1.Mechanism of Action of Kaixinsan in Ameliorating Alzheimer's Disease
Xiaoming HE ; Xiaotong WANG ; Dongyu MIN ; Xinxin WANG ; Meijia CHENG ; Yongming LIU ; Yetao JU ; Yali YANG ; Changbin YUAN ; Changyang YU ; Li ZHANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(1):20-29
ObjectiveTo investigate the mechanism of action of Kaixinsan in the treatment of Alzheimer's disease (AD) based on network pharmacology, molecular docking, and animal experimental validation. MethodsThe Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP) and the Encyclopedia of Traditional Chinese Medicine(ETCM) databases were used to obtain the active ingredients and targets of Kaixinsan. GeneCards, Online Mendelian Inheritance in Man(OMIM), TTD, PharmGKB, and DrugBank databases were used to obtain the relevant targets of AD. The intersection (common targets) of the active ingredient targets of Kaixinsan and the relevant targets of AD was taken, and the network interaction analysis of the common targets was carried out in the STRING database to construct a protein-protein interaction(PPI) network. The CytoNCA plugin within Cytoscape was used to screen out the core targets, and the Metascape platform was used to perform gene ontology(GO) functional enrichment analysis and Kyoto encyclopedia of genes and genomes(KEGG) pathway enrichment analysis. The “drug-active ingredient-target” interaction network was constructed with the help of Cytoscape 3.8.2, and AutoDock Vina was used for molecular docking. Scopolamine (SCOP) was utilized for modeling and injected intraperitoneally once daily. Thirty-two male C57/BL6 mice were randomly divided into blank control (CON) group (0.9% NaCl, n=8), model (SCOP) group (3 mg·kg-1·d-1, n=8), positive control group (3 mg·kg-1·d-1 of SCOP+3 mg·kg-1·d-1 of Donepezil, n=8), and Kaixinsan group (3 mg·kg-1·d-1 of SCOP+6.5 g·kg-1·d-1 of Kaixinsan, n=8). Mice in each group were administered with 0.9% NaCl, Kaixinsan, or Donepezil by gavage twice a day for 14 days. Morris water maze experiment was used to observe the learning memory ability of mice. Hematoxylin-eosin (HE) staining method was used to observe the pathological changes in the CA1 area of the mouse hippocampus. Enzyme linked immunosorbent assay(ELISA) was used to determine the serum acetylcholine (ACh) and acetylcholinesterase (AChE) contents of mice. Western blot method was used to detect the protein expression levels of signal transducer and activator of transcription 3(STAT3) and nuclear transcription factor(NF)-κB p65 in the hippocampus of mice. ResultsA total of 73 active ingredients of Kaixinsan were obtained, and 578 potential targets (common targets) of Kaixinsan for the treatment of AD were screened out. Key active ingredients included kaempferol, gijugliflozin, etc.. Potential core targets were STAT3, NF-κB p65, et al. GO functional enrichment analysis obtained 3 124 biological functions, 254 cellular building blocks, and 461 molecular functions. KEGG pathway enrichment obtained 248 pathways, mainly involving cancer-related pathways, TRP pathway, cyclic adenosine monophosphate(cAMP) pathway, and NF-κB pathway. Molecular docking showed that the binding of the key active ingredients to the target targets was more stable. Morris water maze experiment indicated that Kaixinsan could improve the learning memory ability of SCOP-induced mice. HE staining and ELISA results showed that Kaixinsan had an ameliorating effect on central nerve injury in mice. Western blot test indicated that Kaixinsan had a down-regulating effect on the levels of NF-κB p65 phosphorylation and STAT3 phosphorylation in the hippocampal tissue of mice in the SCOP model. ConclusionKaixinsan can improve the cognitive impairment function in SCOP model mice and may reduce hippocampal neuronal damage and thus play a therapeutic role in the treatment of AD by regulating NF-κB p65, STAT3, and other targets involved in the NF-κB signaling pathway.
