Ardisia is widely used as a hepatoprotective and anti-inflammatory agent in China. However, the active ingredients in Japanese Ardisia and their potential mechanisms of action in the treatment of autoimmune hepatitis (AIH) are unknown. The pharmacodynamic substance and mechanism of action of Japanese Ardisia in the treatment of AIH were investigated using network pharmacology and molecular docking technology in this study. Following that, the effects of Japanese Ardisia were evaluated using the concanavalin A (Con A)-induced acute liver injury rat model. The active ingredients and targets of Japanese Ardisia were searched using the Traditional Chinese Medicine Systems Pharmacology database, and hepatitis-related therapeutic targets were identified through GeneCards and Online Mendelian Inheritance in Man databases. A compound–target network was then constructed using Cytoscape software, and enrichment analysis was performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Molecular docking technology was used to simulate the docking of key targets, and the AIH rat model was used to validate the expression of key targets. Nineteen active chemical components and 143 key target genes were identified. GO enrichment analysis revealed that the treatment of AIH with Japanese Ardisia mainly involved DNA–binding transcription factor binding, RNA polymerase II-specific DNA transcription factor binding, cytokine receptor binding, receptor-ligand activity, ubiquitin-like protein ligase binding, and cytokine activity. In the KEGG enrichment analysis, 165 pathways were identified, including the lipid and atherosclerotic pathway, IL-17 signaling pathway, TNF signaling pathway, hepatitis B pathway, and the AGE–RAGE signaling pathway in diabetic complications. These pathways may be the key to effective AIH treatment with Japanese Ardisia. Molecular docking showed that quercetin and kaempferol have good binding to AKT1, IL6, VEGFA, and CASP3. Animal experiments demonstrated that Japanese Ardisia could increase the expression of AKT1 and decrease the expression of CASP3 protein, as well as IL-6, in rat liver tissues. This study identified multiple molecular targets and pathways for Japanese Ardisia in the treatment of AIH. At the same time, the effectiveness of Japanese Ardisia in treating AIH was verified by animal experiments.Japanese  Autoimmune hepatitis (AIH) is a common liver disease worldwide, seen in both men and women, but predominantly in women. According to epidemiological surveys, the incidence of AIH ranges from 0.67 to 2.0/100,000 people per year, and the prevalence ranges from 4.0 to 42.9/100,000 .The pathogenesis of AIH is not completely understood. AIH is thought to be caused by genetic factors, molecular mimetic mechanisms, immune damage, and a variety of physical and chemical factors ,9,10,11.Ardisia, known as Ardisia japonica or marlberry, is used as a medicinal plant in traditional Chinese medicine. It grows very slowly, and its leaves have a similar appearance to tea leaves. Bright red berries appear under the leaves in autumn, and therefore, it is also called ‘aidicha’ or ‘yedizhu’ in Chinese. Japanese Ardisia is mainly grown in the southern provinces of China, such as Hunan and Guangxi, where it is a popular medicinal herb used in Chinese folk medicine. The Chinese ancient medicine book ‘Compendium of Materia Medica’ records that A. japonica has the effect of ‘detoxification and promoting blood circulation’. The pharmacodynamic components of A. japonica are saponins, coumarins, benzoquinones, and flavonoids [A japonica is commonly used to treat chronic bronchitis, pulmonary tuberculosis, tuberculous pleurisy, and acute icteric hepatitis. Meanwhile, A. japonica has shown remarkable curative effects in the treatment of chronic hepatitis [Japanese avonoids ,14,15. Iavonoids ,17. In cArdisia in the treatment of AIH through network pharmacology and molecular docking analysis of the interaction between drug molecules and AIH-related targets, and to provide a theoretical basis for clinical research. The specific flow chart is shown in Cyberpharmacology can effectively reveal the material basis and mechanism of action of Chinese medicine by systematically and integrally exploring the relationship between drugs and diseases . Thus, tArdisia were obtained by searching the TCMSP database. Nineteen molecules with OB ≥ 30% and DL ≥ 0.18 were identified as bioactive compounds [Oral bioavailability (OB) is the fraction of an orally administered drug that reaches systemic circulation. This is an important consideration for bioactive molecules used as therapeutic agents. Drug likeness (DL) qualitatively assesses the capacity of a molecule to become an orally administered drug based on its bioavailability . The maiompounds , as showArdisia were obtained from the TCMSP database . After screening to remove invalid gene IDs, the targets downloaded from the GeneCards , OMIM databases , and TTD  were crossed with those from the TCMSP database to obtain potential targets for the treatment of AIH in Japanese Ardisia. The obtained data are presented as a Venn diagram  to construct the PPI network (https://www.r-project.org/ accessed on 15 November 2021) are shown in Ardisia active ingredient targets and autoimmune hepatitis disease targets were imported into Cytoscape 3.7.0  for topological analysis. The key targets were sorted according to the degree value, with higher degree values indicating nodes that were more central in the network and more important. Through the PPI protein interaction network, the disease-related targets are found, and the degree value is greater than the median by screening twice to find key targets. Thus, the key target genes for autoimmune hepatitis treatment mainly included AKT1, IL6, VEGFA, CASP3, JUN, MYC, etc. , and the common targets between Japanese Ardisia, its active components, and autoimmune hepatitis were visualized. The data were merged into a component-target network diagram via the merge function in Cytoscape 3.7.0 to obtain the network diagram of ‘Japanese Ardisia–component–gene–autoimmune hepatitis’  and AutoDock software (https://autodock.scripps.edu/ accessed on 16 November 2021) were used to visualize the docking results in the form of two-dimensional and three-dimensional diagrams , and AKT1 expression levels were significantly lower (p < 0.01) in the model group compared to the normal control group. CASP3 protein expression was significantly lower (p < 0.01), AKT1 protein expression was significantly higher (p < 0.05), and IL-6 protein expression was significantly lower (p < 0.05) in the Japanese Ardisia administration group after 10 days compared to the model group.Western blot analyses are shown in AIH is a chronic inflammatory disease characterized by abnormally high levels of serum autoantibodies, hypergammaglobulinemia, and serum transaminases . With thChinese medicine’s multi-component and multi-target properties, and thus its holistic and systemic action characteristics, make it unique in its advantages and potential for complex diseases, but this complexity has also limited its application and development.Ardisia for the treatment of AIH.Cyberpharmacology analyzes drug action at the systemic level and reveals the synergistic mechanism of drug action on the human body, which fits well with the dialectical and holistic view of Chinese medicine theory, and it is expected to bring a breakthrough to Chinese medicine research characterized by a holistic approach, providing new methodological support for Chinese medicine to move from empirical to theoretical science ,25,26. WArdisia. The TCMSP database analysis resulted in the screening of 19 active ingredients. 143 effective targets for the treatment of autoimmune diseases were identified using databases, such as GeneCards and OMIM. According to the results of the component–target network analysis, 150 target genes were associated with the drug-disease target intersection. The core genes were AKT1, IL6, VEGFA, and CASP3. AKT1, also known as protein kinase B, regulates a wide variety of cellular functions, including cell proliferation, survival, metabolism, and angiogenesis, in both normal and malignant cells [IL6 is a pro-inflammatory cytokine with a wide variety of biological functions. It is involved in physiological activities such as the inflammatory response, cellular immunity, and hematopoietic regulation. IL6 plays major roles in the differentiation of B cells into immunoglobulin-secreting cells and antibody production, the activation of T cell proliferation and differentiation, the immune response, and the promotion of inflammatory reactions [IL6 is rapidly synthesized in response to tissue injury or an inflammatory infection. This promotes the body’s defense function by stimulating the acute immune response and the hematopoietic system. When the tissue recovers its homeostasis, IL6 