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Research Article
2025
:22;
79
doi:
10.25259/Cytojournal_47_2025

Study on the correlation between Interleukin 4 and febrile seizures

Department of Pediatrics, The Third Affiliated Hospital of Zunyi Medical University (the First People’s Hospital of Zunyi), Zunyi City, Guizhou Provincial, China.
Department of Pediatric Surgery, Affiliated Hospital of Zunyi Medical University, Zunyi City, Guizhou Provincial, China.
Department of Medicine, The Third Affiliated Hospital of Zunyi Medical University (the First People’s Hospital of Zunyi), Zunyi City, Guizhou Provincial, China.
Department of Pediatrics, People’s Hospital of Daozhen Gelao and Miao Autonomous County, Guizhou Provincial, China.
Author image

*Corresponding author: Bo Huang, Department of Pediatrics, The Third Affiliated Hospital of Zunyi Medical University (the First People’s Hospital of Zunyi), Zunyi City, Guizhou Province, China. huangbo202304@163.com

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Xiang X, Wang S, Tang C, Jin H, Lei L, Mao G, et al. Study on the correlation between Interleukin 4 and febrile seizures. CytoJournal. 2025;22:79. doi: 10.25259/Cytojournal_47_2025

Abstract

Objective:

Febrile seizures (FS) are common in pediatric epilepsy, but their precise etiology remains unclear. Although cytokines such as interleukin (IL)-4, IL-1, and IL-6 are known to influence FS fever responses, their specific role is not fully understood. This study aimed to clarify the correlation between IL-4 levels and febrile convulsions, exploring molecular mechanisms through bioinformatics and animal experiments to enhance the understanding of FS pathogenesis.

Material and Methods:

With the GSE28674 dataset, the K-means clustering algorithm was used to select key genes that regulate IL-4 during feature selection. An animal model of FS was developed, and in vivo experiments were conducted using enzyme-linked immunosorbent assay, flow cytometry, quantitative polymerase chain reaction (qPCR), Western blot, and immunofluorescence for validation.

Results:

In this study, bioinformatics analysis and K-means clustering identified proto-oncogene (Jun), protooncogene (Fos), and Early growth response-1 (Egr1) as upstream regulators of IL-4. Dual-luciferase reporter assays confirmed that these transcription factors could activate the IL-4 promoter. qPCR and Western blot analyses showed that the messenger RNA (mRNA) and protein expression levels of Jun, Fos, Egr1, and IL-4 in the FS group were significantly higher than those in the normal control (NC) group (P < 0.05). In addition, immunohistochemical analysis demonstrated that the expression levels of these proteins in the FS group were significantly higher than those in the NC group (P < 0.001). The study also explored the impact of the IL-4 receptor blocker dupilumab on FS, revealing that the dupilumab group exhibited significantly reduced seizure latency (P < 0.001) and significantly increased seizure duration and Racine scores versus the FS group (P < 0.01). Furthermore, dupilumab significantly decreased the expression of IL-1β, tumor necrosis factor α, and IL-6 in serum (P < 0.001), as well as heat shock protein 70 mRNA and protein expression, glial fibrillary acidic protein, cysteine protease-3, and Bcl-2-associated X protein/B-cell lymphoma 2 in hippocampal tissue (P < 0.001). Flow cytometry analysis indicated an increased T helper cell type 1 (Th1)/T helper cell type 2 (Th2) cell ratio (P < 0.001) and increased apoptosis in the FS and dupilumab groups versus the NC group (P < 0.001), along with decreased cell cycle progression and proliferation ability (P < 0.001). Compared with the FS group, the dupilumab group exhibited a further increase in Th1/Th2 cell ratio and apoptosis (P < 0.001), along with a further decrease in cell cycle progression and proliferation ability (P < 0.001).

Conclusion:

IL-4 and its upstream transcription factors Jun, Fos, and Egr1 may be associated with FS occurrence and development. Moreover, dupilumab appeared to mitigate the symptoms of FS and modulate the associated immune response by blocking the IL-4 receptor.

Keywords

Cytokines
Differentially expressed genes
Dupilumab
Febrile seizures
Interleukin 4

INTRODUCTION

Febrile seizures (FS) are a specific type of epilepsy syndrome that occurs in children aged between 6 months and 5 years due to hyperthermia.[1] They account for approximately 30% of convulsions and have an incidence rate of 2–5%.[2] The exact causes of FS remain unclear, but possible factors include incomplete development of the central nervous system, cytokine-induced neuroinflammation, immune responses, genetics, and other factors.[3] Recent studies on FS have identified a link between the expression levels of cytokines and seizures, with significant changes in interleukin (IL)-6, IL-8, IL-10, and IL-1Ra observed in the serum of children with FS.[4]

IL-4 is a cytokine with multiple biological functions; it is mainly produced by activated T cells, and it exerts regulatory effects on various immune cells in the body.[5] IL-4 can stimulate macrophages and microglia to transform into an anti-inflammatory phenotype, thereby inhibiting the progression of inflammation, promoting tissue repair, and exerting neuroprotective effects.[6] In addition, IL-4 activates and mediates T helper cell type 2 (Th2) immune responses by inducing T helper cells to differentiate into Th2 cells and simultaneously inhibiting monocytes and activated T cells from producing T helper cell type 1 (Th1) cells, thereby exerting anti-inflammatory effects.[7,8]

The mechanisms of action and potential therapeutic value of IL-4 in neurological diseases have garnered considerable attention. IL-4-induced microglia exhibit neuroprotective effects in Parkinson’s disease and have a key role in regulating the physiological functions of the central nervous system.[9] In addition, IL-4’s involvement in tissue repair has been explored because it activates endogenous lymphocytes and promotes the polarization of M2 macrophages, both of which are essential for tissue regeneration.[10] Meanwhile, an increasing number of studies have suggested that children with FS have altered amounts of the anti-inflammatory cytokine IL-4 in their peripheral blood and cerebral fluid. This finding has sparked considerable interest among researchers, who believe that IL-4 may be pivotal in the pathogenesis of FS.[11,12]

At present, there are few studies on the relationship between IL-4 and the onset of FS. The purpose of this study was to clarify the correlation between IL-4 level changes and FS and its molecular mechanism through bioinformatics analysis and animal experiments to provide new ideas for the exploration of the pathogenesis and diagnosis of FS.

