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. 2026 Mar 16;11(12):19440–19453. doi: 10.1021/acsomega.5c13079

Research on the Molecular Mechanism of Ginsenoside Ro in Neuronal Damage Following Subarachnoid Hemorrhage

Jinpeng Wang ‡, Zhixin Zhang §, Jia Liu ‡, Yuemiao Wang ‡, Yuerong Wang †, JingJun Zhang ∥,*, Liangjie Yuan †,*
PMCID: PMC13044643  PMID: 41939302

Abstract

Previous studies have demonstrated the anti-inflammatory, antidepressant, and neuroprotective effects of Ginsenoside Ro. Subarachnoid hemorrhage (SAH), a stroke subtype characterized by bleeding into the subarachnoid space following rupture of intracranial vessels, results in early brain injury (EBI), which critically influences prognosis. Currently, specific treatments for SAH-induced EBI are lacking. This study aimed to investigate the mechanism by which Ginsenoside Ro ameliorates neural injury following SAH, utilizing network pharmacology, molecular docking, qRT-PCR, and Western blot. In this study, we identified 88 common interaction targets between Ginsenoside Ro and SAH. Protein–protein interaction (PPI) network analysis revealed core targets, including TNF-α, EGFR, Bcl-2, SRC, and MMP9. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that these targets are involved in biological processes such as apoptosis, inflammatory response, and blood–brain barrier repair, primarily modulating the MAPK, PI3K-Akt, and estrogen signaling pathways. Molecular docking confirmed strong binding affinity between Ginsenoside Ro and the core targets SRC, EGFR, MMP9, and Bcl-2. Results demonstrated that Ro significantly modulates the expression of EGFR and Bcl-2, and Ginsenoside Ro could significantly enhance cell viability. These findings suggest that Ginsenoside Ro may mitigate SAH-induced neural injury by regulating the EGFR and Bcl-2 pathways, providing a theoretical foundation for potential clinical applications.

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Introduction

Subarachnoid hemorrhage (SAH), a type of stroke characterized by bleeding into the subarachnoid space due to the rupture of blood vessels at the base or on the surface of the brain, manifests with corresponding clinical symptoms. Statistics indicate a global incidence of SAH approximately 9 per 100,000 individuals, with a mortality rate as high as 40%–50%. , With the aging population and the increasing prevalence of hypertension, the need for effective SAH prevention has become increasingly urgent.

The clinical management of SAH encompasses acute phase treatment and prevention of complications. Clinical practice relies on supportive care, such as maintaining cerebral perfusion pressure and controlling intracranial pressure. Concurrently, most targeted intervention addressing pathological mechanisms like inflammation, oxidative stress, and cell apoptosis remain at the experimental stage. , Clinical management has certain limitations. For example, nimodipine may induce adverse cardiovascular effects, including hypotension and tachycardia; , endovascular interventional therapy may be complicated by vascular injury or thrombosis. These limitations underscore the necessity to develop safer and more effective therapeutic strategies.

Ginseng has been utilized as a medicinal herb in China for millennia. Modern pharmacological studies have identified ginsenosides as the primary active components of ginseng, with significant medicinal value. Ginsenosides share a common basic structure, all containing a steroidal nucleus composed of 30 carbon atoms arranged in four rings. Based on differences in the structure of their glycosyl groups, they can be classified into three types: protopanaxadiol-type (PPD, Type A) (e.g., Rb1, Rb2, Rb3, Rc, Rd, Rg3, and Rh2), protopanaxatriol-type (PPT, Type B) (e.g., Re, Rg1, Rg2, and Rh1), and oleanolic acid-type (OA, Type C) (e.g., Ro). We have reviewed existing data and summarized the molecular structures of ginsenosides, as presented in Figure . These steroidal saponins demonstrate a range of pharmacological effects, including anticancer, anti-inflammatory, antidepressant, antiaging, immunomodulatory, and neuroprotective activities. In various models of neurological diseases, ginsenosides exert neuroprotective effects through multiple targets. For instance, Ginsenoside Rg1, a major component of ginseng, has garnered extensive attention in the prevention of neurological diseases. It can alleviate early, middle, and late stages of Alzheimer’s disease (AD) by repairing dendrites and axons, and reducing microglia- and astrocyte-related inflammation; Ginsenoside Rd can effectively inhibit SAH-induced ferroptosis of neurons via the cGAS/STING pathway in rats; Ginsenoside Ro could effectively improve cognitive impairment and neuroinflammation in APP/PS1 mice through the IBA1/GFAP-MAPK signaling pathway.

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Classification and Chemical Structures of Ginsenosides. (All chemical structures is sourced from the public database PubChem database (https://pubchem.ncbi.nlm.nih.gov/)).

This study will explore the potential targets and pathways of Ginsenoside Ro in the treatment of SAH, elucidate its possible molecular mechanism, and provide a theoretical basis for the development of clinically valuable prodrugs.

Materials and Methods

Materials

The mouse hippocampal neuron cell line HT22 (Mus musculus hippocampal neuron cell line HT22) was purchased from Wuhan Procell Life Technology Co., Ltd. Ginsenoside Ro (CAS No. B21068, purity ≥98%) was obtained from Shanghai Yuanye Bio-Technology Co., Ltd. (Shanghai, China). Fetal bovine serum (FBS, batch No. A525670) was acquired from Gibco (USA). SteadyPure Rapid RNA Extraction Kit (batch No. AG21023) was obtained from Hunan Aikerui Biotechnology Co., Ltd. HiFiScript cDNA Synthesis Kit (batch No. CW2569M) and Magic SYBR Mixture (SYBR dye-based qPCR mix, batch No. CW3008M) were purchased from CWBIO Co., Ltd. Primers for Src tyrosine protein kinase, B-cell lymphoma 2 (Bcl-2), epidermal growth factor receptor (EGFR), matrix metalloproteinase 9 (MMP9), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) were synthesized by Wuhan Sevier Biotechnology Co., Ltd.

