HHQG ameliorates acute liver injury (ALI) by inhibiting NLRP3 activation through RASD1-mediated regulation of the PKCδ-NF-κB signaling pathway

Abstract

Acute liver injury (ALI) is a prevalent hepatic condition that poses significant risks to both life and overall health. Traditional Mongolian medicine utilizes Honghua Qinggan Thirteen-Flavor Pills (HHQG) as a primary formula for dispelling liver heat, illustrating both an extensive application in clinical settings and notable therapeutic effectiveness for treating liver ailments such as hepatitis and liver failure. Nevertheless, the molecular mechanisms underpinning the hepatoprotective properties of HHQG remain inadequately understood.We employed a CCl₄-induced mouse model of liver injury alongside network pharmacology analysis, molecular docking studies, and cellular assays to dissect the effects and mechanisms of action of HHQG. Our findings demonstrated that HHQG significantly improved CCl₄-induced liver injury in mice, reducing pathological damage and inflammatory factors. Network pharmacology identified 184 overlapping targets, 6 key genes, and 5 key active components in HHQG. Molecular docking confirmed the binding affinity of these components to RASD1. Gene expression analysis in liver tissue revealed a positive correlation between mRNA expression of RASD1 and NLRP3. Cell experiments demonstrated the role of RASD1 in regulating NLRP3 inflammasome and inflammatory factors. Pretreatment of HHQG attenuated LPS-induced inflammatory response and the activation of PKCδ-NF-κB signaling pathway. In the CCl₄-induced liver injury model, HHQG significantly reduced NLRP3, RASD1, and PKCδ-NF-κB expression.This study revealed that HHQG effectively mitigates CCl₄-induced liver injury by inhibiting the activation of NLRP3 inflammasome by regulating the PKCδ-NF-κB signaling pathway via RASD1. These findings provide novel theoretical support for the rational application of HHQG as a potential hepatoprotective agent.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-24410-z.

Introduction

Acute liver injury (ALI) is a common hepatic disease that poses a serious threat to life and health, and its incidence has gradually risen in recent years, thus becoming a crucial research focus in liver diseases. This disease typically manifests as extensive cellular necrosis and apoptosis, accompanied by severe inflammatory responses^1,2. ALI can be triggered by many factors, including viral infections, drug abuse, and alcohol consumption^3,4. According to statistics, the incidence and mortality rates of ALI vary significantly among different populations, which is closely related to epidemiological factors and patients’ underlying conditions. However, despite various treatment modalities available in clinical practice, the management of ALI faces certain limitations, including insufficient specificity and potential adverse effects^5–7. This makes the identification of novel and effective therapeutic targets both a research hotspot and a significant challenge.

Liver injury is often accompanied by intense inflammatory responses, and macrophages play an important role as key initiators and modulators of inflammatory signals in this process⁸. When drugs or their metabolites induce liver injury, macrophages are swiftly activated, releasing substantial inflammatory mediators (such as TNF-α and IL-6). These mediators not only damage hepatocytes directly but also recruit other immune cells to the site of injury, thus further amplifying the inflammatory response⁹. Also, macrophages can modulate the intensity and duration of inflammation by secreting anti-inflammatory cytokines such as IL-10, thereby maintaining hepatic homeostasis. These characteristics make macrophages an important cellular model for investigating ALI and its associated inflammatory responses.

Within macrophages, the NLRP3 inflammasome works as a critical mechanism regulating inflammatory responses. NLRP3 can recognize different pathogen and cellular damage signals and promote the release of inflammatory mediators¹⁰, thus playing an important role in the progression of ALI. Upon activation of the NLRP3 inflammasome, the release of pro-inflammatory cytokines further contributes to the body’s immune modulation, which is essential for the occurrence and progression of pyroptosis and inflammation^11–14. However, the specific role of NLRP3 in ALI and its relationship with existing therapeutic approaches still require extensive investigation.

Currently, while various hepatoprotective agents have been employed in diagnostic and therapeutic practice, traditional indigenous medicines are particularly noteworthy and demonstrate unique therapeutic potential. The Mongolian medicine formula—Honghua Qinggan 13 Flavor Pills (HHQG)—has achieved remarkable therapeutic efficacy in treating various liver diseases, although its specific mechanisms remain to be investigated. Studies have shown that the hepatoprotective effects of HHQG may be associated with its antioxidant activity, inhibition of the JNK/c-Jun signaling pathway, and regulation of the FasL/Fas signaling pathway for cell apoptosis¹⁵. In addition, HHQG may exert further protective effects by regulating the balance between matrix metalloproteinase (MMP-1) and its inhibitor (TIMP-1), suppressing lipid peroxidation, and modulating liver fibrosis¹⁶. Preliminary investigations have indicated that HHQG significantly inhibited the infiltration of monocytes/macrophages following CCl₄-induced liver injury¹⁷, demonstrating its potential to mitigate inflammatory responses.

In recent years, research on the ras-related dexamethasone induced 1 (RASD1) has attracted increasing attention. Located on chromosome 17p11.2, RASD1 is an activator of G protein signaling that has been demonstrated to be associated with metabolic disorders such as insulin resistance and metabolic associated fatty liver disease (MAFLD)^18,19. However, the precise role of RASD1 in liver injury, particularly its regulatory mechanism in NLRP3 inflammasome activation and subsequent cell death, remains unclear. Therefore, an in-depth investigation into how RASD1 promotes NLRP3-mediated pyroptosis, as well as its potential impact on ALI, will provide new insights for treating hepatic diseases.

Given the pressing need to explore more effective therapeutic strategies, this study aims to systematically evaluate the impact of RASD1 on NLRP3-mediated inflammatory responses, which subsequently exacerbate liver injury. In addition, we employ a multifaceted approach combining network pharmacology, molecular docking, as well as cellular and animal experiments to thoroughly investigate the mechanisms underlying HHQG’s mechanism of action in this process. This research seeks to provide new theoretical foundations and potential clinical solutions for the prevention and treatment of ALI. This study is expected to offer fresh perspectives on the application of ethnic medicine in modern medical practice and pave the way for developing innovative hepatoprotective agents.

Materials and methods

Materials

Preparing HHQG water pills

We have obtained information through World Flora Online (www.worldfloraonline. org) or MPNS ( http://mpns.kew.org ) checked the plant name. The formula for HHQG comprises 13 ingredients: safflower, cloves, lotus seeds, ophiopogon, costus root, chebulic myrobalan, Szechwan Chinaberry Fruit, gardenia, red sandalwood, musk, water buffalo horn, bezoar and vermilion. The specific details can be found in Table S1 attached. Except for musk and vermilion, the remaining 11 ingredients need processing, while vermilion is prepared through levigation. After processing, the medicinal materials are pulverized, sieved, and mixed, then musk is added for blending. The amount of powder is calculated according to the mold. The power is rolled into pills after moistening, then dried to 0.2 g per pill, completing the water-milled pill preparation. Finally, with the vermilion prepared, the pills are coated, polished, and stored.

