Use of TNFRSF1A inhibitor miR-3059-5p in the treatment of stroke

Abstract

The present invention discloses the use of the TNFRSF1A inhibitor miR-3059-5p in the treatment of stroke. Examples of the present invention demonstrate that miR-3059-5p can inhibit neuronal apoptosis and parthanatos death induced by OGD / R by negatively regulating TNFRSF1A expression, thereby alleviating neuronal damage caused by OGD / R. Therefore, the research results of this invention provide a potential new drug for the clinical treatment of stroke.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine and relates to the use of TNFRSF1A inhibitor miR-3059-5p in treating stroke. Background Art

[0002] Ischemic stroke (IS) is an acute cerebrovascular disease that seriously threatens human life and health, and is associated with high mortality and disability risks

[53] . The pathological mechanism of IS has not yet been fully elucidated. Existing evidence suggests that multiple mechanisms are involved in the occurrence and progression of IS, and that these mechanisms interact with each other. Therefore, further exploration of the pathological mechanism of IS will help identify new therapeutic targets.

[0003] Apoptosis is considered one of the primary forms of neuronal cell death induced by ischemia (IS). During the progression of IS, a large number of neurons undergo apoptosis in the ischemic region. This is an active programmed cell death process that occurs under precise genetic regulation in response to environmental stimuli. It is primarily mediated by three signaling pathways: the mitochondrial pathway, the endoplasmic reticulum stress pathway, and the death receptor pathway. This ultimately activates apoptosis-executing proteins such as Caspase-3, leading to cell death. As researchers continue to explore the mechanisms of cell death, a novel form of programmed cell death has been discovered in hypoxic neurons: PARP-1-dependent cell death, also known as parthanatos. Unlike necrosis or apoptosis, this is a regulated, caspase-independent form of cell death. Its development primarily involves overactivation of PARP-1, translocation of AIF from mitochondria to the nucleus, and macrophage migration inhibitory factor (MIF)-dependent DNA degradation. Apoptosis and parthanatos have been shown to play crucial roles in the pathogenesis of IS-induced neuronal cell death. Therefore, this study attempted to identify genes closely related to apoptosis and Parthanatos pathway in IS as key targets for IS treatment. Summary of the Invention

[0004] The present invention provides use of a TNFRSF1A inhibitor in preparing a medicament for preventing or treating stroke.

[0005] Furthermore, the stroke is ischemic stroke.

[0006] The term "inhibitor" refers to any substance that can reduce the activity of TNFRSF1A protein, reduce the stability of TNFRSF1A gene or protein, downregulate the expression of TNFRSF1A protein, reduce the effective action time of TNFRSF1A protein, or inhibit the transcription and translation of TNFRSF1A gene. These substances can be used in the present invention as substances useful for downregulating TNFRSF1A, and thus can be used to prevent or treat stroke.

[0007] The inhibitors include nucleic acid inhibitors, protein inhibitors, proteases, and protein-binding molecules. The nucleic acid inhibitors are selected from interfering molecules that target TNFRSF1A or its transcripts and are capable of inhibiting TNFRSF1A gene expression or transcription, including shRNA (small hairpin RNA), small interfering RNA (siRNA), dsRNA, microRNA, antisense nucleic acids, or constructs capable of expressing or forming such shRNA, small interfering RNA, dsRNA, microRNA, or antisense nucleic acids. The protein-binding molecules are selected from substances that specifically bind to the TNFRSF1A protein, such as antibodies or ligands that are capable of inhibiting TNFRSF1A protein activity.

[0008] In some embodiments of the present invention, the TNFRSF1A inhibitor is a small interfering RNA (siRNA), which is a short, double-stranded RNA molecule that targets and degrades specific mRNAs with homologous, complementary sequences. This process is known as RNA interference (RNA interference). Small interfering RNA can be prepared as a double-stranded nucleic acid, comprising a sense strand and an antisense strand that form a double strand only under hybridization conditions. A double-stranded RNA complex can be prepared from separate sense and antisense strands. For example, the complementary sense and antisense strands are chemically synthesized and then hybridized by annealing to produce a synthetic double-stranded RNA complex.

[0009] In a specific embodiment of the present invention, the TNFRSF1A inhibitor is a "small hairpin RNA (shRNA)," a small, non-coding RNA molecule that forms a hairpin structure. Small hairpin RNA can inhibit gene expression through the RNA interference pathway. As described above, shRNA can be expressed from a double-stranded DNA template. The double-stranded DNA template is inserted into a vector, such as a plasmid or viral vector, and then linked to a promoter for expression in vitro or in vivo. Under the action of the DICER enzyme in eukaryotic cells, shRNA can be cleaved into small interfering RNA molecules, thereby entering the RNAi pathway. "shRNA expression vectors" refer to plasmids commonly used in the art for constructing shRNA constructs. These plasmids typically contain a "spacer sequence" and multiple cloning sites or replacement sequences flanking the "spacer sequence." This allows the DNA sequence corresponding to the shRNA (or its analog) to be inserted into the multiple cloning site or to replace the replacement sequence in both forward and reverse directions. The RNA transcribed from this DNA sequence forms an shRNA (short hairpin) structure. The “shRNA expression vector” is currently available through commercial channels, such as some viral vectors.

[0010] Nucleic acid inhibitors of the present invention, such as siRNA, can be chemically synthesized or prepared by transcribing an expression cassette within a recombinant nucleic acid construct into single-stranded RNA. Nucleic acid inhibitors such as siRNA can be delivered into cells using appropriate transfection reagents or various other techniques known in the art.

[0011] In a specific embodiment of the present invention, the inhibitor of TNFRSF1A is miRNA, and the miRNA is miR-3059-5p or an agent that promotes the expression of miR-3059-5p.

[0012] The reagents for promoting miR-3059-5p expression of the present invention are not limited, as long as they can promote or enhance the expression or activity of miR-3059-5p or substances involved in the upstream or downstream pathways of miR-3059-5p and are effective for treating stroke.

[0013] The reagent for promoting miR-3059-5p expression of the present invention can be used to supplement the loss or deficiency of endogenous miR-3059-5p, thereby treating stroke.

[0014] In a specific embodiment of the present invention, the agent that promotes the expression of miR-3059-5p is miR-3059-5pmimic.

[0015] The miR-3059-5p of the present invention includes a miR-3059-5p precursor and a mature miR-3059-5p. The miR-3059-5p of the present invention can be natural or synthetic, or obtained by transfecting cells with a vector that can express a DNA fragment of miR-3059-5p. The vector includes a viral vector and a eukaryotic vector.

