Abstract Jatrorrhizine (JATR), a natural isoquinoline alkaloid from Coptidis Rhizoma, exhibits various pharmacological activities, including antibacterial, anti-inflammatory, and antitumor effects. While JATR is known to treat chronic gastritis, its therapeutic potential for chronic atrophic gastritis (CAG) and its underlying mechanisms are not fully understood. This study induced CAG in rats using N-Methyl-N′-nitro-N-nitrosoguanidine (MNNG) for 12 weeks through free drinking and force-feeding. Serological metabolomics identified 23 core targets of JATR related to CAG improvement. Reverse transcription-quantitative polymerase chain reaction and western blotting confirmed the involvement of these targets. Molecular docking revealed interactions between JATR and IL-1β and Caspase-3. JATR significantly alleviated gastric inflammation and atrophy, with Kyoto Encyclopedia of Genes and Genomes analysis showing enrichment in the “Nod-like receptor-related pyroptosis pathway”. JATR also enhanced GES-1 cell proliferation and reduced MNNG-induced cell damage. Additionally, JATR downregulated pyroptosis-related (Gasdermin D, NLRP3, Caspase-1) and apoptosis-related (Bcl-2, Bax, Caspase-3) markers. These findings suggest that JATR may ameliorate MNNG-induced CAG by inhibiting the activation of the Nod-like receptor-related pyroptosis pathway, supporting its potential as a therapeutic intervention for CAG. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-025-05502-2. Keywords: Jatrorrhizine, NL family pyrin domain containing 3, Caspase-3, Chronic atrophic gastritis, MNNG, Molecular docking Subject terms: Computational biology and bioinformatics, Molecular biology, Systems biology, Gastroenterology, Medical research Introduction CAG is a precancerous lesion of gastric cancer (PLGC) and is regarded as the primary precancerous lesion from inflammation to gastric cancer (GC)^[38]1. CAG progression is driven by dysregulated inflammation and excessive epithelial cell apoptosis, creating a critical need for multi-target therapies. A multicenter study in China showed that the rate of CAG in patients with chronic gastritis (CG) was as high as 25.8%^[39]2. The current treatment protocols for CAG include proton pump inhibitors (PPIs), H2 blockers, and anti-Helicobacter pylori (Hp) drugs. However, due to the long treatment cycle, side effects, patient compliance, and antibiotic resistance are inevitable^[40]3,[41]4. The recurrence rate of CAG is about 20%, so more drug regimens are urgently needed for CAG treatment^[42]5. Furthermore, it is of great significance to find more effective treatment methods to alleviate the clinical symptoms of CAG patients, prevent CAG from developing into GC, and improve life quality^[43]6. Due to the reversible pathological state of CAG, timely treatment of CAG can effectively prevent the occurrence of GC. Therefore, finding new drugs with improved efficacy and fewer side effects can bring more meaningful treatment options to clinicians and patients. Jatrorrhizine (JATR) is a natural isoquinoline alkaloid from the Coptis Rhizoma. It has been shown to exhibit a variety of pharmacological properties, including gut microbiota balances^[44]7 as well as antibacterial effects^[45]8, antidiabetic effects^[46]9, anti-inflammatory effects^[47]10,[48]11, and antitumor effects. However, the impact of JATR on CAG is unknown. Prolonged and excessive N-nitrosamine intake in the living environment can lead to CAG^[49]12. MNNG is often used to replicate the harmful chemical N-nitrosamines in the human diet and has been used in the laboratory as a carcinogen and chemical mutagen for 60 years. This provides a theoretical basis for utilizing MNNG to replicate a CAG model in the present study^[50]13. Serological metabolomics is used for detecting, identifying, and quantifying as many metabolites as possible in biological samples^[51]14. The primary advantages of serological metabolomics lie in the potential to identify changes in metabolites between different groups and discover new pathophysiological pathways. In the present study, serological metabolomics, traditional pharmacology, and molecular docking methods were used to determine whether JATR could treat MNNG-induced CAG as well as the underlying mechanisms. We look forward to finding an effective monomer component for clinical CAG intervention. Results Serum DM analysis PCA was performed and demonstrated that samples could not be effectively