Reagents and instruments

Carbon tetrachloride (Aladdin, C112044), olive oil (Macklin, O815210), AST/GOT activity kit (Nanjing Jiancheng Bioengineering Institute, China, C010-2–1), ALT/GPT activity kit (Nanjing Jiancheng Bioengineering Institute, China, C009-2–1), paraformaldehyde (Biosharp, BL539A), adhesive slides (Jiangsu Shitai Laboratory Equipment Co., Ltd., 80,312–3161), standard coverslips (Jiangsu Shitai Laboratory Equipment Co., Ltd., 80,340–0130), Masson’s trichrome staining kit (Solarbio, G1340), hematoxylin solution (BASO, BA4097), eosin solution (BASO, BA4098), anti-NLRP3 antibody (Bioss, bs-10021r), anti-GSDMD antibody (Abcam, ab219800), anti-RASD1 antibody (Santa Cruz, sc-398988), anti-RASD1 antibody (Proteintech, 12,634–1-AP), anti-IκB-α antibody (Abmart, T55026), anti-PKCδ antibody (Abcam, ab182126), anti-β-actin antibody (LABLEAD, A0101-1), goat anti-mouse IgG HRP (LABLEAD, S0100-1), PBS powder (Fuzhou Maixin Biotech Co., Ltd., PBS-0060), antigen retrieval solution (Fuzhou Maixin Biotech Co., Ltd., MVS-0099), citrate buffer for antigen retrieval (Fuzhou Maixin Biotech Co., Ltd., MVS-0101), DAB chromogenic kit (Fuzhou Maixin Biotech Co., Ltd., DAB-0031), ready-to-use immunohistochemistry Elivision Super kit (Fuzhou Maixin Biotech Co., Ltd., KIT-9922), non-immune goat serum (Fuzhou Maixin Biotech Co., Ltd., SP KIT-B3), antibody diluent (Fuzhou Maixin Biotech Co., Ltd., ABD-0030), 3% hydrogen peroxide (Zhongbei Gankong Medical Technology Co., Ltd., 371402ZBGK034), RNAiso Plus (Takara, Japan, 9109), chloroform (Aladdin, C109593), FastKing one-step gDNA removal and cDNA synthesis kit (Tiangen Biotech Co., Ltd., Beijing, China, KR118), FastReal qPCR kit (SYBR Green) (Beijing Tiangen Biotech Co., Ltd., FP217), PVDF membrane (Immobilon®, IPVH00010), fetal bovine serum (WILBER, FBS-SaHu-500), DMEM (Gibco, C11965500BT), LPS (Sigma-Aldrich, L2880), Cell Counting Kit-8 (LABLEAD, CK001), RASD1 overexpression vector and interference knockdown (Suzhou Genepharma Co.,Ltd., D02001), siRNA-mate plus transfection reagent (Suzhou Genepharma Co.,Ltd., G04036), Lipofectamine 3000 reagent (LABLEAD, TR002), IL-1β ELISA kit (Jiangsu Jingmei Biotechnology Co., Ltd., JM-02323M1), IL-6 ELISA kit (Jiangsu Jingmei Biotechnology Co., Ltd., JM-02446M1), TNF-α ELISA kit (Jiangsu Jingmei Biotechnology Co., Ltd., JM-02415M1).Tribromoethanol for ready use (MeilunBio , MA0478).

Automated rotary microtome (Leica, Germany), paraffin embedding station (Leica, Germany), slide warmer (Leica, Germany), tissue flotation bath (Leica, Germany), upright microscope (Leica, Germany), fluorescence microscope (Leica, Germany), mini centrifuge (OHAUS, USA), Refrigerated microcentrifuge (Thermo Fisher Scientific, USA), ice maker (Panasonic, Japan), -80 °C ultra-low temperature freezer (Panasonic, Japan), water purification system (Merck Millipore, USA), magnetic stirrer (Yiheng Technology, Shanghai), real-time qPCR (ABI, USA), thermal cycler (Analytik Jena, Germany), low-temperature incubator for shakers (FMC-1000, Japan), high-performance centrifuge (Beckman Coulter, USA), high-speed refrigerated centrifuge (Eppendorf, Germany), automated intelligent staining machine (Shenzhen Dakewe Medical Equipment Co., Ltd., China), multi-mode microplate reader (SpectraMax i3x, USA), mini vertical electrophoresis system (BIO-RAD, USA), electrophoresis system (BG-Power 600, China), CO₂ incubator (Eppendorf, Germany), automated cell counter (Life Technologies, Singapore), micropipettes (Eppendorf, Germany).

Methods

Target prediction and network pharmacology analysis of chemical components in HHQG

To evaluate the pharmacological effects of HHQG in treating liver injury and explore its potential targets, we employed network pharmacology analysis to predict targets for 747 chemical components isolated in our previous research (Wang et al., 2022). We then screened for potential targets associated with “liver injury” and “inflammation” to reveal its mechanism of action.

Target gene screening

In network pharmacology, accurately identifying disease-related target genes is fundamental for network construction and exploring potential mechanisms. This study employed a retrieval strategy combining different databases to ensure the comprehensiveness and reliability of target genes. Specifically, GeneCards, DrugBank, and OMIM were used to screen for potential target genes associated with liver injury and inflammation. In order to construct a complete and non-redundant dataset of target genes, these data were integrated and deduplicated. The obtained sets of target genes laid the foundation for subsequent analysis and contributed to understanding the mechanism of action of HHQG in treating these diseases.

Screening of overlapping targets

By combining the targets of HHQG with those related to liver injury and inflammation, we imported them into the software for analyzing the Venn diagram. The intersection analysis of the Venn diagram can help identify co-expressed hub targets between HHQG and liver injury and inflammation. These overlapping targets may represent important therapeutic targets for the effects of HHQG.

Constructing the network of the drug, active components, and targets

In order to investigate the interactions among active components, targets, and genes, Cytoscape 3.9 was used to construct a visualized network diagram. In addition, network characteristics were analyzed to identify key components related to liver injury and inflammation. The degree values of the components were ranked using the Network Analyzer function, and components with higher degree values are considered potential key active components.