Network Pharmacology Methods

Screening of Potential Targets for Ginsenoside Ro

Using “Ginsenoside Ro” as the keyword and restricting the search object to “Homo sapiens”, the standard molecular structure of Ginsenoside Ro was retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) including its SMILES notation, PubChem CID, and SDF file. These files were uploaded to three target prediction platforms: Swiss Target Prediction (http://www.swisstargetprediction.ch/), PharmMapper (http://www.lilab-ecust.cn/pharmmapper/), and BATMAN-TCM (http://bionet.ncpsb.org/batman-tcm/). Screening parameters were set according to each platform’s standard specifications: “probability >0” for SwissTarget Prediction, “score cutoff >20 and P-value <0.05” for Batman-TCM, and “Norm Fit ≥ 0.9” for PharmMapper. Potential targets were comprehensively collected from these platforms. The targets predicted by the three databases were fully integrated, their naming conventions were carefully checked and standardized, and duplicate data were removed after formatting unification. To ensure the standardization of target information, all predicted targets were validated using the UniProt database (https://www.uniprot.org/), with their ID numbers and naming conventions unified. This step aimed to guarantee the accuracy and reliability of subsequent network construction, pathway enrichment, and mechanism-of-action analysis.

Screening of SAH-Related Targets

Using “subarachnoid hemorrhage” as the keyword, relevant disease targets were collected from the GeneCards database (https://www.genecards.org/) and the OMIM database (https://www.omim.org/). To ensure screening rigor, the median target “score” was set as the threshold for both databases. Targets retrieved from the above databases were merged and deduplicated to identify high-confidence potential key genes. A Venn diagram was constructed to visualize the overlap between Ginsenoside Ro targets and SAH-related targets, yielding their intersection.

Construction of Protein–Protein Interaction Networks (PPI)

We imported the 88 common targets of Ginsenoside Ro and SAH into the STRING database (https://string-db.org/). Using “Multiple names” and “H. sapiens” as search criteria, we set the interaction confidence score threshold to >0.7 to construct the PPI network diagram of common targets. The STRING-generated results were imported into Cytoscape software (version 3.9.1). The “Analyze Network” function was used to calculate the degree values of each node in the network, followed by the “CentiScape 2.2” plugin to screen key targets based on three topological parameters: Degree, Closeness, and Betweenness. In the PPI network, targets are represented as nodes and protein interactions as edges. Nodes with varying colors and sizes indicate different degree values, with larger and redder nodes signifying higher degree values and greater target importance.

GO Enrichment and KEGG Pathway Analysis

GO analysis and KEGG pathway analyses were performed using the DAVID database (https://david.ncifcrf.gov/home.jsp). The overlapping targets were uploaded to the DAVID database for GO enrichment and KEGG pathway analysis. After running the analysis, enrichment results were obtained. Upon completion of the enrichment analysis, the clustered network was exported and sorted by P-values. For GO enrichment analysis, the top 10 representative results from Biological Processes (BP), Cellular Components (CC), and Molecular Functions (MF) categories were selected. Key indicators for different GO classifications and corresponding visualizations were determined. Using the DAVID Web site, the top 20 pathways most strongly associated with SAH were selected for KEGG pathway analysis.

Molecular Docking

We used molecular docking to investigate interactions between Ginsenoside Ro and key SAH targets, focusing on targets with higher “Degree” values. The 2D structure file of Ginsenoside Ro was downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov), imported into Chem3D software to convert to a 3D structure file, and then processed in Pymol software for dehydration and removal of residual ligands. Target protein structures were downloaded from the PDB database (https://www.rcsb.org/) and imported into AutoDock Tools 1.5.7 for hydrogenation, charge calculation, and nonpolar hydrogen bond optimization. The CavityPlus Server (http://repharma.pku.edu.cn/cavityplus) was used to identify docking active sites, followed by molecular docking and binding energy calculations using AutoDock Vina software. Pymol was used to visualize docking results, clearly demonstrating interactions between Ginsenoside Ro and the core SAH target proteins.

qRT-PCR Assay

HT22 cells were cultured in high-glucose DMEM medium supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin. Cells were maintained at 37 °C in a 5% CO2 incubator, and logarithmic growth phase cells were used for experiments. HT22 cells were seeded at 4 × 105 cells/well in a 6-well plate and cultured overnight. Ginsenoside Ro was dissolved in PBS (0.1 mM) to form a stock solution (50 mmol/L), then diluted with cell culture medium to desired working concentrations (12.5, 25, 50, 100 μmol/L). The cells were treated with Ginsenoside Ro at varying concentrations (0 μM, 12.5 μM, 25 μM, 50 μM, and 100 μM) for 24 h. After 24 h treatment, observe cellular morphological changes under an inverted biological microscope and harvest cells. Extract total cellular RNA and synthesize cDNA according to the kit instructions for qRT-PCR analysis. Using GAPDH as an internal reference, the relative mRNA expression levels of target genes were computed using the 2–ΔΔCt method. The primer sequences are presented in Table .

1. Primer Sequences.

Gene Forward primer (5′-3′) Reverse primer (5′-3′)
SRC AGATCACTAGACGGGAATCAGAGC GCACCTTTTGTGGTCTCACTCTC
Bcl-2 TGACTTCTCTCGTCGCTACCGT CCTGAAGAGTTCCTCCACCACC
EGFR TGACTGTCTGGTCTGCCAAAAG ATGCCATCTTCTTCCACTTCGT
MMP9 GCTGGCAGAGGCATACTTGTAC GGTGTTCGAATGGCCTTTAGTG
GAPDH CCTCGTCCCGTAGACAAAATG TGAGGTCAATGAAGGGGTCGT
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Cell Viability

Cell viability was detected using the CCK-8 reagent. HT22 cells were seeded at a density of 1 × 105 cells/mL per well in a 96-well plate, with 100 μL of cell suspension per well. When the cell fusion rate reached over 90%, Ginsenoside Ro (100 μM) was preincubated for 1 h, followed by cotreatment with 80 μM hemoglobin for 24 h. A total of 10 μL of CCK-8 solution was added per well, and the plate was incubated at 37 °C for 2 h. The absorbance at 450 nm wavelength was measured using an enzyme-labeled instrument, and cell viability was calculated.

Western Blot

Cells were lysed using RIPA lysis buffer to obtain protein extracts, the concentrations of the protein were quantified with a BCA kit. Protein samples were boiled for 5 min. The proteins were separated by polyacrylamide sulfate gel electrophoresis and blocked with 5% skim milk for 2 h, and then primary antibodies (EGFR or Bcl-2) were incubated overnight at 4 °C. Subsequently, specific secondary antibodies were incubated at room temperature for 2 h. The antigen–antibody complexes were detected with enhanced chemiluminescence (ECL) reagent and visualized by Imager.