MATERIAL AND METHODS

Animal model

A total of 24 specific pathogen-free-grade Sprague-Dawley male rats (7 weeks old and 0.18–0.22 kg; Chongqing Enswell Biotechnology Co., Ltd.) were used in this study. All rats were kept under similar conditions: temperature of 23℃ ± 2℃, humidity of 35–60%, 12 h light/dark cycle, and free access to drinking water and food. After 1 week of acclimatization, the animals were subjected to the experiment. All experimental procedures strictly adhered to the “Regulations on the Management of Experimental Animals” and international ethical guidelines for animal experiments. This study was approved by the Institutional Ethics Committees of the Third Affiliated Hospital of Zunyi Medical University (the First People’s Hospital of Zunyi) (Ethics Review No. [2022]-2-33).

A total of 24 rats were randomly divided into three groups: The normal control (NC) group, the FS model group, and the IL-4 receptor antagonist group (dupilumab). The IL-4 receptor antagonist group was provided with 10 mg/kg dupilumab (SAR-231893, MCE, Shanghai, China) through subcutaneous injection every 3 days, with a total of two doses. The dose of 10 mg/kg was selected based on preliminary dose-response studies [Figure S1a and b], which indicated that this concentration effectively modulated IL-4 receptor activity without causing significant side effects in the rats. The NC group and the FS group were injected with an equal volume of physiological saline. After the subcutaneous injection of dupilumab, the FS model group and the IL-4 receptor antagonist group rats underwent the hot water bath method to establish the FS model.[13] Specifically, the rats in the FS group and the IL-4 receptor antagonist group were placed in a transparent glass tube (diameter 10 cm and height 50 cm) with small everted holes at the bottom. The tube was vertically placed in a constant-temperature water bath (45℃ ± 0.25℃. Adjusting the depth of the water in the tube with rubber pads at the bottom ensured that the rats stood along the wall of the tube with only their heads exposed. Seizures were induced once in the morning and afternoon for each rat, for a total of 10 inductions over 5 consecutive days. The occurrence of seizures was observed, and the latency, severity, and duration of the seizures were recorded. After the model was established, rats from each group were anesthetized with 1% sodium pentobarbital (0.5 mL/100 g; P3761, Sigma– Aldrich, St. Louis, Missouri, USA) and euthanized by cervical dislocation. Subsequently, peripheral blood, serum, and hippocampal tissue samples were collected for testing.

SUPPLEMENTARY FIGURE

Racine scoring for FS rats

The severity of seizures in rats was assessed using the Racine scoring method: [14] Level 0: No adverse reactions; Level I: Facial clonus and chewing movements; Level II: Muscle spasms primarily consisting of nodding or tail shaking; Level III: Unilateral clonus and spasms; Level IV: Bilateral clonus of forelimbs, accompanied with a standing posture; and Level V: Tonic-clonic seizures, sustained standing, strong body arching, and falling.

Differentially expressed gene (DEG) screening

The dataset Gene Expression Omnibus (GEO) Series accession number 28674 (GSE28674) was obtained from the GEO database (https://www.ncbi.nlm.nih.gov/geo/), which contained seven FS samples and 11 normal samples. EdgeR package (Bioconductor, Melbourne, Australia) was used to screen DEGs, with P < 0.05 and |log2FC| ≥ 1 as the screening conditions. The DAVID database (https://davidbioinformatics.nih.gov/) was used to conduct the gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of upregulated and downregulated DEGs. The K-means clustering algorithm was used to cluster DEGs, and the elbow rule was used to determine the optimal K value. The online database STRING (https://string-db.org/) generated a diagram of protein-protein interaction (PPI) network. The maximal clique centrality (MCC) algorithm was used in the cytoHubba plug-in of Cytoscape 3.8.0 (University of California, California, USA) to screen the top ten genes in the PPI network as key genes.

Enzyme-linked immunosorbent assay (ELISA) detection

The expression levels of IL-1β, tumor necrosis factor α (TNF-α), and IL-6 in serum were detected using ELISA kits. Rat IL-1β kit (RX302869R, Ruixin Biotech, Quanzhou, China), rat TNF-α ELISA kit (RX302058R, Ruixin Biotech, Quanzhou, China), and rat IL-6 ELISA kit (RX302856R, Ruixin Biotech, Quanzhou, China) were used.

Flow cytometry

Th1/Th2 cell ratio: Heparin anticoagulated blood (1.5 mL) was collected from rats treated in groups, and 3 mL of lymphocyte separation solution (P8630, Solarbio, Beijing, China) was added to a test tube. After diluting the blood with an equal volume of phosphate-buffered saline (PBS) solution, the upper layer of the lymphocyte separation medium was carefully added and centrifuged. After the removal of the test tube, mononuclear cells were carefully absorbed at the liquid-phase junction. Subsequently, 3 mL of PBS solution (PB180327, Pricella, Wuhan, China) was added, mixed well, and centrifuged at ×1500 g for 5 min. The supernatant was then discarded. Each group of cells was resuspended in PBS for washing, transferred to a 1.5 mL Eppendorf (EP) tube, and centrifuged at 1000 rpm for 5 min. The supernatant was then discarded. The cell pellet was carefully resuspended in 100 μL PBS, 5 μL anti-rat CD4 fluorescein isothiocyanate (FITC) (AR00401-50, MULTI SCIENCES, Hangzhou, China) was added, the cells were mixed and incubated at room temperature in the dark for 20 min, and a blank control was set at the same time. After incubation, 1 mL of PBS was added, mixed evenly, and centrifuged. The supernatant was discarded, and this procedure was repeated. After lightly blowing off the centrifuged cells, 100 μL of PBS was added carefully to resuspend the cell pellet. About 5 μL of phycoerythrin (PE) Rat Anti-Mouse Interferon-gamma (554412, BD Biosciences, New Jersey, USA) was added, and the cells were mixed and incubated at room temperature in the dark for 20 min in blank control. After incubation, the suspension was supplemented with 1 mL of PBS, and the previously described procedures were repeated. Subsequently, a fixative solution was added, incubated in the dark, and centrifuged at 500 g for 5 min. A membrane-breaking agent was added and incubated in the dark for 15 min. Followed by incubation, 1 mL of PBS washing solution was supplied. The mixture was centrifuged at ×500 g for 5 min, and the supernatant was discarded. Fluorescently labeled allophycocyanin (APC) Rat Anti-Mouse IL-4 antibody (562045, BD Biosciences, New Jersey, USA) was used, mixed, and cultured, added with 1 mL of washing solution, and centrifuged at ×500 g for 5 min. After we discarded the supernatant, we added 500 mL of PBS or 500 mL of 1% PFA for fixation and analysis on a flow cytometer (CytoFLEX, Beckman, Brea, California, USA).