Molecular docking

This study employed molecular docking to evaluate the binding affinity between active components in HHQG and targets. Based on the integration of the protein data bank (PDB) and ligand database (PubChem), analysis was conducted using PyMol, Chem3D, and Autodock. The crystal structure of RASD1 was selected from the PDB database, and ligands of key active components in HHQG were chosen from PubChem. PyMol was used for processing target proteins, while Chem3D was used to optimize the 3D structure of ligands, remove hydrogen atoms, and generate suitable file formats for docking. Subsequently, Autodock 4.4.6 was used for further preprocessing of targets, and AutoDock Vina was employed to calculate the binding energy between each target protein and ligand. The docking pose with the lowest binding energy and optimal mode was selected. Finally, PyMol was used to visually analyze the binding modes and interaction interfaces between ligands and target proteins, and ligands that could potentially serve as effective targets for treating liver injury and inflammation were selected.

Animal grouping and modeling

45 C57BL/6 mice (male, 6–8 weeks old, 20–22 g) were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. (China). The license number is SCXK (Beijing) 2021–0006, and the certificate number of animal quality is 110,011,241,106,067,472. The mice were housed in the Animal Center of Inner Mongolia Medical University under conditions set at 23 ± 3 °C, humidity of 60 ± 10 RH%, air exchange rate of 40.1 ACH, pressure difference of 10 Pa, and a 12/12 light/dark cycle. This study was approved by the Animal Research Ethics Committee with the approval number 2022DW258, and animal care and handling followed the guidelines issued by the Ethics Committee of Inner Mongolia Medical University.

After one week of acclimatization, the mice were randomly divided into control group, model group, and HHQG (treatment) group, with 15 mice in each group. The HHQG group was administered HHQG (0.6165 g/kg) by gavage once daily for 7 consecutive days ¹⁷. In addition, the control and model groups were given an equal volume of saline. Four hours after the gavage on the last day, the model group and HHQG group received a single intraperitoneal injection of CCl₄ mixture (olive oil : CCl₄ = 4:1) at a dose of 0.1 mL/(10 g·BW), while the control group received an intraperitoneal injection of the same dose of olive oil. On day 2, day 5, and day 7 after CCl₄ injection, 5 mice from each group were euthanized, and samples were collected and stored at -80 °C. Before euthanasia is carried out, C57BL/6 mice are first anesthetized to ensure complete loss of consciousness. C57BL/6 mice are anesthetized by intraperitoneal injection of 1.25% tribromoethanol at a dose of 0.3 ml per 10 g of body weight. After confirming deep anesthesia, euthanasia is performed by cervical dislocation in accordance with the guidelines approved by the Ethics Committee of Inner Mongolia Medical University and international animal welfare standards, to minimize pain and discomfort.

In vitro cell grouping and modeling

RAW264.7 cells were cultured in DMEM supplemented with 10% fetal bovine serum in an incubator (37 °C and 5% CO₂). When the confluency reached over 80%, cells were digested and evenly plated. The control group received no treatment, the model group was treated with 1000 ng/ml LPS for 24 h, and the HHQG group was treated with 100 μg/ml HHQG for 12 h, followed by 1000 ng/ml LPS for 24 h. For siRNA and miRNA groups, knockdown and the transfections for overexpression were performed first. After 24 h, the CON siRNA and CON miRNA groups received no further treatment, the model siRNA and model miRNA groups were treated with 1000 ng/ml LPS for 24 h, and the HHQG siRNA and HHQG miRNA groups were first treated with 100 μg/ml HHQG for 12 h, and then followed by 1000 ng/ml LPS for 24 h. For all groups, supernatants were collected, and RNA was extracted 24 h after treatment, while proteins were extracted and preserved 48 h after treatment for analysis.

RASD1 overexpression/constructing knockout system

RAW264.7 macrophages were seeded in 6-well plates and cultured for 24 h at 37 °C with 5% CO₂. Following standard transfection protocols, cells were transfected with RASD1-specific siRNA or RASD1 overexpression plasmid.

ALT and AST test and histopathological staining

Mouse blood was centrifuged at 3,000 rpm for 15 min at 4 °C to obtain serum. Commercial AST/GOT activity kit and ALT/GPT activity kit were used to detect ALT and AST activity according to the instructions.

Liver tissues were fixed overnight in 4% paraformaldehyde, embedded in paraffin, and sectioned at 4 μm. H&E staining was used to illustrate the degree of injury. Masson’s trichrome staining was used to demonstrate how severe collagen deposition is.

Proteomic analysis

Liver tissues from the control, model, and HHQG groups were collected and ground in liquid nitrogen to maintain sample stability. The ground samples were separately added to appropriate amounts of SDT lysis buffer (sodium dodecyl sulfate-detergent) and transferred to centrifuge tubes (EP tubes). Samples were treated in a boiling water bath for 3 min, then sonicated at 4 °C for 2 min using an ultrasonic disruptor. Centrifugation was performed at 16,000 g for 20 min, and the supernatant was collected for subsequent analysis. The BCA assay was used to determine the total protein concentration in each sample. Protein samples were sent to Shanghai Bioprofile for DIA proteomics. Spectronaut software was used to integrate mass spectrometry data, perform database searches, and conduct DIA quantitative analysis of proteins. The database used was Uniprot Mus musculus (Mouse)[10090]-87552 20,240,325.fasta, available at https://www.uniprot.org/10090. Differentially expressed proteins (DEPs) were determined based on the criterion of |FC|≥ 1.2. DAVID was used for GO and pathway analysis of DEPs, and the parameters were set to count = 2 and ease = 0.05. For continuous data, the test for homogeneity of variance was performed. If data met homogeneity of variance, ANOVA was used for comparison; if not, non-parametric tests were employed. Differences were considered significant if p < 0.05.

Immunohistochemistry

Liver tissues were fixed overnight in 4% paraformaldehyde, embedded in paraffin, and sectioned at 4 μm thickness. Sections were baked at 65 °C for over 2 h to enhance tissue adhesion. After rehydration, sections were washed three times with PBS buffer for 5 min each, then subjected to heat-induced antigen retrieval for 4 min. Subsequently, these sections underwent natural cooling at room temperature and were washed again three times with PBS buffer (as above). After antigen retrieval, endogenous peroxidase activity was blocked with 3% H₂O₂ for 15 min and followed by 3 PBS buffer washes (as above). After that, sections were blocked with 5% bovine serum albumin (BSA) at room temperature for 45 min to reduce non-specific binding. Primary antibodies against NLRP3 (1:200), GSDMD (1:500), RASD1 (1:200), and PKCδ (1:2000) were then applied and incubated overnight at 4 °C, followed by 3 PBS buffer washes (as above). Sections were incubated with a ready-to-use IHC kit for 15 min, followed by 3 PBS buffer washes (as above). After color development using a DAB substrate kit, sections were counterstained, mounted with neutral balsam, and observed and photographed under a microscope.