separated from each other in unsupervised models without grouping conditions; therefore, PLS-DA was performed. PLS-DA is a supervised model evaluation index that can be utilized to detect DMs between diverse groups. The metabolic phenotypes of the Vehicle, the Model, and the JATR-H were distinguished in electrospray ionization (ESI)+ and ESI− modes (Fig. [52]1A,D). PLS-DA was performed between the model and the vehicle groups (Fig. [53]1B,E). R2 = 0.935, Q2 = 0.102 in ESI− mode (Fig. [54]2E), and R2 = 0.949, Q2 = 0.125 in ESI+ mode (Fig. [55]2F), suggesting that the metabolites have a good explanatory degree to the model and that the results are notable under ESI+ and ESI− modes. PLS-DA was also performed between the Model and the JATR-H groups (Fig. [56]1C,F). The result indicated R2 = 0.948, Q2 = 0.145 in ESI− mode (Fig. [57]2G), and R2 = 0.937, Q2 = 0.0503 in ESI+ mode (Fig. [58]2H), suggesting that the metabolites had a good explanatory degree for JATR intervention in ESI− mode, while ESI+ mode has a poor predictive ability. Based on the OPLS-DA method, the DMs among the Vehicle, Model, and JATR-H groups were categorized as significant DMs according to VIP ≥ 1.0, P < 0.05 (Fig. [59]2A–D). In total, 12 serum biomarkers (6 types each for ESI+ and ESI−) were finally obtained. The relevant information is shown in Table [60]4 and 23 DM-related target genes were ultimately obtained. Fig. 1. [61]Fig. 1 [62]Open in a new tab Metabolic profiles and differentiation of the vehicle, model, and JATR-H groups (n = 8) by multivariate analysis. The PCA score plots in ESI− mode (A) and ESI+ mode (D). PLS-DA score plots between the vehicle and model groups in ESI− mode (B) and ESI+ mode (E), between the model and JATR-H groups in ESI− mode (C) and ESI+ mode (F), (n = 8). Fig. 2. [63]Fig. 2 [64]Open in a new tab Metabolite volcano plot of the OPLS-DA model for the vehicle and model groups in ESI− mode (A) and ESI+ mode (B), between the model and JATR-H groups in ESI− mode (C) and ESI+ mode (D). 100 permutation tests to evaluate the quality of the OPLS-DA model between the vehicle and model groups in ESI− mode (E) and ESI+ mode (F), between the model and JATR-H groups in ESI− mode (G) and ESI+ mode (H). Table 4. Primers sequences of real-time PCR analyses for mRNA expression. GES-1 genes Forward Reverse GAPDH GGAAGCTTGTCATCAATGGAAATC TGATGACCCTTTTGGCTCCC Bcl-2 GGAGGATTGTGGCCTTCTTTG AGACAGCCAGGAGAAATCAAACA Bax CGGGTTGTCGCCCTTTTCTA GAGGAAGTCCAATGTCCAGCC Cyclin D1 AGCTGTGCATCTACACCGAC GAAATCGTGCGGGGTCATTG IL-1β CGATCACTGAACTGCACGCTC ACAAAGGACATGGAGAACACCACTT NLRP3 ATTGAGCACCAGCCATTCCC GAGTGTTGCCTCGCAGGTAAAG GSDMD TGGTTATTGACTCTGACTTGGACG ATCTGTCAGGAAGTTGTGGAGGC Caspase1 TCGCTTTCTGCTCTTCCACA GGCATCTGCGCTCTACCATCT [65]Open in a new tab Correlation analysis between potential biomarkers and serological indices Spearman correlation analysis was applied to evaluate the correlation between metabolic biomarkers and serological indices among the Vehicle, Model, and JATR-H groups. The results demonstrated that there was no correlation between PGI and Indoleacetic, but a positive correlation between PGI and 1-Methylnicotinamide. Additionally, 8 metabolites (indole-3-carboxaldehyde, biochanin A, 5′-s-methylthioadenosine, N-α-acetyllysine, 5′-l-methylthioadenosine, kynurenic acid, uracil, and indoleacetic acid) exhibited positive correlations with IL-18 and IL-1β. Furthermore, these metabolites showed negative correlations with GAS-17, PGI, and PGII. Therefore, the results demonstrated a close correlation between potential biomarkers and serological indices (Fig. [66]3). Fig. 3. [67]Fig. 3 [68]Open in a new tab Spearman analysis of correlation potential biomarkers and serological indices among the vehicle, the CAG group, and the JATR-H group. Pathways associated with the DM-related genes A total of 23 endogenous DM-related genes were screened following the intervention of JATR for CAG (Fig. [69]4A). Subsequently, KEGG enrichment demonstrated that the potential pathways of the DM-related genes included “NOD-like receptor-related pyrodeath”, “MAPK signal pathway”, and “Neurotrophin signaling pathway”. Therefore, the “NOD-like receptor-related pyrodeath-dependent pathway” was selected for further exploration (Fig. [70]4B). Gene Ontology analysis demonstrated that the CCs associated with JATR treatment for CAG included “long-term potentiation”, “vesicle” and “membrane-bounded vesicle”. The related MFs included “dopaminergic