Systemic sclerosis (SSc) is a rheumatic disease characterised by vasculopathy, inflammation and fibrosis. Its aetiopathogenesis is still unknown, and the pathways/mechanisms of the disease are not clarified. This study aimed to perform in silico analysis of the already Mass Spectrometry (MS)-based discovered biomarkers of SSc to extract possible pathways/mechanisms implicated in the disease. We recorded all published candidate MS-based found biomarkers related to SSc. We then selected a number of the candidate biomarkers using specific criteria and performed pathway and cellular component analyses using Enrichr. We used PANTHER and STRING to assess the biological processes and the interactions of the recorded proteins, respectively. Pathway analysis extracted several pathways that are associated with the three different stages of SSc pathogenesis. Some of these pathways are also related to other diseases, including autoimmune diseases. We observe that these biomarkers are located in several cellular components and implicated in many biological processes. STRING analysis showed that some proteins interact, creating significant clusters, while others do not display any evidence of an interaction. All these data highlight the complexity of SSc, and further investigation of the extracted pathways/biological processes and interactions may help study the disease from a different angle. Despite intensive research, the aetiopathogenesis of the disease remains poorly understood. An interaction between genetic, epigenetic alterations and environmental factors is suggested3. Remarkably, SSc, like other AIDs, occurs more frequently in females than in males and its incidence and prevalence vary according to the geographical region and study4.Systemic sclerosis (SSc) is a chronic, heterogeneous, multisystemic, connective tissue autoimmune disease (AID). Vasculopathy, immune system abnormalities-inflammation and excessive deposition of collagen-fibrosis are characteristic features of SSc5. Interstitial lung disease (ILD) and pulmonary arterial hypertension (PAH) are the most common types of pulmonary involvements in SSc. They are likely life-threatening as they account for 60% of death in the disease6.SSc is divided into two subgroups; limited cutaneous SSc (lcSSc) and diffused cutaneous SSc (dcSSc), based on clinical manifestations. In lcSSc, skin thickening is usually limited to the face, ankles, wrists and distal to knees and elbows. DcSSc involves skin thickening proximal to the knees and elbows and damage of internal organs 7. In addition, it is essential for biomarkers discovery; disease-specific proteins that can be used and distinguish a pathological from a non-pathological condition. These biomarkers have several applications. We can use them for better classification, early prognosis, more accurate diagnosis and therapeutic targeting of the disease. In addition, many of the candidate biomarkers might also be interconnected and help extract critical physiopathological pathways8.Besides genetics and environmental factors, proteome and pathways dysregulation may play a crucial role in the pathogenesis of SSc. Proteins are considered the structural and functional molecules of the living organism and are responsible for the cell’s phenotype. Proteomics is the only way to study protein–protein interaction, the mechanism/pathways of disease, and the environmental effect at the level of the organism9. MS, a high-throughput analytical method, allows the detection, identification and quantification of proteins in many samples such as biopsies, saliva and plasma10. In addition, various studies use different MS proteomic techniques such as matrix-assisted laser desorption/ionisation time-time-of-flight (MALDI-TOF) and surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF)8.Early-stage proteomic studies employed the two-dimensional gel electrophoresis (2DE) application. In recent years, newly developed proteomics methodologies based on MS enabled more robust studiesIn this article, we gather published candidate MS-based discovered biomarkers of SSc and then further analyse a number of these molecules selected based on specific criteria through in silico online tools for the first time to extract possible pathways involved in the development of the disease.11. We recorded all biomarkers and grouped them based on general SSc, SSc subtypes; lcSSc and dcSSc and lung involvements (PF and ILD) related to SSc. All candidate MS-based proteomic biomarkers for SSc discovered until 2021 were collected/extracted through two extensive systematic reviews12 for biomarker identification and qualification in clinical proteomics. These criteria are the following: justification of the clinical question, description of the subjects, samples, methodology and statistical assessment, validation of the results, acknowledgement of limitations and authors contribution statement.The quality of data reported through recorded studies was evaluated according to the eight criteria recommended by Mischak et alThe selection of proteins for in silico analysis was performed using two different approaches.p-value ≤ 0.05 & Fold Change (FC) ≥ 1.5 or ≤ 0.67 or expressed only in disease or control samples.The first selection of proteins for in silico analysis was performed based on three combined criteria; (1) proteins that were extracted through full text research articles, and (2) proteins that were extracted through the articles that fulfilled the first five quality assessment criteria  and (3) proteins with The second selection of proteins for in silico analysis was performed including proteins that fulfilled the above criteria and were also validated with additional methods.We performed in silico analysis in general SSc, dcSSc, lcSSc and lung involvements groups.(https://maayanlab.cloud/Enrichr/)13 to classify the proteins/genes based on the following ontologies: (a) KEGG 2021 Human16 and (b) GO Cellular Component 2021. We performed separate pathway analyses for the upregulated and downregulated proteins.We used the Enrichr Web Server (http://www.pantherdb.org/), Version 17.0 (released 2020–02-22)17. This tool classified/sub-classified proteins (and their genes) into PANTHER GO-Slim Biological Processes.We analysed all selected proteins using the Protein Analysis Through Evolutionary Relationships (PANTHER)—Gene List Analysis tool (http://www.interactivenn.net/) to easily visualise common and unique pathways through different analyses and subtypes18.We produced the Venn diagrams using the InteractiVenn tool (http://string-db.org/)19 to assess the interactions of selected genes/proteins. We set the confidence level to 0.700 (high). We pulled interactions based on database, experiments, and co-expression.We used the Search Tool for Retrieval of Interacting Genes/Proteins—STRING Version: 11.5 47. Out of these studies, 25 were published as full text research articles. Two systematic reviews by Balanescu P et al.11 record these studies, where a total of 655 candidate proteomic biomarkers were identified  or Liquid Chromatography (LC). Proteins were identified with MALDI-TOF, SELDI-TOF or Tandem MS (MS/MS) techniques. Multiple Reaction Monitoring (MRM) and older-standard methods  were used to validate these proteins.All full text research articles included identification and description of clinical question 25/25) as well as sampling description (25/25). In the most of the studies, authors descripted the assessment of the subjects (24/25) and statistical evaluation (23/25) as well as presented the experimental methodology (24/25). However, validation of the results (14/25), acknowledge limitations (7/25) and authors contribution (10/25) are lacked from several manuscripts. All these details are shown in additional file 5/25 as wp ≤ 0.05 & FC ≥ 1.5) and downregulated (p ≤ 0.05 & FC ≤ 0.67) selected proteomic biomarkers. We investigated the different subtypes separately; general SSc . Collagen-containing extracellular matrix (GO:0062023) and focal adhesion (GO:0005925) are among these significant components.We used Enrichr for the GO Cellular Component 2021 analysis Fig. . In all We performed PANTHER analysis to classify the proteins/genes into different biological processes Fig. . DysreguWe used the STRING 11.5 database to assess whether the selected SSc candidate proteomic biomarkers have an interaction between them Fig. A-D. SomeAll in silico analyses were performed on a smaller group of 21 candidate validated biomarkers for SSc. Enrichr KEGG 2021 Human, Enrichr GO Cellular Component 2021 and PANTHER biological processes analyses results are shown in Additional file 49. Therefore, this study aimed to use a number of selected candidate proteomic biomarkers recorded to date for SSc to extract the central pathways implicated in the pathogenesis of SSc.SSc is a rheumatic AID with complex aetiopathogenesis and heterogeneous clinical manifestations. Despite that SSc is characterised by vasculopathy, immune system abnormalities and fibrosis, the molecules implicated in these processes are not fully elucidated. Several “omics” studies have been performed on SSc; however, the pathways and the mechanisms involved in the disease are still unclearWe used the Enrichr Web Server to perform pathway analysis. Several extracted pathways are associated with immunity, as immune system abnormalities and inflammation are prominent features of SSc pathogenesis. Previous studies on SSc have already reported some of the pathways and molecules we pulled through this analysis.50. In our study, we identified 17 dysregulated (upregulated/downregulated) molecules implicated in this pathway. Interestingly, these molecules are involved in both the coagulation and the complement  pathway cascades. Previous studies on SSc have also reported dysregulated proteins implicated in this pathway. Senaldi et al.51 report that C3d and ratios of C3d:C3 and Ba:factor B were higher in patients with dcSSc than controls, while C4d:C4, C4d, C3d:C3 and C3d levels were higher in patients with lcSSc compared to controls. These results show that activation of the complement system occurs in patients with SSc and might be associated with the clinical severity of the disease51. In a more recent study, Landi et al.23 observed decreased complement C3a levels in patients with PF compared to healthy smoking controls. In addition, pathway analysis showed that the dysregulated proteins in that study are involved in pathways associated with disease pathogenesis 23. Ludwicka-Bradley et al.52 also report that imbalance of the coagulation cascade, especially release of the thrombin molecule, is associated with the earliest SSc events following tissue injury and is mainly observed in SSc patients with lung disease.The complement system is the central mechanism of antibody-mediated immunity and part of the innate immune system. The primary function of this system is to recognize and eliminate foreign pathogens either through the stimulation of phagocytosis or direct killing53. Acosta-Herrera et al.54 have reported the association of this pathway with SSc. They performed sequential conditional analyses of the human leukocyte antigen (HLA) region. They conclude on seven amino acids, nine classical alleles and nine Single Nucleotide Polymorphisms (SNPs) associated with the disease and its subtypes.Antigen processing and presentation is an additional pathway extracted through our analysis (7 molecules) associated with SSc and all AIDs. This pathway is responsible for processing and presenting the foreign antigen to the appropriate immune cells through the Major Histocompatibility Complex (MHC) mechanismp-value only from the general SSc downregulated proteins (4 