Cell apoptosis was detected using the Annexin V FITC/propidium iodide (PI) Apoptosis Kit (40302ES50, Yeasen Biotechnology, Shanghai, China). The cell cycle was detected using the Flow Cytometry Cell Cycle Kit (AC12L543, LIFE-iLAB BIO, Shanghai, China). Cell proliferation was detected using the BeyoClick EdU-647 Cell Proliferation Detection Kit (C0081S, Beyotime, China). Rat cells were tested quarterly for mycoplasma contamination using PCR-based methods, and the results were negative.

Quantitative polymerase chain reaction (qPCR) detection

Extracted total RNA was reversely transcribed according to the Goldenstar RT6 complementary deoxyribonucleic acid (cDNA) Synthesis Kit Ver.2 (TSK302M, Qingke, Beijing, China), and fluorescence quantitative analysis was carried out following the guidelines of 2 × T5 Fast qPCR Mix kit (SYBR Green I, TSE002, Qingke, Beijing, China). Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as an internal control. The polymerase chain reaction (PCR) primer sequences are shown in Table 1. Relative expression levels were calculated using the 2−△△Ct method, which represents the fold difference in target gene expression in the experimental group compared with the control group.

Table 1: Primer sequence.
Name Sequence (5’-3’)
Jun-F AGACGCTTGAGTTGAGAGCC
Jun-R CTTCCATGGGTCCCTGCTTT
Fos-F CTCTGACTCACTGAGCTCGC
Fos-R CACAGCCTGGTGTGTTTCAC
Egr1-F ATCAAAGCCTTCGCCACTCA
Egr1-R GTGTAAGCTCATCCGAGCGA
IL-4-F TGTAGAGGTGTCAGCGGTCT
IL-4-R TCAGTGTTGTGAGCGTGGAC
HSP70-F CGGTAGAGGCCCGTCTTTTT
HSP70-R GCAGCGGTCGCTATACTCAT
GFAP-F TTGACCTGCGACCTTGAGTC
GFAP-R TCTTCGCCCTCCAGCAATTT
Caspase-3-F ACCGATGTCGATGCAGCTAA
Caspase-3-R GGTGCGGTAGAGTAAGCATA
Bax-F CGTCTGCGGGGAGTCACG
Bax-R AGCCATCCTCTCTGCTCGAT
Bcl-2-F GAACTGGGGGAGGATTGTGG
Bcl-2-R GGGGTGACATCTCCCTGTTG
GAPDH-F CAATCCTGGGCGGTACAACT
GAPDH-R TACGGCCAAATCCGTTCACA

Jun: Jun proto-oncogene, Fos: Fos proto-oncogene, Egr1: Early growth response-1, IL-4: Interleukin 4, GAPDH: Glyceraldehyde-3-phosphate dehydrogenase, HSP70: Heat shock protein 70, caspase-3: Cysteine protease-3, GFAP: Glial fibrillary acidic protein, Bax: Bcl-2-associated X protein, Bcl-2: B-cell lymphoma 2, A: Adenine, C: Cytosine, G: Guanine, T: Thymine

Western blot detection

Total proteins were extracted and separated by electrophoresis and then transferred to a polyvinylidene fluoride membrane (10600023, Amersham, Hessen, Germany). This membrane was sealed with 5% skimmed milk and rinsed 3 times with tris-buffered saline with tween 20 (TBST). After dilution at 1:1000, the primary antibody was added and incubated overnight at 4℃, followed by TBST washing again; the secondary antibody was adjusted to a certain concentration with a seal solution (1:2000) and then incubated at room temperature for 1 h. After three washes with TBST, each time for 10 min, mixed the enhanced chemiluminescence exposure solution (34580, Thermo, Massachusetts, USA) according to the ratio of solution A: B at 1:1, covered the whole film evenly, reacted for 1 min, and placed in the exposure instrument (U.S., Bio-Rad, Universal Hood II) for detection. The primary antibodies were as follows: Jun proto-oncogene (Jun) (A11378, ABclonal, Wuhan, China), Fos proto-oncogene (Fos) (A0236, ABclonal, Wuhan, China), p-Jun proto-oncogene (p-Jun) (AP0048, ABclonal, Wuhan, China), p-Fos proto-oncogene (p-Fos) (AP0038, ABclonal, Wuhan, China), early growth response-1 (Egr1) (A7266, ABclonal, Wuhan, China), IL-4 (A4988, ABclonal, Wuhan, China), Heat shock protein 70 (HSP70) (A23457, ABclonal, Wuhan, China), glial fibrillary acidic protein (GFAP) (A19058, ABclonal, Wuhan, China), cysteine protease-3 (caspase-3) (A11319, ABclonal, Wuhan, China), Bcl-2-associated X protein (Bax) (A19684, ABclonal, Wuhan, China), B-cell lymphoma 2 (Bcl-2) (A19693, ABclonal, Wuhan, China), and GAPDH (A19056, ABclonal, Wuhan, China). The secondary antibody was horseradish peroxidase (HRP)-conjugated Goat anti-rabbit immunoglobulin G (IgG) (H + L) (AS014, ABclonal, Wuhan, China). One-way analysis of variance (ANOVA) was used for group comparisons, and data analysis and graphical representation were facilitated through GraphPad Prism 8.0 software.