synapse”, “protein binding”, and “endocytosis” (Fig. [71]4C). Fig. 4. [72]Fig. 4 [73]Open in a new tab Visualization of gene-related information affecting endogenous DM. (A) The target genes for DM; (B) Visualized diagram of the pathway; (C) GO enrichment results of the DM-related genes. DM Differential metabolites. Effects of JATR on macroscopic pathological After 12 weeks of modeling, compared with the Vehicle group, the gastric tissue in the model group showed microdamage, a pale color, thinning, and disorganized gastric folds (Fig. [74]5A). After 4 weeks of JATR treatment, the rats had vitality, no diarrhea, weight gain, and an increased food intake. By two-factor analysis of variance, the body weight of the JATR-H, JATR-L, and model groups was statistically significant (P < 0.05; Fig. [75]5B). To observe the therapeutic effect of JATR on the CAG model rats, the histological changes of the gastric tissues were detected via H&E staining after 4 weeks of treatment. The irregular arrangement, cystic dilation, and inflammatory cell infiltration were observed in the gastric tissues of the Model group. However, following JATR intervention, the tissue samples had a regular arrangement and a marked decrease in inflammatory cell infiltration. These results indicated that the CAG model was replicated successfully and that JATR could relieve the histological lesions of gastric tissues in CAG model rats (Fig. [76]5C). Fig. 5. [77]Fig. 5 [78]Open in a new tab Effects of JATR on macroscopic pathological changes of gastric mucosa stomach tissue in CAG rats (A). Bodyweight of rats during the treatment period (B). JATR relieved histological lesions of gastric tissues in CAG rats induced by MNNG (C). Data were expressed as mean ± SD (n = 8). *P < 0.05, **P < 0.01 versus model; ^##P < 0.01 versus vehicle. JATR improves serum cytokine levels and decreases gastric mucosal cell apoptosis The serum levels of gastrointestinal hormones and inflammatory factors were measured. The results showed that the levels of PGI and PGI/PGII in the Model group were decreased, while the levels of GAS-17, IL-18, and IL-1β were increased. However, after JATR treatment, the levels of PGI and PGI/PGII were significantly increased (P < 0.05), while the levels of GAS-17, IL-18, and IL-1β were significantly decreased (P < 0.05). The data suggested that JATR treatment improved the gastrointestinal hormone and inflammatory cytokine levels in CAG model rats (Fig. [79]6A–E). TUNEL staining was applied to detect the apoptosis of cells in the gastric tissues from each group. According to the number of TUNEL+ cells, the degree of apoptosis in the Model group was the highest, which decreased following JATR intervention (Fig. [80]6F–K). Fig. 6. [81]Fig. 6 [82]Open in a new tab JATR regulated the serological levels of gastrointestinal hormones and inflammatory cytokines in CAG rats induced by MNNG, (A) GAS-17, (B) PGI, (C) PGI/PGII, (D) IL-18, (E) IL-1β were detected using ELISA kits. The apoptosis status of gastric tissue in CAG rats was imaged histologically by TUNEL staining (F–K). Data were expressed as mean ± SD (n = 8). *P < 0.05, **P < 0.01 versus model; ^##P < 0.01 versus vehicle. Molecular dynamics simulation and binding free energy calculations It is easier to bind when the binding energy is low, and a higher affinity is generally defined when the binding energy is less than 7 kcal/mol^[83]15. The results showed that the binding energies of Caspase3 and IL-1β to JATR were − 4.3 and − 7.4 kcal/mol, respectively, indicating a high affinity (Fig. [84]7). Fig. 7. [85]Fig. 7 [86]Open in a new tab Molecular docking results of JATR on IL-1β and caspase 3. (A) JATR-IL-1β. (B) JATR-caspase 3. Effect of JATR on pyroptosis-associated protein expression in CAG model rats The effect of JATR on pyroptosis-associated protein expression in gastric mucosal cells was determined. Initially, the gastric mucosal cells of the Model group exhibited higher levels of pyroptosis-associated proteins, including IL-1β, Gasdermin D (GSDMD), NLR family pyrin domain containing 3 (NLRP3), and Caspase-1, compared with the Vehicle group. Following JATR administration, the corresponding protein expression levels were significantly reversed (P < 0.05). These results verified an inactivation of pyroptosis by JATR treatment in CAG model rats (Fig. [87]8). Fig. 8. [88]Fig. 8 [89]Open in a new tab JATR affected the pyroptosis-associated protein expression in CAG rats induced