[0016] The viral vector may be any suitable vector, including but not limited to retroviral vectors, adenoviral vectors, adeno-associated viral vectors, herpes virus (eg, herpes simplex virus, vaccinia virus, and Epstein-Barr virus) vectors, and alphavirus vectors.

[0017] The eukaryotic expression vector can be any appropriate expression vector, including but not limited to pCMV-Myc expression vector, pcDNA3.0 expression vector, pcDNA3.1 expression vector, pEGFP expression vector, pEF Bos expression vector, pTet expression vector, pTRE expression vector, or a vector modified based on a known expression vector, such as pBin438, pCAMBIA1301, etc.

[0018] A DNA fragment expressing miR-3059-5p can be obtained by searching the miRNA database (http: / / microrna.sanger.ac.uk / sequences / ) for the location and specific sequence information of miR-3059-5p on the genome, determining the location of the initial miRNA of miR-3059-5p based on the genome sequence, designing specific primers within the 500-800 bp range upstream and downstream of the initial miRNA location of miR-3059-5p, and amplifying the sequence between the primers to obtain a DNA fragment expressing miR-3059-5p.

[0019] The TNFRSF1A inhibitors of the present invention can be administered via liposomes, which serve to target the drug to specific tissues and increase the drug's half-life. Liposomes include, but are not limited to, emulsifiers, foaming agents, liquid lipids, solid lipids, insoluble monolayers, phospholipid dispersants, and surfactants. The liposomes may also include agents capable of binding to receptor molecules in targeted cells or other therapeutic or immunogenic compositions.

[0020] The present invention also provides a medicine for treating cerebral stroke, which comprises a TNFRSF1A inhibitor.

[0021] The medicine of the present invention also includes a pharmaceutically acceptable carrier. The medicine of the present invention is prepared by combining the active ingredient and the pharmaceutically acceptable carrier through conventional pharmaceutical processes.

[0022] The phrase "pharmaceutically acceptable carrier" is art-recognized and includes, for example, pharmaceutically acceptable materials, compositions, or excipients that participate in carrying or transporting any subject composition from one organ or part of the body to another organ or part of the body, such as liquid or solid fillers, diluents, solvents, or encapsulating materials. Each carrier must be "acceptable" in the sense of being compatible with the other ingredients of the subject composition and not injurious to the patient. In certain embodiments, a pharmaceutically acceptable carrier is pyrogen-free. Some examples of materials that can be used as pharmaceutically acceptable carriers include: (1) sugars, such as lactose, glucose, and sucrose; (2) starches, such as corn starch and potato starch; (3) cellulose and its derivatives, such as sodium carboxymethylcellulose, ethylcellulose, and cellulose acetate; (4) powdered tragacanth; (5) malt; (6) gelatin; (7) talc; (8) cocoa butter and suppository waxes; (9) oils, such as peanut oil, cottonseed oil, sunflower oil, sesame oil, olive oil, corn oil, and tantalum oil. soybean oil; (10) glycols such as propylene glycol; (11) polyols such as glycerol, sorbitol, mannitol, and polyethylene glycol; (12) esters such as ethyl oleate and ethyl laurate; (13) agar; (14) buffers such as magnesium hydroxide and aluminum hydroxide; (15) alginic acid; (16) pyrogen-free water; (17) isotonic saline; (18) Ringer's solution; (19) ethanol; (20) phosphate buffer; and (21) other nontoxic compatible substances used in pharmaceutical preparations.

[0023] "Administering" refers to the method of administering a dose of a drug to a patient. The compositions used in the methods of the present invention can be administered by a route selected from, but not limited to, inhalation, ocular, parenteral, dermal, transdermal, oral, rectal, sublingual, perilingual, nasal, topical, and oral administration. Parenteral administration includes intravenous, intraperitoneal, subcutaneous, and intramuscular administration. The preferred method of administration can vary depending on a variety of factors, such as the components of the composition being administered and the severity of the condition being treated.

[0024] The pharmaceutical compositions of the present invention are prepared in a manner known to those skilled in the art, such as by conventional dissolution, lyophilization, mixing, granulation or molding methods. Methods well known in the art for making formulations are described in, for example, Remington: The Science and Practice of Pharmacy, 20th ed., A.R. Gennaro, ed., 2000, Lippincott Williams & Wilkins, Philadelphia, and Encyclopedia of Pharmaceutical Technology, J. Swarbrick and J.C. Boylan, eds., 1988-1999, Marcel Dekker, New York.

[0025] The dosage of any agent used in the medicament of the present invention can be readily determined by one skilled in the art. Desirably, the dosage of the agent in the medicament of the present invention will be sufficient to alleviate the symptoms of a stroke in a patient. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Shows the changes in cerebral blood flow on the ischemic side of MCAO / R model mice;

[0027] Figure 2 Figures showing the overall analysis results of gene expression levels in mRNA-seq samples, including (A): FPKM box plot; (B): inter-sample correlation coefficient heat map; (C): two-dimensional PCA plot; (D): three-dimensional PCA plot; points of different colors in the figure represent samples from different groups;

[0028] Figure 3 A volcano plot showing the distribution of DEGs. Note: The horizontal axis represents the fold change of gene expression in different samples; the vertical axis represents the statistical significance of the change in gene expression. The scattered points in the figure represent each gene, red dots represent significantly upregulated genes, blue dots represent significantly downregulated genes, and gray dots represent genes with no significant difference. The five genes with the lowest Padj values and the most statistical significance are marked in each of the upregulated and downregulated genes.

[0029] Figure 4 A graph showing the enrichment score results of the ssGSEA analysis of sample expression matrix paired with apoptosis and Parthanatos death-related gene sets;

[0030] Figure 5 The results of temporal analysis are shown in Figure 1, where (A) indicates the enriched functional pathway information related to differentially expressed genes; (B) indicates the relationship between the expression information of relevant genes in the pathway and the temporal characteristics of the disease.