2.Rapid Identification of Different Parts of Nardostachys jatamansi Based on HS-SPME-GC-MS and Ultra-fast Gas Phase Electronic Nose
Tao WANG ; Xiaoqin ZHAO ; Yang WEN ; Momeimei QU ; Min LI ; Jing WEI ; Xiaoming BAO ; Ying LI ; Yuan LIU ; Xiao LUO ; Wenbing LI
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(2):182-191
ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi, so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS) combined with Smart aroma database and National Institute of Standards and Technology(NIST) database were used to characterize the aroma components in different parts of N. jatamansi, and the aroma components were quantified according to relative response factor(RRF) and three internal standards, and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis(OPLS-DA) and cluster thermal analysis based on variable importance in the projection(VIP) value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose, and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data, and the rapid identification model of different parts of N. jatamansi was established by principal component analysis(PCA), discriminant factor alysis(DFA), soft independent modeling of class analogies(SIMCA) and statistical quality control analysis(SQCA). ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi, of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components, the contents of five components(ethyl isovalerate, 2-pentylfuran, benzyl alcohol, nonanal and glacial acetic acid,) in the aboveground part of N. jatamansi were significantly higher than those in the underground part(P<0.01), the contents of β-ionone, patchouli alcohol, α-caryophyllene, linalyl butyrate, valencene, 1,8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part(P<0.01). Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82, and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted, respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%, the validation score of the SIMCA model for discrimination of the two parts was 99, and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose(PCA, DFA, SIMCA and SQCA) can realize the rapid identification of different parts of N. jatamansi. Combining the two results, it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.
3.Textual Research on Key Information of Famous Classical Formula Jiegengtang
Yang LEI ; Yuli LI ; Xiaoming XIE ; Zhen LIU ; Shanghua ZHANG ; Tieru CAI ; Ying TAN ; Weiqiang ZHOU ; Zhaoxu YI ; Yun TANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(7):182-190
Jiegengtang is a basic formula for treating sore throat and cough. By means of bibliometrics, this study conducted a textual research and analysis on the key information such as formula origin, decocting methods, and clinical application of Jiegengtang. After the research, it can be seen that Jiegengtang is firstly contained in Treatise on Febrile and Miscellaneous Disease, which is also known as Ganjietang, and it has been inherited and innovated by medical practitioners of various dynasties in later times. The origins of Chinese medicines in this formula is basically clear, Jiegeng is the dried roots of Platycodon grandiflorum, Gancao is the dried roots and rhizomes of Glycyrrhiza uralensis, the two medicines are selected raw products. The dosage is 27.60 g of Glycyrrhizae Radix et Rhizoma and 13.80 g of Platycodonis Radix, decocted with 600 mL of water to 200 mL, taken warmly after meals, twice a day, 100 mL for each time. In ancient times, Jiegengtang was mainly used for treating Shaoyin-heat invasion syndrome, with cough and sore throat as its core symptoms. In modern clinical practice, Jiegengtang is mainly used for respiratory diseases such as pharyngitis, esophagitis, tonsillitis and lung abscess, especially for pharyngitis and lung abscess with remarkable efficacy. This paper can provide literature reference basis for the modern clinical application and new drug development of Jiegengtang.
4.Textual Research on Key Information of Famous Classical Formula Jiegengtang
Yang LEI ; Yuli LI ; Xiaoming XIE ; Zhen LIU ; Shanghua ZHANG ; Tieru CAI ; Ying TAN ; Weiqiang ZHOU ; Zhaoxu YI ; Yun TANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(7):182-190
Jiegengtang is a basic formula for treating sore throat and cough. By means of bibliometrics, this study conducted a textual research and analysis on the key information such as formula origin, decocting methods, and clinical application of Jiegengtang. After the research, it can be seen that Jiegengtang is firstly contained in Treatise on Febrile and Miscellaneous Disease, which is also known as Ganjietang, and it has been inherited and innovated by medical practitioners of various dynasties in later times. The origins of Chinese medicines in this formula is basically clear, Jiegeng is the dried roots of Platycodon grandiflorum, Gancao is the dried roots and rhizomes of Glycyrrhiza uralensis, the two medicines are selected raw products. The dosage is 27.60 g of Glycyrrhizae Radix et Rhizoma and 13.80 g of Platycodonis Radix, decocted with 600 mL of water to 200 mL, taken warmly after meals, twice a day, 100 mL for each time. In ancient times, Jiegengtang was mainly used for treating Shaoyin-heat invasion syndrome, with cough and sore throat as its core symptoms. In modern clinical practice, Jiegengtang is mainly used for respiratory diseases such as pharyngitis, esophagitis, tonsillitis and lung abscess, especially for pharyngitis and lung abscess with remarkable efficacy. This paper can provide literature reference basis for the modern clinical application and new drug development of Jiegengtang.