synthesis is discontinued [IL6 pathway is associated with liver injury and hepatocellular carcinoma [VEGFA induces endothelial cell proliferation, promotes cell migration, inhibits apoptosis, and induces the permeabilization of blood vessels. It is essential for both physiological and pathological angiogenesis. CASP3 is a cysteine aspartate protease that participates in the activation cascade of cysteine proteases. CASP3 plays an important role in inflammation and tumor progression [This study provides key information about the anti-hepatitis effect of Japanese nt cells . IL6 is eactions . IL6 is ontinued . The conarcinoma . VEGFA igression . It is hgression , and it gression  and tumogression .Ardisia has a therapeutic effect on hepatitis via a mechanism that may be related to key molecules involved in the regulation of autoimmune hepatitis. It inhibits associated inflammatory factors by regulating various signaling pathways, downregulating the concentrations of serum hyaluronic acid and tumor necrosis factor, protecting hepatocytes from injury, reducing liver inflammation, and protecting against lipid peroxidation [Ardisia is related to the inflammatory response, cell cycle regulation, and hormone metabolism. In the KEGG enrichment analysis, 163 pathways were identified, including the lipid and atherosclerosis pathway, IL-17 signaling pathway, TNF signaling pathway, human cytomegalovirus infection pathway, fluid shear stress and atherosclerosis pathway, hepatitis B pathway, and AGE–RAGE signaling pathway in diabetic complications. It can be seen that the pathway is mainly related to oxidative stress, immune regulation, and inflammatory responses, with the AGE-RAGE signaling pathway being closely related to inflammation, which activates the MAPK and NF-KB pathways and interferes with immune and oxidative stress responses [Ardisia, which affects the secretion of certain substances by acting on specific receptors or enzymes, to achieve its therapeutic effect.Japanese xidation . Inflammxidation . GO enriesponses . TNF is esponses . The IL-Ardisia, with the key targets AKT1, IL6, VEGFA, and CASP3, the docking binding energy and the number of intermolecular hydrogen bonds were obtained. The results showed that quercetin and kaempferol had a good binding ability with the key targets and can spontaneously bind to form a stable binding conformation.The binding interaction between each compound and its receptor was scored by the molecular docking program. A lower score indicated more stable binding between the ligand and its receptor ,40. ThroArdisia is effective in the treatment of AIH. Western blot analysis revealed that Japanese Ardisia could reduce the expression of CASP3 and IL-6 while increasing the expression of AKT1. These proteins are involved in the AGE–RAGE signaling pathway in diabetic complications. According to this, the Japanese Ardisia may be able to modulate these key targets to achieve therapeutic effects on immune liver injury.Animal studies have shown that Japanese Additionally, there are also limitations to the research at this stage, as network pharmacology techniques can only predict drug composition and targets qualitatively. High-performance liquid chromatography (HPLC) or ultraviolet spectrophotometry (UV) should be used to determine the plausibility of the screened active ingredients, and this should be combined with pharmacology, pharmacodynamics, and pharmacokinetics to make the screened active ingredients and mechanism of action more convincing.http://tcmspw.com/tcmsp.php (accessed on 14 November 2021)), GeneCards (http://www.genecards.org (accessed on 14 November 2021)), Online Mendelian Inheritance in Man ), the Therapeutic Target Database , the Search Tool for Retrieval of Interacting Genes (STRING) protein interaction database (https://string-db.org (accessed on 15 November 2021)), Cytoscape 3.7.0 (http://www.cytoscape.org (accessed on 15 November 2021)), and the Protein Data Bank (PDB) protein structure database (https://www.rcsb.org/pdb (accessed on 16 November 2021)) were used in this study.The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, an analysis platform  and screened for active compounds by oral bioavailability (OB) and drug similarity (DL), as well as potential targets of action for activity, the active compounds obtained from the screening are presented in the form of a list.The components of Japanese https://www.r-project.org/ accessed