,780 mg/kg, n = 6), HFD + JCFH (threefold the human equivalent dose, 2340 mg/kg, n = 6), HFD + Polyene Phosphatidylcholine (PPC) (human equivalent dose,177.84 mg/kg, n = 6) and ND+ JCF (human equivalent dose,780 mg/kg, n = 6) groups. Daily gavage started at week 9. At week 16, after fasting, body weight and liver condition were recorded, and mice were euthanized with pentobarbital sodium. Mouse tissues and feces were collected for histopathological, molecular biological, and multi-omics analyses. JCF effectively slowed MAFLD progression in mice by decreasing hepatic lipid accumulation and inflammation. Treatment with JCF significantly reduced hepatic triglycerides and inflammatory markers, including TNF-α and IL-6. JCF enhanced lipid metabolism, repaired the intestinal barrier, and lowered inflammatory cytokines in the intestines, as indicated by reduced serum LPS and restored tight junction proteins expression, such as claudin-1 and occludin. Fecal microbiota analysis indicated that JCF treatment elevated Lactobacillus levels and reduced Colidextribacter levels, correlating with enhanced metabolic profiles. The primary bioactive compounds identified in JCF responsible for these therapeutic effects were betulinic acid, cholic acid, deoxycholic acid, oleanolic acid, and pectolinarigenin. Transcriptomic analysis showed that JCF regulated key pathways involved in lipid metabolism, including the pparγ-cd36 axis and modulation of ox-LDL levels. The results indicate that JCF effectively mitigates MAFLD by influencing the gut-liver axis and lipid metabolism. JCF alleviates MAFLD by modulating the gut-liver axis and lipid metabolism. Its effects involve improving gut barrier function, regulating microbiota, and targeting the pparγ-cd36 axis. Active compounds like betulinic acid support its therapeutic potential. JCF shows promise as a novel treatment for MAFLD, with further clinical studies needed.

With the general improvement in living standards in recent years, people’s living habits, including their dietary habits, have changed. More people around the world do not follow a healthy diet, leading to an increase in morbidity and even mortality due to digestive system diseases, which shows an increasing trend every year. The advantage of traditional Chinese medicine (TCM) in treating digestive system diseases is evident. Consequently, the mechanisms of action of single Chinese herbs and compound Chinese medicines have become the focus of research. The research method of the network pharmacology system was highly consistent with the holistic concept of TCM, and provided a new perspective and theoretical basis for basic research on digestive system diseases. This article summarizes the common databases currently used in research on TCM. It also briefly introduces the basic methods and technologies of network pharmacology studies. It also summarizes the advancements of network pharmacology technology through a comprehensive literature search on PubMed. Based on this analysis, we further explored the role of TCM in treating digestive system diseases, including chronic gastritis, gastric cancer, ulcerative colitis, and liver cirrhosis. This study provides new ideas and references for treating digestive system diseases with TCM in the future and serves as a reference for relevant researchers.

Hepatocellular carcinoma (HCC), one of the leading causes of cancer‑related mortality worldwide, is challenging to identify in its early stages and prone to metastasis, and the prognosis of patients with this disease is poor. Treatment options for HCC are limited, with even radical treatments being associated with a risk of recurrence or transformation in the short term. Furthermore, the multi‑tyrosine kinase inhibitors approved for first‑line therapy have marked drawbacks, including drug resistance and side effects. The rise and breakthrough of immune checkpoint inhibitors (ICIs) have provided a novel direction for HCC immunotherapy but these have the drawback of low response rates. Since avoiding apoptosis is a universal feature of cancer, the induction of non‑apoptotic regulatory cell death (NARCD) is a novel strategy for HCC immunotherapy. At present, NARCD pathways, including ferroptosis, pyroptosis and necroptosis, are novel potential forms of immunogenic cell death, which have synergistic effects with antitumor immunity, transforming immune ‘cold’ tumors into immune ‘hot’ tumors and exerting antitumor effects. Therefore, these pathways may be targeted as a novel treatment strategy for HCC. In the present review, the roles of ferroptosis, pyroptosis and necroptosis in antitumor immunity in HCC are discussed, and the relevant targets and signaling pathways, and the current status of combined therapy with ICIs are summarized. The prospects of targeting ferroptosis, pyroptosis and necroptosis in HCC immunotherapy are also considered.