Statistical Analysis

The data were presented as the mean ± standard error of the mean (SEM). Statistical analyses were performed using GraphPad Prism Software 5.0 (USA). One-way analysis of variance (ANOVA) followed by Tukey’s posthoc tests was employed to compare distinct groups. The threshold for statistical significance was set at p < 0.05.

Results

Identification of Ginsenoside Ro Targets Involved in SAH

After removing duplicates from the Swiss Target Prediction, PharmMapper, and Batman-TCM databases, a total of 313 potential targets for Ginsenoside Ro were identified. Following searches within the GeneCards and OMIM databases, a cumulative total of 1845 SAH-associated targets were acquired subsequent to merging and deduplication procedures. The Venn diagram depicts the targets of Ginsenoside Ro and SAH (Figure ), indicating 88 overlapping targets, which constitute 4.3%. These shared targets potentially function as crucial therapeutic targets for Ginsenoside Ro in the treatment of SAH.

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Venn diagram of common targets between Ginsenoside Ro and SAH.

PPI Network Diagram and Core Gene Screening

Using the STRING database, 88 common targets were imported to construct a protein–protein interaction (PPI) network. This network consisted of 72 nodes connected by 774 edges (Figure ). Leveraging Cytoscape facilitated a comprehensive analysis of node topological features and produced an optimized and visually intuitive PPI network diagram (Figure A). The PPI network demonstrates intricate interactions among potential targets, where the significance of nodes is denoted by their size and colorlarger nodes and darker colors representing higher importance. By setting thresholds for “Closeness”, “Betweenness”, and “Degree”, the top 10 core targets were identified. Utilizing Cytoscape, a core target network diagram (Figure B) was constructed, which included TNF, EGFR, Bcl-2, SRC, MMP9, NFKB1, ALB, MAPK1, ESR1, and IGF1.

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PPI network map of intersecting targets.

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PPI Network Visualization (A) visualization of PPI network for intersecting targets. (B) Visualization of PPI network for the top 10 targets with the highest Degree values.

EBI, encompassing neuronal apoptosis, serves as a fundamental cause of neurological deterioration subsequent to SAH. Post-SAH, the expression of activated epidermal growth factor receptor (EGFR), nuclear factor-κB-inducing kinase (NIK), and nuclear factor-κB (NF-κB) was detected in degenerating cortical neurons. The EGFR/NIK/NF-κB pathway has been implicated in neuronal apoptosis subsequent to SAH , in mice. Matrix metalloproteinase-9 (MMP9) plays a pivotal role in blood-brain barrier (BBB) disruption and cerebral edema following SAH. During the early injury phase subsequent to SAH, the expression and activity of MMP9 increase significantly. By degrading extracellular matrix proteins, damaging tight junction proteins, and disrupting the basement membranes of blood vessels, MMP9 enhances the permeability of the BBB, thereby leading to cerebral edema and secondary convulsions. The expression of MMP9 may be regulated by cytokine signaling pathways, including the NF-κB and mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathways. Activation of these pathways further potentiates the effects of MMP9, resulting in exacerbated BBB disruption. Modulating these signaling pathways may effectively alleviate MMP9-induced cerebral edema and neural injury, presenting potential therapeutic targets for the management of SAH.

GO Enrichment Analysis

We conducted GO enrichment analysis on 88 potential targets via the DAVID database, which included analyses of biological process (BP), cellular component (CC), and molecular function (MF). This analysis resulted in 562 statistically significant GO entries. Among them, 408 BP entries demonstrated that differentially expressed genes were significantly enriched in pathways including positive regulation of cell migration, response to bacteria, and response to wound. This implies that the gene set might play a pivotal role in cellular dynamic behaviors (such as migration and repair) and immune responses (such as bacterial recognition). 49 CC entries predominantly encompassed subcellular structures, such as vacuoles, extracellular matrix, and membrane rafts. 105 MF entries were correlated with enzyme activity pathways typified by protein kinase activity and endopeptidase activity, along with molecular interaction pathways like protease binding and glycosaminoglycan binding. GO terms were ranked according to the p-value, and the top 10 entries with the lowest p-values from each category were visualized via MicroBioinformatics. The most significant entries were intuitively presented in the enrichment analysis diagram (Figure ).

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GO function enrichment analysis (top 10). (A) The size of each bubble corresponds to the gene expression in a specific pathway, and the color saturation of the bubble indicates the significance of enrichment. (B) This histogram shows the top 10 enriched items for each GO category (BP, CC, and MF) with small P-values among 88 potential targets. The P-value reflects the statistical significance of enrichment, and the smaller the P-value, the higher the significance.

KEGG Pathway Analysis

In order to uncover the specific signaling pathways associated with the 88 potential targets, we imported these targets into the DAVID database for KEGG pathway analysis. This analysis identified a total of 168 enriched signaling pathways, which were sorted according to the P-value. The top 20 representative entries were presented in a statistically significant bubble plot and a classification histogram for visualization purposes (Figure ). KEGG pathways exhibited significant clustering and were closely associated with pathways related to environmental information processing (e.g., MAPK signaling pathway, PI3K/Akt signaling pathway, Ras signaling pathway), cellular processes (e.g., apoptosis, focal adhesion), and organism-system pathways (e.g., relaxin signaling pathway, estrogen signaling pathway, T cell receptor signaling pathway, pathways associated with organism systems, and pathways related to human diseases such as pathways in cancer, lipid and atherosclerosis, and proteoglycans in cancer).

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Diagram of KEGG enrichment analysis (top 20). (A) The bubble chart shows the top 20 enriched KEGG signaling pathways in the reverse order of P-values. Each bubble represents a specific pathway, where the bubble area indicates the number of enriched genes in the pathway. The intensity of the bubble color indicates the importance of enrichment, and the depth of red represents higher importance. (B) The histogram illustrates the enrichment frequency and significance of each pathway. The length of each bar corresponds to the gene count, representing the enrichment score and significance level. A taller bar indicates a larger count and a higher degree of enrichment.