on 15 November 2021) to remove duplicate regions of gene targets, the intersection of the active ingredient and disease target was obtained and plotted as a Venn diagram.GeneCards, OMIM, and TTD were used to identify hepatitis-related gene targets. Specific search parameters, such as the keyword ‘autoimmune hepatitis’, were used for data collection. Using R 4.0.4 software  network was constructed according to proximity centrality, intermediate centrality, and degree value, and the key targets were screened using Cytoscape 3.7.0. The cross-targets of Japanese The previously acquired common genes and the associated active ingredients were visualized and analyzed using Cytoscape 3.7.0 software.Ardisia for autoimmune hepatitis treatment were imported into the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. GO was selected for enrichment analysis, KEGG was selected for pathway analysis, and the p-value threshold was set at <0.05 to determine the enrichment pathways of key targets. An advanced bubble diagram was constructed from the enrichment results: the smaller the p-value, the higher the enrichment; the larger the bubble, the richer the genes were.The potential targets of Japanese AKT1), interleukin 6 (IL6), vascular endothelial growth factor A (VEGFA), and caspase 3 (CASP3) were selected as the target proteins for molecular docking experiments. The three-dimensional structures of AKT1, IL6, VEGFA, and CASP3 were downloaded from the PDB protein structure database and saved in PDB format [https://autodock.scripps.edu/ accessed on 16 November 2021) for molecular docking, and the docking results were analyzed using the PyMOL (https://pymol.org/2/ accessed on 16 November 2021) visualization tool.The two-dimensional structures of quercetin, kaempferol, and laricitrin were obtained from the TCMSP database and saved as a Mol2 file. AKT serine/threonine kinase 1 , the concentrate was centrifuged at 5000 rpm for 15 min, the supernatant was collected and concentrated to 1.5 g/mL , and the obtained concentrate was refrigerated at 4 °C [The whole herb of Japanese  at 4 °C ,44.n = 6), con A group (n = 6), and extract of Japanese Ardisia (EJA) (n = 6) groups after being fed adaptively for a week. The control and model groups were given saline, while the administration group was given 36 g/kg of Japanese Ardisia by gavage once daily for 10 days. One hour after the last dose, all groups were given 25 mg/kg con A in the tail vein, except for the control group which was given an equal amount of saline in the tail vein, rats were euthanized 12 h after con A treatment, and their livers were dissected from the rats.SPF-grade male SD (Sprague-Dawley) rats, weighing (200 ± 10) g, with six animals per cage were housed in specific pathogen-free facility with a 12 h light and 12 h dark cycle at 22 °C. All mice were randomly divided into three groups, control group  (Cat.No.C009-2-1) and aspartate transaminase (AST) (Cat.No.C010-1-1) measurements were performed according to the instructions provided by the kit supplier.All the animals were provided by Hunan Sleek Jingda Laboratory Animal Co. License No. SCXK (Xiang) 2019-0005. Animal welfare and experimental procedures followed the regulations of the Animal Ethics Committee of Guilin Medical College.Tissue removed from 2.8.2 was fixed in 4% paraformaldehyde, paraffin sections were embedded, and, finally, the pathological sections were observed by HE staining, and the pathological changes of liver tissues were observed under an electron microscope.AKT1 , CASP3 , IL-6 , β-actin antibody , and incubated them overnight at 4 °C. Then, we incubated them with goat anti-rabbit IgG (H + L) and goat anti-mouse Ig G (H + L) for 1 h at room temperature. The protein bands were visualized using an ECL chemiluminescence kit  and quantified under Image J system, version 6.0.To verify the protein expression level, we extracted protein from rat liver tissue, weighed a certain amount of liver tissue, fully lysed it with RIPA lysis solution , used SDS-PAGE electrophoresis, and then transferred it to PVDF  membrane. We then blotted and closed them at room temperature for one hour, and then we incubated them with p < 0.05 was used to indicate statistical significance.The experimental results are presented as mean ± SEM for each group, with at least three independent experiments. The differences between the treatment and normal groups were analyzed by a one-way analysis of