RT-qPCR

Total RNA was extracted from liver tissues and RAW264.7 cells using Trizol, then reverse transcribed to cDNA using the FastKing One-Step gDNA Removal and cDNA Synthesis Kit. PCR was performed using the FastReal qPCR kit and StepOnePlus Real-Time PCR Systems. All procedures followed the manufacturer’s instructions, and β-actin was used as the internal reference gene. Relative changes in gene expression were calculated using the 2 − ΔΔCT method. Primer sequences are listed in Table 1.

Table 1.

primer sequence.

Gene name	Forward Primer	Reverse Primer
TNF-α	CCCTCACACTCAGATCATCTTCT	GCTACGACGTGGGCTACAG
IL-6	CCAAGAGGTGAGTGCTTCCC	CTGTTGTTCAGACTCTCTCCCT
IL-1β	GCAACTGTTCCTGAACTCAACT	ATCTTTTGGGGTCCGTCAACT
CCL2	TTAAAAACCTGGATCGGAACCAA	GCATTAGCTTCAGATTTACGGGT
NLRP3	CAAGGCTGCTATCTGGAGGAA	TGCAACGGACACTCGTCATC
ASC	ACTGTGCTTAGAGACATGGGC	TGGTCCACAAAGTGTCCTGTT
Caspase-1	CTATGGACAAGGCACGGGAC	TCAGCTGATGGAGCTGATTGA
RASD1	CCTCTCTATCCTCACAGGAGAC	CTCTTCGAATGAGTCGCGG
GSDMD	ATGCCATCGGCCTTTGAGAAA	AGGCTGTCCACCGGAATGA
IL-18	TCCAACTGCAGACTGGCAC	GGCAGGAGTCCAGAAAGCAT
NF-κB	ATGGCAGACGATGATCCCTAC	TGTTGACAGTGGTATTTCTGGTG
PKCδ	CCTCCTGTACGAAATGCTCATC	GTTTCCTGTTACTCCCAGCCT
β-actin	GGCTGTATTCCCCTCCATCG	CCAGTTGGTAACAATGCCATGT

Western blotting

Total protein was extracted from liver tissues and RAW264.7 cells, separated by SDS-PAGE, and transferred to PVDF membranes. Membranes were blocked with TBS solution containing 5% skimmed milk powder at room temperature for 90 min. Primary antibodies (i.e., NLRP3 1:200, GSDMD 1:500, RASD1 1:100, IκB-α 1:500, PKCδ 1:1000, and internal reference β-actin 1:1000) were diluted in TBS solution containing 1% skimmed milk powder. Membranes were incubated with diluted primary antibody solutions overnight at 4 °C. HRP-conjugated secondary antibodies were diluted (1:1000) in TBS solution containing 1% skimmed milk powder and incubated at room temperature for 1 h. Subsequently, DAB chromogen was used for color development.After color development was completed, the blot strips were photographed with a cell phone and subsequently image processed using Photoshop 24.0.0 software.

CCK8 assay

RAW264.7 cells were cultured in 96-well plates at 5,000 cells/well for 12 h and then treated with different concentrations of HHQG/LPS (10 μl) for 12 h/24 h. After that, CCK8 reagent (10 μl) was added, and OD values at 450 nm were measured after 4 h/2 h.

ELISA assay

Cell supernatants were collected, and commercial ELISA kits were used to test the expression of inflammatory factors IL-1β, IL-6, and TNF-α.

Statistical analysis

GraphPad Prism 9 (GraphPad Software, CA, USA) was used for correlation and statistical analysis. p < 0.05 was considered statistically significant. Data are presented as mean ± SD of three experimental replicates.

Results

Protective effects of HHQG on liver-injured mice

Weight gain in the model group (with CCl₄-induced injury) was significantly lower than in the control group (p < 0.01), while weight gain in the HHQG treatment group was significantly higher than that in the model group (p < 0.01) (Fig. 1A). Pathological analysis revealed significant damage to the liver lobule in the model group after 2 days accompanied by massive inflammatory cell infiltration and collagen deposition. As the injury progressed to day 5 and day 7, inflammation and collagen deposition were somewhat alleviated. The HHQG group significantly inhibited liver injury as early as day 2 after treatment, and liver injury essentially recovered by day 7, indicating no signs of inflammatory response (Figs. 1B, C). Serological analysis indicated that ALT and AST activity increased significantly 2 days after CCl₄ treatment (p < 0.001), while HHQG significantly reduced these two indicators (p < 0.05). Although AST levels continued to rise in the model group 5 and 7 days post-injury, no significant changes were observed in the HHQG group, indicating that HHQG’s preventive effect was optimal in the early stages of liver injury (Figs. 1D, E). In addition, levels of inflammatory factors, such as CCL2, IL-6, and TNF-α, significantly increased 2 days after CCl₄ injury (p < 0.01) and continued to increase at day 5. Although they decreased at day 7, CCL2 and TNF-α remained higher than the control group (p < 0.05). The levels of inflammatory factors in the HHQG group were significantly lower than those in the model group at all time points (p < 0.05) (Figs. 1F-H).

Fig. 1.

HHQG alleviates CCl4-induced liver injury in mice. (A) Changes in body weight following CCl₄-induced liver injury. (B) Histopathological changes in liver tissue observed by H&E trichrome staining (200 ×). (C) Histopathological changes in liver tissue observed by Masson’s trichrome staining (200 ×). (D) Serum ALT activities. (E) Serum AST activities.Data are presented as mean ± SD from three independent experiments.(F) mRNA expression of IL-6 in liver tissue. (G) mRNA expression of TNF-α in liver tissue.(H) mRNA expression of CCL2 in liver tissue.Data are presented as mean ± SD from three independent experiments. (I) mRNA expression of RASD1 in liver tissue(*p < 0.05, **p < 0.01, ***p < 0.001, ns indicates no significant difference.)

RASD1 expression in the model group significantly increased on day 2 after injury and remained elevated through day 5 and day 7 (p < 0.001). In contrast, RASD1 expression in the HHQG group was significantly lower than the model group at the same time points (p < 0.05) and further decreased by day 7, suggesting that the repair of liver injury was near completion (Fig. 1I). These findings indicate that HHQG demonstrates significant preventive effects in the early stages of liver injury (day 2), and it possibly exerts its protective effects against liver injury by modulating inflammatory responses through RASD1.

Network pharmacology analysis of chemical components in HHQG for treating liver injury and inflammation

To further investigate the effects of HHQG in alleviating liver injury, we conducted the following network pharmacology analysis using 76 active components of HHQG¹⁷ .