by MNNG. Cropped blots are displayed; full-length blots are provided in Supplementary Information. Data were expressed as mean ± SD (n = 8), and the experiments were repeated 3 times. *P < 0.05, **P < 0.01 versus Model; ^##P < 0.01 versus vehicle. JATR inhibits the apoptosis of gastric mucosal cells in CAG model rats The apoptosis of cells in the Model group was higher than that of the Vehicle group, which was relieved by JATR treatment. Western blotting was utilized to detect the expression of apoptosis-related proteins. The level of anti-apoptotic protein, Bcl-2, was significantly decreased (P < 0.01), while proapoptotic protein, Bax (P < 0.01), and cleaved Caspase-3 (P < 0.01) were increased in the Model group (Fig. [90]9). As expected, JATR treatment increased Bcl-2 expression and decreased Bax and Caspase-3 expression. Therefore, the results indicated that JATR could inhibit the apoptosis of gastric mucosa cells in CAG model rats. Fig. 9. [91]Fig. 9 [92]Open in a new tab JATR affected the expression of apoptosis-associated proteins in gastric tissues of CAG rats induced by MNNG. The expression levels of Bcl-2, Bax, and cleaved caspase-3 were measured using western blotting. Cropped blots are displayed; full-length blots are provided in Supplementary Information. Data were expressed as mean ± SD (n = 8), and the experiments were repeated 3 times. *P < 0.05, **P < 0.01 versus model; ^##P < 0.01 versus vehicle. JATR alleviates MNNG co-incubated GES-1 cell injury GES-1 cell viability was detected via a CCK-8 kit. Initially, the optimum concentration of MNNG (10, 20, 30, 40, 50, 60, and 80 μM) and different incubation times (6 h, 12 h, 24 h, 36 h, and 48 h) were explored. The best cell survival rate was defined as close to 60%^[93]16,[94]17. The results showed that 40 μM MNNG for 24 h exhibited the best outcome (Fig. [95]10A). Furthermore, the protective effect of JATR at different concentrations (2.5, 5, 10, 20, 30, 40, 60, and 80 μM) was explored (Fig. [96]10B). Ultimately, 5, 10, and 20 μM JATR were selected for co-culturing with MNNG (40 μM) for 24 h (Fig. [97]10C). Finally, 40 μM MNNG and 10 μM, 20 μM JATR was selected to for the follow-up study. Fig. 10. [98]Fig. 10 [99]Open in a new tab Effect of MNNG and JATR on cell viability of GES-1 (A); Cell survival rate of GES-1 treated with different doses of MNNG for different times; (B) Cell survival rate of GES-1 treated with different doses of JATR (C). Protective effect of JATR pretreatment on proliferation of MNNG co-culturing with GES-1 cells. Histogram of NLRP3 (D), Caspase1 (E), GSDMD (F), IL-1β (H), Cyclin D1 (I), Bcl-2 (J) and Bax (K) mRNA expression in MNNG co-cultured GES-1 cells by qRT-PCR. Data were shown as mean ± SD (n = 6). *P < 0.05, **P < 0.01 versus model; ^##P < 0.01 versus vehicle. JATR alleviates MNNG-induced GES-1 cell injury by anti-apoptosis and anti-pyroptosis effects To further validate that JATR (10 or 20 μM) alleviates MNNG-induced GES-1 cell injury by regulating apoptosis-associated and pyroptosis-associated mRNA expression, the expression levels of NLRP3, GSDMD, Caspase1, Bax, Bcl2, Cyclin D1, and IL-1β were evaluated. The results indicated that JATR intervention significantly decreased the relative mRNA expression levels of NLRP3, GSDMD, Caspase1, Bax, Bcl2, Cyclin D1, and IL-1β, which were induced by MNNG co-cultured cells (P < 0.05) (Fig. [100]10D–J). Discussion MNNG has been widely used in laboratory experiments in the study of CAG and GC. The methods mainly simulate the carcinogenic process of human improper intake of nitrate and its transformation into nitrosamine in the stomach^[101]17,[102]18, which provides a theoretical basis for the successful establishment of the CAG model in rats by MNNG. Apoptosis is an active intrinsic mechanism of programmed cell death. The dynamic integrity of gastric mucosal cells is maintained by sustaining the balance between cell proliferation and apoptosis-associated injury. When suffering harmful stimuli, the malignant transformation of cells is prevented by triggering apoptosis to maintain the normal function of tissues. If the apoptosis status is out of balance, the abnormal proliferation of cells would lead to neoplastic cells. Therefore, the intervention of gastric cell proliferation and apoptosis is an important method to prevent CAG occurrence^[103]19. The results of the present study showed that the longer the incubation of GES-1 cells with MNNG, the stronger the