Pathway Enrichment Analysis of Core Targets

The 10 core targets of Ginsenoside Ro and SAH were imported into the DAVID database. Analysis of classical pathways, including KEGG enrichment analysis, was conducted, and a horizontal gradient bar chart (Figure ) was generated, displaying the top 20 enriched pathways with the lowest FDR values. In Figure , the length of each bar corresponds to the proportion of overlapping genes and the relative enrichment value within a specific pathway. Orange squares represent genes in each pathway. Notably, the estrogen signaling pathway plays a crucial role in the repair of subarachnoid hemorrhage (SAH)-induced neural damage by Ginsenoside Ro, which is consistent with previous relevant research findings. Importantly, among the core targets involved in this pathway (shown in Figure ), EGFR and Bcl-2two targets we have validated at both the mRNA and protein levels-occupy pivotal positions in the estrogen signaling pathway (shown in Figure ), serving as the core regulatory nodes that link Ginsenoside Ro to the neuroprotective function of this pathway. These two targets, together with other related genes such as MAPK1 and MMP9, form a key regulatory module within the estrogen signaling pathway, which may be speculated to be the critical molecular link underlying the neuroprotective effect of Ginsenoside Ro against SAH-induced injury.

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Horizontal gradient bar chart with overlapping genes of KEGG enrichment analysis of core targets (top 20).

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Effect of Ginsenoside Ro on the mRNA expressions of Bcl-2, EGFR, MMP9, and SRC in HT22 cells (x̅ ± s, n = 3). The mRNA expression levels of Bcl-2, EGFR, MMP9, and SRC between controls and Ro treatment groups were detected by real-time quantitative polymerase chain reaction (A–D). Effect of Ginsenoside Ro on the protein expressions of Bcl-2, EGFR (E–G). Results are shown as x̅ ± s, n = 3, * p < 0.05.

A Sankey + dot plot diagram was generated for the seven pathways most significantly associated with SAH (Figure ). The left panel displays a chord diagram illustrating gene pathway associations, where thicker lines and darker colors indicate stronger correlations. The right-hand side showcases a bubble diagram that emphasizes highly enriched pathways. Darker hues and larger bubbles signify a higher degree of gene enrichment within the pathway. The figure indicates a notable enrichment of lipid and atherosclerosis pathways in the right bubble diagram, encompassing associated genes such as CYP2C8, SRC, EGFR, MAPK1, NFKB1, Bcl-2, SOD2, and MMP9. These genes offer novel targets and insights for exploring therapeutic strategies against SAH from multiple perspectives, including inflammation, oxidative stress, and lipid metabolism.

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KEGG Sankey + dot plot.

Molecular Docking Results

We selected four core targets with high degree values and pathway relevance for molecular docking with Ginsenoside Ro. The affinities between Ginsenoside Ro and SRC, epidermal growth factor receptor (EGFR), matrix metalloproteinase-9 (MMP9), and Bcl-2 were −10.1, −9.1, −9.1, and −9.7 kcal/mol, respectively, indicating strong binding activity across all targets. Generally, docking energy values below −4.25 kcal/mol indicate moderate binding activity, values below −5.0 kcal/mol indicate good binding activity, and values below −7.0 kcal/mol indicate strong binding activity. Visualization using PyMOL revealed the lowest-energy binding conformation (Figure ).

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Affinities between Ginsenoside Ro and Bcl-2­(A), EGFR­(B), MMP9­(C), SRC­(D).

Ginsenoside Ro Upregulates the mRNA and Protein Expression of Bcl-2 and EGFR

To verify whether Ginsenoside Ro exerts its effects by regulating the gene expression of SRC, EGFR, MMP9, and Bcl-2, this study carried out qRT-PCR experiments. The results presented in Figure A–D demonstrate that the relative Bcl-2 mRNA expression showed an overall upward trend at different Ro concentrations (ranging from 12.5 μM to 100 μM) following 24 h cell treatment. The Bcl-2 mRNA expression in the 100 μM Ro-treated group was significantly higher than that in the control group (P < 0.05). The relative expression of EGFR mRNA gradually increased, with the expression in the 100 μM Ro-treated group being significantly higher than that in the control group (P < 0.05). For MMP9 mRNA and SRC mRNA relative expression levels, showed a slight initial increase followed by stabilization across different Ro concentrations (0, 12.5 μM, 25 μM, 50 μM, 100 μM), with no significant differences between groups. We also detected the protein expression of Bcl-2 and EGFR. The results showed that 100 μM Ginsenoside Ro could significantly upregulate the protein expression of EGFR (P < 0.05). The protein expression level of Bcl-2 was upregulated by 23.9%, but there was no significant change.

Ginsenoside Ro Enhances the Vitality of HT22 Cells by Upregulating the Protein Expression of Bcl-2

In order to further investigate the molecular mechanism of the protective effect of Ginsenoside Ro on neurons after subarachnoid hemorrhage, we established a hemoglobin-induced subarachnoid hemorrhage (SAH) cell model using HT22 neurons. The cells were treated with 100 μM Ro for 24 h. The results showed that 100 μM Ro significantly enhanced the cell viability compared with the SAH group (Figure A). 100 μM Ro could significantly upregulate the expression of antiapoptotic protein Bcl-2 compared with the SAH group. (Figure B)

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Protective effect of Ginsenoside Ro on hemoglobin-induced HT22 cell damage (x̅ ± s, n = 3). Cell viability was detected by CCK-8 (A); The protein expression of Bcl-2 was detected by Western blot (B). SAH vs Control group,*p < 0.05; SAH vs Ro (100 μM)+SAH, # p < 0.05.