variance using GraphPad Prism 8.0 . Ardisia, and finally determined the effect of Japanese Ardisia anti-AIH on the expression of key target proteins by Western blotting analysis. Japanese Ardisia tends to work through the IL-17 signaling pathway, the TNF signaling pathway, the AGE–RAGE signaling pathway in diabetic complications, and other targets such as AKT1, IL-6, and CASP3 to exert drug effects. The potential signaling pathways uncovered in this study lay the theoretical groundwork and point the way for future experimental validation.In summary, we first performed a network pharmacology and molecular docking approach to elucidate the anti-AIH effects and potential mechanisms of Japanese


Many clinical studies have reported a relatively high incidence of osteoporosis and fragility fractures in patients with Cushing syndrome (CS). However, few papers have investigated osteoporosis and CS in terms of pathogenesis, so this study explores the association between the 2 and predicts upstream micro-ribonucleic acids (miRNAs) through bioinformatics, which provides potential targets for simultaneous pharmacological interventions in both diseases and also provides a basis for pathological screening.We used Genecards, Online Mendelian Inheritance in Man and Therapeutic Target Database databases to screen the targets of osteoporosis and Cushing syndrome; import target genes to Database for Annotation, Visualization and Integrated Discovery for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis; the intersecting genes were uploaded to Search Tool for the Retrieval of Genes and Genomes database to construct protein–protein interaction network; Cytoscape software was used to screen core genes, and Molecular Complex Detection module was used to analyze cluster modules; finally, the NetworkAnalyst data platform was used to predict the miRNAs that interact with core genes.The core genes of osteoporosis and Cushing syndrome were insulin, tumor necrosis factor, signal transducer and activator of transcription 3 (STAT3), interleukin-6, insulin-like growth factor 1, etc. A total of 340 upstream miRNAs including hsa-let-7a-5p, hsa-mir-30a-5p and hsa-mir-125b-5p were predicted. The biological processes involved include regulating the transcription of ribonucleic acid polymerase II promoter and participating in the transduction of cytokine signaling pathways, which focus on the binding of nerve system ligand, JAK-STAT signaling pathway, Rap1 signaling pathway, PI3K-Akt signaling pathway, etc.Osteoporosis and Cushing syndrome are closely related in terms of targets and molecular mechanisms. In this study, bioinformatics methods were used to identify their targets and mechanisms, providing potential targets for drug simultaneous regulation of the 2 diseases, and providing a new direction for exploring the relationship between diseases. Cushing syndrome is a group of symptoms and signs caused by abnormally elevated cortisol from multiple causes, and can be divided into Cushing disease of pituitary origin  and Cushing disease of adrenal origin , which is an important cause of secondary osteoporosis. The prevalence of bone loss and osteoporosis in Cushing syndrome (CS) patients has been reported to be 60% to 80%, 30% to 65%, respectively.,4 The incidence of fragility fracture is 30% to 50%.Osteoporosis is a systemic skeletal disease characterized by a decrease in bone density and bone mass, and the associated factors are complex and diverse.Therefore, it is urgent to clarify the relationship between osteoporosis and Cushing syndrome and to reduce the risk of osteoporosis in CS patients. Integration of genetic data from osteoporosis and Cushing syndrome using bioinformatics to explore the association and provide targets for simultaneous pharmacological interventions in both diseases, as well as a theoretical basis for pathological screening.https://www.genecards.org/), Online Mendelian Inheritance in Man (http://www.omim.org), Therapeutic Target Database (http://db.idrblab.net/ttd/) databases to screen for disease-related targets. To obtain high accuracy, the top 300 genes with high correlation scores were selected from the Genecards database. The results were combined and de-duplicated and then screened through the Uniprot database to identify the clearly certified target genes among them as the final target genes for osteoporosis and Cushing syndrome, and finally mapped the target genes for osteoporosis and