molecules). Chemokines, also known as chemotactic cytokines, regulate the recruitment and migration of immune cells. These molecules were found to be associated with several rheumatic diseases, including SSc, systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA)55. For instance, Van Bon et al.28 reported that the plasma level of CXCL8 is higher in SSc patients than in healthy controls, while PPBP is lower. However, Scambi et al.26 reported that the levels of PPBP is higher in serum of dcSSc and lcSSc patients compared to healthy controls.Chemokine signalling and IL-17 signalling are two additional pathways extracted from our analysis and associated with immune system regulation. The chemokine signalling pathway was extracted with a significant 56. However, its exact role on the disease has not been elucidated. Some studies reported that IL-17A expression is higher in serum of SSc patients, and others reported it lower in SSc patients than in healthy controls56. In addition, Wakhlu et al.57 showed that high levels of IL-6, IL-17A and TGF β1 molecules in serum of SSc patients are associated with skin fibrosis and ILD. This pathway was significantly extracted from three out of four subgroups in our analysis, but 7 different molecules than the above are implicated. Although many studies reported dysregulated chemokine and interleukin molecules associated with SSc, chemokine and IL-17 signalling pathways are extracted through pathway analysis using SSc dysregulated proteins for the first time in our study.IL-17 family is a group of six inflammatory cytokines that are associated with cancer progression and AIDs. Despite that IL-17 signalling pathway is a cytokines pathway that includes several activators and inhibitors, previous studies reported that it might be implicated in fibrosis of SSc pathogenesis58. In a previous study, Xu et al.59 performed KEGG pathway analysis of ITGA5, ITGB2, and ITGB5 that were found to be upregulated in the skin of SSc patients compared to control and reported that these proteins are implicated in the leukocyte transendothelial migration pathway. In our study, this pathway was significantly extracted from general SSc (upregulated proteins) and lung disease related to SSc (downregulated proteins) subgroups . Our results show that ITGAM and MMP9 proteins are mainly dysregulated for leukocyte transendothelial migration, indicating that they might promote lung disease related to SSc by affecting this procedure.Leukocyte transendothelial migration is also an essential pathway. CD4 + T lymphocytes transendothelial migration is enhanced in SSc, and the migrating cells present an activated phase60. This process has a crucial role in maintaining tissue homeostasis by removing apoptotic cells61. Receptors of phagocytes are categorized into opsonic and non-opsonic. The non-opsonic receptor directly recognises substances on the phagocytic target surface, while the opsonic receptor identifies host-derived proteins bound to the foreign particle. Complement and Fc are the most essential and well-characterised opsonic phagocytic receptors61. Previous studies showed that defects in the clearance of apoptotic cells might lead to several diseases, including AIDs62. Davis et al.63 showed that anti-FcγR autoantibodies are detected in the serum of SSc patients but not in controls. In addition, Kadono et al.64 in a more recent study, report that the levels of anti-FcγRIIB/C autoantibodies in the serum of SSc patients are significantly higher than in healthy controls. These findings support the idea that phagocytosis is implicated in the pathogenesis of SSc, but further studies are needed to elucidate its exact role.Interestingly, phagosome, as well as Fc gamma R-mediated phagocytosis pathways, were also extracted in our analysis. Phagocytosis is a fundamental process for innate immune response where the specialised phagocytes such as macrophages, monocytes, dendritic cells, and neutrophils recognise, engulf and eliminate the pathogenic microorganisms65. Peroxisome proliferator-activated receptors (PPARs); PPAR-α, -β/δ, and γ are nuclear receptors that regulate several processes, including inflammation, differentiation and cell proliferation66. Previous studies prove that PPAR-γ is implicated in the pathogenesis of SSc, especially aberrant expression of PPAR-γ contributes to fibrosis and vascular remodelling stages67. Shiwen et al.68 showed reduced expression of PPAR-γ in fibroblasts of patients with dcSSc compared to healthy controls. In addition, Marangoni et al.69 reported that PPAR-γ is also related with SSc at the genetic level, as PPAR-γ intronic SNP (rs10865710) is associated with SSc susceptibility. Interestingly, in our study, PPARs signalling pathway was extracted, but the implicated proteins are included in all three signals and not only in the PPAR-γ part.Peroxisomes are essential organelles that regulate lipid homeostasis. They also interact with some pathogens to escape the immune response, turn off/on pivotal cellular immune signalling and control the interaction between host and pathogen.70 suggested that PPAR-γ expression in SSc is suppressed by excessive activity of TGF-ß and may contribute to the abnormal activation of fibroblast and fibrogenesis. This signalling pathway regulates several cellular processes, including extracellular matrix (ECM) synthesis, cell differentiation, apoptosis and cell growth71. Increased levels of TGF-β1 in tissue and serum of patients with SSc suggest that it might be implicated in fibrosis. In addition, studies showed that TGF-β signalling could be a mediator of experimental PAH and blocking of this signalling was shown to reduce the severity of PAH71. Dantas et al. assessed the levels of the active TGF-β1 isoform in skin biopsies and serum from patients with SSc and healthy controls. They reported that the serum level of TGF-β1 was significantly higher in patients compared to controls. At the same time, no significant difference was observed in the mRNA expression of TGFB1 in skin biopsies of patients with SSc compared to controls. They also noted that patients with SSc who have high levels of TGF-β1 in serum are more likely to have dcSSc, DU, SSc (Anti-Topoisomerase) ATA + , higher Rodnan skin score and lung fibrosis. These results suggest that this molecule might be a marker for vascular and fibrotic manifestations of SSc72.TGF-beta is a pathway interconnected with PPAR signalling and significantly extracted from our analysis . Wei et al73. Xu et al.59 showed that protein and mRNA levels of three integrins  are upregulated in SSc patients than in controls. Pathway analysis showed that these proteins/genes are implicated in leukocyte transendothelial migration, focal adhesion, ECM–receptor interaction and ECM turnover. This pathway was extracted in our study, not only from integrin proteins but also from the collagen family proteins. Focal adhesion and cell adhesion molecules pathways were also extracted from our analysis. Adhesion molecules are proteins that mediate cell-to-ECM as well as cell-to-cell interaction. Based on their function, these molecules are located on the surface of different cells and implicated in several processes, including T-Cell Mediated Immunity and leukocyte migration and fibrogenesis75. Although these two pathways were not discussed in depth in previous studies, Hasegawa et al.76 report that serum adhesion molecules can be used as predictive biomarkers for early SSc. In addition, in our previous study, we report that the ICAM1 protein is significantly over-expressed in affected than unaffected skin biopsies of patients with SSc10.The ECM-receptor interaction is also included in the essential signalling pathways associated with SSc, especially in fibrosis. Several previous studies identified dysregulated proteins implicated in this pathway and suggest that it plays a crucial role in developing the disease79. Agache et al.80 reported that platelet activation molecules such as P-selectin are associated with disease severity and activity. It was also reported that platelets of SSc patients have a high response to collagen, adenosine diphosphate, adrenaline and 5-hydroxytryptamine, which are correlated with different processes77. Even though oxidative phosphorylation is essential for energy production in the organism, an abnormal function of this mechanism might lead to a pathological condition through the overproduction of Reactive Oxygen Species (ROS). For example, high levels of ROS were observed in the skin fibroblast of patients with SSc compared to healthy controls79. In addition, oxidative stress, which is the imbalance and accumulation of ROS, may cause endothelial cells activation and damage/dysfunction78. All of these pathways discussed above were extracted with a significant p-value either in one or more of our 1st selection analyses and might be implicated in the pathogenesis of SSc. Although in the 2nd selection the number of validated proteins was relatively small, complement and coagulation cascades and IL-17 signalling pathway were also extracted through these analyses with a significant p-value. Interestingly, Wnt signalling pathway, that is associated with SSc, was extracted through the 2nd selection analyses only with a significant p-value  and an increased expression of Lef1 (Wnt target) and Frizzled2 (Wnt receptor) in dcSSc compared to healthy controls skin biopsies. In addition, an immunohistochemical study showed an elevated expression of nuclear β- catenin  in these skin biopsies. These evidences suggest a hyperactivation of Wnt signalling in patients with SSc and support that this pathway plays a key role in the pathogenesis of fibrosis in SSc82.Platelet activation and oxidative phosphorylation are also crucial pathways that contribute to all stages of SSc pathogenesis: vasculopathy, autoimmunity and fibrosis and they were extracted from our analysisp-value and were common in all analyses; general SSc, dcSSc, lcSSc and lung disease related-SSc. In all analyses except from lcSSc, the collagen-containing extracellular matrix (GO:0062023), related to SSc fibrosis, was extracted in the top-10 cellular components. Interestingly, collagen-containing extracellular matrix (GO:0062023) was also extracted with a significant p-value in the general SSc group of the 2nd selection analysis  were extracted and are presented in Fig. 00 were eThis study shows that many proteins with different functions are implicated in the pathogenesis of SSc. Pathway analysis confirms the heterogeneity of the disease as the recorded dysregulated proteins are involved in approximately 240 different pathways. Different pathways and molecules are involved in various stages of SSc pathogenesis and different SSc subtypes. Some of the extracted pathways are also related to other diseases, including AIDs, indicating that they share common mechanisms. Some of the significantly extracted pathways were associated with SSc in previous studies, but some of them were not studied in depth. Cellular component and biological process analyses confirmed the complexity of the disease as the recorded molecules are implicated in 13 different biological processes and located in more than 230 cellular components. All these analyses that were performed for the first time for all the MS-based SSc proteomic biomarkers in our study are essential for producing new data associated with the disease pathogenesis, for the identification/determination of the biological mechanisms and molecular interactions that lead to the disease, and for developing novel aspects for further studies.Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.Supplementary Information 5.Supplementary Information 6.Supplementary Information 7.