Immunofluorescence detection

After dewaxing and rehydration of hippocampal tissue paraffin sections, immunofluorescence staining was performed. Antigen retrieval was carried out for 30 min, and 0.5% Triton X-100 (ST795, Beyotime, Shanghai, China) was applied to the tissue sections for 60 min at room temperature. Subsequently, these samples were treated using goat serum, added with primary antibody (diluted 1:200), and incubated at 4℃ overnight. Furthermore, a secondary antibody (diluted 1:300) was supplied for incubation for 1.5 h. Thereafter, 4’,6-diamidino-2-phenylindole (DAPI) staining (C1005, Beyotime, Shanghai, China) was conducted in the dark for 5 min to stain the nuclei, followed by washing off excess DAPI with PBS. Eventually, samples were sealed by adding an anti-fluorescence quenching reagent. Imaging of the sections was performed using the Mshot inverted microscope (MF53, Guangzhou Ming-Mei Technology Co., Ltd., China). The primary antibodies were as follows: IL-4 (bs-0581R, Bioss antibodies, Beijing, China), Egr1 (bs-1076R, Bioss antibodies, Beijing, China), Jun (bsm-42050M, Bioss antibodies, Beijing, China), p-Jun (bs-3210R, Bioss antibodies, Beijing, China), Fos (bs-10172R, Bioss antibodies, Beijing, China), and p-Fos (bs-3153R, Bioss antibodies, Beijing, China). The secondary antibodies were Cy3 Goat Anti-Mouse IgG (H + L) (AS008, ABclonal, Wuhan, China) and Cy3 Goat Anti-Rabbit IgG (H + L) (AS007, ABclonal, Wuhan, China).

Dual-luciferase reporter gene assay

The 293T cells (LH-H080, Laibaiha (Shanghai) Biotechnology Co., Ltd., Shanghai, China) were subjected to short tandem repeat (STR) identification to exclude exogenic cell contamination. The STR identification report can be found in the supplementary material. In this study, 293T cells showed negative results on testing quarterly for mycoplasma contamination through PCR-based methods. After reviving and passaging 293T cells, vector construction was performed. Through the predictions from analysis websites, a 2,000 bp fragment of the IL-4 promoter region was synthesized and cloned into the dual-luciferase reporter plasmid pGL4.11-basic, referred to as pGL4.11- wild-type (WT). In addition, mutation sites within the 2,000 bp sequence of the IL-4 promoter were introduced and cloned into the same reporter vector, resulting in the construct promega luciferase (pGL) 4.11-mut. For co-transfection of plasmids, 50 μL of culture medium devoid of antibiotics and serum was added, followed by 1 μg of plasmid DNA (mixed in appropriate groups), and lightly mixed using a pipette. Then, 1.6 μL of nanofusion transfection reagent was added, mixed lightly, and left at room temperature for 5–20 min before adding to the cells in a 12-well plate.

  • Verification of Jun binding sites with IL-4, consisting of five groups:

    ① plasmid cloning DNA (pcDNA) 3.1-NC + pGL4.11-NC + Promega Renilla Luciferase-Thymidine Kinase (PRL-TK);

    ② pcDNA3.1-NC + pGL4.11-WT + PRL-TK;

    ③ pcDNA3.1-JUN + pGL4.11-NC + PRL-TK;

    ④ pcDNA3.1-JUN + pGL4.11-WT + PRL-TK;

    ⑤ pcDNA3.1-JUN + pGL4.11-mut + PRL-TK;

  • Verification of Fos binding sites with IL-4, consisting of five groups:

    ① pcDNA3.1-NC + pGL4.11-NC + PRL-TK;

    ② pcDNA3.1-NC + pGL4.11-WT + PRL-TK;

    ③ pcDNA3.1-FOS + pGL4.11-NC + PRL-TK;

    ④ pcDNA3.1-FOS + pGL4.11-WT + PRL-TK;

    ⑤ pcDNA3.1-FOS + pGL4.11-mut + PRL-TK;

  • Verification of Egr1 binding sites with IL-4, consisting of five groups:

    ① pcDNA3.1-NC + pGL4.11-NC + PRL-TK;

    ② pcDNA3.1-NC + pGL4.11-WT + PRL-TK;

    ③ pcDNA3.1-Egr1 + pGL4.11-NC + PRL-TK;

    ④ pcDNA3.1-Egr1 + pGL4.11-WT + PRL-TK;

    ⑤ pcDNA3.1-Egr1 + pGL4.11-mut + PRL-TK.

Statistical analysis

Group comparisons were executed through one-way ANOVA with the Tukey post hoc test method, and data analysis and graphical representation were facilitated through GraphPad Prism 8.0 software (GraphPad Software, LLC, California, USA). For comparisons between the two groups, the independent samples t-test was used to assess the significance of differences between the means. The measurement data were expressed as mean ± standard deviation. Statistical significance was set at P < 0.05.

RESULTS

Analysis of DEGs

A total of 50 significantly differentially expressed messenger RNAs (mRNAs) were screened from the GSE28674 dataset [Figure 1a], of which 44 were upregulated and six were downregulated [Figure 1b]. These DEGs were mainly enriched in biological processes, such as response to reactive oxygen species, response to mechanical stimuli, and cellular response to chemical stress in GO [Figure 1c]. KEGG enrichment analysis showed that these DEGs were mainly concentrated in signaling pathways such as the mitogen-activated protein kinase (MAPK) signaling pathway, advanced glycation end-products (AGE)-receptor for AGE (RAGE) signaling pathway, TNF signaling pathway, and relaxin signaling pathway [Figure 1d].

Differentially expressed mRNAs between NC group and FS group. (a) Heatmap: The expression levels of differentially expressed genes in each sample [fragments per kilobase per million (FPKM) values] were log-transformed with base 2, and Euclidean distances were calculated. Hierarchical clustering was then performed to obtain the overall clustering results for the samples. In the figure, rows represent genes, and columns represent samples. The differences in gene expression across samples are reflected by changes in the heatmap colors. (b) Volcano map: The X-axis represents the log-transformed fold change of differentially expressed genes in the comparison group. The Y-axis represents the negative log-transformed P-value of the statistical significance of the expression change. Each point represents a specific gene, with red indicating significantly upregulated genes, blue indicating significantly downregulated genes, and gray indicating genes with no significant expression difference. (c) GO enrichment: The X-axis represents GO terms under the BP category, and the Y-axis represents the number of candidate target genes annotated to that term (including its sub-terms). (d) KEGG enrichment: The X-axis represents the number of target genes corresponding to each KEGG pathway, and the Y-axis represents the KEGG pathway names. The color indicates the significance of pathway enrichment; redder colors indicate higher significance. P-value represents statistical significance. mRNA: Messenger RNA, NC: Normal control, FS: Febrile seizures, GO: Gene ontology, BP: Biological process, KEGG: Kyoto encyclopedia of genes and genomes.
Figure 1:
Differentially expressed mRNAs between NC group and FS group. (a) Heatmap: The expression levels of differentially expressed genes in each sample [fragments per kilobase per million (FPKM) values] were log-transformed with base 2, and Euclidean distances were calculated. Hierarchical clustering was then performed to obtain the overall clustering results for the samples. In the figure, rows represent genes, and columns represent samples. The differences in gene expression across samples are reflected by changes in the heatmap colors. (b) Volcano map: The X-axis represents the log-transformed fold change of differentially expressed genes in the comparison group. The Y-axis represents the negative log-transformed P-value of the statistical significance of the expression change. Each point represents a specific gene, with red indicating significantly upregulated genes, blue indicating significantly downregulated genes, and gray indicating genes with no significant expression difference. (c) GO enrichment: The X-axis represents GO terms under the BP category, and the Y-axis represents the number of candidate target genes annotated to that term (including its sub-terms). (d) KEGG enrichment: The X-axis represents the number of target genes corresponding to each KEGG pathway, and the Y-axis represents the KEGG pathway names. The color indicates the significance of pathway enrichment; redder colors indicate higher significance. P-value represents statistical significance. mRNA: Messenger RNA, NC: Normal control, FS: Febrile seizures, GO: Gene ontology, BP: Biological process, KEGG: Kyoto encyclopedia of genes and genomes.