Discussion

Bcl-2 is a core protein in the Bcl-2 family, which exhibits antiapoptotic functions. Located on organelle membranes, it engages in interactions with other family members to preserve the integrity of the mitochondrial membrane. This action inhibits the release of pro-apoptotic factors, such as cytochrome c, into the cytoplasm, consequently obstructing the apoptotic process. In the realm of SAH research, a multitude of studies have disclosed a strong correlation between Bcl-2 and SAH. ,, 24 h subsequent to SAH, widespread neuronal apoptosis transpires in the cerebral cortex, accompanied by a substantial decline in the expression levels of Bcl-2. Upregulation of Bcl-2 suppresses neuronal apoptosis and alleviates early brain injury subsequent to SAH. This suggests Bcl-2 may serve as a key regulatory target for counteracting early post-SAH brain injury. Subsequent to SAH, ferrous ions released from decomposed blood components can initiate the Fenton reaction, leading to the generation of a significant quantity of reactive oxygen species (ROS) and inducing oxidative stress. Direct impairment to mitochondria leads to the disruption of membrane structure. Since Bcl-2′s antiapoptotic function depends on binding to mitochondrial membranes, membrane disruption reduces Bcl-2 stability, making it more susceptible to proteasome degradation. This alters mitochondrial membrane permeability and accelerates neuronal apoptosis. Additionally, oxidative stress promotes the expression of pro-apoptotic proteins and activates the caspase family to initiate apoptosis. Therefore, the role of Ginsenoside Ro in upregulating Bcl-2 is crucial. This action may enhance mitochondrial membrane stability to reduce the release of pro-apoptotic factors such as cytochrome c. It may also antagonize pro-apoptotic proteins and cross-regulate pathways including endoplasmic reticulum stress and PI3K/AKT, thereby inhibiting neuronal apoptosis. This holds significant potential value for mitigating early brain injury following SAH. In this study, Ginsenoside Ro can upregulate the gene expression of Bcl-2, and there is an upward trend in protein expression, but it is not statistically significant. In the ex vivo SAH model, Ginsenoside Ro could upregulate the expression of Bcl-2 protein, indicating that under pathogenic conditions, Ginsenoside Ro has the effect of inhibiting cell apoptosis and enhancing cell viability, which is related to upregulating Bcl-2 protein expression.

The EGFR is closely associated with cardiovascular diseases. Following SAH, oxygenated hemoglobin can activate heparin-binding epidermal growth factor (HB-EGF) with high affinity for heparin via matrix metalloproteinases. HB-EGF then binds to EGFR, inhibiting potassium channels and causing contraction of cerebral arterial smooth muscle cells. Following SAH, expression of other EGFR ligands such as tenascin-C (TNC) is also significantly upregulated. This coordinated change in the ligand family is not coincidental but represents a key feature of EGFR activation in the pathological process of SAH. Experimental evidence indicates that SAH activates EGFR, contributing to cerebral vasospasm development, a process likely mediated through the EGFR-ERK1/2 pathway. Additional studies suggest the EGFR/NIK/NF-κB pathway participates in neuronal apoptosis following mouse SAH. In summary, EGFR overexpression in the pathological context of SAH may be associated with cerebral vasospasm. Some studies have certified that heightened EGFR expression might contribute to the repair of vascular injury. The upregulating effect of Ginsenoside Ro on EGFR warrants further investigation.

Mitogen-activated protein kinase (MAPK) is implicated in cerebral vasospasm following SAH. In a canine model of secondary SAH, the upstream MAPK regulator SRC tyrosine kinase (SRC) was found to contribute to severe cerebral vasospasm development. The mechanism remains unclear, but it is speculated to involve platelet-derived growth factor receptor (PDGFR). Under oxidative stress, ROS may indirectly phosphorylate PDGFR by activating SRC, leading to cerebral vasospasm. This provides crucial clues for exploring the joint role of SRC and PDGFR in cerebral vasospasm. Furthermore, SRC exhibits additional biological effects in the pathophysiological processes following SAH. Studies indicate that inhibiting phosphorylated SRC (p-SRC) reduces vascular permeability, alleviates cerebral edema, decreases degradation of VE-cadherin and p120-catenin, maintains blood-brain barrier integrity, and mitigates EBI. However, another study indicates that activating the SRC/EGFR/STAT3 signaling pathway suppresses neuronal apoptosis. Within this pathway, SRC trans-activates EGFR, phosphorylating the downstream signaling molecule STAT3. STAT3 phosphorylation may participate in the upregulation of the antiapoptotic protein Bcl-2, which is likely the primary mechanism underlying its neuroprotective effects.

Following cerebral hemorrhage, the expression level of MMP9 in brain tissue increases, exacerbating early brain injury and cerebral vasospasm after SAH. MMP9 can mediate apoptosis by cleaving extracellular matrix through the FasL/Fas pathway. Furthermore, MMP9 degrades matrix components and tight junction proteins of the blood-brain barrier, increasing its permeability and triggering neuroinflammation and cerebral edema, thereby causing EBI. Symptoms are alleviated following MMP9 inhibition. , Studies indicate that the elevated MMP9 levels after SAH primarily originate from reactive astrocytes. Furthermore, MMP9 activates multiple proinflammatory factors and chemokines, thereby stimulating inflammatory responses. These further damage vascular endothelial cells, disrupt normal vascular vasomotor function, and contribute to the development of cerebral vasospasm. Thus, pharmacologically inhibiting MMP9 activity represents a key therapeutic strategy for SAH.

In normal cells, Ginsenoside Ro showed no statistically significant difference in the gene-level regulation of SRC and MMP9. However, this does not imply that Ro lacks regulatory effects on these targets. Subsequent studies will establish in vivo and in vitro models of SAH to investigate the regulatory mechanisms of Ginsenoside Ro on the aforementioned four targets under pathological conditions, providing experimental evidence for developing prodrugs with clinical value.

In this study, we used network pharmacology, molecular docking, and molecular biology experimental techniques to explore the possible molecular targets of Ginsenoside Ro in the treatment of subarachnoid hemorrhage for the first time. These results reveal the multitarget and multipathway characteristics of Ginsenoside Ro in alleviating SAH-induced neural injury, and suggest that Ginsenoside Ro may exert neuroprotective effects by regulating the EGFR and Bcl-2 signaling pathways. This study provides novel mechanistic insights and a theoretical basis for developing potential therapeutic strategies for SAH-induced early brain injury.

Strengths and Weaknesses of This Study

Strengths of This Study

First, this study focuses on a critical clinical unmet need: subarachnoid hemorrhage (SAH)-induced early brain injury (EBI) lacks specific and effective therapeutic interventions, and our research targets this gap by exploring the neuroprotective potential of Ginsenoside Ro, which has been proven to have anti-inflammatory and neuroprotective effects in previous studies. This makes the research highly clinically relevant and translational, providing a new direction for the development of therapeutic strategies for SAH-induced EBI. Second, this study reveals the multitarget and multipathway regulatory mechanism of Ginsenoside Ro in ameliorating SAH-induced neural injury. Through PPI network, GO and KEGG enrichment analyses, we identified core targets (TNF-α, EGFR, Bcl-2, SRC, MMP9) and key signaling pathways (MAPK, PI3K-Akt, estrogen signaling pathways) involved in the process, which not only explains the potential molecular mechanism of Ginsenoside Ro’s neuroprotective effect, but also provides multiple candidate targets for subsequent in-depth research on SAH treatment.