To analyze the pharmacological mechanism of Epimedium in regulating heart failure (HF) based on the network pharmacology method, and to provide a reference for the clinical application of Epimedium in treating HF. Obtaining the main active ingredients and their targets of Epimedium through TCMSP  database. Access to major HF targets through Genecards, OMIM, PharmGKB, Therapeutic Target Database, Drug Bank database. Protein interaction analysis using String platform and construction of PPI network. Subsequently, Cytoscape software was used to construct the “Epimedium active ingredient-heart failure target” network. Finally, the molecular docking is verified through the Systems Dock Web Site. The core active ingredients of Epimedium to regulate HF are quercetin, luteolin, kaempferol, etc. The core targets are JUN, MYC, TP53, HIF1A, ESR1, RELA, MAPK1, etc. Molecular docking validation showed better binding activity of the major targets of HF to the core components of Epimedium. The biological pathways that Epimedium regulates HF mainly act on lipid and atherosclerotic pathways, PI3K-Akt signaling pathway, and chemoattractant-receptor activation. And its molecular functions are mainly DNA-binding transcription factor binding, RNA polymerase II-specific DNA-binding transcription factor binding, and neurotransmitter receptor activity. This study reveals the multi-component, multi-target and multi-pathway mechanism of action of Epimedium in regulating mental failure, and provides a basis for the clinical development and utilization of Epimedium to intervene in HF. In developed countries, the prevalence of known HF is generally estimated at 1% to 2% of the general adult population and increasing as the world’s population expands and ages. As a traditional kidney tonic, Epimedium has the function of “tonifying the liver and kidney, strengthening the muscles and bones, and dispelling wind and dampness.” Modern pharmacological studies have shown that Epimedium has good intervention effects on cardiovascular diseases under the pharmacological effects of cardiovascular protection, immune regulation and anti-inflammation. In HF models, epimedium based formulations inhibited myocardial transforming growth factor-β1 expression and alleviated HF by reversing ventricular hypertrophy. However, the role of the active ingredients in the formula and the intervention mechanism of HF has not been fully clarified.Heart failure (HF) is a disease caused by various causes of structural changes or dysfunction of the heart, filling of the ventricles or impaired blood expulsion. In this study, we investigated the material basis and mechanism of action of Epimedium in the treatment of HF using network pharmacology. Molecular docking of some key targets will lay the foundation for the future development and application of Epimedium in the treatment of HF.Traditional Chinese medicine network pharmacology prioritizes disease-related genes by drug-gene-disease co-module association to predict the target spectrum and pharmacological effects of effective compounds in Chinese herbal medicines. Preliminary screening was then performed to obtain effective active compounds and their protein targets based on 2 properties: oral availability  ≥ 30% and drug-like properties ≥ 0.18. After screening, the protein targets are uniformly converted into corresponding genes in the Uniprot protein database.Compound components using the Traditional Chinese Medicine System Pharmacology Database (TCMSP).We searched for related genes by entering “heart failure” in Gene Cards, OMIM, PharmGKB, Therapeutic Target Database and Drug Bank, and obtained disease targets and Epimedium therapeutic targets. The common target was selected as the potential target of Epimedium for the treatment of HF.The active ingredient-HF target of Epimedium was plotted with Venny to create a Venn diagram. The intersecting targets are then submitted to the STRING database to build a protein protein interaction network (PPI), where the interaction information of each protein is automatically scored, with higher scores indicating higher confidence in protein interactions. For the input target, the biological species was set to “Homo sapiens” and the minimum interaction threshold was set to “highest confidence.” The obtained high-confidence protein interactions data were used to construct PPI. Three parameters of GO function, Biological Process, Molecular Function and Cellular Component, were selected for gene enrichment analysis, screening P < .01, and results were visualized using R.GO and KEGG enrichment analysis of the active ingredients of Epimedium-HF targets using R Cluster Profiler package.The network topology parameters of the effective components and targets are analyzed using CytoScape’s built-in Network Analyzer, including connectivity, betweenness centrality (BC) and closeness centrality (CC), etc. The selection criterion is to choose the Degree that is greater than the median value of all points, and finally the targets that meet the median values of BC and CC as the core targets. The core targets and the main active ingredients are determined based on the network topology parameters, and the 2 are used for molecular docking. The binding activity of the key active ingredient to the target was evaluated by binding, and the results of compound and protein docking were observed and analyzed using PyMOL software.AutoDock Vina was used as the molecular docking software. For further validation, the key active ingredients of Epimedium with the top 3 “Degree” values were selected for molecular docking with the top 3 “Degree” ranked targets in the PPI network. The 2D structures of the key active ingredients were downloaded using the PubChem database and saved in SDF file format. ChemBio3D software was used to retouch to SDF file format and optimize its 3D structure and save as mol2 format. The crystal structures of the targets were downloaded from the PDB database and processed using PyMOL software for removal of water molecules, hydrogenation, etc. The 3D structures of key active ingredients of Epimedium were then converted to pdbqt file format using AutoDock Tools with the target crystal structure, and molecular docking was performed using Autodock Vina software.The active ingredients and targets of Epimedium were initially extracted as 130 species by searching the TCMSP database, and 23 major active ingredients were obtained after screening, including quercetin, luteolin, kaempferol, etc. Other active ingredients of Epimedium  was significantly expressed in congestive HF due to ischemic or dilated cardiomyopathy.,14 RELA(p65) is a transcriptionally active subunit of activated nuclear factor-κB (NF-κB) dimer containing RELA and p50, which has the role of promoting gene expression in various biological processes such as immune response, inflammation, development, apoptosis and tumorigenesis. Inhibition of p65 improves cardiac function, reduces ventricular mass, and decreases myocardial cell apoptosis. MYC is a multifunctional transcription factor that regulates the expression of numerous genes in cell growth, proliferation and apoptosis and metabolic pathways. High MYC expression drives tumor initiation, progression and maintenance, and is associated with aggressive cancer and poor prognosis. Study found that MYC expression was significantly increased in bone marrow samples from patients with HF compared to normal subjects. HIF transcription factors are the main regulators of the cellular response to hypoxia. HIF-1α is expressed in a variety of cancer and immune cells and promotes tumor development, invasion and metastasis by inducing angiogenesis, as well as regulating cellular metabolism in the hypoxic tumor microenvironment. In addition, HIF-1α is involved in the inflammatory response. HF is a chronic inflammatory process that is closely associated with hypoxia. It was found that HIF-1α mRNA expression was increased in failing hearts during disease exacerbation in rats with HF. TP 53 is a tumor suppressor that regulates cell cycle, apoptosis, and DNA repair by regulating gene expression in response to cellular stress. Under physiological conditions, TP53 is functionally active to maintain cardiac structure, but elevated TP53 expression can lead to myocardial fibrosis, myocardial hypertrophy, myocyte apoptosis, non-myocyte proliferation, and left ventricular dilation leading to cardiac dysfunction. Therefore, inhibition of TP53 may serve as one of the effective therapeutic strategies to prevent the transition from cardiac hypertrophy to HF. MAPK 1 promotes cell proliferation and differentiation through cell cycle