[0031] Figure 6 Figures showing the selection and validation of the soft threshold β in WGCNA, where (A) is a cluster dendrogram of the GSE23160 samples; (B) is the relationship between the soft threshold β (abscissa) and the scale-free fit index R2 (ordinate); the relationship between the soft threshold β (abscissa) and the average adjacency coefficient (ordinate); the red line represents 0.9; (C) is the frequency histogram of the soft connectivity k when the soft threshold β is selected as 16, showing that there are few connections between genes; when the soft threshold β is 16, the scale-free fit index R2 is 0.9;

[0032] Figure 7Figure showing the results of identifying gene modules associated with target disease characteristics, including (A): DEGs hierarchical clustering tree, where different colors in the color row below the tree represent different gene modules; (B): Heat map of the correlation between modules and cell apoptosis, Parthanatos death, etc., where each cell represents the correlation between the gene module and the corresponding disease trait, including the correlation coefficient and P value, and the color depth represents the magnitude of the correlation;

[0033] Figure 8 The results of the screening of key genes are shown in Figure 1, where (A) is the intersection of related gene sets; (B) is the PPI analysis;

[0034] Figure 9 The results show the changes in TNFRSF1A expression levels in the OGD / R model and the MCAO / R model, where (A) is the mRNA level of TNFRSF1A in the OGD / R model; (B) is the protein level of TNFRSF1A in the OGD / R model; (C) is the mRNA level of TNFRSF1A in the MCAO / R model; (D) is the protein level of TNFRSF1A in the MCAO / R model, Note: **P<0.01, ****P<0.001;

[0035] Figure 10 Figures showing the prediction and validation results of TNFRSF1A upstream miRNAs, including (A): DemiRNA volcano plot, where the scattered points represent individual miRNAs, red dots represent significantly upregulated miRNAs, blue dots represent significantly downregulated miRNAs, and gray dots represent miRNAs with no significant differences; (B): Venn diagram analysis of the intersection of miRNAs predicted by miRDB, TargetScan, and sequencing data DemiRNAs; (C): Dual-luciferase reporter assay results; (D): Western blot analysis of TNFRSF1A protein expression levels in HT-22 cells specifically transfected with miR-3059-5p inhibitor or miR-3059-5p mimic, Note: **P<0.01, ***P<0.001;

[0036] Figure 11Figures showing the regulatory effect of miR-3059-5p on TNFRSF1A and its effect on OGD / R-induced cell death and apoptosis of Parthanatos cells, including (A): Western blot detection of PARP-1 protein expression and relative quantitative analysis of cells in each group, (B): AIF protein expression and relative quantitative analysis in mitochondria, (C): AIF protein expression and relative quantitative analysis in the nucleus; (D): Relative quantitative analysis of TUNEL staining results of HT-22 cells in each group; (E) TUNEL staining results of HT-22 cells in each group, Note: *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001. DETAILED DESCRIPTION

[0037] The present invention will be further described below with reference to specific examples. It should be understood that the specific embodiments described herein are presented by way of example and are not intended to limit the present invention. The main features of the present invention may be applied to various embodiments without departing from the scope of the present invention.

[0038] Example Use of TNFRSF1A Inhibitor miR-3059-5p in Treating Stroke

[0039] 1. Experimental steps

[0040] 1. Experimental animals and cell lines

[0041] The mice used in this study were all SPF (Specified-pathogens free), healthy male C57BL / 6J, aged 6-8 weeks, weighing 20-25 g, purchased from Beijing Huafukang Biotechnology Co., Ltd. (certificate number: SCXK 2019-0008). All mice were housed in the animal breeding room of Tianjin Institute of Anesthesiology at a rate of 4-6 per cage and were allowed to freely access food and drinking water. The breeding environment temperature was maintained at 20-24°C, the humidity was 40-60%, and the day and night cycle was 12 hours. Before the experiment began, the mice were adaptively fed for one week. All animal experimental procedures in this study were approved by the Experimental Animal Management Committee of Tianjin Medical University.

[0042] The mouse hippocampal neuronal cell line HT-22 used in this study was purchased from Zhongqiao Xinzhou Biotechnology Co., Ltd. Culture medium was DMEM supplemented with 10% fetal bovine serum (FBS) and 1% P / S (P: penicillin 10,000 U / ml, S: streptomycin 10,000 U / ml) and maintained in a cell culture incubator at 37°C and 5% CO .

[0043] 2. Experimental methods

[0044] 2.1 HT-22 cell culture

[0045] (1) Cell recovery

[0046] ① Remove the cell cryopreservation tube from liquid nitrogen and quickly thaw it in a 37℃ constant temperature water bath.

[0047] ② After the liquid in the cryopreservation tube is completely thawed, transfer it to a sterile centrifuge tube, add 2-3 ml of complete culture medium and mix thoroughly, centrifuge at 1000 rpm for 5 minutes at room temperature, and discard the supernatant.

[0048] ③ Add 1 ml of complete culture medium and gently pipette to resuspend the cell pellet. Evenly inoculate the cell suspension into a T25 cm cell culture flask or a 10 cm cell culture dish, add 4-7 ml of complete culture medium, and gently shake the culture flask / dish to evenly distribute the cells. The culture conditions are 37°C and 5% CO2.

[0049] (2) Cell passage

[0050] ① When the cell confluence reaches 80%-90% under an inverted microscope, discard the original culture medium and add 2 ml of sterile PBS solution to gently wash the cells twice.

[0051] ② Add 1 ml of 0.25% trypsin and gently shake the culture flask / dish to allow the trypsin to completely cover the adherent cells.

[0052] ③ Digest in a 37°C incubator. The digestion time varies slightly depending on the cell type. Observe the cell morphology intermittently under a microscope. When the cells shrink, become round, or float, add complete culture medium to terminate the digestion. Gently pipette several times to obtain a uniform cell suspension.

[0053] ④ Centrifuge at 1000 rpm for 5 minutes at room temperature, discard the supernatant, resuspend the pellet evenly with 1 ml of complete culture medium, and inoculate it into a new cell culture flask / dish at a subculture ratio of 1:3 for further culture.

[0054] (3) Cell cryopreservation

[0055] ① Once the cells reach over 80% confluency, they can be frozen. Discard the original culture medium, rinse with sterile PBS, digest with 0.25% trypsin, terminate digestion with complete culture medium, and centrifuge to obtain a cell pellet. The above steps are exactly the same as those for cell passaging.

[0056] ② Add 1 ml of cell freezing solution to the cell pellet, gently pipette to mix, and transfer to a 2 ml cell freezing tube. Clearly label the cell name, freezing date, and cell generation number.

[0057] ③ Place the cryovials in a cell freezing box, freeze at -80°C overnight, and then transfer to a liquid nitrogen tank for long-term storage.