Screening of liver injury and inflammation targets

Inflammation is a crucial factor in the progression of liver injury. Therefore, we searched GeneCards, DrugBank, and OMIM using "Drug-Induced Acute Liver Injury" and “inflammation” as keywords to construct target datasets for Drug-Induced Acute Liver Injury and inflammation. We obtained 2 target sets, and after removing duplicate targets, 1993 disease targets were acquired (Table S2).

Overlapping target screening

The 511 regulatory targets of chemical components in HHQG overlapped with 1993 targets of liver injury and inflammation, and 184 overlapping targets were obtained (Fig. 2A).

Fig. 2.

Overlapping target screening and network construction for HHQG in treating liver injury and inflammation. (A) Venn diagram illustrating overlapping targets between targets of HHQG’s chemical components identified in vitro and those of livery injury and inflammation.(B) Network analysis of HHQG’s active chemical components, key targets, and liver injury/inflammation pathways in vitro.

Constructing the network of HHQG-active components-overlapping targets

A network of HHQG, its active components, and overlapping targets for treating liver injury and inflammation was constructed. This network comprises 184 overlapping targets interconnected with active component nodes. The network includes 76 active components, 261 nodes, and 826 edges. An analysis of degree values identified the top 5 active components: Quercetin, Genistein, Apigenin, Emodin, and Kaempferol, which were considered key components for subsequent molecular docking (Fig. 2B).

Molecular docking of active components in HHQG with RASD1

To verify the binding between the main active components and RASD1, we conducted molecular docking analysis using the 5 key active components screened from the above results: Quercetin, Genistein, Apigenin, Emodin, and Kaempferol with RASD1. The results indicated good binding between all 5 components and RASD1. (Table 2, Figs. 3A–E) This result suggests that the active components of HHQG may have protective effects on the liver by binding to RASD1.

Table 2.

Binding energy data of HHQG key active ingredients and RASD1.

NO	PubChem CID	Test compounds	Affinity
1	5,280,343	Quercetin	−9.9
2	5,280,443	Apigenin	−9.5
3	5,280,863	Kaempferol	−9.5
4	5,280,961	Genistein	−9.0
5	3220	Emodin	−8.3

Fig. 3.

Molecular docking analysis of key active components in HHQG with RASD1. (A)Molecular docking of RASD1 with Quercetin.(B) Molecular docking of RASD1 with Genistein.(C) Molecular docking of RASD1 with Apigenin.(D) Molecular docking of RASD1 with Emodin.(E) Molecular docking of RASD1 with Kaempferol. (In the figures of molecular docking, the stick model represents the active molecule, the red stick structure shows the carbon skeleton of the small-molecule ligands, the green parts are amino acid residues, and the yellow dashed lines indicate chemical bonds formed between active components and amino acid residues.)

Cell experiments to study HHQG regulation of RASD1 expression affecting NLRP3-mediated inflammatory response

Determining the optimal concentration of HHQG

The anti-inflammatory effects and mechanisms of the HHQG on LPS-induced RAW264.7 macrophages. First, the CCK-8 assay was used to evaluate the effects of HHQG and LPS on the viability of RAW264.7 macrophages to determine the optimal concentration. The experiment indicated that the viability of RAW264.7 cells significantly decreased when the concentration of HHQG exceeded 200 μg/ml (p < 0.01). Therefore, 50 μg/ml, 100 μg/ml, and 200 μg/ml were selected as the concentrations for subsequent experiments (Fig. 4A).

Fig. 4.

Optimization of HHQG concentration and construction of RASD1-silenced and overexpressed RAW264.7 cell models for studying inflammatory response regulation. (A) Cell viability of Raw264.7 cells under different concentrations of HHQG. (B) Cell viability of Raw264.7 cells under different concentrations of LPS. (C) Cell viability of Raw264.7 cells under different concentrations of HHQG after LPS treatment. (D) Changes in the mRNA expression of RASD1 after its overexpression in Raw264.7 cells. (E) Changes in the mRNA expression of RASD1 at different sites following RASD1 knockdown in Raw264.7 cells. (siRASD1 is the RASD1-knockdown group, and miRASD1 is the RASD1-overexpression group) (Data are presented as mean ± SD from three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001, and ns indicates no significant difference.)

In determining the effect of LPS on cell proliferation, after adding different concentrations of LPS, the results indicated that at 1000 ng/ml, cell proliferation decreased to about 50%. Therefore, 1000 ng/ml LPS was selected as the condition for subsequent experiments to simulate moderate inflammatory response and reduce cytotoxicity (Fig. 4B).

In determining the optimal concentration of HHQG, RAW264.7 cells were cultured under different concentrations of HHQG (50 μg/ml, 100 μg/ml, 200 μg/ml) for 12 h, followed by treatment with 1000 ng/ml LPS for 24 h to induce an inflammatory response. The results indicated that at 100 μg/ml of HHQG, cell proliferation reached its maximum. Therefore, 100 μg/ml HHQG was selected for subsequent studies to further explore its mechanism in alleviating inflammatory response (Fig. 4C).

Constructing RAW264.7 cell models with silenced and overexpressed RASD1

To investigate the role of RASD1 in NLRP3 inflammasome and its mediated inflammatory response, we constructed RAW264.7 cell models with silenced and overexpressed RASD1. Target gene expression was determined by qPCR. Results indicated that in the RASD1-silencing group, RASD1 expression at site 149 was significantly reduced (p < 0.01), thus confirming this site as an effective gene-silencing target. Conversely, in the RASD1 overexpression group, RASD1 expression was significantly increased (Figs. 4D, E).

Inhibitory effect of HHQG on LPS-induced inflammatory response and the impact of changes in RASD1 expression on NLRP3 inflammasome

We investigated the regulatory role of HHQG in LPS-induced inflammatory response and the effect of changes in RASD1 expression on NLRP3 inflammasome and its downstream inflammatory factors. Results indicated that under LPS, expression of inflammatory factors, key components of NLRP3 inflammasome, downstream inflammatory factors, and GSDMD were significantly upregulated. When RASD1 was knocked down, gene expression of inflammatory factors (IL-1β, IL-6, TNF-α, CCL2), and key components of NLRP3 inflammasome (NLRP3, ASC, and caspase-1) were significantly downregulated, accompanied by notable downregulation of downstream inflammatory factors IL-1β and IL-18. Conversely, when RASD1 was overexpressed, the expression of these genes was significantly upregulated. However, with HHQG pretreatment, significant reductions in the components of NLRP3 inflammasome, downstream inflammatory factors, and GSDMD expression were observed regardless of RASD1 knockdown or overexpression. The results of Western blotting also confirmed these findings (Figs. 5A, B, 6A-F, 7A-F, and 8A, B).

Fig. 5.