Background: Hepatocellular carcinoma (HCC) is one of the most malignant tumors worldwide. The ST6 β-galactoside α-2, 6-sialyltransferase 1 (ST6GAL1) has been found aberrantly expressed in a variety of cancers including HCC, but its function and mechanism in regulating liver inflammation remain to be investigated. This study aimed to explore the role of ST6GAL1 in HCC. The data of ST6GAL1 expression, prognosis, and clinical parameters were collected and further analyzed from the public databases including The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), and Gene Expression Omnibus (GEO). The HCC rat model was constructed by intraperitoneal injection of diethylnitrosamine. The mRNA and protein expression levels of ST6GAL1 in rat liver tissues were detected by real-time quantitative polymerase chain reaction, capillary electrophoresis, and Western blot. Results: The ST6GAL1 mRNA and protein expression levels were both lower in HCC tissues compared with normal liver tissues in the public databases and HCC rat model. The survival analysis showed that upregulation of ST6GAL1 was an independent prognostic factor for good prognosis in HCC patients. The ST6GAL1 mRNA expression showed a negative correlation with ST6GAL1 methylation levels. Enrichment analysis showed that ST6GAL1 expression was most associated with metabolic, cancer, estrogen, axon guidance, cAMP, and PI3K-AKT signaling pathways. The ST6GAL1 mRNA expression negatively correlated with liver inflammation status and proportion of NK CD56bright, NK CD56dim, pDC, and CD8+ T cells in liver. Conclusion: Compared with normal tissues, ST6GAL1 was lower expressed in HCC tumor tissues, and the downregulation of ST6GAL1 was associated with a poor prognosis in HCC patients. ST6GAL1 could further affect the infiltration of immune cells to exert anti-inflammation function in liver. Our study indicated that ST6GAL1 could be a potential biomarker and therapeutic target to assess the prognosis and regulate the immune cells infiltration level of HCC.

Background: Natural killer (NK) cells are a type of innate immune cell that recognize and eliminate tumor cells and infected cells, without prior sensitization or activation. Herein, we aimed to construct a predictive model based on NK cell-related genes for hepatocellular carcinoma (HCC) patients and assess the feasibility of utilizing this model for prognosis prediction.Methods: Single-cell RNA-seq data were obtained from the Gene Expression Omnibus (GEO) database to identify marker genes of NK cells. Univariate Cox and lasso regression were performed to further establish a signature in the TCGA dataset. Subsequently, qPCR and immunohistochemistry (IHC) staining were employed to validate the expression levels of prognosis signature genes in HCC. The effectiveness of the model was further validated using two external cohorts from the GEO and ICGC datasets. Clinical characteristics, prognosis, tumor mutation burden, immune microenvironments, and biological function were compared for different genetic subtypes and risk groups. Finally, molecular docking was performed to evaluate the binding affinity between the hub gene and chemotherapeutic drugs.Results: A total of 161 HCC-related NK cell marker genes (NKMGs) were identified, 28 of which were significantly associated with overall survival in HCC patients. Based on differences in gene expression characteristics, HCC patients were classified into three subtypes. Ten prognosis genes (KLRB1, CD7, LDB2, FCER1G, PFN1, FYN, ACTG1, PABPC1, CALM1, and RPS8) were screened to develop a prognosis model. The model not only demonstrated excellent predictive performance on the training dataset, but also were successfully validated on two independent external datasets. The risk scores derived from the model were shown to be an independent prognosis factor for HCC and were correlated with pathological severity. Moreover, qPCR and IHC staining confirmed that the expression of the prognosis genes was generally consistent with the results of the bioinformatic analysis. Finally, molecular docking revealed favorable binding energies between the hub gene ACTG1 and chemotherapeutic drugs.Conclusion: In this study, we developed a model for predicting the prognosis of HCC based on NK cells. The utilization of NKMGs as innovative biomarkers showed promise in the prognosis assessment of HCC.