[0058] 2.2 Establishment of OGD / R model

[0059] An OGD / R model was established to simulate the ischemia and reperfusion process in vitro. The specific steps are as follows: HT-22 cells were seeded in culture flasks / dishes for 24 hours to ensure adherence. The original complete cell culture medium was discarded, and the cells were gently washed three times with sterile PBS. The culture medium was replaced with sugar-free DMEM medium and cultured for 6 hours in a hypoxic incubator containing 94% N2-1% O2-5% CO2 at 37°C, i.e., oxygen-glucose deprivation, simulating the ischemia phase. The sugar-free DMEM medium was discarded, the cells were washed with PBS, and high-glucose DMEM complete medium was added. The cells were transferred to a 37°C, 5% CO2 incubator and cultured for another 24 hours. This process simulates the post-ischemia reperfusion phase.

[0060] 2.3 Preparation of MCAO / R model

[0061] The MCAO / R model was established using male C57BL / 6J mice (20-25 g, 8 weeks old) using the following steps:

[0062] (1) Preoperative preparation: Before surgery, mice were deprived of food and water for 12 h, weighed, and divided into groups.

[0063] (2) Specific modeling steps

[0064] ① Mice were anesthetized by inhalation of isoflurane (induction concentration 4%, maintenance concentration 1%-1.5%) and fixed on the operating table in the supine position. During the modeling process, the mice were kept warm.

[0065] ② Prepare and disinfect the skin from above the sternum to the neck, make a longitudinal incision of approximately 1 cm along the midline of the neck, and use ophthalmic forceps to bluntly separate the muscles, fascia, and nerves under a stereomicroscope. Free the left common carotid artery (CCA) and tie a slipknot with 6-0 silk thread.

[0066] ③ Dissect the CCA upwards to free the internal carotid artery (EAC) and external carotid artery (ICA). Thread and ligate the distal end of the ECA along with the thyroid artery. Pass a 6-0 suture between the ligature and the CCA bifurcation and tie a loose knot.

[0067] ④ Use microscissors to make a small oblique cut between the virtual knot and the ligature. Insert the suture plug and tighten the virtual knot. The force should be enough to allow the suture plug to just slide inside the blood vessel without bleeding.

[0068] ⑤ Cut the ECA close to the ligature at the distal end of the ECA, adjust the angle so that the suture plug is inserted into the ICA, and continue to push the suture plug forward along the ICA until you feel slight resistance. Stop pushing the suture plug. At this time, its front end completely blocks the origin of the middle cerebral artery. Tie a slipknot at the broken end of the ECA to fix the suture plug.

[0069] ⑥ Suture the subcutaneous tissue and skin layer by layer and disinfect. After 1 hour of ischemia, withdraw the suture plug outward, allowing its tip to retreat to the ECA to ensure reperfusion of CCA blood into the middle cerebral artery. Resuture and disinfect, and inject 1 ml of normal saline intraperitoneally for fluid replacement.

[0070] ⑦ For mice in the sham group, the surgical procedure was the same as above, except that the suture tip was inserted into the ICA but not into the middle cerebral artery. Mice were housed separately after surgery, and body temperature was maintained and fluids were promptly administered.

[0071] 2.4 Laser Microcirculation Blood Flow Imaging Detection of Cerebral Blood Flow

[0072] After anesthesia, mice were placed in the prone position. The head was prepared and disinfected. The skin was cut open along the midline of the skull to expose the skull. The PeriCam PSI system was activated, the animal was positioned in the center of the field of view, and blood perfusion images were acquired. Subsequently, a MCAO / R model was established in the mice, and blood perfusion at the same site was repeatedly monitored to ensure the success rate and stability of the model.

[0073] 2.5 RNA extraction and quality control (QC) from tissues or cells

[0074] (1) Sample processing

[0075] ① Brain tissue sampling and homogenization: After 24 hours of reperfusion, mice were deeply anesthetized and sacrificed, and the mouse brains were quickly removed on ice. After removing the cerebellum, the brains were quickly rinsed with pre-cooled PBS solution (RNase-free). The left (ischemic) hemibrain was sampled in each group, weighed, and stored in 2 ml RNase-free screw-thread cryovials, which were then quickly placed in liquid nitrogen for storage. The sampling time did not exceed 2 minutes, and the entire sampling process was ensured to be RNase-free. Three samples from the same group were randomly mixed into one test sample, and three replicates were set up for each group. Approximately 100 mg of brain tissue was weighed on an electronic balance, 1 ml of TRIzol was added, and the tissue was ground into a homogenate using a tissue high-throughput grinder and incubated at room temperature for 5 minutes.

[0076] ② Cell lysis: When the cell confluence in the 6-well plate reaches 80%-90%, discard the cell culture supernatant, wash twice with enzyme-free PBS solution, add 1 ml of TRIzol and gently pipette the cells. After standing at room temperature for 5 minutes, transfer the lysate into a 1.5 ml EP tube, centrifuge at 12000 rpm for 5 minutes, and recover the supernatant.

[0077] (2) RNA extraction

[0078] ① Add 200 μl of chloroform, cover the EP tube tightly, shake vigorously, and let it stand at room temperature for 10-15 minutes.

[0079] ② Centrifuge at 12,000 rpm for 15 minutes at 4°C. Carefully aspirate the upper aqueous phase containing RNA (approximately 500 μl), making sure the pipette tip does not touch the middle white protein layer. Transfer the upper aqueous phase to a new EP tube.

[0080] ③ Add isopropanol (about 500 μl) equal to the volume of the upper water layer into the EP tube, mix thoroughly, and let it react at room temperature for 10 minutes.

[0081] ④ Centrifuge at 12,000 rpm for 15 minutes at 4°C. The white precipitate at the bottom of the tube is RNA. Aspirate as much of the supernatant as possible.

[0082] ⑤ Add 1 ml of 75% ethanol (pre-chilled at 4°C) to the RNA pellet and gently mix to wash the RNA pellet. Centrifuge at 12,000 rpm at 4°C for 5 minutes. Discard the supernatant and air-dry the RNA pellet.

[0083] ⑥ Dissolve the RNA in 50 μl DEPC water, let it stand for 5 minutes, and gently pipette to completely dissolve it.

[0084] ⑦RNA integrity detection: Use 1.5% agarose gel electrophoresis to identify the integrity of RNA. Usually, the brightness ratio of the 28s RNA and 18s RNA bands of eukaryotes is 2:1.

[0085] ⑧ RNA purity and concentration detection: NanoDrop2000 was used to detect the OD value and concentration of RNA. Purity was determined based on the OD260 / OD280 ratio. RNA with a value between 1.8 and 2.0 was considered of good quality and could be used for subsequent experiments.

[0086] ⑨RNA samples can be stored at -80℃ for a long time.