Upstream regulatory genes of IL-4 are Jun, Fos, and Egr1

The K-means clustering algorithm was used for cluster analysis of DEGs, and the elbow rule determined the optimal K value to be 4 [Figure 2a]. DEGs were divided into four clusters, and Jun, Fos, and Egr1 were distributed in the same cluster [Figure 2b]. Among the TOP10 core genes of PPI are Jun, Fos, Egr1, Cyr61, Dusp1, Atf3, Nr4a1, Ctgf, Serpine1, and Btg2 [Figure 2c and d]. Among the TOP10 core genes of PPI, the top three Jun, Fos, and Egr1 were all known upstream transcription factors of IL-4.[15,16] The analysis of DEGs showed that they were all significantly upregulated in the FS group, suggesting their role as molecular mechanisms associated with increased IL-4 levels.

Screening of upstream regulatory genes of IL-4 in the GEO database. (a) Elbow method to determine the optimal K value. (b) Cluster plot; PPI network diagram to screen key genes: (c) Network diagram of all genes. (d) Top 10 gene network diagram, the color ranges from red to yellow, indicating the level of importance, with red representing high importance. IL: Interleukin, PPI: Protein–protein interaction.
Figure 2:
Screening of upstream regulatory genes of IL-4 in the GEO database. (a) Elbow method to determine the optimal K value. (b) Cluster plot; PPI network diagram to screen key genes: (c) Network diagram of all genes. (d) Top 10 gene network diagram, the color ranges from red to yellow, indicating the level of importance, with red representing high importance. IL: Interleukin, PPI: Protein–protein interaction.

Jun, Fos, and Egr1 can activate the IL-4 promoter

The dual-luciferase reporter gene assay [Figure 3a-c] suggested that the transcription factors Jun, Fos, and Egr1 may activate the IL-4 promoter. This conclusion was based on the observation that their overexpression increased firefly luciferase activity linked to the IL-4 promoter. The activation of the IL-4 promoter by Jun, Fos, and Egr1 was likely achieved through binding to specific DNA sequences within the promoter. This was inferred from the differences in luciferase activity driven by WT and mutant promoters, where the activity of the mutant promoter did not show significant changes, suggesting that the activation by these transcription factors depends on specific DNA binding sites. Furthermore, the experiments confirmed that the overexpression of Jun, Fos, and Egr1 did not cause non-specific alterations in luciferase activity. This was demonstrated by comparing a promoter with a non-specific sequence (NC) with the WT promoter, showing that these transcription factors specifically activated the IL-4 promoter without affecting the non-specific sequence.

Regulatory effects of Jun, Fos, and Egr1 on IL-4. (a) Verification of Jun binding sites with IL-4 (n = 3). Compared with pcDNA3.1-NC + pGL4.11-WT + PRL-TK, ✶✶✶P < 0.001; Compared with pcDNA3.1-JUN + pGL4.11-WT + PRL-TK, ###P < 0.001. (b) Verification of Fos binding sites with IL-4 (n = 3). Compared with pcDNA3.1-NC + pGL4.11-WT + PRL-TK, ✶✶✶P < 0.001; Compared with pcDNA3.1-FOS + pGL4.11-WT + PRL-TK, ###P < 0.001. (c) Verification of Egr1 binding sites with IL-4 (n = 3). Compared with pcDNA3.1-NC + pGL4.11-WT + PRL-TK, ✶✶✶P < 0.001; Compared with pcDNA3.1-Egr1 + pGL4.11-WT + PRL-TK, ###P < 0.001. Jun: Jun proto-oncogene, Fos: Fos protooncogene, Egr1: Early growth response-1, IL: Interleukin, NC: Normal control, WT: Wild-type.
Figure 3:
Regulatory effects of Jun, Fos, and Egr1 on IL-4. (a) Verification of Jun binding sites with IL-4 (n = 3). Compared with pcDNA3.1-NC + pGL4.11-WT + PRL-TK, P < 0.001; Compared with pcDNA3.1-JUN + pGL4.11-WT + PRL-TK, ###P < 0.001. (b) Verification of Fos binding sites with IL-4 (n = 3). Compared with pcDNA3.1-NC + pGL4.11-WT + PRL-TK, P < 0.001; Compared with pcDNA3.1-FOS + pGL4.11-WT + PRL-TK, ###P < 0.001. (c) Verification of Egr1 binding sites with IL-4 (n = 3). Compared with pcDNA3.1-NC + pGL4.11-WT + PRL-TK, P < 0.001; Compared with pcDNA3.1-Egr1 + pGL4.11-WT + PRL-TK, ###P < 0.001. Jun: Jun proto-oncogene, Fos: Fos protooncogene, Egr1: Early growth response-1, IL: Interleukin, NC: Normal control, WT: Wild-type.