Effect of RASD1 expression on NLRP3 mRNA levels in LPS-induced RAW264.7 macrophages. (A) Changes in NLRP3 mRNA expression levels following RASD1 overexpression in Raw264.7 cells. (B) Changes in NLRP3 mRNA expression levels at different RASD1 knockdown sites in Raw264.7 cells. (siRASD1 is the RASD1-knockdown group, and miRASD1 is the RASD1-overexpression group) (Data are presented as mean ± SD from three independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001, and ns indicates no significant difference.)

Fig. 6.

Effect of RASD1 expression on inflammatory factor mRNA and protein levels in LPS-induced RAW264.7 macrophages. (A) mRNA expression of CCL2 in Raw264.7 cells following RASD1 knockdown and overexpression. (B) mRNA expression of IL-6 in Raw264.7 cells following RASD1 knockdown and overexpression. (C) mRNA expression of TNF-α in Raw264.7 cells following RASD1 knockdown and overexpression. (D) Protein expression of IL-1β in Raw264.7 cell supernatant following RASD1 knockdown and overexpression. (E) Protein expression of IL-6 in Raw264.7 cell supernatant following RASD1 knockdown and overexpression. (F) Protein expression of TNF-α in Raw264.7 cell supernatant following RASD1 knockdown and overexpression. Data are presented as mean ± SD from three independent experiments. (siRASD1 is the RASD1-knockdown group, miRASD1 is the RASD1-overexpression group, *p < 0.05VS.CON; ^♆p < 0.05VS.Model; ^◑p < 0.05VS.HHQG; ^▲p < 0.05VS.Model siRASD1; ^●p < 0.05VS.Model miRASD1).

Fig. 7.

Effect of RASD1 expression on NLRP3 inflammasome components and downstream inflammatory factors in LPS-induced RAW264.7 macrophages. (A) mRNA expression of NLRP3 in Raw264.7 cells following RASD1 knockdown and overexpression. (B) mRNA expression of ASC in Raw264.7 cells following RASD1 knockdown and overexpression. (C) mRNA expression of caspase-1 in Raw264.7 cells following RASD1 knockdown and overexpression. (D) mRNA expression of GSDMD in Raw264.7 cells following RASD1 knockdown and overexpression.(E) mRNA expression of IL-1β in Raw264.7 cells following RASD1 knockdown and overexpression. (F) mRNA expression of IL-18 in Raw264.7 cells following RASD1 knockdown and overexpression. Data are presented as mean ± SD from three independent experiments. (siRASD1 is the RASD1 knockdown group, miRASD1 represents the RASD1 overexpression group, *p < 0.05VS.CON; ^♆p < 0.05VS.Model; ^◑p < 0.05VS.HHQG; ^▲p < 0.05VS.Model siRASD1; ^●p < 0.05VS.Model miRASD1).

Fig. 8.

Protein expression of NLRP3, RASD1, and GSDMD in LPS-induced RAW264.7 macrophages following RASD1 modulation. (A) Protein expression of NLRP3, RASD1, and GSDMD in Raw264.7 cells following RASD1 overexpression and the results of the statistical analysis of the strip gray value. (B) Protein expression of NLRP3, RASD1, and GSDMD in Raw264.7 cells following RASD1 knockdown and the results of the statistical analysis of the strip gray value. (Each band in the figure represents a different blot, all samples are from the same experiment, and the blots were processed in parallel.) (siRASD1 is the RASD1-knockdown group, and miRASD1 is the RASD1-overexpression group).

Effects of HHQG on PKCδ-NF-κB signaling pathway

We used qPCR to investigate the influence of RASD1 on the expression of PKCδ and NF-κB, as well as the intervention effect of HHQG in the LPS-induced inflammation model. Results indicated that when RASD1 was knocked down, the expression of PKCδ and NF-κB was significantly downregulated, indicating that RASD1 had a positive regulatory effect on the expression of these two factors. Conversely, when RASD1 was overexpressed, the expression of PKCδ and NF-κB was significantly upregulated, thus further confirming the positive correlation between RASD1 and these factors. In the LPS-induced inflammation model, we found that the expression of PKCδ and NF-κB was significantly upregulated. However, after cells were treated with HHQG, the expression of these two factors was significantly downregulated, suggesting that HHQG can effectively inhibit LPS-induced upregulation of PKCδ and NF-κB expression, thereby potentially exerting anti-inflammatory effects through regulating this signaling pathway (Figs. 9A–D).

Fig. 9.

Effect of RASD1 modulation on PKCδ-NF-κB signaling pathway in RAW264.7 macrophages. (A) mRNA expression of NF-κB genes in Raw264.7 cells following RASD1 knockdown and overexpression. (B) mRNA expression of PKCδ genes in Raw264.7 cells following RASD1 knockdown and overexpression.(C) Protein expression of NF-κB and PKCδ in Raw264.7 cells following RASD1 overexpression and the results of the statistical analysis of the strip gray value. (D) Protein expression of NF-κB and PKCδ in Raw264.7 cells following RASD1 knockdown and the results of the statistical analysis of the strip gray value. (Each band in the figure represents a different blot, all samples are from the same experiment, and the blots were processed in parallel.) (Data are presented as mean ± SD from three independent experiments.siRASD1 is the RASD1-knockdown group, and miRASD1 is the RASD1-overexpression group, *p < 0.05VS.CON; ^♆p < 0.05VS.Model; ^◑p < 0.05VS.HHQG; ^▲p < 0.05VS.Model siRASD1; ^●p < 0.05VS.Model miRASD1.)

Animal experiments validating the effects of HHQG in alleviating CCl₄-induced liver injury and inflammation by inhibiting RASD1 and PKCδ-NF-κB signaling pathway

Effects of HHQG on expression changes of RASD1, NLRP3 Inflammasome, and its downstream inflammatory factors

The results of qPCR indicated that in the model group, the mRNA expression of RASD1, NLRP3, ASC, caspase-1, IL-1β, IL-18, and GSDMD was significantly upregulated on day 2 post-injury (p < 0.05), continued to intensify on day 5, and maintained high expression until day 7 (p < 0.001). The HHQG group significantly downregulated the expression of these genes at all time points (2, 5, 7 days) post-injury (p < 0.05), indicating that HHQG inhibits the activation of RASD1 and NLRP3 inflammasome and the production of downstream inflammatory factors (Fig. 1I and Figs. 10A–F). Correlation analysis revealed a significant and positive linear correlation between RASD1 and NLRP3 mRNA expression (Fig. 10G) (r = 0.5727, p < 0.05), suggesting that RASD1 may be involved in regulating the activation of NLRP3 inflammasome.

Fig. 10.