[0087] 2.6 High-throughput sequencing of brain tissue mRNA and miRNA

[0088] The cDNA library construction and sequencing were completed by Shanghai Zhongke New Life Biotechnology Co., Ltd.

[0089] 2.7 Sequencing Data Analysis

[0090] (1) Gene expression analysis

[0091] The raw data were quality assessed, and clean reads (remaining data after filtering the raw data) were aligned to the designated reference genome using HISAT2 software (v.2.2.1.0). Sequence similarity comparisons were performed using known reference gene sequences and annotation files as a database to identify the expression abundance of each protein-coding gene in each sample. FeatureCounts software was used to calculate the FPKM expression level of each gene in each sample.

[0092] (2) Differential mRNA and miRNA expression analysis

[0093] First, the official gene (GAPDH) for each sample was used as a reference to determine whether sample normalization was necessary. Then, principal component analysis (PCA) was used to reduce the data dimensionality using the FactoMineR and fectoextraR packages to determine whether the groups could be well distinguished. Differential expression analysis between the two groups was performed using DESeq2 in the R language. FPKM values were first log2-transformed to avoid statistical bias due to normal distribution issues. Using this transformed matrix, empirical Bayesian estimation was used to analyze differentially expressed genes. Differentially expressed genes were identified as follows: a fold change (FC) of |log2FC| > 1 and an adjusted P value (Padj) < 0.05. Volcano plots were created using the R ggplot2 package to visualize differentially expressed genes (DEGs).

[0094] 2.8 Public Database

[0095] (1) Data download

[0096] The expression data for the GSE21360 dataset and platform file GPL6885 were downloaded from the GEO database (http: / / www.ncbi.nlm.nih.gov / geo / ). Samples were 8-10 week-old male C57BL / 6J mice. The dataset includes transcriptional profiles of the cerebral cortex at different time points (2 hours, 8 hours, and 24 hours) after sham and MCAO model reperfusion. Detailed sample information is shown in Table 1.

[0097] Table 1 Sample information of GEO database

[0098]

[0099] (2) Main bioinformatics analysis methods

[0100] 1) Single-sample gene set enrichment analysis (ssGSEA)

[0101] Genes associated with apoptosis and Parthanatos (PARP-1-dependent cell death) were extracted from the XDeathDB database (https: / / pcm2019.shinyapps.io / XDeathDB / ). ssGSEA was used to calculate the enrichment of each sample in GSE23160 for the apoptosis-related gene set and the Parthanatos death-related gene set. The corresponding mechanism score in the transcriptome expression matrix was derived using the reference gene set. The score represents the level of upregulation or downregulation of the relevant gene in the sample.

[0102] 2) Weighted correlation network analysis (WGCNA)

[0103] The WGCNA algorithm is a method for analyzing gene expression matrixes from multiple samples with diverse phenotypic information. Genes with similar expression patterns are clustered to form modules, and their associations with specific diseases or disease features are identified. In this study, to narrow the scope of WGCNA analysis and more accurately reflect changes in correlation during acute cerebral ischemia-reperfusion injury, we used DEGs screened from sequencing data as the analysis targets. We combined multiple disease-related traits (disease status, modeling time, apoptosis score, and Parthanatos score) in the GSE23160 dataset to perform WGCNA analysis. We identified modules with the strongest correlations between the target DEGs and the target disease phenotypes, as well as key genes within these modules. During the WGCNA analysis, the dispersion between different sequencing samples and phenotypic traits was first assessed to remove outliers. Then, the correlation values were multiplicatively calculated to determine the optimal soft threshold (power). The selected soft threshold was used for network construction and module analysis was performed in conjunction with phenotypic information. Finally, modules with strong and statistically significant correlations (P < 0.05) were screened to identify the genes within these modules.

[0104] 3) Protein-protein interaction (PPI) network construction

[0105] Using the STRING online database (https: / / string-db.org / ), we predicted potential interactions between protein-coding genes and constructed a protein-protein interaction (PPI) network. The resulting PPI network was imported into Cytoscape (v3.9.0) software for further visualization and network analysis. Nodes in the network represent proteins, and node degree represents the number of interactions a protein node possesses. The coding genes with the highest degree were considered key genes in the PPI network.

[0106] 2.9 GSEA pathway timing analysis

[0107] Using the GESECA function of the fgseaR package, we remotely connected to the MSigDB database and analyzed the identified DEGs to obtain enriched functional pathway information related to the DEGs. We ranked the correlations based on the Padj values obtained, and plotted a heat map depicting the pathway information. Finally, using trait information accompanying post-modeling time, we combined the expression information of genes associated with the most statistically significant pathways with the temporal traits for temporal analysis, thereby obtaining information on pathway activation during different stages of disease development.

[0108] 2.10 Prediction of upstream regulatory miRNAs of key genes using bioinformatics

[0109] We used the bioinformatics online websites TargetScan (http: / / www.targetscan.org) and miRDB (https: / / www.mirdb.org) to predict upstream regulatory miRNAs for the key genes identified previously. To better align the resulting miRNAs with disease status, we combined the predictions from these online websites with the differentially expressed miRNAs identified through sequencing analysis and used the Venn online analysis tool (http: / / bioinformatics.psb.ugent.be / webtools / Venn / ) to identify shared miRNAs.

[0110] 2.11 Dual luciferase reporter gene assay

[0111] (1) Construction of recombinant plasmid

[0112] The NCBI database was searched to identify the potential binding site for mmu-miR-3059-5p in the 3'UTR region of the TNFRSF1A gene, along with a 237-bp sequence nearby. Mutant 3'UTR fragments were generated by altering some of the complementary sequence bases. Primers were designed and synthesized by Qingke Biotechnology. The wild-type TNFRSF1A 3'UTR (WT) and mutant TNFRSF1A 3'UTR (MUT) fragments were amplified by PCR and cloned into the pmirGLO vector. Successfully cloned plasmids were transformed, extracted, and sequenced for use in cell transfection.

[0113] (2) Cell transfection

[0114] ① 293T cells were cultured in DMEM medium containing 10% FBS, 293T cells in the logarithmic phase were digested and resuspended, and 2×10 5 The cells were seeded at a density of 100 / ml in a 24-well plate and cultured in a 37°C, 5% CO2 incubator.

[0115] ② When the cell confluency reaches about 80%, transfect the cells according to the following groups, with 3 replicates per group:

[0116] Table 2 Cell grouping

[0117]

[0118] ③ Prepare the transfection mixture: Solution A: Add 0.6 μg plasmid + 20 pmol miRNA oligo to 50 μl serum-free DMEM medium and mix gently. Solution B: Add 2 μl Lipofectamine 2000 to 50 μl serum-free DMEM medium and mix gently. Mix solutions A and B thoroughly and let stand at room temperature for 20 minutes.