processes while inhibiting apoptosis. Study shows that MAPK 1 promotes cardiomyocyte proliferation. In addition to its important role in human reproduction, ESR also has a significant impact on adipose tissue and metabolism, bone, cardiovascular, brain and immunity. ESR1 KO mice were found to have reduced myocardial hypertrophy. Common ESR1 polymorphisms are significantly associated with age-related changes in left ventricular structure. Mechanisms of susceptibility to adverse cardiac left ventricular remodeling as we age may help identify new therapeutic targets for the prevention of HF. The above literature research shows that the target screening of Epimedium is consistent with the results of a large number of pharmacological experiments, and the relationship between the pharmacological components and the target action can be further investigated at a later stage based on the predicted results.Predicting drug targets reveals important information about the relationship between drugs and molecular mechanisms of action, which is important for facilitating drug development. A total of 189 intersecting targets were screened by constructing a PPI network map of Epimedium intervention targets in HF. The targets with the strongest correlation of Degree values were JUN, RELA, MYC, HIF1A, TP53, MAPK1, and ESR1. JUN family proteins play important roles in the regulation of inflammatory responses, oxidative stress, and cell survival, proliferation and differentiation.,29 NF-κB, which is closely related to inflammation, mediates inflammation, apoptosis and extracellular matrix remodeling after activation by TNF-α. PI3K/Akt signaling pathway plays an important role in the regulation of cardiomyocyte growth, myocardial angiogenesis, and cell death. Meanwhile, activation of this pathway can induce monocyte chemotaxis, macrophage migration, increased intracellular lipid accumulation, neovascularization and lesion dysfunction, all of which are closely related to atherosclerotic plaque formation. In HF-related studies, the literature suggests that drugs can reduce reactive oxygen species production and myocardial apoptosis as well as reduce myocardial hypertrophy by modulating the PI3K/Akt signaling pathway. miRNA expression is altered by environmental chemicals such as metals, organic pollutants, cigarette smoke, pesticides and carcinogenic drugs. For example, arsenic regulates the PI3K/AKT/mTOR pathway through 2 different mechanisms to induce cell proliferation and apoptosis. Long-term exposure to arsenic promotes cell proliferation and tumor transformation, and induces non-carcinogenic diseases such as cardiovascular disease. Therefore, it is hypothesized that the active ingredients in Epimedium may affect the downstream genes and pathways through PI3K/Akt signaling pathway, thus regulating the development of HF.The results of GO functional enrichment analysis suggest that Epimedium affects HF through the action of related biological processes, molecular functions, and cellular composition. The results of KEGG pathway enrichment analysis showed that Epimedium achieves HF regulation through related disease pathways and signaling pathways, such as lipid and atherosclerosis, PI3K/Akt signaling pathway, and Chemical carcinogenesis-receptor activation. Atherosclerosis is a chronic inflammatory condition, and inflammation is an important causative mechanism of HF. Inflammatory factor TNF-α induces cardiomyocyte hypertrophy, activates metalloproteinases, inhibits metalloproteinase inhibitors, and leads to myocardial fibrosis.The molecular docking results showed that quercetin had the lowest docking energy with JUN, suggesting that quercetin, as the core component of Epimedium, plays a major regulatory role in HF. The combination of Luteolin and JUN is more advantageous, and to a certain extent, it synergizes with quercetin, kaempferol and other components to enhance the regulatory effect on JUN.,38 Icariside reduces NF-κB p65 (RELA) nuclear translocation by inhibiting or reducing NF-κB signaling pathway, reducing the levels of inflammatory factors such as TNF-α, IL-1β and IL-6, interfering with myocardial ischemia-reperfusion injury and inhibiting the progression of aortic atherosclerosis may be the potential mechanisms of Epimedium to regulate HF. Epimedium II, the active ingredient of Epimedium, down-regulates the activity of oxidative stress-related proteins such as JUN and inhibits the expression of TP53, thereby reducing cardiomyocyte apoptosis and improving left ventricular remodeling.A review of domestic and international studies showed that Epimedium down-regulates PI3K and Akt phosphorylation levels by inhibiting the activation of PI3K/Akt signaling pathway, reducing the proliferation of cancer cells and their ability to invade and migrate, and accelerating cancer cell apoptosis. Epimedium significantly inhibits MYC expression and alleviates cardiac dysfunction. Icariside down-regulates HIF-1α and other expressions to promote the proliferation and migration of endothelial progenitor cells, thereby repairing damaged endothelium and promoting. Quercetin regulates c-myc to inhibit apoptosis in cardiomyocytes during cardiac hypertrophy. Quercetin attenuates sodium nitrite-induced hypoxia in rats by inhibiting the HIF-1α pathway has a protective effect on cardiac tissue. Vanadium quercetin complex inhibits cancer progression by regulating pathways such as TP53 and downregulates cell proliferation associated with increased apoptotic events. Quercetin may protect against cardiovascular disease by regulating MAPK signaling cascade. In addition, quercetin protects against myocardial ischemia-reperfusion injury by reducing oxidative stress, inhibiting the inflammatory cascade, apoptosis and PI3K/Akt pathway. Luteolin inhibits AP-1 DNA binding activity to exert anti-inflammatory and other effects. Luteolin inhibits cell proliferation by reducing TNF-α-induced RELA expression. Luteolin inhibits PI3K/Akt and MAPK pathways to regulate TP53 expression for anti-proliferative and pro-apoptotic effects. Luteolin regulates endothelial dysfunction through multiple pathways such as MAPK and PI3K/Akt, inhibits apoptosis, and thus improves cardiomyocyte contractile function.,50 Kaempferol activates anti-inflammatory activity by blocking lipopolysaccharide-induced signaling pathways such as AP-1 in macrophages, thereby inhibiting the release of inflammatory mediators. Anti-inflammatory effect of kaempferol against lipopolysaccharide-induced mastitis is associated with inhibition of NF-κB p65. Kaempferol inhibits MAPK pathway and regulates oxidative stress to reduce apoptosis and improve cardiac function. Kaempferol promotes PI3K and Akt phosphorylation and downregulates PI3K/Akt pathway to induce apoptosis in cancer cells, which has an important role in cardiovascular and other diseases.In addition, many components in Epimedium can regulate HF gene expression, such as quercetin, luteolin, and kaempferol. It was shown that quercetin significantly inhibited the expression levels of RELA, JUN mRNA and protein in lipopolysaccharide-induced mouse sarcolemma and exerted anti-inflammatory and antioxidant effects.In summary, MYC, HIF-1α, NF-κB, JUN, TP53 and other genes as downstream regulators of PI3K/Akt signaling pathway, it is hypothesized that Epimedium may regulate the expression of the above genes through PI3K/Akt signaling pathway, and then regulate the downstream signaling pathways of PI3K/Akt pathway, such as HIF-1 signaling pathway and NF-κB signaling pathway, to exert intervention in HF. In this study, the mechanism of Epimedium’s intervention in HF was elucidated from the regulatory effects of Epimedium on the genes of JUN, MYC and TP53 and their protein expressions, which provided a basis for the clinical application of Epimedium to regulate HF. Due to the limitations of the network pharmacology methodology and the complexity of the chemical reactions occurring during the decoction of herbal components. The chemical composition of Epimedium decoction and the metabolites of its active ingredients in vivo were not included in the analysis of this study. In future, further screening on this basis will be followed by cellular or animal experiments to validate the main regulatory targets of Epimedium.Chen Boyang wrote this paper. Li Yuexing and Yan Yiping collected data. Yu Haiyang, Zhao Lingjie, Guan Liancheng, Zhang Xufei and Zhao Jie analyzed and organized data, Chen Yunzhi reviewed the manuscript.Data curation: Yu Haiyang, Zhao Lingjie, Guan Liancheng, Zhang Xufei, Zhao Jie.Funding acquisition: Chen Yunzhi.Writing – original draft: Chen Boyang, Li Yuexing, Yan Yiping.