5.Jiawei Xiaoyao San exerts anti-liver cancer effects via exosomal miRNA pathway
Xiaoming LIU ; Jinlai CHENG ; Rushuang LI ; Niuniu LI ; Qiuyun QIN ; Meng XIA ; Chun YAO
Chinese Journal of Tissue Engineering Research 2025;29(19):4052-4062
BACKGROUND:Previous studies by our research group discovered that Jiawei Xiaoyao San has a significant anti-liver cancer effect,but the specific mechanism of action was unclear. OBJECTIVE:To investigate the regulatory effects of the traditional Chinese medicine formula Jiawei Xiaoyao San on the levels of miRNAs in plasma exosomes of rats with diethylnitrosamine chronically induced primary liver cancer,based on high-throughput sequencing combined with bioinformatics. METHODS:SD rats were randomly divided into a blank control group,a liver cancer model group,and a Jiawei Xiaoyao San treatment group.Liver cancer models were induced by continuous administration of diethylnitrosamine for 12 weeks.Starting from the 17th week,rats in the Jiawei Xiaoyao San treatment group were administered Jiawei Xiaoyao San once daily until the end of the 20th week,while rats in the blank control and liver cancer model groups were given an equivalent volume of saline.Anti-hepatocellular carcinoma effects were validated by assessing the morphological structure of rat liver tissues,along with the expression of the hepatocellular carcinoma markers,Glypican-3 protein and serum alpha-fetoprotein.Plasma exosomes from each group of rats were isolated using ultracentrifugation.High-throughput sequencing technology was used to screen for differentially expressed miRNAs in rat plasma exosomes.Bioinformatics was used to predict the potential biomarkers through which Jiawei Xiaoyao San exerts its anti-liver cancer effects via liver cancer-derived exosomal miRNAs,followed by functional analysis. RESULTS AND CONCLUSION:(1)Jiawei Xiaoyao San significantly improved the morphological structure of liver tissues in a rat model of liver cancer.Compared with the liver cancer model group,the expression of liver cancer markers Glypican-3 protein and serum alpha-fetoprotein was significantly reduced in the Jiawei Xiaoyao San treatment group.(2)Bioinformatics analysis showed that in the Jiawei Xiaoyao San group,upregulated miR-223-3p in the liver cancer model group had target binding sites with genes E2F1 and NCOA1,which were closely related to liver cancer survival and prognosis.Therefore,Jiawei Xiaoyao San has a therapeutic effect on liver cancer,possibly by targeting negative regulation of NCOA1/E2F1 through liver cancer plasma-derived exosomal miR-223-3p,thereby playing anti-liver cancer effect.
6.Construction of recombinant epitope tandem vaccine of herpes simplex virus type 1 glycoprotein B and glycoprotein D and its immunoprotective effect
Yuxuan LIU ; Xiaoming DONG ; Jikun YANG ; Jinsong ZHANG ; Jing WANG
International Eye Science 2025;25(4):530-536
AIM: To design and construct recombinant epitope nucleotides vaccine of glycoprotein B(gB)and glycoprotein D(gD)of herpes simplex virus type 1(HSV-1), and to investigate its immunoprotective effects and tissue expression in animal models.METHODS: The HSV-1 gB and gD epitope genes were selected and tandem assembled to construct the recombinant protein-coding gene X, which was transducted into the prokaryotic expression vector pET28(a). The recombinant protein was synthesized and utilized to generate monoclonal antibodies, which were subsequently used to immunize New Zealand white rabbits. The immunogenicity of the purified protein and the presence of polyclonal antibodies in the serum were tested through separating serum from cardiac blood, and the serum antibody titers were determined. The pcDNA3.1-X was successfully constructed as a eukaryotic expression vector and immunized the female BALB/c mice aged 4 to 6 wk via intramuscular injection. Serum antibodies and immune-related cytokines were quantified using enzyme-linked immunosorbent assay(ELISA). The expression of the X protein in the ocular, trigeminal ganglion, and brain tissues of the mice was assessed.RESULTS: The target polyclonal antibody was identified with a serum antibody titer of 1:3200 in the rabbit serum after immunized by recombinant protein X. Upon immunizing mice with the eukaryotic recombinant plasmid pcDNA3.1-X, the concentration of HSV-1 serum IgM antibodies of the experimental group was 12.13±0.85 ng/L, which was significantly higher than that of the vector control group(0.49±0.44 ng/L; t=21.07, P<0.001). The concentrations of cytokines interleukin IL-2, IL-4, IL-10, and IFN-γ in the experimental group were 11.63±0.60, 22.65±1.47, 85.75±14.12, and 114.90±6.39 ng/L, respectively, all of which were significantly higher than those in the vector control group and the blank control group(all P<0.05). Immunohistochemical staining revealed the presence of target protein X in the eyeball, trigeminal ganglion, and brain tissue.CONCLUSION: The HSV-1 gB and gD tandem epitope nucleotides vaccine pcDNA3.1-X was successfully constructed, which activates a remarkable immune response and is stably expressed in the eyeball, trigeminal ganglion, and brain tissue. This study provides a foundation for further research of an HSV-1 recombinant antigen epitope tandem vaccine.