The IL-4 content in the serum was detected by ELISA, indicating that its content in the FS groups was remarkably higher than that in the NC group (P < 0.01, [Figure 4a]). qPCR results implied that the mRNA expression of Jun, Fos, Egr1, and IL-4 in the FS groups significantly increased versus those in the NC group (P < 0.01, [Figure 4b-e]). Western blot of hippocampal tissue revealed considerably higher expression of Jun, Fos, p-Jun, p-Fos, Egr1, and IL-4 in the FS groups versus the NC group (P < 0.05, [Figure 4f-l]). Compared with the NC group, the p-Jun/Jun ratio significantly decreased (P < 0.05), while the p-Fos/Fos ratio significantly increased (P < 0.05) in the FS group [Figure 4m and n].

Effect of FS on the expression of IL-4, Jun, Fos, and Egr1. (a) ELISA detection of IL-4 content (n = 3). (b-e) qPCR to detect the expression of IL-4, Jun, Fos, and Egr1 mRNA (n = 3). (f-l) Western blot protein expression of Jun, Fos, p-Jun, p-Fos, Egr1, and IL-4 (n = 3). (m and n) Western blot protein expression of p-Jun/Jun and p-Fos/Fos. Compared with the NC group, ✶P < 0.05, ✶✶P < 0.01, and ✶✶✶P < 0.01. Jun: Jun proto-oncogene, Fos: Fos proto-oncogene, Egr1: Early growth response-1, IL: Interleukin, NC: Normal control, WT: Wild-type, FS: Febrile seizures, ELISA: Enzyme-linked immunosorbent assay, qPCR: Quantitative polymerase chain reaction, mRNA: Messenger RNA.
Figure 4:
Effect of FS on the expression of IL-4, Jun, Fos, and Egr1. (a) ELISA detection of IL-4 content (n = 3). (b-e) qPCR to detect the expression of IL-4, Jun, Fos, and Egr1 mRNA (n = 3). (f-l) Western blot protein expression of Jun, Fos, p-Jun, p-Fos, Egr1, and IL-4 (n = 3). (m and n) Western blot protein expression of p-Jun/Jun and p-Fos/Fos. Compared with the NC group, P < 0.05, P < 0.01, and P < 0.01. Jun: Jun proto-oncogene, Fos: Fos proto-oncogene, Egr1: Early growth response-1, IL: Interleukin, NC: Normal control, WT: Wild-type, FS: Febrile seizures, ELISA: Enzyme-linked immunosorbent assay, qPCR: Quantitative polymerase chain reaction, mRNA: Messenger RNA.

Immunohistochemistry analysis of protein expression levels in hippocampal tissue revealed increased expression of Jun, p-Jun, Fos, p-Fos, Egr1, and IL-4 in the FS groups compared with the NC group (P < 0.01, [Figure 5a-h]).

Expression levels of Jun, p-Jun, Egr1, Fos, p-Fos, and IL-4 proteins. (a-d) Jun, p-Jun, and Egr1 protein detected by immunohistochemistry in each group (×400, scale 50 μm) (n = 3). (e-h) Fos, p-Fos, and IL-4 proteins detected by immunohistochemistry in each group (×400, scale 50 μm) (n = 3). Compared with NC group ✶✶P < 0.01, ✶✶✶P < 0.001. Jun: Jun proto-oncogene, Fos: Fos proto-oncogene, Egr1: Early growth response-1, IL: Interleukin, NC: Normal control.
Figure 5:
Expression levels of Jun, p-Jun, Egr1, Fos, p-Fos, and IL-4 proteins. (a-d) Jun, p-Jun, and Egr1 protein detected by immunohistochemistry in each group (×400, scale 50 μm) (n = 3). (e-h) Fos, p-Fos, and IL-4 proteins detected by immunohistochemistry in each group (×400, scale 50 μm) (n = 3). Compared with NC group P < 0.01, P < 0.001. Jun: Jun proto-oncogene, Fos: Fos proto-oncogene, Egr1: Early growth response-1, IL: Interleukin, NC: Normal control.

Effects of IL-4 receptor blockade on FS

The Racine scores for seizure behavior in rats across different groups [Figure 6a-c] showed that compared with the NC group, the FS group and dupilumab group had a significantly reduced seizure latency (P < 0.01), and a significantly increased seizure duration and Racine scores (P < 0.001). The dupilumab group exhibited significantly reduced seizure latency and significantly increased seizure duration and Racine scores versus the FS group (P < 0.01).

Comparison of Seizure Behavior in Rats Across Groups. (a) Seizure latency (n = 12). (b) Seizure duration (n = 12). (c) Racine score (level) (n = 12). ✶✶P < 0.01, ✶✶✶P < 0.001 versus the NC group; ##P < 0.01, ###P < 0.001 versus the FS group. NC: Normal control group, FS: Febrile seizure.
Figure 6:
Comparison of Seizure Behavior in Rats Across Groups. (a) Seizure latency (n = 12). (b) Seizure duration (n = 12). (c) Racine score (level) (n = 12). P < 0.01, P < 0.001 versus the NC group; ##P < 0.01, ###P < 0.001 versus the FS group. NC: Normal control group, FS: Febrile seizure.

The expression analysis of TNF-α, IL-1β, and IL-6 in serum [Figure 7a-c] showed that the expression levels of these three factors were significantly higher in the FS and dupilumab groups compared with those in the NC group (P < 0.001). Compared with the FS group, the dupilumab group showed a significantly higher expression (P < 0.001). The results of qPCR analysis of mRNA expression of HSP70, GFAP, caspase-3, Bax, and Bcl-2 in hippocampal tissue [Figure 7d-h] indicated that the mRNA levels of HSP70, GFAP, caspase-3, and Bax were significantly higher in the FS and dupilumab groups than in the NC group (P < 0.001), whereas the mRNA expression of Bcl-2 was significantly lower in the FS and dupilumab groups than in the NC group (P < 0.001). Compared with the FS group, the dupilumab group showed a significant increase in the expression of HSP70, GFAP, caspase-3, and Bax (P < 0.01) but a significant decrease in the expression of Bcl-2 (P < 0.001). Western blot analysis of protein expression levels in hippocampal tissue [Figure 7i-n] showed that HSP70, GFAP, caspase-3, and Bax were significantly upregulated in the FS and dupilumab groups than in the NC group (P < 0.001). By contrast, Bcl-2 expression was significantly lower in the FS and dupilumab groups than in the NC group (P < 0.001). In addition, compared with the FS group, the dupilumab group exhibited a significant increase in HSP70, GFAP, caspase-3, and Bax expression (P < 0.01) and a significant reduction in Bcl-2 expression (P < 0.001).