Weaknesses of the Study and Future Improvement Directions

This study mainly focuses on target screening, prediction, and preliminary in vitro validation (qRT-PCR), and lacks in vivo experimental verification (e.g., SAH animal models). In vivo experiments are essential to confirm the neuroprotective effect of Ginsenoside Ro in the physiological environment of SAH, as well as the expression and functional changes of core targets and signaling pathways in vivo. In future research, we will establish SAH animal models to verify the therapeutic effect of Ginsenoside Ro and further confirm the regulatory mechanism of key targets (such as EGFR and Bcl-2) in vivo.

Acknowledgments

The authors thank the Shandong Provincial Natural Science Foundation (Grant No. ZR2022MH210) for its support. The TOC graphic was created using BioRender.

All data used in the present work could be obtained from the corresponding author. The data supporting this study are available within the manuscript.

⊥.

J.W. and Z.Z. contributed equally to this work. L.Y. contributed to the study design and revised the manuscript. J.W. and Z.Z. contributed to the molecular biology experiments and the drafting of the manuscript. J.L., Yuemiao.W., and Yuerong.W contributed to cell studies and data analysis. J.Z. has revised the manuscript. All authors contributed to data interpretation and review/critical revision of the manuscript.

This work was supported by the Shandong Provincial Natural Science Foundation (Grant No. ZR2022MH210).

All procedures performed in studies involving animals were in accordance with the ethical standards of the National Institutes of Health guide for the care and use of Laboratory animals (NIH Publications No. 8023, revised 1978) and were approved by the Animal Ethics Committee of Shandong First Medical University. Research involving human and animal participants. This article does not contain any studies with human participants.

The authors declare no competing financial interest.