Cellulose is the first rich biological polysaccharide in nature and has many excellent properties, so it is being developed as a variety of drug carriers. Moreover, applications in drug delivery, biosensors/bioanalysis, immobilization of enzymes and cells, stem cell therapy, and skin tissue repair are also highlighted by many studies. Coronary heart disease, as one of the diseases with the highest incidence, is urgent to enhance the survival outcome and life quality of patients with coronary heart disease, whereas the mechanism of cellulose's interaction with the human body remains unclear. However, the mechanism of cellulose's interaction with the human body remains unclear. We obtained 92 genes associated with cellulose and coronary heart disease through the intersection of different databases. Ten key genes were identified: HRAS, STAT3, HSP90AA1, FGF2, VEGFA, CXCR4, TERT, IL2, BCL2L1, and CDK1. Molecular docking of the 10 genes revealed their association with their respective receptors. Analysis by KEGG and GO has discovered that these related targets were more enriched in metabolic- and activation-related functions, which further confirmed that cellulose polysaccharides can also interact with cardiovascular diseases as molecules. In the end, we screened out six key genes that were more associated with the prognosis  and constructed a signature, which has a good predictive effect and has significant statistical significance. Our study is the first study to explore the interaction targets of cellulose and CHD and to construct a prognostic model. Our findings provide insights for future molecular design, drug development, and clinical trials. Coronary heart disease refers to the accumulation of some lipid substances similar to atherosclerosis in the intima of the artery and becomes white plaques, which gradually increase to cause arterial stenosis, blocked blood flow, resulting in heart ischemia, and angina pectoris , 2. WithPolysaccharides, being formed by glycosidic bonds of long carbohydrate molecules with monosaccharide units, , 7 existAt the macrolevel, the intake of cellulose can regulate the intestinal microbiota of the human body . The intTherefore, it is very important to find relevant targets and molecular pathways as the basis for research. We hypothesized that pathways related to cell membrane signaling, cell stability, and drug response were most affected. Studies have reported that immune responses are closely related . Howeverhttp://www.swisstargetprediction.ch/) and Similarity ensemble approach (SEA) search server (https://sea.bkslab.org/). For selecting the query molecule in the online database named SwissTargetPrediction, the standardized screening threshold of taking the protein as target was set to be >0. In the SEA database, we screened targets for the cellulose and recorded those with E-values of <10–5 for cellulose-target analysis. The targets for coronary heart disease (CHD) were obtained from the following five databases, including DisGeNET database (https://www.disgenet.org/), the DrugBank database (https://www.drugbank.ca/), GeneCards database (https://www.genecards.org/), MalaCards database , and Online Mendelian Inheritance in Man database . Afterward, a CHD-related gene set was generated by uniting the results from these databases.In the cause of finding the targets of cellulose, two online databases for targets of medications' searching and screening were applied: SwissTargetPrediction (https://www.ncbi.nlm.nih.gov/geo/) database  were screened out to onwards acquire data of gene expression. Supported by the GEO2R (http://www.ncbi.nlm.nih.gov/geo/geo2r/) analysis, genes that are diversely expressed with the cutoff criteria of |Log2FC| more than one and adjusted P-value <0.05 were selected in comparison with normal heart tissues.The previously published datasets downloaded from NCBI Gene Expression Omnibus  according to the intersection of the target genes of CHD and cellulose. Ninety-two intersectant targets were obtained following inputting 8,051 differentially expressed genes in CHD and 146 target genes of cellulose. The coincident target genes between both cellulose and CHD were displayed in the overlapping domain after amalgamation and striking out the duplicates.Venn diagram was established by utilizing VENNY 2.1 (https://string-db.org/). The genes that met the interaction grade exceeding the threshold (≥0.4) were sorted for the generation of PPI network. The PPI network was depicted by Cytoscape 3.8.2 software (https://cytoscape.org/), and a highly connected sub-networks were screened out by the Molecular Complex Detection (MCODE) plugin (version 1.5.1) of Cytoscape with a threshold cutoff being equaled to two, cutoff of node score being equaled to 0.2, K-core being equaled to two, and max depth being equaled to 100.The network of PPI cellulose and CHD reclosing targets in Venn diagram was constructed by utilizing the database STRING (http://metascape.org/gp/index.html#/main/step1). Bioinformatics (http://www.bioinformatics.com.cn) was used to visualize the representative enriched terms. The results include cellular component (CC), biological process (BP), and molecular function (MF) discovered by GO analysis and key signaling pathways generated by KEGG analysis that were finally presented in bar and bubble graph.Enrichment analyses by GO and KEGG were performed to pursue the biological capabilities of the overlapping target genes by utilizing the online Metascape (https://pubchem.ncbi.nlm.nih.gov/). With the software OpenBabel 2.4.1, those data were converted to the format of mol2. The proteins of relevant receptors encrypted by the opted target genes were searched in the UniProt database (http://www.uniprot.org/). In addition, 3D compositions of the protein receptors were acquired from the Protein Data Bank (PDB) database (https://www.rcsb.org/). PyMol software and AutoDockTools 1.5.6 software were used to perform the dehydration and hydrogenation process for the protein molecules, respectively. Finally, cellulose and protein receptors were docked by utilizing AutoDock Vina software.Molecular docking analyses of cellulose and the major relevant targets were performed to validate the reliability of the prediction results. The two-dimensional (2D) structure of cellulose was downloaded and obtained from the database named PubChem  curves were used to evaluate the performance of genetic risk models. Moreover, “survivalROC” R packages were used to examine the prognosis prediction efficiency and other clinical characteristics. An analysis named Cox regression was applied to assess the independent prognostic value of clinical characteristics. With the aim of estimating the likelihood of survival outcomes, a survival map by nomogram was constructed using R package named “rms” according to risk score and clinical features. It was also examined by analysis of multivariate Cox regression. The relative function of nomogram was appraised by C index, ROC, and calibration chart.An overall 147 cellulose-related target genes were obtained from SwissTargetPrediction and SEA search server after removing duplication and combining the results . A totalThe network of PPI derived from database named STRING was constructed to explore the complex interactions among these 92 intersectant targets that were considered to be the interactive targets of cellulose and CHD. The target proteins and the interactions of these proteins are denoted by the nodes and edges, respectively, and the number of stria in the network of PPI indicated the level of correlations and target ranks . MoreoveThe aforementioned 92 overlapping genes undergone the GO enrichment analysis, and the most significant 10 catalogs of biological process (BP), cellular component (CC), and molecular function (MF) were clarified, respectively . The resKEGG enrichment analysis was used to analyze the 92 intersectant genes as well for a further investigation of the underlying pathways of cellulose influencing CHD. The bar and bubble chart illustrated the top 17 significant results ,C, and tThe ten target gene-encoded proteins in PPI subnetwork, including HRAS, STAT3, HSP90AA1, FGF2, VEGFA, CXCR4, TERT, IL2, BCL2L1, and CDK1, were selected to carry out molecular docking analyses with cellulose, respectively. The outcomes from molecular docking demonstrated that the cellulose has the capabilities to enter and connect the active pocket of all selected receptors . The doc*HSP90AA1 + (0.0239) *FGF2 + (0.1721) *TERT + (0.0799) *IL2 + (−0.1204) *BCL2L1 + (0.617) *CDK1. According to the distribution of risk score, the patients with CHD were divided into high-risk groups and low-risk groups. The curve from analyzed Kaplan–Meier survival indicated that the overall survival probability of high-risk group was inferior to the low-risk group, and the AUCs for 1, 3, and 5 years were 0.861, 0.939, and 0.886 in the training dataset  is a group of diseases with many forms including myocardial infarction, angina pectoris, ischemic cardiomyopathy, asymptomatic, and sudden cardiac death. Constant factors (such as age and gender) and variable factors  interact together and become causes of coronary heart disease . At the Polysaccharide derivatives such as cellulose derivatives have attracted increasing attention due to their relative abundance and ability to maintain drug release. Rossana B Simeoni et al. explored the possibility of using bacterial cellulose (BC) membrane patches containing co-cultured cells to limit post-myocardial infarction pathology , 40. Thein vitro and in vivo experiments to verify the capabilities of relevant targets. At present, cellulose modified to be used in the treatment of diseases is still a long way to go. The research on this application in medical materials science and pharmacology is not deep enough, and interdisciplinary research should be further proposed. More animal studies need to be conducted to explore potential safety and efficacy metrics. Therefore, more efforts are needed in this field.Our study is the first study to explore the interacting targets of cellulose and CHD with the construction of a prognostic signature. Our findings provide insights for future molecular design, drug development, and clinical trials. However, our study still has limitations, for instance, we did not conduct The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.LL, YZ, and HL completed data download, data collation, and data analysis. LL and YD created the charts. MW organized the figures. LL and JL completed the writing of Introduction and Discussion and carefully revised the article and finished editing the paper. YZ wrote the rest of the article. All authors contributed to the article and approved the submitted version.This study is supported by research on the role and mechanism of TLR4 signaling pathway in the development of anxiety induced coronary heart disease, Hubei Health Commission, WJ2021F061, 2021.01-2022.12.