[0119] ④ Remove the original cell culture supernatant, wash with PBS three times, add the transfection mixture, and continue to culture in a 37°C, 5% CO2 incubator.

[0120] ⑤ Replace the culture medium with fresh one after 6 hours and detect the luciferase activity after 24 hours.

[0121] (3) Luciferase activity detection

[0122] ①Discard the cell culture supernatant and wash the cells twice with PBS. Add 100 μl / well of cell lysis buffer and lyse at room temperature for 15 minutes.

[0123] ②Pipette the cells to lyse them thoroughly, collect the lysate into a 1.5ml EP tube, centrifuge at 12000rpm for 5min, and collect the supernatant.

[0124] ③ Pipette 5 μl of supernatant into a 96-well plate, add 40 μl of firefly luciferase detection reagent II (LAR II), mix well, and detect the fluorescence intensity in a multifunctional microplate reader.

[0125] ④ Add 40 μl of Renilla luciferase substrate (Stop&Glo), mix well, and detect the fluorescence intensity in a multifunctional microplate reader.

[0126] ⑤ The detection results were normalized using the firefly luciferin intensity value / Renilla luciferin intensity value, with pmirGLO-null as the internal control.

[0127] 2.12 HT-22 cell transfection

[0128] The experimental HT-22 cells were randomly divided into: blank control group, transfection with miR-3059-5pmimic (catalog number: miR1160304024404-1-5, Guangzhou RiboBio Company), transfection with irrelevant sequence mimic (NC mimic, catalog number: miR1N0000001-1-5, Guangzhou RiboBio Company), transfection with miR-3059-5p inhibitor (catalog number: miR30014811-4-5, Guangzhou RiboBio Company), and transfection with irrelevant sequence inhibitor (NC inhibitor, catalog number: miR3N0000001-4-5, Guangzhou RiboBio Company).

[0129] ①HT-22 cells were cultured at 1×10 6 Cells were seeded into 6-well plates and cultured normally. Transfection was performed when the cell confluence reached 70%.

[0130] ② Dilute Lipofectamine 3000 with Opti-MEM medium: Take two 1.5ml EP tubes and add 125μl of Opti-MEM medium to each. Then add 3.75μl and 7.5μl of Lipofectamine 3000, respectively, and mix thoroughly. The purpose of setting two concentrations is to explore the appropriate dose of Lipofectamine 3000 for HT-22 cells.

[0131] ③ Dilute the plasmid with Opti-MEM medium: Take a 1.5ml EP tube, add 250μl Opti-MEM, 5μg miR-3059-5p mimic / inhibitor (or NC mimic / inhibitor), then add 10μl P3000 reagent (2μl / μg plasmid), and mix thoroughly.

[0132] ④ Take 125 μl of each solution prepared in the first two steps, mix thoroughly, and incubate at room temperature for 10-15 minutes.

[0133] ⑤ Add the above mixture (250 μl) to a 6-well plate and incubate HT-22 cells at 37°C for 48 h. Observe under a fluorescence microscope or detect the transfection efficiency by real-time quantitative PCR.

[0134] 2.13 Real-time quantitative PCR detection

[0135] (1) Extraction of total RNA from tissues or cells

[0136] Proceed according to conventional methods.

[0137] (2) In vitro reverse transcription of RNA into cDNA

[0138] Add the reagents listed in Table 3 to the RNase / DNase-free PCR tube in sequence and operate on ice.

[0139] Table 3 Reverse transcription system 1

[0140]

[0141] Shake gently, centrifuge briefly at low speed, incubate at 65°C for 5 min, and cool on ice.

[0142] Add the reagents listed in Table 4 to the above PCR tubes in sequence and operate on ice.

[0143] Table 4 Reverse transcription system 2

[0144]

[0145] Mix gently, incubate at 42°C for 60 min, and heat at 70°C for 5 min to terminate the reaction. The reaction product can be used directly in subsequent experiments or aliquoted and stored in a -80°C freezer.

[0146] (3) Real-time fluorescence quantitative PCR detection steps

[0147] ①The primer sequences used are shown in Table 5.

[0148] Table 5 Primer sequences

[0149]

[0150] ② The diluted cDNA (100 ng / μl) was used as a template, and the reaction system was as shown in Table 6.

[0151] Table 6 Real-time fluorescence quantitative PCR detection system

[0152]

[0153] ③ Set the reaction program: pre-denaturation at 95℃ for 30s; PCR reaction: 95℃ for 10s, 60℃ for 30s, for a total of 40 cycles; melting curve: 95℃ for 15s, 60℃ for 1min, heating by 0.3℃ every 15s, and 95℃ for 15s.

[0154] ④Data analysis: Fluorescence quantitative PCR instrument was used to detect the Ct value of each template. -ΔΔCt The relative expression levels of the target genes in the experimental and control groups were calculated, ΔCt=Ct(target gene)-Ct(internal reference), ΔΔCt=ΔCt(experimental group)-ΔCt(control group).

[0155] 2.14 TUNEL staining to detect cell apoptosis

[0156] 1) Place sterile cell slides into a 96-well plate and culture HT-22 cells at a density of 1×10 4 The cells were seeded into 96-well plates at a density of 100 cells / well and cultured overnight at 37°C in 5% CO2.

[0157] 2) According to the experimental design, cells in different groups are intervened.

[0158] 3) Wash the cells three times with PBS and fix them with 4% paraformaldehyde at room temperature for 15 minutes.

[0159] 4) Wash the cells three times with PBS, add 0.3% Triton X-100 permeabilization solution, and incubate at room temperature for 5 minutes.

[0160] 5) Prepare the TUNEL working solution according to the TUNEL assay kit instructions. Do not freeze the solution. Add 50 μl of TUNEL working solution to each well and incubate at 37°C in the dark for 1 hour.

[0161] 6) Wash with PBS three times, 5 minutes each time. Stain with DAPI for 5 minutes in the dark. Observe and count positive cells in random areas under a fluorescence microscope.

[0162] 2.15 Western blot detection of TNFRSF1A and Parthanatos death-related protein expression levels in mouse hippocampus tissue

[0163] (1) Extraction of total hippocampal protein

[0164] ① After deep anesthesia, mice were killed by cervical dislocation and placed on ice for decapitation to remove the brain.