References

  1. Macdonald R. L.. Delayed neurological deterioration after subarachnoid haemorrhage. Nat. Rev. Neurol. 2014;10(1):44–58. doi: 10.1038/nrneurol.2013.246. [DOI] [PubMed] [Google Scholar]
  2. Al-Khindi T., Macdonald R. L., Schweizer T. A.. Cognitive and functional outcome after aneurysmal subarachnoid hemorrhage. Stroke. 2010;41(8):e519–e536. doi: 10.1161/STROKEAHA.110.581975. [DOI] [PubMed] [Google Scholar]
  3. Ding M., Jin L., Wei B., Cheng W., Liu W., Li X., Duan C.. Tumor necrosis factor-stimulated gene-6 ameliorates early brain injury after subarachnoid hemorrhage by suppressing NLRC4 inflammasome-mediated astrocyte pyroptosis. Neural Regener Res. 2024;19(5):1064–1071. doi: 10.4103/1673-5374.385311. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Yang B. S. K., Gusdon A. M., Ren X. S., Jeong H. G., Lee C. H., Blackburn S., Choi H. A.. Update on Strategies to Reduce Early Brain Injury after Subarachnoid Hemorrhage. Curr. Neurol. Neurosci. Rep. 2025;25(1):14. doi: 10.1007/s11910-024-01396-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Heffren J., McIntosh A. M., Reiter P. D.. Nimodipine for the prevention of cerebral vasospasm after subarachnoid hemorrhage in 12 children. Pediatr. Neurol. 2015;52(3):356–360. doi: 10.1016/j.pediatrneurol.2014.11.003. [DOI] [PubMed] [Google Scholar]
  6. Lee K. H., Lukovits T., Friedman J. A.. ″Triple-H″ therapy for cerebral vasospasm following subarachnoid hemorrhage. Neurocrit. Care. 2006;4(1):68–76. doi: 10.1385/ncc:4:1:068. [DOI] [PubMed] [Google Scholar]
  7. Jabbarli R., Pierscianek D., Rölz R., Darkwah Oppong M., Kaier K., Shah M., Taschner C., Mönninghoff C., Urbach H., Beck J.. et al. Endovascular treatment of cerebral vasospasm after subarachnoid hemorrhage: More is more. Neurology. 2019;93(5):e458–e466. doi: 10.1212/WNL.0000000000007862. [DOI] [PubMed] [Google Scholar]
  8. Ito H., Ito M.. Recent trends in ginseng research. J. Nat. Med. 2024;78(3):455–466. doi: 10.1007/s11418-024-01792-4. [DOI] [PubMed] [Google Scholar]
  9. Zheng M., Xin Y., Li Y., Xu F., Xi X., Guo H., Cui X., Cao H., Zhang X., Han C.. Ginsenosides: A Potential Neuroprotective Agent. Biomed Res. Int. 2018;2018:8174345. doi: 10.1155/2018/8174345. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Li J., Zhao J., Wang X., Lin Z., Lin H., Lin Z.. Ginsenoside - a promising natural active ingredient with steroidal hormone activity. Food Funct. 2024;15(4):1825–1839. doi: 10.1039/D3FO05484E. [DOI] [PubMed] [Google Scholar]
  11. Yang S. J., Wang J. J., Cheng P., Chen L. X., Hu J. M., Zhu G. Q.. Ginsenoside Rg1 in neurological diseases: From bench to bedside. Acta Pharmacol. Sin. 2023;44(5):913–930. doi: 10.1038/s41401-022-01022-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Jiang G. Y., Yang H. R., Li C., Liu N., Ma S. J., Jin B. X., Yan C., Gong H. D., Li J. Y., Yan H. C.. et al. Ginsenoside Rd alleviates early brain injury by inhibiting ferroptosis through cGAS/STING/DHODH pathway after subarachnoid hemorrhage. Free Radical Biol. Med. 2025;228:299–318. doi: 10.1016/j.freeradbiomed.2024.12.058. [DOI] [PubMed] [Google Scholar]
  13. Li T., Chen J., Xie Z., Fang J., Wu Q., Cao X., Chen Z., Wang Y., Fan Q., Wang Q., Liu J.. Ginsenoside Ro ameliorates cognitive impairment and neuroinflammation in APP/PS1 mice via the IBA1/GFAP-MAPK signaling pathway. Front. Pharmacol. 2025;16:1528590. doi: 10.3389/fphar.2025.1528590. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Peng J., Zuo Y., Huang L., Okada T., Liu S., Zuo G., Zhang G., Tang J., Xia Y., Zhang J. H.. Activation of GPR30 with G1 attenuates neuronal apoptosis via src/EGFR/stat3 signaling pathway after subarachnoid hemorrhage in male rats. Exp. Neurol. 2019;320:113008. doi: 10.1016/j.expneurol.2019.113008. [DOI] [PubMed] [Google Scholar]
  15. Nakano F., Kanamaru H., Kawakita F., Liu L., Nakatsuka Y., Nishikawa H., Okada T., Suzuki H.. Epidermal Growth Factor Receptor Mediates Neuronal Apoptosis After Subarachnoid Hemorrhage in Mice. Stroke. 2023;54(6):1616–1626. doi: 10.1161/STROKEAHA.122.041977. [DOI] [PubMed] [Google Scholar]
  16. Pan P., Zhao H., Zhang X., Li Q., Qu J., Zuo S., Yang F., Liang G., Zhang J. H., Liu X.. et al. Cyclophilin a signaling induces pericyte-associated blood-brain barrier disruption after subarachnoid hemorrhage. J. Neuroinflammation. 2020;17(1):16. doi: 10.1186/s12974-020-1699-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Peng J., He J., Hu X., Xia Y.. GPR30 alleviated subarachnoid hemorrhage-induced blood-brain barrier dysfunction by activating the PI3K/Akt and Nrf2/HO-1 pathways. Am. J. Physiol Cell Physiol. 2024;327(1):C65–C73. doi: 10.1152/ajpcell.00035.2024. [DOI] [PubMed] [Google Scholar]
  18. Lin C. L., Dumont A. S., Su Y. F., Dai Z. K., Cheng J. T., Tsai Y. J., Huang J. H., Chang K. P., Hwang S. L.. Attenuation of subarachnoid hemorrhage-induced apoptotic cell death with 17 beta-estradiol. Laboratory investigation. J. Neurosurg. 2009;111(5):1014–1022. doi: 10.3171/2009.3.JNS081660. [DOI] [PubMed] [Google Scholar]
  19. Dai X., Liu S., Cheng L., Huang T., Guo H., Wang D., Xia M., Ling W., Xiao Y.. Betaine Supplementation Attenuates S-Adenosylhomocysteine Hydrolase-Deficiency-Accelerated Atherosclerosis in Apolipoprotein E-Deficient Mice. Nutrients. 2022;14(3):718. doi: 10.3390/nu14030718. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Bojuan L., Youdong Z., Lei W., Lixin X., Jinyang M.. Oleanolic Acid Alleviates Neuronal Ferroptosis in Subarachnoid Hemorrhage by Inhibiting KEAP1-Nrf2 and NF-κB Pathways. Drug Dev. Res. 2025;86(3):e70105. doi: 10.1002/ddr.70105. [DOI] [PubMed] [Google Scholar]
  21. Zhang Y., Yang X., Ge X., Zhang F.. Puerarin attenuates neurological deficits via Bcl-2/Bax/cleaved caspase-3 and Sirt3/SOD2 apoptotic pathways in subarachnoid hemorrhage mice. Biomed Pharmacother. 2019;109:726–733. doi: 10.1016/j.biopha.2018.10.161. [DOI] [PubMed] [Google Scholar]
  22. Zhang H., Xu L., He Y., Zhang Z., Zhang J., Yu Q., Liu Y., Wang X., Zhang A., Wang K.. et al. Tat-NR2B9c attenuates oxidative stress via inhibition of PSD95-NR2B-nNOS complex after subarachnoid hemorrhage in rats. Neuropharmacology. 2024;251:109905. doi: 10.1016/j.neuropharm.2024.109905. [DOI] [PubMed] [Google Scholar]
  23. Gaillard T.. Evaluation of AutoDock and AutoDock Vina on the CASF-2013 Benchmark. J. Chem. Inf. Model. 2018;58(8):1697–1706. doi: 10.1021/acs.jcim.8b00312. [DOI] [PubMed] [Google Scholar]