inhibitory effect of MNNG on cell proliferation. Additionally, the higher the concentration of MNNG, the stronger the effect on promoting apoptosis. Following intervention with JATR, the apoptosis of GES-1 cells was significantly inhibited, and the inhibition of cell proliferation was also reversed (Fig. [104]11). Fig. 11. [105]Fig. 11 [106]Open in a new tab Schematic diagram of MNNG ameliorates MNNG-induced chronic gastric mucosal injury by upregulating pyroptosis and apoptosis. Pyroptosis is another form of programmed cell death which is characterized by necrosis, cell swelling, pore formation in plasma membranes, and proinflammatory cytokine release, with the most important proinflammatory cytokines including IL‐1β and IL‐18^[107]20,[108]21. Apoptosis and pyroptosis interact in CAG by balancing cell death and inflammation, with JATR regulating both pathways. In the present study, the protein expression levels of NLRP3, Caspase-1, GSDMD, and the downstream proinflammatory cytokines, IL-18 and IL-1β, were significantly increased in the gastric mucosa of the Model group compared with the Vehicle group. Following treatment with JATR, the expression levels of these proteins were significantly decreased compared with the Model group. These results are in agreement with the study by Semper^[109]22. Both IL-18 and IL-1β are inflammatory factors belonging to the IL-1 superfamily and changes in their expression could reflect the type II immune response^[110]22. In the present study, the elevated expression levels of both IL-18 and IL-1β in serum (detected by ELISA) indicated the severity of inflammation in the Model group. Following treatment with JATR, the serological levels of IL-1β and IL-18 were significantly decreased, indicating a favorable therapeutic effect. IL1-β is the strongest factor known to inhibit gastric acid secretion and a lack of gastric acid secretion will lead to an increase in gastric atrophy^[111]23. That is, the level of IL-1β is negatively correlated with the severity of gastric mucosa atrophy. In the present study, the expression levels of IL-1β and Cyclin D1 were detected by ELISA, western blotting, and Reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The results showed that the IL-1β level was decreased following JATR treatment, which could reflect the effective repair of gastric mucosa cells in CAG model rats. Cyclin D1 protein is not expressed in normal gastric tissues^[112]24 and expression gradually increases with the injury of gastric mucosa cells such as in CSG, CAG, PLGC, and GC. In the present study, Cyclin D1 expression in the JATR-L and JATR-H groups gradually decreased in a statistically significant manner compared with the Model group. The gastrointestinal hormone, GAS-17, is secreted by G cells of the digestive system, and combined with PGI and PGI/PGII, is likely to directly reflect the severity of gastric mucosa atrophy^[113]25,[114]26. The changes in GAS-17, PGI, and PGI/PGII levels in the present study indicated that JATR could significantly improve the CAG. In CAG, the interplay between apoptosis and pyroptosis creates a pathogenic loop, which JATR disrupts to restore mucosal homeostasis. JATR offers clinical advantages over existing therapies by targeting the pyroptosis-apoptosis axis, with potential for CAG treatment. Our study has limitations, including the use of a 4-week short-term model that may not fully capture long-term therapeutic effects and the potential for off-target interactions due to JATR’s multi-target mechanism. We acknowledge these constraints to provide a balanced interpretation of our findings, which also highlights opportunities for future long-term and target-specific investigations. Future research should prioritize long-term in vivo studies and human clinical trials to validate JATR’s efficacy and expand its translational impact on CAG therapy. Materials and methods Materials and reagents JATR (purity, 98%) was purchased from Chroma Biotechnology Co. Ltd. The N-methyl-N′-nitro-N-nitrosoguanidine (MNNG, purity, 98.5%) was purchased from Shanghai Macklin Company. The positive drug Vitacoenayme was obtained from Jiangsu Hengxin Pharmaceutical Company. Enzyme-linked immunosorbent assay (ELISA) kits for IL-18 and IL-1β were obtained from Abbkine, while GAS-17, PGI, and PGII kits were purchased from Nanjing Jiancheng Bioengineering Institute. All antibodies and other related reagents in western blotting assay were obtained from