[0165] ② Use ophthalmic scissors to cut the skin on the top of the skull along the sagittal line and use ophthalmic forceps to peel off the skull, taking care not to damage the brain tissue. Completely remove the left (ischemic) hemisphere brain tissue. Peel off the cerebral cortex on ice to expose the hippocampus. After separating it from the surrounding tissue, quickly transfer it to an EP tube and proceed immediately to the next step or store it in a liquid nitrogen tank.

[0166] ③ After weighing the tissue, add a mixture of RIPA and PMSF at a ratio of 1:10000:100. Disrupt and homogenize the tissue using an ultrasonic tissue disruptor. Centrifuge at 15,000 rpm for 5 minutes at 4°C and collect the supernatant.

[0167] (2) Western blot detection steps

[0168] ① Protein concentration determination: Add different concentrations of BSA standards (0, 0.025μg / μl, 0.05μg / μl, 0.1μg / μl, 0.2μg / μl, 0.3μg / μl, 0.4μg / μl, 0.5μg / μl) to the standard wells of a 96-well plate in sequence, 20μl / well, with 2 replicates for each well. Take 20μl of the protein to be tested and add it to the sample wells, with 3 replicates for each sample. Add 200μl of pre-mixed BCA working solution (reagent A:reagent B = 50:1) to each well, mix well, incubate at 37℃ in the dark for 30 minutes, and measure the OD562nm value with a microplate reader. Draw a standard curve based on the measured values of the BSA standards to calculate the concentration of the test sample.

[0169] ②Convert 30 μg of protein into the corresponding volume according to the concentration, add 5× Loading buffer at a ratio of total volume: 5× Loading buffer = 4:1, mix well, boil in a metal bath at 100°C for 10 minutes, and centrifuge at 12,000 rpm for 10 minutes.

[0170] ③ Electrophoresis: Use a 4-20% SurePAGE™ gradient precast gel and fill the electrophoresis tank with sufficient electrophoresis buffer. Add the sample to the loading well and 3 μl of protein marker to each of the two side wells. Perform electrophoresis at a constant voltage of 130V.

[0171] ④ Transfer: Trim the gel according to the molecular weight indicated by the protein marker, retaining the gel corresponding to the target protein. Cut the PVDF membrane to the appropriate size and activate it by soaking in methanol before use. Assemble the transfer cassette, ensuring that the sponge, gel, PVDF membrane, and sponge are placed in the order from negative to positive. Insert the cassette into the eBlot L1 Rapid Wet Transfer Apparatus for transfer.

[0172] ⑤ Blocking: Take out the PVDF membrane, soak it in 5% skim milk, and block it on a shaker at room temperature for 2 hours.

[0173] ⑥ Antibody Incubation: After blocking, rinse the PVDF membrane in TBST buffer for 5 min three times. Add primary antibodies at appropriate dilutions: TNFRSF1A 1:1000, PARP-1 1:1000, AIF 1:1000, Histone H3 1:5000, COX IV 1:5000, GAPDH 1:5000, and incubate overnight at 4°C on a shaker. The next day, wash the membrane with TBST buffer for 10 min three times. Then, soak the PVDF membrane in the corresponding secondary antibody (1:5000) based on the primary antibody species and incubate at room temperature for 90 min. Repeat the TBST wash for 10 min three times.

[0174] ⑦ Development and Image Acquisition: In a dark environment, mix ECL working solutions A and B in equal proportions to prepare a luminescent solution and evenly drip it onto the PVDF membrane. Place the PVDF membrane in an exposure machine and use AlphaView software for exposure and image acquisition.

[0175] 2.16 Statistical Analysis

[0176] GraphPad Prism 8.0.2 software was used for statistical analysis of the experimental data. The t-test was used to compare the data between groups, and one-way analysis of variance was used to compare multiple groups. The results were expressed as mean ± standard deviation (x ± s). Differences were considered statistically significant when P < 0.05.

[0177] 2. Experimental Results

[0178] 1. Monitoring cerebral blood flow to determine the stability of the MCAO / R model

[0179] Laser microcirculation blood flow imaging was used to detect cerebral blood flow in mice during the modeling period. The results showed that immediately after the middle cerebral artery was blocked by the suture, the cerebral blood flow on the obstructed side of the mice decreased to 23.18% ± 1.14% of the baseline value. When the suture was removed 60 minutes after the blockage, the cerebral blood flow returned to 76.28% ± 3.24% of the baseline value. Figure 1 A). Cerebral blood perfusion imaging of the mouse brain at baseline, immediately after suture insertion, and 24 hours after reperfusion. Figure 1 B.

[0180] 2. Overall analysis of gene expression in mRNA-seq samples

[0181] According to the FPKM value of each sample, draw a box plot ( Figure 2 A). The correlation of gene expression levels between samples is an important indicator for testing experimental reliability. The higher the correlation coefficient between samples, the more similar the expression patterns between samples are. In this sequencing, the correlation coefficients between all samples were greater than 0.8, indicating good replication effect and continued subsequent analysis ( Figure 2B). Principal component analysis (PCA) was used to evaluate the differences between the Sham and MCAO / R groups and the clustering quality of the biological replicates within the groups. It was found that the samples between the two groups could be significantly distinguished, and the clustering of the samples in the same group was acceptable ( Figure 2 C,D).

[0182] 3. Analysis of differential expression between the sham group and the MCAO / R group

[0183] The differential expression of genes between the sham group and the MCAO / R group was analyzed using the screening threshold of |log2FC|>1 and Padj<0.05, and the results were visualized by drawing a volcano plot. A total of 1107 differentially expressed genes (DEGs) were identified, of which 919 genes were upregulated and 188 genes were downregulated. The top 5 genes with the most significant upregulation and downregulation were marked ( Figure 3 ).

[0184] 4. Cell apoptosis and Parthanatos score of each sample

[0185] ssGSEA was used to calculate the cell apoptosis and Parthanatos death scores of each sample. The results showed that the cell apoptosis and Parthanatos death scores of the MCAO / R group were significantly higher than those of the Sham group ( Figure 4 ).

[0186] 5. GSEA Time Series Analysis

[0187] like Figure 5 As shown in A, a heat map of statistically significant pathways was obtained. Among them, the TNFA_SIGNALING_VIA_NFKB and APOPTOSIS pathways are the pathways that need special attention in the future. A temporal analysis was performed on the most statistically significant TNFA_SIGNALING_VIA_NFKB pathway, and the results are shown in Figure 5 As shown in Figure B, the pathway is always activated over time after model establishment, indicating that this pathway plays a certain role in the occurrence and progression of the disease.