  24. Vogler M., Braun Y., Smith V. M., Westhoff M. A., Pereira R. S., Pieper N. M., Anders M., Callens M., Vervliet T., Abbas M.. et al. The BCL2 family: from apoptosis mechanisms to new advances in targeted therapy. Signal Transduction Targeted Ther. 2025;10(1):91. doi: 10.1038/s41392-025-02176-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Chen X., Luo X., Hu H., Xu Q.. NBTI attenuates neuroinflammation and apoptosis partly by ENT1/NLRP3/Bcl2 pathway after subarachnoid hemorrhage in rats. NeuroReport. 2021;32(17):1341–1348. doi: 10.1097/WNR.0000000000001733. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Fujii M., Sherchan P., Soejima Y., Hasegawa Y., Flores J., Doycheva D., Zhang J. H.. Cannabinoid receptor type 2 agonist attenuates apoptosis by activation of phosphorylated CREB-Bcl-2 pathway after subarachnoid hemorrhage in rats. Exp. Neurol. 2014;261:396–403. doi: 10.1016/j.expneurol.2014.07.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Lauzier D. C., Jayaraman K., Yuan J. Y., Diwan D., Vellimana A. K., Osbun J. W., Chatterjee A. R., Athiraman U., Dhar R., Zipfel G. J.. Early Brain Injury After Subarachnoid Hemorrhage: Incidence and Mechanisms. Stroke. 2023;54(5):1426–1440. doi: 10.1161/STROKEAHA.122.040072. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Su L. J., Zhang J. H., Gomez H., Murugan R., Hong X., Xu D., Jiang F., Peng Z. Y.. Reactive Oxygen Species-Induced Lipid Peroxidation in Apoptosis, Autophagy, and Ferroptosis. Oxid. Med. Cell. Longevity. 2019;2019:5080843. doi: 10.1155/2019/5080843. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Ge S., Jing Z., Wang L., Cui X., Zhang X., Wang X.. Iron Metabolism and Ferroptosis in Early Brain Injury after Subarachnoid Haemorrhage. Mol. Neurobiol. 2024;61(12):10736–10746. doi: 10.1007/s12035-024-04218-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Chen Q., Xu H., Xu A., Ross T., Bowler E., Hu Y., Lesnefsky E. J.. Inhibition of Bcl-2 sensitizes mitochondrial permeability transition pore (MPTP) opening in ischemia-damaged mitochondria. PLoS One. 2015;10(3):e0118834. doi: 10.1371/journal.pone.0118834. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Wang Y., Chai C., Lin W., Cao J., Li Z., Jin Y., Xu Y., Zhang J., Qu Y., Zhan J.. et al. Oxidative stress-mediated PANoptosis and ferroptosis: Exploration of multimodal cell death triggered by an AIE-active nano-photosensitizer via photodynamic therapy. Theranostics. 2025;15(14):6665–6685. doi: 10.7150/thno.111635. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Makki N., Thiel K. W., Miller F. J. Jr.. The epidermal growth factor receptor and its ligands in cardiovascular disease. Int. J. Mol. Sci. 2013;14(10):20597–20613. doi: 10.3390/ijms141020597. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Koide M., Penar P. L., Tranmer B. I., Wellman G. C.. Heparin-binding EGF-like growth factor mediates oxyhemoglobin-induced suppression of voltage-dependent potassium channels in rabbit cerebral artery myocytes. Am. J. Physiol.: Heart Circ. Physiol. 2007;293(3):H1750–1759. doi: 10.1152/ajpheart.00443.2007. [DOI] [PubMed] [Google Scholar]
  34. Nakano F., Kawakita F., Liu L., Nakatsuka Y., Nishikawa H., Okada T., Shiba M., Suzuki H.. Link Between Receptors That Engage in Developing Vasospasm After Subarachnoid Hemorrhage in Mice. Acta Neurochir., Suppl. 2020;127:55–58. doi: 10.1007/978-3-030-04615-6_9. [DOI] [PubMed] [Google Scholar]
  35. Nakano F., Kawakita F., Liu L., Nakatsuka Y., Nishikawa H., Okada T., Kanamaru H., Pak S., Shiba M., Suzuki H.. Anti-vasospastic Effects of Epidermal Growth Factor Receptor Inhibitors After Subarachnoid Hemorrhage in Mice. Mol. Neurobiol. 2019;56(7):4730–4740. doi: 10.1007/s12035-018-1400-6. [DOI] [PubMed] [Google Scholar]
  36. Kusaka G., Kimura H., Kusaka I., Perkins E., Nanda A., Zhang J. H.. Contribution of Src tyrosine kinase to cerebral vasospasm after subarachnoid hemorrhage. J. Neurosurg. 2003;99(2):383–390. doi: 10.3171/jns.2003.99.2.0383. [DOI] [PubMed] [Google Scholar]
  37. Gaetani P., Tancioni F., Grignani G., Tartara F., Merlo E. M., Brocchieri A., Rodriguez y Baena R.. Platelet derived growth factor and subarachnoid haemorrhage: a study on cisternal cerebrospinal fluid. Acta Neurochir. 1997;139(4):319–324. doi: 10.1007/BF01808827. [DOI] [PubMed] [Google Scholar]
  38. Lei H., Kazlauskas A.. A reactive oxygen species-mediated, self-perpetuating loop persistently activates platelet-derived growth factor receptor α. Mol. Cell. Biol. 2014;34(1):110–122. doi: 10.1128/MCB.00839-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Han Y. W., Liu X. J., Zhao Y., Li X. M.. Role of Oleanolic acid in maintaining BBB integrity by targeting p38MAPK/VEGF/Src signaling pathway in rat model of subarachnoid hemorrhage. Eur. J. Pharmacol. 2018;839:12–20. doi: 10.1016/j.ejphar.2018.09.018. [DOI] [PubMed] [Google Scholar]
  40. Dang B., Duan X., Wang Z., He W., Chen G.. A Therapeutic Target of Cerebral Hemorrhagic Stroke: Matrix Metalloproteinase- 9. Curr. Drug Targets. 2017;18(12):1358–1366. doi: 10.2174/1389450118666170427151657. [DOI] [PubMed] [Google Scholar]
  41. Liang Y., Yang C., Lin Y., Parviz Y., Sun K., Wang W., Ren M., Yan L.. Matrix metalloproteinase 9 induces keratinocyte apoptosis through FasL/Fas pathway in diabetic wound. Apoptosis. 2019;24(7–8):542–551. doi: 10.1007/s10495-019-01536-w. [DOI] [PubMed] [Google Scholar]
  42. Tian W., Kyriakides T. R.. Matrix metalloproteinase-9 deficiency leads to prolonged foreign body response in the brain associated with increased IL-1beta levels and leakage of the blood-brain barrier. Matrix Biol. 2009;28(3):148–159. doi: 10.1016/j.matbio.2009.02.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Sunny A., James R. R., Menon S. R., Rayaroth S., Daniel A., Thompson N. A., Tharakan B.. Matrix Metalloproteinase-9 inhibitors as therapeutic drugs for traumatic brain injury. Neurochem. Int. 2024;172:105642. doi: 10.1016/j.neuint.2023.105642. [DOI] [PubMed] [Google Scholar]
  44. Ahmadighadykolaei H., Lambert J. A., Raeeszadeh-Sarmazdeh M.. TIMP-1 Protects Tight Junctions of Brain Endothelial Cells From MMP-Mediated Degradation. Pharm. Res. 2023;40(9):2121–2131. doi: 10.1007/s11095-023-03593-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Feng D., Zhou J., Liu H., Wu X., Li F., Zhao J., Zhang Y., Wang L., Chao M., Wang Q.. et al. Astrocytic NDRG2-PPM1A interaction exacerbates blood-brain barrier disruption after subarachnoid hemorrhage. Sci. Adv. 2022;8(39):eabq2423. doi: 10.1126/sciadv.abq2423. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Woo M. S., Park J. S., Choi I. Y., Kim W. K., Kim H. S.. Inhibition of MMP-3 or −9 suppresses lipopolysaccharide-induced expression of proinflammatory cytokines and iNOS in microglia. J. Neurochem. 2008;106(2):770–780. doi: 10.1111/j.1471-4159.2008.05430.x. [DOI] [PubMed] [Google Scholar]

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Data Availability Statement

All data used in the present work could be obtained from the corresponding author. The data supporting this study are available within the manuscript.

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