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Hypericum perforatum (HP) is widely used for depressive therapy. Nevertheless, the antidepressant effect and potential mechanism of hyperoside (Hyp), the main active component of HP, have not been determined. Materials and Methods: We performed ultra-performance liquid chromatography–quadrupole-time-of-flight–tandem mass spectrometry (UPLC-Q-TOF-MS/MS) technology to analyze the components in HP. Using data mining and network pharmacology methods, combined with Cytoscape v3.7.1 and other software, the active components, drug-disease targets, and key pathways of HP in the treatment of depression were evaluated. Finally, the antidepressant effects of Hyp and the mechanism involved were verified in chronic-stress-induced mice. Results: We identified 12 compounds from HP. Hyp, isoquercetin, and quercetin are the main active components of HP. The Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), the Analysis Platform, DrugBank, and other databases were analyzed using data mining, and the results show that the active components of HP and depression are linked to targets such as TNF-, IL-2, TLR4, and so on. A potential signaling pathway that was most relevant to the antidepressant effects of Hyp is the C-type lectin receptor signaling pathway. Furthermore, the antidepressant effects of Hyp were examined, and it is verified for the first time that Hyp significantly alleviated depressive-like behaviors in chronic-stress-induced mice, which may be mediated by inhibiting the NLRP1 inflammasome through the CXCL1/CXCR2/BDNF signaling pathway. Conclusion: Hyp is one of the main active components of HP, and Hyp has antidepressant effects through the NLRP1 inflammasome, which may be connected with the CXCL1/CXCR2/BDNF signaling pathway.Background and Objectives:  Depression, as a common mental illness endangering the physical and mental health of the global population, is one of the most serious diseases, affecting 20% of the world’s population, and is an important factor in the rising suicide rate in the 21st century , that maHypericum perforatum (HP) is a perennial herb of the genus. HP is in the Garcinia family, known as St. John’s wort in Europe [The application of medicinal plants and natural compounds to diseases is a new trend in clinical medical research. n Europe . It has n Europe . It is sn Europe .Hyp is a natural flavonol glycoside found in various plants. Medical research has found that Hyp exhibits various pharmacological effects, including anticancer, anti-inflammatory, antibacterial, antiviral, antidepressant, blood-vessel-protecting, digestive-system-regulating, and organ-protective effects ,9,10. OvHP (the plant part name is “whole herb”) was provided by Sigma-Aldrich  Trading Co., Ltd.  . Hyp  was supplied by Shanghai Yuanye Biological Products Co., Ltd.  (No. B20631). Paroxetine was provided by Aladdin  Trading Co., Ltd. .Sterile Sprague–Dawley (SD) male rats  and C57BL/6 male mice  were bought by Shanghai Slack Laboratory Animal Company. Rats and mice were kept in their respective animal chambers  on a 12-h dark/light cycle. The animal studies in this article were conducted by the Guide for the Care and Use of Laboratory Animals. Rats and mice were acclimated to water and standard laboratory chow for one week before the experiment. All operations, including those involving rats and mice, were conducted in accordance with the Guide for the Relevant Chinese Laws and the Care and Use of Laboratory Animals and were approved by the Shanghai Jiao Tong University Institutional Animal Care and Use Committee .n = 3) and (2) the HP-300 mg/kg group  [We randomly divided SD rats into two groups: (1) the control group.  . The SD We used Eppendorf tubes to collect the blood samples, which were then centrifuged. Then, we transferred the plasma samples to Eppendorf tubes and stored them in a −80 °C freezer for further analysis. After treating 200 L of plasma with 800 L of methanol, the sample was vortexed for three minutes and centrifuged at 14,000 rpm at 4 °C for ten minutes to precipitate proteins. After centrifugation, the supernatant was collected, transferred to another tube, and evaporated to dryness. The samples were then dissolved in 60% methanol (50 L) and centrifuged at 14,000 rpm for ten minutes for later analysis.m/z. Data acquisition was automatically calibrated. With the MS/MS mode, argon was used as the collision gas, and the collision energy ranged from 10–40 eV (from low to high).LC-MS raw data were acquired using the Agilent 1290 Q-TOF/MS and Mass Hunter qualitative software. UPLC separation was performed on the samples using an Agilent Poroshell 120 EC-C18 150 mm, 1.9 mm column, on which each sample was analyzed. The mobile phases consisted of (A) 0.1% formic acid in water and (B) acetonitrile, and the following were the optimum UPLC elution conditions: 0–12 min, 10–20% B; 12–18 min, 20–35% B; 18–20 min, 35–10% B, after 1 min. Analyses were conducted at a flow rate of 0.3 mL/min and at a column temperature of 45 °C. 5 μL was the volume of the injection. Agilent 6545 Q-TOF-MS/MS used the Dual Agilent Jet Stream electrospray ionization source (ESI). MS conditions: positive ion mode. gas temperature, 320 °C; fragment voltage, 175 V; sheath gas flow, 8 L/min; and sheath gas temperature, 350 °C, respectively. The range of data acquisition was from 100 to 1000 http://tcmspw.com/tcmsp.php; 1 December 2021) is a unique systematic pharmacology platform for traditional Chinese medicine, highlighting the role of systematic pharmacology in traditional Chinese medicine. Using the “Hypericum perforatum” filter as an analysis platform, the TCMSP database was used to retrieve all active ingredients of HP with an oral bioavailability (OB) of 30% and drug-likeness (DL) of 0.18 as screening criteria. The candidate genes were corrected and identified using the UniProt  database. We collected depression-related gene targets in the DrugBank database  using the keywords “major depression”, “depression”, or “unipolar depression”. VENNY2.1  was used to obtain the Venn diagram, which showed the intersection of depression and HP. The gene ontology (GO) function  analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of co-action targets were conducted via the David database . The common targets of active components and potential targets of depression were collected and input into the Cytoscape 3.7 software to construct a component–target–disease interaction network that visualized and integrated topological parameters. The STRING database builds functional connections in protein networks by collecting and integrating all known and predicted protein functional associations. The identified potential proteins were imported into STRING  to obtain the corresponding relationships of protein interactions, and protein–protein interaction (PPI) networks were constructed by Cytoscape 3.7 software.The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform , (2) the CUMS group (n = 5), (3) the CUMS+Hyp (36 mg/kg) group (n = 5) [n = 5). We gave mice saline, Hyp, or paroxetine by gavage for four weeks. Paroxetine was used as a positive control for antidepressants. After the experiment, the mice were euthanized using the cervical spine dislocation method (the specific method is the same as that used on rats).Research has shown that the most generally reliable, used, and effective depression model is chronic unpredictable mild stress (CUMS) . The CUM (n = 5) , and (4)The degree of the animal’s response to the reward is reflected in the consumption of sugar water, and the interest of humans was simulated by the consumption of sucrose water by the mice. The day after the last stress session, in order to measure the anhedonia as previously described, the SPT was performed . Then, aAs previously introduced, the tail-suspension test was performed . To begiTo further determine the depression-like behavior of mice, we performed FST experiments. Studies have shown that the forced swim test is a highly reliable test for assessing depressive-like behavioral states in mice . The exp−ΔΔCT method.At the end of all the behavioral experiments, we killed the mice and harvested their brains. Total RNA was extracted from mouse hippocampus tissues using the TRIzol reagent  and other chemical reagents. Then, we reverse-transcribe RNA into cDNA using the Prime Script First Strand cDNA Synthesis Kit . We used standard methods to PCR-amplify cDNA. Primer sequences required for this experiment are shown in t-test or one-way analysis of variance (ANOVA) to compare differences. At p < 0.05, statistically significant differences were indicated.All experimental data were analyzed with GraphPad Prism. The data are represented as means± SEM. We used an unpaired, two-tailed Student’s To explore the absorption of HP in vivo, we must know its complex chemical composition. HP extract was qualitatively analyzed using UPLC-Q-TOF/MS. To begin, we created a library of HP ingredients (primarily Hyp). In the literature, we summarized and qualitatively analyzed 12 components of HP. Based on ChemSpider, the name and formula of the compound, the molecular weight, and the chemical structure of the compound were provided. To improve the peak capacity and resolution of HP absorption, we optimized the UPLC-Q-TOF/MS condition.By means of comparing all known compounds with reference standards, they were identified. References were from UPLC-Q-TOF/MS literature ,27, and p < 0.05). The serotonergic synapse, calcium signaling pathway, dopaminergic synapse, and the other 14 signaling pathways relevant to depression were discovered. These pathways were mainly relevant to two pathways of metabolism, four pathways of anti-cancer, three pathways of neuroprotection, two pathways of cardiovascular function, three pathways of signal transduction, and three pathways of anti-inflammation.We used the method of VENNY 2.1 software to identify 43 overlapping targets by matching the 104 genes with the genes relevant to disease A. We impWe used UPLC-QTOF-MS/MS to analyze the components in plasma from rats after administration of water extract from HP. p < 0.05), the C-type lectin receptor signaling pathway related to depression was identified. The results are consistent with the anti-inflammatory effects of HP and its main active components [The targets corresponding to the main active components of HP were obtained through the SwisStargetPrediction website, and depressive-related genes were obtained through the DisGeNET and OMIM websites. A total of eight intersection targets were obtained after the intersection A. HP’s mmponents , its antmponents , its antmponents , its neumponents , its antmponents , and itsmponents . For examponents . Studiesmponents . While tmponents  as well mponents ,40. ThusIn order to further explore the antidepressant effect of Hyp, we established a CUMS depression model and administered Hyp for treatment. After the depression model was completed, we tested the depression-like behaviors with the TST, FST, and SPT. Compared to the control group, the CUMS group indicated slow body weight gain A, signifThe expression of the NLRP1 inflammasome complex in the hippocampus was detected by the method of PCR ,40. Our Chronic stress induces an inflammatory response, which downregulates BDNF and promotes CXCL1 secretion. Chronic stress activates the expression of the NLRP1 inflammasome, which triggers this inflammatory response ,40. To rSeveral clinical trials have conducted relevant studies on the manifestations and characteristics of various mental disorders ,43,44,45In this experiment, UPLC-QTOF-MS/MS was used to detect the water extract of HP, and 12 main compounds, including Hyp, were obtained. They play a role in pharmacological effects by influencing 43 overlapping genes that exert themselves in the treatment of HP. The activity-target network diagram of HP was constructed by introducing the activity-target information into the Cytoscape software. As can be seen from the result, the same active compound can correspond to different targets, which fully indicates that HP anti-depression has the features of multi-targets and multi-ingredients, with a total of 166 genes and 290 intersections. There were 22 Hyp and depression intersection targets among them, and 43 potential HP targets in the treatment of depression were involved 16 related signaling pathways. In addition, the C-type lectin receptor signaling pathway is the most important signaling pathway. In addition, UPLC-QTOF-MS/MS analysis of plasma samples of water extract of HP in SD rats confirmed that the main components in blood were Hyp, isoquercetin, and quercetin. We performed network pharmacology analysis on the intersection of HP’s main active component targets and depression targets. Therefore, these findings prove that Hyp has multi-targets and multi-ingredient synergistic influences and exerts its efficacy, providing a basis for the study of multi-component and multi-target synergistic effects.BDNF belongs to the family of neurotrophins and plays a critical role in the survival, development, and maintenance of the nervous system . Many stHyp is the main antidepressant component of HP. Its antidepressant effect may be through the NLRP1 inflammasome. CXCL1/CXCR2/BDNF signaling pathway may mediate the effect. These research findings supply an experimental basis for the clinical application of Hyp in depression treatment.