Effect of HHQG on mRNA expression of NLRP3 inflammasome components and downstream inflammatory factors in CCl4-induced liver injury. (A) mRNA expression of NLRP3 in liver tissue.(B) mRNA expression of ASC in liver tissue. (C) mRNA expression of caspase-1 in liver tissue. (D) mRNA expression of IL-18 in liver tissue. (E) mRNA expression of IL-1β in liver tissue. (F) mRNA expression of GSDMD in liver tissue. (G) Correlation analysis between RASD1 and NLRP3 (r = 0.5727, p < 0.05).

Western blotting and immunohistochemistry analyses indicated that in the model group, protein expression of RASD1, NLRP3, and GSDMD was upregulated at day 2, day 5, and day 7 after liver injury, while that of RASD1, NLRP3, and GSDMD in the HHQG group was downregulated. (Figs. 11A–D).

Fig. 11.

Effect of HHQG on protein expression of RASD1, NLRP3, and GSDMD in CCl4-induced liver injury. (A) Protein expression of RASD1, GSDMD, and NLRP3 in liver tissue and the results of the statistical analysis of the strip gray value. (B) Immunohistochemical staining of RASD1 in liver tissue (200 ×). (C) Immunohistochemical staining of NLRP3 in liver tissue (200 ×). (D) Immunohistochemical staining of GSDMD in liver tissue (200 ×).(Each band in the figure represents a different blot, all samples are from the same experiment, and the blots were processed in parallel.)

Effects of HHQG on expression changes in the PKCδ-NF-κB signaling pathway

The results of qPCR indicated that in the model group, the mRNA expression of PKCδ was significantly higher than in the control group on day 2 after injury (p < 0.01), while changes in the mRNA expression of NF-κB were not significant. As the injury time extended (day 5 and day 7), the expression of NF-κB and PKCδ continued to increase and peaked at day 7 after injury (p < 0.01). In the HHQG group, the mRNA expression of NF-κB exhibited no significant change on day 2 after injury, while the mRNA expression of PKCδ was lower than in the model group (p < 0.05). At day 5 and day 7 after injury, the expression of both NF-κB and PKCδ was significantly downregulated (p < 0.05) (Figs. 12A, B). Immunohistochemistry analysis indicated that in the CCl4-induced liver injury model, PKCδ expression was upregulated on day 2 after injury, slightly downregulated on day 5, but still exhibited some expression on day 7. The expression of PKCδ was downregulated in the HHQG group (Fig. 12C).

Fig. 12.

Effect of HHQG on mRNA and protein expression of PKCδ-NF-κB signaling pathway in CCl4-induced liver injury. (A) mRNA expression of NF-κB in liver tissue. (B) mRNA expression of PKCδ in liver tissue.(C) Immunohistochemical staining of PKCδ in liver tissue (200 ×).(Each band in the figure represents a different blot, all samples are from the same experiment, and the blots were processed in parallel.) (D) Protein expression of NF-κB and PKCδ in liver tissue and the results of the statistical analysis of the strip gray value.(Data are presented as mean ± SD from three independent experiments. *p < 0.05, **p < 0.01, and ns indicates no significant difference.)

Additionally, the results of Western blotting indicated that in the CCl4-induced liver injury model, protein expression of NF-κB and PKCδ was upregulated at day 2, day 5, and day 7 after injury. The expression of these proteins was downregulated in the HHQG group (Fig. 12D).

Discussion

This study systematically explored the mechanisms by which Mongolian medicine HHQG inhibits inflammation and alleviates liver injury, with a focus on analyzing the promoting effect of RASD1 on the activation of the NLRP3 inflammasome and the inhibitory effect of HHQG on it. Through network pharmacology, the main active components of HHQG were screened, and 184 related targets were identified (among which 5 were candidate active components). Combining molecular docking and experimental verification, we revealed that HHQG exerts a liver—protecting effect by interfering with RASD1 and its downstream inflammatory pathways, providing theoretical and experimental bases for the modern research of ethnic medicines and the development of new liver-protecting drugs.

Regarding the molecular mechanism, this study found that the expression of RASD1 (AGS1/Dexras1) was significantly up—regulated in liver injury and showed a significant positive linear correlation with the activation of the NLRP3 inflammasome. Overexpression of RASD1 promoted NLRP3 activation and up—regulated the expression of genes related to pyroptosis, suggesting that RASD1 plays an important pro—inflammatory role in inflammatory signal transduction^20,21. Correspondingly, HHQG could significantly down—regulate the expression of RASD1 and NLRP3, indicating that it may inhibit the activation of the NLRP3 inflammasome by suppressing RASD1, thereby alleviating pyroptosis and exerting a liver—protecting effect^22,23. The results of network pharmacology and molecular docking supported the possibility that the candidate components in HHQG could bind to RASD1, suggesting the possibility of direct interaction between components and targets. However, the specific contributions and synergistic mechanisms of each component still need further analysis.

Previous studies have suggested that RASD1 can negatively regulate PKCδ by interfering with its autophosphorylation and affecting PKCδ activity through an isoprenoid—dependent membrane—localization mechanism¹⁸. The activation of PKCδ is closely related to the expression of pro—inflammatory genes mediated by NF—κB (such as TNF—α, IL—6, IL—1β) and has been confirmed to be involved in the pathological processes in both CCl4—induced liver injury and LPS—induced inflammation models^24–26. This study showed that the mRNA levels of PKCδ and NF—κB were significantly increased on the 2nd, 5th, and 7th days after injury and reached a peak on the 7th day, suggesting that this pathway plays a key role in the progression of liver inflammation. We also found that RASD1 regulates the PKCδ—NF—κB signal: knockdown of RASD1 could reduce the expression of PKCδ and NF—κB, while overexpression enhanced their expression. HHQG could effectively inhibit the activation of PKCδ—NF—κB, further supporting the hypothesis that HHQG alleviates inflammation by regulating RASD1 and thus affecting the PKCδ—NF—κB axis.

In addition, starting from Mongolian medical theory, this study attempted to integrate the traditional concepts of “holism” and "treatment based on syndrome differentiation" with modern molecular mechanisms. According to Mongolian medical theory, the liver is the main circulation channel of “Xila” and has hematopoietic functions. Liver diseases often manifest as "liver—heat syndrome". HHQG is mainly composed of safflower, combined with bezoar, gardenia, and myrobalan, etc. It is clinically used for clearing heat, soothing the liver, detoxifying, and regulating the balance of the “Three Roots”, emphasizing holistic treatment. Within this framework, this study further partially explained the “holistic” mechanism of action of HHQG from the perspective of RASD1 and NLRP3 inflammasome activation, supplementing and expanding the previous evidence on the protective mechanisms of HHQG, such as antioxidant effects, inhibition of JNK/c—Jun, regulation of the FasL/Fas and MMP—1/TIMP—1 balance, and inhibition of lipid peroxidation¹⁵, as well as our previous observation that HHQG inhibits CCl4—induced infiltration of monocytes/macrophages¹⁷.