7.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
8.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
9.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
10.Protective effect and mechanism of Longshengzhi capsules on cerebral ischemia-reperfusion injury in rats
Huanle FANG ; Xiaoming LI ; Yaming ZHOU ; Xin ZHANG ; Xiaoxi LIU ; Yanbin CHEN
China Pharmacy 2024;35(7):813-818
OBJECTIVE To explore the protective effect and mechanism of Longshengzhi capsules on cerebral ischemia- reperfusion injury in rats. METHODS The model of middle cerebral artery occlusion (MCAO) was established by using the improved thread occlusion method. The experiment was divided into six groups: sham surgery group (only separating blood vessels without inserting thread plugs, given the same volume of normal saline), model group (modeling, given the same volume of normal saline), nimodipine group (positive control, modeling, dose of 20 mg/kg), and low-dose, medium-dose, and high-dose groups of Longshengzhi capsules (modeling, doses of 0.72, 1.44 and 2.88 g/kg, respectively), with 10 mice in each group. Each group was given corresponding medication solution/normal saline by gavage, once a day, for 7 consecutive days. One hour after the last administration, the Zea Longa scoring method was used to score the neurological deficits in each group of rats, and the ABC enzyme-linked immunosorbent assay was used to detect the serum levels of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in rats; TTC staining was used to observe the volume of cerebral infarction in rats and calculate the cerebral infarction volume ratio. Hematoxylin eosin staining was used to observe the pathological changes in the brain tissue of rats. Immunohistochemical staining was used to detect the positive expression of NLRP3 protein in the brain tissue of rats. Real-time fluorescence quantitative PCR was used to detect mRNA relative expressions of Toll-like receptor 4 (TLR4) and nuclear factor-κB (NF-κB) in the brain tissue of rats. Western blot assay was adopted to detect the relative expressions of TLR4, NLRP3 and phosphorylated NF-κB (p-NF-κB) protein in the brain tissue of rats and its intracellular NF-κB protein. RESULTS Compared with the sham surgery group, the neural dysfunction score, serum levels of TNF-α and IL-6, cerebral infarction volume ratio, relative expression levels of NF-κB and TLR4 mRNA, as well as protein relative expressions of TLR4, NLRP3 and p-NF-κB in the brain tissue, and relative protein expression of intracellular NF-κB were increased significantly in the model group (P<0.01); the enlarged gap and significant edema were observed in cortical nerve cells of brain tissue in rats, with a large amount of inflammatory cell infiltration; the positive expression of NLRP3 protein in brain tissue of rats obviously increased. Compared with the model group, the levels of the above indicators in the medium-dose and high-dose groups of Longshengzhi capsules, as well as the Nimodipine group, were reversed to varying degrees, and most differences were statistically significant (P<0.05 or P<0.01); the pathological morphology observation showed a significant improvement, and the positive expression of NLRP3 protein in the brain tissue of rats was obviously reduced. CONCLUSIONS Longshengzhi capsules may inhibit TLR4/NF-κB/NLRP3 signaling pathway and neuroinflammatory response, thereby achieving a protective effect against cerebral ischemia-reperfusion injury in rats.

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