Effects of IL-4 receptor blocker on FS. (a-c) ELISA detected the expression levels of IL-1β, TNF-α, and IL-6 in serum (n = 3). (d-h) qPCR measured the mRNA expression levels of HSP70, GFAP, caspase-3, Bax, and Bcl-2 in hippocampal tissue (n = 3). (i-n) Western Blot assessed the protein expression levels of HSP70, GFAP, caspase-3, Bcl-2, and Bax in hippocampal tissue (n = 3). ✶✶✶P < 0.001 versus NC group, ##P < 0.01, ###P < 0.001 versus FS group. NC: Normal control group, FS: Febrile seizure, IL-6: Interleukin 6, IL-1β: Interleukin 1β, TNF-α: Tumor necrosis factor α, Jun: Jun proto-oncogene, Fos: Fos proto-oncogene, Egr1: Early growth response-1, IL-4: Interleukin 4, GAPDH: Glyceraldehyde-3-phosphate dehydrogenase, HSP70: Heat shock protein 70, caspase-3: Cysteine protease-3, GFAP: Glial fibrillary acidic protein, Bax: Bcl-2-associated X protein, Bcl-2: B-cell lymphoma 2.
Figure 7:
Effects of IL-4 receptor blocker on FS. (a-c) ELISA detected the expression levels of IL-1β, TNF-α, and IL-6 in serum (n = 3). (d-h) qPCR measured the mRNA expression levels of HSP70, GFAP, caspase-3, Bax, and Bcl-2 in hippocampal tissue (n = 3). (i-n) Western Blot assessed the protein expression levels of HSP70, GFAP, caspase-3, Bcl-2, and Bax in hippocampal tissue (n = 3). P < 0.001 versus NC group, ##P < 0.01, ###P < 0.001 versus FS group. NC: Normal control group, FS: Febrile seizure, IL-6: Interleukin 6, IL-1β: Interleukin 1β, TNF-α: Tumor necrosis factor α, Jun: Jun proto-oncogene, Fos: Fos proto-oncogene, Egr1: Early growth response-1, IL-4: Interleukin 4, GAPDH: Glyceraldehyde-3-phosphate dehydrogenase, HSP70: Heat shock protein 70, caspase-3: Cysteine protease-3, GFAP: Glial fibrillary acidic protein, Bax: Bcl-2-associated X protein, Bcl-2: B-cell lymphoma 2.

Flow cytometry was performed to analyze the Th1/Th2 cell ratio [Figure 8a and b], cell apoptosis [Figure 8c and d], cell proliferation [Figure 8e and f], and cell cycle [Figure 8g and h] in peripheral blood. The results indicated a significant increase in the Th1/Th2 cell ratio and cell apoptosis (P < 0.05), whereas cell cycle progression and cell proliferation were significantly reduced in the FS and dupilumab groups compared with the NC group (P < 0.001). In the dupilumab group compared with the FS group, the Th1/Th2 cell ratio and cell apoptosis showed a significant increase (P < 0.001), whereas cell cycle progression and cell proliferation exhibited a significant decrease (P < 0.001).

Effect of FS on IL-4 content and Th1/Th2 ratio. (a and b) Th1/Th2 ratio (n = 3), (c and d) cell apoptosis (n = 3), (e and f) cell proliferation (n = 3), and (g and h) cell cycle. ✶P < 0.05, ✶✶✶P < 0.001 versus NC group; ###P < 0.001 versus FS group. NC: Normal control group, FS: Febrile seizure, Th1: T helper cell type 1, Th2: T helper cell type 2, IL-4: Interleukin 4.
Figure 8:
Effect of FS on IL-4 content and Th1/Th2 ratio. (a and b) Th1/Th2 ratio (n = 3), (c and d) cell apoptosis (n = 3), (e and f) cell proliferation (n = 3), and (g and h) cell cycle. P < 0.05, P < 0.001 versus NC group; ###P < 0.001 versus FS group. NC: Normal control group, FS: Febrile seizure, Th1: T helper cell type 1, Th2: T helper cell type 2, IL-4: Interleukin 4.

DISCUSSION

High fever in children can cause disorders of the central nervous system, affect normal brain cell tissue, and lead to convulsions.[17] Repeated attacks of FS or prolonged convulsions cause brain hypoxia, which causes irreversible damage to the nervous system and brain cells, resulting in sequelae.[18,19] Cytokines can regulate neurotoxic neurotransmitters released by neurons during the inflammatory process, causing an imbalance between the two neurotransmitters and convulsions.[20] In recent years, changes in cytokine levels have been reported in clinical studies of children with FS. Previous animal and clinical studies have shown that IL-1β, IL-6, and IL-10 are abnormally expressed in children with FS at molecular and gene levels, and they vary in different convulsion-related diseases.[21] Hahas reported that IL-4 levels are elevated in patients with FS, suggesting that IL-4 may participate in the pathogenesis of FS.[11] This study explored the correlation between the change in IL-4 levels and FS and its mechanism of action through bioinformatics analysis.

IL-4 is an anti-inflammatory cytokine produced by B cells and T cells, which can activate mast cells to induce the IgE response, thereby promoting the body’s specific response, participating in humoral immunity,[22] and inhibiting expression of pro-inflammatory cytokines, such as IL-1β and TNFα.[23,24] IL-4 plays an important role in the immune response; its classic role includes activating and mediating Th2 immune responses by inducing T helper cells to differentiate into Th2 cells and simultaneously inhibiting monocytes and activated T cells to produce Th1 type cells, thereby exerting an anti-inflammatory effect.[25] The balance between Th1 and Th2 immune cells is particularly important for maintaining the stability of the body’s immune function, and Th1/Th2 imbalance leads to the occurrence of allergic diseases and immune disorders.[26] The experimental results in the present study confirmed that the IL-4 content increased significantly in FS animal models, so as Th1/Th2 ratio. IL-4 receptor blockers promote an increase in the Th1/Th2 ratio in animal models of FS, proving that IL-4 has a regulatory effect on the balance of Th1/Th2 in febrile convulsions. During FS, cells may produce higher levels of anti-inflammatory cytokines as a defense mechanism.[11]