[0188] 6. Weighted co-expression network construction and key module identification

[0189] The samples in GSE23160 were clustered using the Pearson correlation coefficient, and a sample cluster dendrogram and a heat map of the correlation between the target clinical characteristics were drawn ( Figure 6A), it can be observed that there are no outlier samples in the cluster tree. According to the selection criteria of the soft threshold β, that is, the scale-free fitting index R2>0.8 and the average adjacency coefficient<100, the appropriate soft threshold β is selected ( Figure 6 B). When β = 16, R2 = 0.9, and the slope is -1.38, the gene expression network at this time can be considered to be approximately a scale-free network distribution ( Figure 6 C).

[0190] A systematic clustering tree was constructed between genes. The dynamic hybrid shear tree algorithm was used to identify several gene modules represented by different colors. Modules with the same color indicate that the genes in them have a high degree of co-expression. Cluster analysis merged modules with high similarity, and finally obtained blue modules, turquoise modules, and gray modules. The gray modules represent genes that cannot be classified into any module ( Figure 7 A). Finally, the obtained gene modules were analyzed for correlation with traits such as apoptosis, Parthanatos death, disease, and reperfusion time. It was found that the turquoise color module characteristic genes were significantly positively correlated with the above traits (P<0.05, Figure 7 B).

[0191] 7. PPI analysis of key genes

[0192] The turquoise module genes (317) were extracted and the intersection with the apoptosis and Parthanatos death related gene sets was obtained by Wayne analysis, and finally 12 key genes were obtained ( Figure 8 A). PPI analysis was performed on key genes. The two genes with the highest degree (the number of connections between a node and other nodes in the network) were TNFRSF1A and Caspase-8 ( Figure 8 B) Combined with the TNFA_NF-κB signaling pathway enriched in 2.2.5 temporal analysis, the key factor TNFRSF1A was identified.

[0193] 8. Expression of the key gene TNFRSF1A

[0194] After identifying the key gene TNFRSF1A, we used qPCR and Western blot techniques to verify the effect of IS on TNFRSF1A expression levels in vitro and in vivo. The results showed that compared with the control group, the expression levels of TNFRSF1A mRNA and protein in HT22 cells treated with OGD / R were significantly increased ( Figure 9 A, B); Similarly, compared with the Sham group, the expression of TNFRSF1A mRNA and protein in the brain tissue of mice in the MCAO / R group was significantly increased ( Figure 9 C, D).

[0195] 9. Prediction and validation of TNFRSF1A upstream miRNA

[0196] Differential expression analysis was performed on the miRNA-seq sequencing results of the sham group and MCAO / R group samples. The screening thresholds were set as |log2FC|>1 and Padj<0.05. A total of 994 differentially expressed miRNAs (DemiRNAs) were identified, of which 774 were upregulated and 220 were downregulated. Figure 10 A. TargetScan and miRDB online databases were used to predict TNFRSF1A upstream regulatory miRNAs, and the predicted results were intersected with the sequencing data DemiRNA by Wayne analysis. A total of 5 miRNAs (mmu-miR-3059-5p, mmu-miR-3102-3p, mmu-miR-223-5p, mmu-miR-324-5p, and mmu-miR-5621-3p) were obtained. Figure 10 B. Among them, only mmu-miR-3059-5p was significantly downregulated in the MCAO / R group, while the expression of the other four miRNAs was upregulated. Therefore, miR-3059-5p was selected as the upstream regulatory miRNA of the IS key gene TNFRSF1A, and the binding relationship between the two was further verified.

[0197] The wild-type TNFRSF1A 3'UTR (WT) binding sequence and the mutant TNFRSF1A 3'UTR (MUT) binding sequence were constructed, cloned into luciferase reporter plasmids, and co-transfected with miR-3059-5pmimic or NC mimic into 293T cells. The experimental results showed that ( Figure 10 C), co-transfection of TNFRSF1A 3'UTR (WT) and miR-3059-5p mimic significantly reduced the fluorescence intensity in 293T cells, while no decrease in fluorescence intensity was detected in the TNFRSF1A 3'UTR (MUT) group. In addition, overexpression of miR-3059-5p in HT-22 cells significantly decreased the expression of TNFRSF1A protein (P<0.01); conversely, inhibition of miR-3059-5p levels in HT-22 cells significantly increased the expression of TNFRSF1A protein (P<0.01), see Figure 10 D.

[0198] 10. Effect of miR-3059-5p on OGD / R-induced apoptosis of HT-22 cells and death of Parthanatos

[0199] Through rescue experiments, we further studied the regulatory effect of miR-3059-5p on TNFRSF1A and its effect on cell parthanatos and apoptosis in HT-22 cells treated with OGD / R. Western blot results showed that ( Figure 11 AC), compared with the Control group, the expression level of PARP-1 in neurons of the OGD / R group was significantly increased (P<0.0001), AIF translocated from mitochondria to the nucleus, and the expression level of AIF in the nucleus was significantly increased (P<0.0001); compared with the OGD / R group, overexpression of miR-3059-5p significantly reduced the expression of PARP-1 in OGD / R-treated neurons (P<0.0001). At the same time, although there was no statistically significant change in the expression of AIF in mitochondria of HT-22 cells after overexpression of miR-3059-5p, the expression level of AIF in the nucleus was significantly decreased (P<0.01), indicating that the translocation of AIF to the nucleus was inhibited. After further transfection of TNFRSF1A overexpression plasmid, the expression of PARP-1 and nuclear AIF in the OGD / R+miR-3059-5p+pcDNA-3.1-TNFRSF1A group were significantly higher than those in the OGD / R+miR-3059-5p+pcDNA-3.1 group, suggesting that overexpression of TNFRSF1A can reverse the inhibitory effect of miR-3059-5p on cell death. Similarly, we used TUNEL staining to examine cell apoptosis in each group. The results showed that overexpression of miR-3059-5p significantly reduced the apoptosis rate of HT-22 cells (P<0.0001), but overexpression of TNFRSF1A partially reversed this effect of miR-3059-5p (P<0.01). Figure 11 D, E.

[0200] The above embodiments are only provided for understanding the method and core concept of the present invention. It should be noted that, without departing from the principles of the present invention, a number of improvements and modifications may be made to the present invention by a person skilled in the art, and such improvements and modifications shall fall within the scope of protection of the claims of the present invention.

Claims

1. Use of a TNFRSF1A inhibitor in the preparation of a drug for preventing or treating ischemic stroke, wherein the TNFRSF1A inhibitor is miR-3059-5p.

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