Introduction: COVID-19 (SARS-CoV-2) has been linked to organ damage in humans since its worldwide outbreak. It can also induce severe sperm damage, according to research conducted at numerous clinical institutions. However, the exact mechanism of damage is still unknown.Methods: In this study, testicular bulk-RNA-seq Data were downloaded from three COVID-19 patients and three uninfected controls from GEO to evaluate the effect of COVID-19 infection on spermatogenesis. Relative expression of each pathway and the correlation between genes or pathways were analyzed by bioinformatic methods.Results: By detecting the relative expression of each pathway and the correlation between genes or pathways, we found that COVID-19 could induce testicular cell senescence through MAPK signaling pathway. Cellular senescence was synergistic with MAPK pathway, which further affected the normal synthesis of cholesterol and androgen, inhibited the normal synthesis of lactate and pyruvate, and ultimately affected spermatogenesis. The medications targeting MAPK signaling pathway, especially MAPK1 and MAPK14, are expected to be effective therapeutic medications for reducing COVID-19 damage to spermatogenesis.Conclusion: These results give us a new understanding of how COVID-19 inhibits spermatogenesis and provide a possible solution to alleviate this damage. Globally, up to May 2022, there have been more than 520,000,000 confirmed cases of COVID-19, including 6,000,000 deaths, reported to WHO . Identification of DEGs Analysis of gene expression between samples from three COVID-19 patients and three uninfected controls from GEO was conducted using “limma” package  in R sofhttps://www.wikipathways.org)) )  is a bioys.org))  softwarep-value of differential gene enrichment  is based on hypergeometric method. The formula is:N is the number of genes with Pathway annotation in all genes; n is the number of differentially expressed genes in N; m is the number of genes annotated as a particular Pathway in all genes; m represents the number of differentially expressed genes annotated as a specific Pathway. The calculated p-value will be further corrected by multiple tests to obtain corrected p-value. Usually, we use adj p-value < .05 as the threshold, and the pathway satisfying this condition is defined as the pathway that is significantly enriched in differentially expressed genes.The calculation of Single sample gene set enrichment analysis (ssGSEA) ranks thep-value < .05.The “GSVA”  softwarehttp://www.string-db.org/)  and the plug-in Molecular Complex Detection (MCODE) was used to screen functional modules to identify hub genes. A p-value < .05 was considered statistically significant.Protein–protein interaction networks is a database of known and predicted protein–protein interactions  . It currhttp://www.R-project.org/).Build a cross-network to study the interaction sites between pathways using topGO . Correla1) Many biological processes were harmed as a result of COVID-19 infection, including spermatogenesisVarious organs in the body were severely damaged after being infected by COVID-19 through ACE2 receptor. The testis, which has a high level of ACE2 expression in the body, cannot be spared . Previouin vivo will be considerably impacted after COVID-19 infection. By downloading GEO’s bulk-RNA-seq data from three COVID-19 patients and three uninfected controls, Differential genes between the two groups were screened, and differential genes function enrichment analysis was performed to better understand how COVID-19 impacts spermatogenesis in the human testis.Many biological processes We used the R package “LIMMA” to examine the differences genes between the two groups. Analysis revealed 15850 mRNAs in the testes of controls and COVID-19 patients, of which 2,645 were up-regulated while 2,789 were down-regulated . These findings imply that during specific biological processes, COVID-19 infection triggers dynamic alterations at the molecular level. In order to further explore the changes of testicular biological processes after COVID-19 infection, we carried out KEGG, GO, WIKIPATHWAYS functional enrichment analysis of differential genes.p-value of the enrichment pathway to better highlight the effect of COVID-19 on the testis. In the upregulated genes after COVID-19 infection, GO enrichment mainly concentrated in: Viral transcription, Viral gene expression, Response to insulin, Response to peptide hormone, Translation initiation  COVID-19 inducing senescence in testicular cells after COVID-19 infectionTherefore, we explored the COVID-19 patient’s sperm differentiation level. The important enzyme CA2 in the sperm differentiation process was considerably reduced in COVID-19 group . At the Based on the previous analysis of the top 30 pathways in GO, KEGG, WIKIPATHWAYS functional enrichment pathway of the differentially expressed genes up and down after COVID-19 infection, we can see that cell cycle related pathways  occur repeatedly in GO, KEGG, WP enrichment pathways of downregulated gene sets . MultiplIn order to better understand how COVID-19 negatively affects patients’ spermatogenesis, we concentrate on the most significant pathways especially cell cycle related ones. Interestingly, in the top 10 pathways of KEGG enrichment within the up-regulated genes after infected with COVID-19, cellular senescence pathway is the most significant one . At the To confirm our hypothesis, we first found out pathways linked to cellular senescence based on past researches, such as the mTOR, MAPK, P53 signaling pathway . At the In order to further explore how COVID-19 induces cellular senescence and how cellular senescence further affects other pathways, we scored the relevant biological signal pathways by ssGSEA. The method for calculating the ssGSEA score and the enrichment significance of differential genes are explained in detail in method. Through the analysis of the ssGSEA scoring method and the enrichment scores of GO, KEGG, WIKIPATHWAYS, we can see that the higher the specificity of genes in a specific pathway, the less the number of genes, the more beneficial to the enrichment significance of differential genes such as GO, KEGG, WIKIPATHWAYS, On the other hand, ssGSEA means that the more accurate the number of related genes in a specific pathway, the more extreme the gene distribution is, and the more obvious the score is.3) COVID-19 induced testicular cell senescence through MAPK signaling pathwayIt is well known that there are many senescence-related genes. We can see from the analysis of KEGG Senescence Pathway and GO Senescence Pathway that KEGG Senescence Pathway mainly includes 19 senescence-related genes, while GO Senescence Pathway contains 130 senescence-related genes. This may occur when the senescence-related genes in KEGG Senescence Pathway are used for ssGSEA scoring, and the scores related to senescence genes obtained will be offset by the scores of genes that are not effectively included in the KEGG Senescence Pathway but are closely related to senescence, and ultimately affect the scoring results. This inference can be verified in the ssGSEA scoring of KEGG Senescence Pathway and GO Senescence Pathway . At the It is well known that cellular senescence is a special cell state and is characterized by slow proliferation and cell cycle arrest . Cellular = .999, p < .001).We examined the top 20 signaling pathways significantly positively linked with the cellular senescence in COVID-19 patients to further understand how COVID-19 induces testicular cell senescence. These pathways can be found mostly in the KEGG MAPK Signaling Pathway, KEGG P53 Signaling Pathway, Wp Activation of Nlrp3 Inflammasome by Sars-cov2 and Wp Ras Signaling . Among tMAPK signaling pathway is mainly composed of four subfamilies, namely, 1) Extracellular-signal-regulated protein kinase (ERK), 2) P38 mitogen-activated protein kinase (p38 MAPK), 3) C-Jun N-terminal kinase (JNK), 4) Extracellular signal-regulated kinase 5 (ERK5). These MAPK subfamilies are participate in a variety of signal transduction pathways, including ERK, which regulates cell growth and differentiation, and p38 MAPK signaling pathways , which aWe looked at the relationship between the MAPK signaling pathway and other pathways in COVID-19 patients in this study. In the COVID-19 group, MAPK pathway was significantly positively correlated with Coronavirus disease COVID-19, and negatively correlated with sperm differentiation. Cell senescence and Coronavirus disease COVID-19 and sperm differentiation also have the same trend with MAPK pathway . We invevia the MAPK signaling pathway. The top 20 pathways that most negatively correlated with cellular senescence were KEGG Cytosolic DNA Sensing Pathway, KEGG Cytosolic DNA Sensing Pathway, KEGG Cytosolic DNA Sensing Pathway, KEGG Butanoate Metabolism, KEGG Erbb Signaling Pathway, KEGG Drug Metabolism Cytochrome P450, Wp Estrogen Metabolism, Wp Cholesterol Biosynthesis Pathway, Wp Cholesterol Biosynthesis Process, KEGG Gap Junction, KEGG Gly Pyruvate Metabolism KEGG etc.  