Although this study has obtained multi—faceted evidence on the mechanism, there are still several limitations. Firstly, HHQG is a multi—component compound, and the interactions among its components and their relative contributions to the RASD1/PKCδ/NLRP3 pathway are not yet clear. Secondly, this study is mainly based on animal/cell models, and the clinical relevance and dose—response relationship need to be verified in more clinical or translational studies. Finally, the precise molecular mechanism by which RASD1 regulates the inflammasome (such as whether it involves specific upstream receptors, ubiquitination, or phosphorylation modifications) still requires in—depth molecular biology research (including protein interactomics and signal transduction kinetics analysis).

In conclusion, this study shows that HHQG may inhibit the activation of the PKCδ—NF—κB and NLRP3 inflammasomes by suppressing RASD1, thereby alleviating the inflammatory response and liver injury. This finding provides a molecular basis for the modern pharmacological research of Mongolian medical prescriptions and offers new ideas for liver—protecting strategies targeting RASD1. Future research should focus on analyzing the action spectrum and synergistic effects of monomer components, clarifying the molecular downstream mechanisms of RASD1, and conducting pre—clinical/clinical translational studies to evaluate its therapeutic potential.

Conclusion

Our research provides preliminary evidence suggesting that the Mongolian medicine compound HHQG can down-regulate RASD1 and the associated PKCδ-NF-κB signaling pathway in the experimental models used, accompanied by a reduction in NLRP3-related inflammatory responses and an improvement in liver injury phenotype.

Abbreviations

HHQG

Honghua qinggan 13 flavor pills

RASD1

Ras related dexamethasone induced 1

PKCδ

Protein kinase C delta type

NF-κB

Nuclear factor -kappa B

NLRP3

NLR family pyrin domain containing 3

ASC

PYD and CARD domain containing

Caspase-1

Cysteinyl aspartate specific proteinase-1

ALT

Alanine aminotransferase

GOT

Glutamic oxaloacetic transaminase

AST

Aspartate Transaminase

GPT

Glutamic pyruvic transaminase

CCL2

C-C motif chemokine ligand 2

IL-6

Interleukin-6

TNF-α

Tumour necrosis factor-alpha

PPI

Protein-protein interaction

GO

Gene ontology

KEGG

Kyoto encyclopedia of genes and genomes

AKT1

AKT serine/threonine kinase 1

TNF

Tumor necrosis factor

TP53

Tumor protein p53

ALB

Albumin

JUN

Jun proto-oncogene

ApP-1

Transcription factor subunit

PPARG

Peroxisome Proliferator activated receptor Gamma

JNK/c-Jun

C-Jun N-terminal kinase

FasL/Fas

Factor-related Apoptosis ligand/Factor-related apoptosis

MMP-1

Matrix metallopeptidase 1

TIMP-1

TIMP metallopeptidase inhibitor 1

GSDMD

Gasdermin D

IκB-α

Inhibitor of NF-κB

HRP

Horseradish peroxidase

PBS

Phosphate buffer saline

DAB

Diaminobenzidine

PCR

Polymerase chain reaction

qPCR

Quantitative polymerase chain reaction

RT-qPCR

Real-time quantitative polymerase chain reaction

ELISA

Enzyme linked immunosorbent assay

PVDF

Polyvinylidene fluoride

DMEM

Dulbecco’s modified eagle medium

LPS

Lipopolysaccharides

CCl₄

Carbon tetrachloride

H2O2

Hydrogen peroxide

IL-1β

Interleukin-1beta

IL-18

Interleukin-18

OMIM

Online mendelian inheritance in man

String

Search tool for recurring instances of neighbouring genes

PDB

Protein data bank

OD

Optical density

HE

Hematoxylin-eosin

EP

Eppendorf mic

BCA

Bicinchoninic acid

DIA

Data-independent acquisition

DEPs

Differentially expressed proteins

ANOVA

Analysis of variance

SDS-PAGE

Sodium dodecyl sulfate–polyacrylamide gel electrophoresis

TBS

Tris-buffered saline

CCK8

Cell counting kit-8

WB

Western blot assay

BP

Biological processes

CC

Cellular component

MF

Molecular function

IL-17

Interleukin-17

FC

Fold change

Wnt

Wingless/integrated

MRNA

Messenger RNA

iNOS

Inducible nitric oxide synthase

Author contributions

Conceived and designed the experiments: Chunli Ma, Yulong Bao, Linghong Wang. Performed the experiments: Lili Cao, Mei Hong, Xiufang Bao, Linyun Zhao, He Tong. Analyzed the data: Xin Zhang, Mutu Eerdec, Qiqige Buren, Hua Lian, Lili Dai, Guleng Amu，Chengyuan Ma. Drafted and revised the manuscript: Yulong Bao, Chunli Ma, Li Wang.

Funding

Open access funding provided by Inner Mongolia Medical University. Supported by Program for Innovative Research Team in Universities of lnner Mongolia Autonomous Region (Grant number: NMGIRT2418); Supported By Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region (Grant number: NJYT23052); the first-class discipline research project (Grant number: YLXKZX-NYD-009); the Natural Science Foundation of Inner Mongolia (Grant number: 2021MS08029, 2024MS08054, and 2024LHMS08024); the general project of Inner Mongolia Medical University (Grant number: YKD2022MS006, YKD2021MS043, and YKD2024MS007); the Duxue Talent Program of Inner Mongolia Medical University (Grant number: ZY20243102); the Shanxue Talent Program of Inner Mongolia Medical University (Grant number: ZY20242109); the key project of Inner Mongolia Medical University (Grant number: YKD2022ZD008); Science and Technology Plan of the Inner Mongolia Automous Region (Grant number: 2021GG0098);The Inner Mongolia Medical University Doctoral Fund Start-up Project (Grant number: YKD2024BSQD022); Project of Mongolian Medicine Collaborative Innovation Center, Inner Mongolia Autonomous Region (Grant number: MYYXTPY202401); Science and technology project of public hospital Research Union Fund (2024GLLH0148); Inner Mongolia Medical University 2025 Maker Cultivation Project (101322025138; 101322025102).

Data availability

The datasets used during the current study available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ethical approval and consent to participate

The animal experiment was approved by the Medical Ethics Committee of Inner Mongolia Medical University (Document No.: YKD202405027) and was conducted in accordance with the National Research Council’s Guide for the Care and Use of Laboratory Animals. The present study is reported in accordance with ARRIVE guidelines.