commercial sources and the specific information is shown in Table [115]1. Table 1. Antibodies information. Antibodies Dilution Manufacturers Cat. no. Antibodies Dilution Manufacturers Cat. no. Anti-IL-1β 1:1000 Boster Biotech BOS703BP70 Goat anti-rabbit IgG 1:10,000 ZSGB-BIO ZB-2301 Anti-Bax 1:1000 Boster Biotech BA0315-2 Anti-GSDMD 1:1000 Abcam ab219800 Anti-Bcl-2 1:1000 Boster Biotech A00040-2 Anti-Caspase1 1:1000 Boster Biotech BM4291 Anti-Cyclin D1 1:1000 Boster Biotech BST17044272 Anti-Cleaved-Cas3 1:5000 Abcam ab32042 Anti-Capase3 1:1000 Boster Biotech BM3957 GAPDH antibody 1:10,000 Proteinech 60004-12 [116]Open in a new tab Animal handing and ethical declaration Chongqing Kang Animal Breeding Center (Permission No. SCXK (Y) 2022-0140) supplied forty healthy male Sprague–Dawley (SD) rats that were 180–220 g. The rats were fed under specific pathogen-free (SPF) conditions, with a temperature of 25 ± 0.5 °C, humidity at 55 ± 5%, and under a 12 h light–dark cycle. The rats were divided into five groups (n = 8 each) at random, Vehicle, Model, JATR-L (20 mg/kg/d), JATR-H (40 mg/kg/d)^[117]27, and Vitacoenzyme (200 mg/kg/d). Except for the Vehicle group, all rats were free access to 170 μg/mL MNNG (Cat No.70-25-7) solution ^[118]28 prepared in black bottles for 12 weeks. Meanwhile, the rats were also forced to 170 μg/mL MNNG solution once every other day. Subsequently, the CAG model rats were administered the corresponding drugs daily, which were mixed as a suspended solution with 0.5% carboxymethyl cellulose sodium (CMC-Na), while the Vehicle group rats were only administrated CMC-Na solution^[119]16. After 4 weeks of treatment, all rats were anesthetized via intraperitoneal injection of ethyl carbamate (200 mg/100 g body weight) and sacrificed through abdominal aorta blood collection (Fig. [120]12). The stomach was subdivided. The collected blood was centrifuged at 3000 rpm/min at 4 °C for 15 min and the supernatant was stored at − 80 °C for subsequent tests. Fig. 12. [121]Fig. 12 [122]Open in a new tab Experimental design of MNNG-induced CAG and drug treatment. All animal procedures were carried out by following the Guide for the Care and Use of Laboratory. The research was approved by the Chongqing Academy of Animal Science Animal Ethics Committee (Approval ID: XKY-20240820). This study is reported following ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments). Pharmacodynamic indicators Serum markers associated with CAG were measured by IL-18 (Cat.No.: JM-01454R1), Pepsinogen I (PGI, Cat. No.: MM-0491R1), Pepsinogen II (PGII, Cat. No.: MG-0164R1), Gastrin-17 (GAS-17, Cat. No.: JM-10448R1), and IL-1β (Cat. No.: MM-0194R1). Hematoxylin and eosin (H&E) staining was used for gastric histopathological analysis. The H&E-stained sections were observed, analyzed, and imaged by a microscope (Nikon Eclipse Ni-U) and imaging Software [NIS-Elements 4.0 (Nikon, Japan)]^[123]29. TUNEL assay The TUNEL staining kit (Servicbio, China) was applied to determine the apoptosis of gastric tissue. The gastric sections were washed in PBS solution for 3 cycles. Subsequently, 100 μL of 10% proteinase K solution was incubated with the sections at 37 °C for 30 min, followed by 3 cycles of PBS washing. TdT enzyme solution (50 μL) was then incubated with the sections at 37 °C for 1 h. After washing, the sections were mixed with streptavidin-fluorescein solution (5 μL) and labeling buffer (45 μL), stored in the dark at 37 °C for 30 min, and then stained with DAPI solution^[124]30. Finally, the sections were observed, analyzed, and imaged using a fluorescence microscope (Nikon, Japan). Serological metabolomics analysis Main instruments and samples pretreatment Acetonitrile and methanol were supplied by Merck, Germany. All other reagents were analytically pure. The sample pretreatment process was as follows: The 200 μL serum sample was aliquoted into a 1.5 mL centrifuge tube, 600 μL methanol was added, and then the mixture was vortexed and shaken for 3 min. The sample was then centrifuged at 4 °C for 10 min (14,000 rpm/min), and all the supernatant was collected in a sample bottle to be measured. The quality control samples were processed as follows: The 200 μL serum sample was aliquoted into a centrifuge tube and mixed by vortexing to prepare two parallel quality control solutions. The 200 μL serum sample was aliquoted into a 1.5 mL centrifuge tube, 600 μL of methanol was added, and then the mixture was vortexed