This study, using bioinformatics analysis, identified that FS-associated genes, including Fos, Jun, and Egr1, are upstream transcription factors of IL-4 and are significantly upregulated in the febrile convulsion group. Fos and Jun are immediate early genes found in nerve cells, playing a role in pain signal transmission. They rapidly respond to and express incoming signals triggered by neurotransmitters, hormones, nerve impulses, and external stimuli.[27] c-Fos protein must combine with c-Jun-transcribed mRNA to encode the Jun protein to co-mediate expression. Under normal physiological conditions, the c-Fos protein is only expressed at a low level; when stimulated by internal and external stress or when brain tissue is damaged, the expression of the c-Fos protein in central neurons increases rapidly. Chronic stress causes neurobiochemical changes and damages brain structure, resulting in depression and mental illness.[28] Egr1 plays a crucial role in neuronal plasticity in hippocampal formation.[29] Simultaneously, an abnormal increase in Egr1 expression in hippocampal neurons was detected in the epileptic state.[30] Studies in humans have found that recurrent FS may cause hippocampal damage.[31] IL-4 is a promising target for treating peripheral nerve injury and enhancing nerve recovery.[32] These results suggested that IL-4 may mediate nerve injury during FS through the regulation of upstream transcription factors.

The current research further investigated the effects of the IL-4 receptor blocker dupilumab on FS. As a monoclonal antibody targeting IL-4Rα, dupilumab selectively inhibits the key signaling pathways of IL-4 and IL-13, blocking Th2-type inflammatory pathways and reducing pathological responses associated with Th2-type inflammation.[33] The results showed that the dupilumab group had significantly shorter seizure latency, reduced seizure duration, and lower Racine scores compared with the FS group, indicating its effectiveness in alleviating FS symptoms. In addition, levels of IL-1β, TNF-α, and IL-6 in the serum of the dupilumab group significantly decreased. The mRNA and protein expression levels of HSP70, GFAP, and caspase-3 and the Bax/Bcl-2 ratio in hippocampal tissue were also reduced, suggesting that dupilumab may exert its effects by modulating the inflammatory and apoptotic pathways. Flow cytometry analysis revealed that the Th1/Th2 cell ratio and apoptosis rate in the dupilumab group further increased, whereas cell cycle progression and proliferation capacity further decreased. These changes suggested that IL-4 may influence the immune response in FS by regulating the Th1/Th2 balance. IL-4 triggered IL-4R/Signal Transducer and Activator of Transcription 6 (STAT6) signaling, leading to Th2 cell differentiation through the transcription factor GATA3 in an autocrine manner.[34,35] During Th2 cell differentiation, the activation of the IL-4-IL-4Rα-STAT6 positive feedback loop accelerates Th2 cell differentiation and determines the corresponding characteristics.[36] The findings of this study may offer insights into potential therapeutic interventions for FS by targeting the IL-4 signaling pathway. Dupilumab, an IL-4 receptor blocker, could be an appropriate choice for alleviating FS symptoms and modulating the immune response. However, several challenges exist in translating these results into human treatment. First, the safety and efficacy of dupilumab in pediatric populations need to be thoroughly investigated, especially given the developmental complexity of the immune system in children. Second, the role of IL-4 in other immune responses should be carefully considered because the modification of IL-4 could have broad effects beyond seizure control, possibly affecting immune homeostasis. Finally, the precise timing and dosage of IL-4 blockage to optimize therapeutic outcomes for FS should be determined through clinical trials. In conclusion, although IL-4 and its upstream regulators may represent novel targets for FS therapy, further research is necessary to confirm the clinical relevance and safety of these findings in human patients.

Despite the promising results of this research, this study had several limitations. First, the animal model used in this study could not fully replicate the complexity of human FS, and the results may not directly translate to human cases. In addition, although dupilumab significantly affected various cytokines and immune markers, the long-term effects of blocking IL-4 in the context of FS remain unclear. The immunomodulatory effects observed may also have implications for other immune-driven conditions, and further studies are required to assess potential side effects or contraindications when considering dupilumab for clinical use. Furthermore, the study primarily focused on IL-4 and its upstream regulators, but other cytokines and signaling pathways likely contribute to the pathophysiology of FS. A comprehensive examination of the cytokine network involved in FS could provide a broad understanding of the disease.

SUMMARY

Our research findings suggested that IL-4 and its upstream transcription factors Jun, Fos, and Egr1 are essential for the onset and progression of FS. Dupilumab effectively alleviates the symptoms and related immune responses of FS by blocking the IL-4 receptor. These results provide referential and potential direction toward the treatment of FS and significant insights for future research. Future studies could further explore the mechanisms of IL-4 and its upstream transcription factors in FS, as well as the potential applications of dupilumab in treating FS.

AVAILABILITY OF DATA AND MATERIALS

This article contains all the data supporting the findings of this study.

ABBREVIATIONS

BP: Biological processes

DEGs: Differentially expressed genes

ELISA: Enzyme-linked immunosorbent assay

FS: Febrile seizures

GO: Gene ontology

KEGG: Kyoto encyclopedia of genes and genomes

PPI: Protein–protein interaction

qPCR: Quantitative polymerase chain reaction

TNF-α: Tumor necrosis factor α

AUTHOR CONTRIBUTIONS

XX: Designed the study and drafted the initial manuscript; SW, CYT, and HJJ: Conducted the experimental research; LL, GM, and XH: Analyzed the experimental data; BH: Supervised the progress of the experiments and the drafting of the initial manuscript. All authors participated in manuscript revision, read, and approved the submitted version. All authors meet the ICMJE authorship requirements.

ACKNOWLEDGMENT

Not applicable.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

All experimental procedures strictly adhere to the “Regulations on the Management of Experimental Animals” and international ethical guidelines for animal experiments. Approval has been obtained from the Institutional Ethics Committees of the Third Affiliated Hospital of Zunyi Medical University (the First People’s Hospital of Zunyi) (Ethics Review No. (2022)-2-33). Informed consent to participate is not required as this study does not involve human subjects.

CONFLICT OF INTEREST

The authors declare no conflict of interest.

EDITORIAL/PEER REVIEW

To ensure the integrity and highest quality of CytoJournal publications, the review process of this manuscript was conducted under a double-blind model (authors are blinded for reviewers and vice versa) through an automatic online system.

FUNDING: This study was sponsored by the Fund Project of the Guizhou Provincial Health Commission (No. gzwjkj 2020-1-140).

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