The Prominent Negative Role of Cellular senescence on Androgen SynthesisMAPK pathway and cellular senescence exhibit a Similar negative correlation with testosterone synthesis, cholesterol synthesis, glycolysis and pyruvate metabolism . ThroughAndrogen synthesis is well recognized to be converted from cholesterol, and adequate androgen synthesis is critical for spermatogenesis . The queWe evaluated the signaling pathways closely associated to cholesterol and testosterone synthesis, specifically the signaling pathways strongly related to cell cycle, to better understand how they regulate the synthesis of cholesterol and testosterone. In the top 20 most negatively correlated pathways related to testosterone synthesis pathway, we can see that KEGG Wnt Signaling Pathway, Wp Ras Signaling, KEGG Citrate Cycle Tca Cycle, KEGG MAPK Signaling Pathway, Go Senescence, KEGG Long Term Potentiation are significantly negatively correlated, which are mainly concentrated in the pathways related to cell cycle inhibition . BetweenKEGG Wnt Signaling Pathway, KEGG Glycosaminoglycan Degradation, Wp Ras Signaling, KEGG Citrate Cycle Tca Cycle, KEGG MAPK Signaling Pathway, and Go Senescence were among the top 20 negative pathways correlated with the cholesterol synthesis pathway , which GConsistent with expectations, the positive and negative correlation pathways of testosterone synthesis pathway and cholesterol synthesis pathway were highly similar, and the pathways that inhibited the normal cycle of cells had a significant negative correlation with the two, especially cellular senescence. Interestingly, pyruvate metabolism and glycolysis signaling pathways were positively correlated with both, suggesting that there was an indivisible relationship between effective energy metabolism and androgen synthesis.Wp Cholesterol Metabolism Includes Both Bloch And Kandutschrussell Pathways, Wp Cholesterol Biosynthesis Pathway, KEGG Glycolysis gluconeogenesis Pathway were positively correlated with the testosterone synthesis pathway In both Control group and COVID-19 group . It was r < −.9, p < .05) were detected by PPI on STRING website, and the top 20 genes were obtained. At the same time, PPI was applied to 800 positive correlated genes with STAR  to produce the top 20 genes (5) The negative correlation between cellular senescence with pyruvate and lactate generationThe difference in the expression level of STAR, CYP11A1 in androgen synthesis were analyzed to better understand the effect of COVID-19 on androgen synthesis. The two rate-limiting enzyme genes reduced dramatically after COVID-19 infection , resulti20 genes . PPI was20 genes . Interes20 genes .5 The nein vivo by lactate dehydrogenase. The major mechanism for the synthesis of pyruvate and lactate in vivo is glycolysis, implying that adequate glycolysis is required for normal spermatogenesis  were detected by PPI on STRING website, and the top 20 genes were obtained  in order to produce the top 20 ones . Firstly, 637 genes with strong negative correlation with HK1  (6) MAPK pathway plays an important role in COVID-19 infection inhibiting spermatogenesis. Targeted MAPK pathway drugs are expected to effectively inhibit the damage of COVID-19 to spermatogenesis.In the relevant literatures, 13 genes have been proven to have effects on cellular senescence. Interestingly, MAPK1 is the most obvious gene that has a negative relationship with HK1( < .001) . This geCOVID-19 induces testicular cell senescence primarily through extracellular regulated protein kinases (ERK) and p38 mitogen-activated protein kinase (p38 MAPK) in four subfamilies of the MAPK signaling pathway, as shown in the previous analysis . Throughhttps://www.proteinatlas.org/)  . At the as.org/) , which ias.org/) , and in as.org/) . In concFrom the previous results, we can see that MAPK1 and MAPK14 play an important role in COVID-19 infection on cellular senescence and inhibition of androgen synthesis and reducing glycolysis. In combination with the recommendations of Chinese patent medicines in the current new coronavirus treatment guidelines, we found that Qingfei Paidu Decoction, Jinhua Qinggan Granule, Reduning Injection, Tanreqing Injection and Shufeng Jiedu Capsules all played certain therapeutic effects on MAPK1 and MAPK14 targets in patients with COVID-19 infection after consulting a large number of literatures. Interestingly, the majority of these patented Chinese medications target multiple MAPK enzymes in the MAPK pathway, including the MAPK1, MAPK8, MAPK14 .COVID-19 has been linked to male spermatogenesis dysfunction in numerous previous studies, however the exact mechanism is still unknown. ACE2, as an essential role in COVID-19 infected testis, mainly expressed in Sertoli cells and Leydig cells. This study speculaed that COVID-19 can induce testicular cell senescence through MAPK signaling pathway, and cellular senescence negatively correlated with glycolysis metabolism, normal pyruvate and lactate metabolism mainly performed in Sertoli cells, testosterone synthesis and cholesterol synthesis mainly performed in Leydig cells. Drugs target on MAPK signaling pathway, especially on MAPK1, MAPK14, are expected to become effective therapeutic drugs to reduce the induction of cell senescence by COVID-19.Cellular senescence is a special state of cells, which can permanently stop the cell cycle , and at via the CXCR2 receptor reinforces senescence—PubMed). These components enhance the MAPK signaling pathway in turn, aggravating cellular senescence, resulting in a vicious loop that worsens the spermatogenesis damage induced by cellular senescence. In conclusion, it can see that MAPK pathway was activated by inflammation induced by COVID-19, which further aggravated testicular cell senescence.To further understand how COVID-19 induces cellular senescence, we analyzed the correlation between cellular senescence and other pathways, and found that MAPK pathway was most positively correlated with cellular senescence. MAPK pathway can be activated by all kinds of inflammatory factors, products of oxidative stress. In particular, ERK and P38-MAPK in the MAPK pathway are enriched in the process of cell senescence induced by inflammatory factors, oxidative stress and other factors in this study . IL1-β, Previous research has found that COVID-19-induced senescence exacerbates lung injury, lung failure, cardiac dysfunction, nervous system infection, and gut injury , 19. COVCOVID-19 has been linked to spermatogenesis damage in prior studies . AccordiTo learn more about how COVID-19 inhibits spermatogenesis, particularly cellular senescence, the disease’s principal pathological change. We discovered that testicular cell senescence negatively correlated with glycolysis pathway, normal pyruvate metabolism, testosterone synthesis pathway and cholesterol synthesis pathway.in vivo is mainly converted from cholesterol through a series of biochemical processes  , p38 mitogen activated protein kinase (p38 MAPK), c-Jun N-terminal kinase (JNK) , extracellular signal regulated kinase 5 (ERK5) . PeirouvAs an important member of the MAPK pathway, MAPK enzymes are a group of evolutionary conserved serine, threonine protein kinases, which are activated by a series of extracellular stimuli including peptide growth factors, cytokines, hormones and various cell stressors, such as oxidative stress and endoplasmic reticulum stress, and ultimately mediate signal transduction from the cell membrane to the nucleus. They control a variety of cell functions, including inflammation, proliferation, differentiation, survival, cancer, and death . Our stuActivation of p38 (MAPK14) -MAPK pathway promotes inflammation, vasoconstriction and thrombosis, and contributes to viral life cycle . PreviouIn summary, this study found that COVID-19 could induce testicular cell senescence through MAPK signaling pathway. Cellular senescence in the coordination of MAPK signaling pathway, which further affected the normal synthesis of cholesterol and androgen, inhibited the normal synthesis of lactate and pyruvate, and ultimately affected spermatogenesis. The medications targeting MAPK signaling pathway, especially MAPK1 and MAPK14, are expected to be effective therapeutic medications for reducing COVID-19 damage to spermatogenesis. These result give us a new insight into how COVID-19 inhibits spermatogenesis and provide a possible solution to mitigate this damage.