and shaken for 3 min. The sample was then centrifuged at 4 °C for 10 min (14,000 rpm/min), and 200 μL supernatant was collected^[125]31. Chromatography conditions The chromatographic conditions for the samples for which metabolome tests were performed are listed in Table [126]2. Table 2. Chromatography conditions. The conditions Liquid phase system Waters AcquityTM UPLC liquid phase system Columns ACQUITY UPLC® HSST3C[18] (2.1 mm × 100 mm, 1.8 μm) Mobile phase set A: 0.1%-formic acid aqueous solution B: 0.1%-formic acid acetonitrile solution Gradient elution set 0–6.0 min, 5–45% B; 6.0–8.0 min, 45–75% B; 8.0–12.0 min, 75–85% B; 12.0–12.5 min, 85–100% B; 12.5–14.0 min, 100% B; 14.0–14.5 min, 100–5% B [127]Open in a new tab Mass spectrometry conditions The mass spectrometry conditions for the samples for which metabolome tests were performed are listed in Table [128]3. Table 3. Mass spectrometry conditions. The conditions MS^E continuum Electro-spray ionization (ESI) Locking mass solution Leucine Enkephalin (ESI− m/z at 554.2615, ESI+ m/z at 556.2771) solution MS conditions set Capillary voltage ESI− 2.5 kV, ESI+ 3.0 kV Gas flow rate 800 L/h Ion source temperature 140 °C Cone hole voltage 40 V Collision energy 10–45 V Gas temperature 450 °C Interval scan time 0.2 s Mass scan range 50–1200 m/z [129]Open in a new tab Data extraction and pattern recognition analysis MassLynx v 4.1 software was used for data acquisition, Progenesis QI v 2.4 software was used for data alignment, peak extraction, sample grouping, deconvolution, and normalization, and SIMCA v 13.0 was used for multivariate analysis of each group. For unsupervised principal component analysis (PCA), supervised partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares Discrimination analysis (OPLS-DA), results with VIP > 1, P < 0.05, and FC ≥ 2 were considered potential biomarkers. In PLS-DA/OPLS-DA, R^2/Q^2 validated model reliability via 200 permutations; Q^2 > 0.5 and R^2 > 0.7 ensured rigor. The overfitting of the PLS-DA model was verified by the permutation test. Through comparing the Progenesis QI online database with the Human Metabolome Database ([130]https://hmdb.ca/) and relevant literature, the differential metabolites (DMs) were identified. Pathway enrichment analysis The related genes of the serological DMs were screened using a Venn diagram of the different groups. Subsequently, the DM-related genes were uploaded into the DAVID database (version 6.8, [131]https://david.ncifcrf.gov/) to predict the cell components (CC), molecular function (MF), biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. After integrating this information into the software of Cytoscape (version 3.2.1), a visualized network of “Disease-JATR-DM target-pathway” was constructed. Western blotting analysis The gastric tissue (80 mg) was transferred into 1.5 mL tubes, and RIPA buffer containing protease inhibitor and phosphorylation inhibitor was added. Then, two steel beads were placed in each tube and ground with a low-temperature grinder 5 times for 30 s each time. The samples were centrifuged in a cryogenic centrifuge at 12,000 rpm for 10 min. The protein content was detected with a BCA kit. An equal amount of protein from each sample was loaded and separated using a 10% SDS-PAGE gel. The gel was cut horizontally according to molecular weight and transferred into a polyvinylidene fluoride membrane. After blocking, the primary antibody was incubated with the membrane in a shaking bed at 4 °C overnight. Subsequently, after 3 cycles of TBST washing, a secondary antibody was incubated with the membrane at room temperature for 2 h. Finally, after a final wash with TBST for 3cycles, the bands were developed and analyzed. Each target protein was tested three times. Molecular docking Molecular docking was performed using AutoDock Vina (v1.2.3), with protein structures (Caspase3: PDB 1R4G; IL-1β: PDB 1ITF) prepared by removing water, co-crystallized ligands, and adding hydrogen atoms in PyMOL (v2.5). Ligand structures of JATR components were imported from PubChem, converted to PDBQT format, and docked within a 20 Å × 20 Å × 20 Å grid box centered on the proteins’ active sites using default docking parameters. Binding free energy (kcal/mol) was calculated by the software’s scoring function, and interactions with binding energies ≤ − 7 kcal/mol were considered high-affinity. GES-1 cells culture condition, proliferation, and viability assay Purchased from FuHeng (Shanghai, China), GES-1 cells were cultured in Dulbecco’s Modified Eagle’s Medium containing 10% fetal bovine serum under the following conditions: 5% CO[2] and 95% air-humidified atmosphere at 37 °C in a cell culture chamber. Cell Counting Kit (CCK)-8 was used for cell viability evaluation. The cells were collected, centrifuged, counted, and aliquoted into 96-well plates at a density of 5 × 10^3 cells/well. After pretreatment with JATR solution for 2 h, a 40 mM MNNG solution was incubated for 24 h. CCK-8 detection solution was added to each well and incubated for 1 h. Finally, the absorbance at 450 nm was measured using a Synergy TM H1 instrument (BioTek, American). The viability rate was calculated using the optical density value. Each test was performed three times under the same conditions. Extraction of RNA and analysis by quantitative real-time polymerase chain reaction (qRT-PCR) The total RNA content of GES-1 cells incubated with MNNG and JATR were extracted by Trizol reagent. The total RNA was reverse-transcribed into synthetic cDNA using a Primer Script RT reagent Kit. The relative RNA levels were quantified by qPCR using the SYBR Green Super Mix Kit (Servicebio, China) combined with custom primers (Table [132]4) and the AB7300 thermal cycler (Biosystems, USA). Using GAPDH as the normalization control, the 2−ΔΔCq protocol was used to calculate the relative mRNA expression level (Table [133]5). Table 5. Identified serum differential metabolites from different groups. Groups Differential metabolites HMDB-ID VIP score Up/down Mode Model/vehicle Indole-3-carboxyaldehyde HMDB0029737 2.66 ↓^# ESI^− 1-Methylnicotinamide HMDB0000699 2.39 ↓^# ESI^+ Biochanin A HMDB0002338 2.22 ↓^# ESI^+ 5′-S-Methylthioadenosine HMDB0001173 2.18 ↓^# ESI^+ N-Alpha-acetyllysine HMDB0000446 1.64 ↑^# ESI^− Uracil HMDB0000300 1.45 ↑^# ESI^+ Model/JATR 5′-l-Methylthioadenosine HMDB0001173 2.92 ↑* ESI^+ Kynurenic acid HMDB0000715 2.66 ↑* ESI^− Indol-3-carboxyaldehyde HMDB0029737 2.42 ↑* ESI^− Uracil HMDB0000300 1.82 ↓* ESI^+ 1-Methylnicotinamide HMDB0000699 1.57 ↑* ESI^+ Indoleacetic acid HMDB0000197 1.04 ↓* ESI^+ [134]Open in a new tab *P < 0.05 compared with the Model group (n = 8). ^#P < 0.05 compared with the Vehicle. Statistics analysis All experimental data were displayed as mean ± standard deviation, and SPSS 23.0 (IBM Corp.) software was used for statistics analysis. The data were analyzed using a one-way analysis of variance followed by the Bonferroni method. P < 0.05 was considered a statistically significant difference, with P < 0.01 indicating a highly statistically significant difference. All experimental results were visualized using GraphPad Prism (version 9.0). Conclusions In conclusion, the present study showed that JATR significantly improved gastric damage in CAG model rats. The results suggested the JATR treatment of CAG was primarily associated with the inhibition of pyroptosis and apoptosis-related factors. We consider that these results could form the basis for follow-up studies on JATR treatment for CAG. Electronic supplementary material Below is the link to the electronic supplementary material. [135]Supplementary Material 1^ (1.1MB, pdf) Author contributions Z.S. and S.L. Validation, investigation, data curation, visualization, writing—original draft. Z.F. and Z.Y. Investigation, writing-review and editing. Y.G. and T.Q. Investigation, validation, writing—review and editing. Y.H. and R.Y. Plan and supervise experiments, writing-review and editing. Funding This study was supported by the Chongqing medical scientific research project (Joint project of Chongqing Health Commission and Science and Technology Bureau) of China (No. 2025ZYYB004) and the Guizhou Provincial Basic Research Program (Natural Science) under Grant number Qianke He Foundation-ZK [2024] General 367. Data availability Data will be made available on request. Declarations Competing interests The authors declare no competing interests. Ethics statement All animal procedures were carried out by following the Guide for the Care and Use of Laboratory. The research was approved by the Chongqing Academy of Animal Science Animal Ethics Committee (Approval ID: XKY-20240820). This study is reported following ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments). Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Contributor Information Rong Yu, Email: rongyu2025@yeah.net. Yong He, Email: 104469456@qq.com. References