Cushing syndrome to obtain the intersecting genes.The keywords “Osteoporosis” and “Cushing syndrome” were used to search for Genecards (https://david.ncifcrf.gov/) database, respectively. And set P < .05, FDR < 0.05 for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The top 3 GO pathways and the top 5 KEGG pathways were screened by P value from smallest to largest, respectively.The target genes of osteoporosis and Cushing syndrome were imported into the Database for Annotation, Visualization and Integrated Discovery (https://string-db.org/cgi/input.pl) database can be used to present and evaluate protein interaction relationships. The intersecting genes of osteoporosis and Cushing syndrome were uploaded to STRING database to construct protein–protein interaction (PPI) network, download the tsv format of PPI network, import it into Cytoscape 3.8.0 software, (https://cytoscape.org/), and use network analyzer plug-in to perform node connectivity (degree), combined score (combined score) based on visual representation. Finally, the top 10 genes were selected as the core target genes for osteoporosis-Cushing syndrome, and the parameters were set as degree = 2, node score = 0.2, k-core = 2, and max. depth = 100 for cluster module analysis of the intersecting genes.Search Tool for the Retrieval of Genes and Genomes (STRING)  is a platform that allows online gene expression analysis for differential gene screening, functional enrichment analysis, and gene-miRNA network construction. In this study, the NetworkAnalyst 3.0 platform, miRTarBase database was used to predict miRNAs that may interact with core target genes.NetworkAnalyst 3.0  from highest to lowest: INS (degree: 38), tumor necrosis factor (TNF) (degree: 36), signal transducer and activator of transcription 3 [STAT3 degree: 34)], interleukin-6 (IL6) (degree: 33), insulin-like growth factor 1 [IGF1 (degree: 32)], ALB (degree: 31), VEGFA (degree: 31), CTNNB1 (degree: 30), IL1B (degree: 28), PPARG (degree: 26)  through the STAT3/PTTG signaling pathway, promoting the formation of tumor blood vessels and aggravating the condition of CS patients, while VEGF can help the proliferation and differentiation of osteoblasts, promote the recruitment and survival of osteoclasts, and promote bone formation. IGF1, as an osteogenic differentiation factor, can upregulate the expression of protein kinase and alkaline phosphatase mesenchymal stem cells, and participate in cartilage anabolism and repair. Animal experiments found that different concentrations of IGF1 played a positive role in regulating the expression of both cartilage layer and subchondral bone genes. In contrast, excessive INS promoted IGF1 overexpression, enhanced 17α-hydroxylase activity, and increased androgen synthesis and secretion in CS patients.Cushing syndrome is often associated with insulin (INS) resistance, and its complication rate of diabetes is as high as 43.3%.,31 Rap1 signaling pathway is mainly involved in the regulation of bone resorption, and its expression in mature osteoclasts can cause pathological bone loss. The PI3K-Akt signaling pathway, an important pathway regulating cell proliferation, differentiation and metabolism, promotes angiogenesis and proliferation of tumor cells in pituitary adenomas and inhibits apoptosis. It also affects bone metabolism by controlling the proliferation and differentiation of osteoblasts and osteoclasts, and is a key pathway affecting the coordination of osteoblast and osteoclast functions. Animal experiments–37 confirmed that activation of the PI3K/AKT signaling pathway reduces estrogen and testosterone levels, thereby regulating osteoblast differentiation and apoptosis of osteoclasts. The neurological receptor-ligand interaction pathway, a collection of neuroactive receptors located on the plasma membrane, maintains the stability of the neuroendocrine system and has been shown to be associated with the development of pituitary adenomas in studies using microarray data.,39The JAK-STAT signaling pathway is composed of the JAK family and STAT family, and many inflammatory cytokines such as IL-6 interact with their receptors to upregulate the differentiation of osteoblasts and osteoclasts through the JAK-STAT signaling pathway, affecting the production of bone trabeculae and regulating bone metabolism.In this study, we used bioinformatics to search for common target genes and pathways between osteoporosis and Cushing syndrome, and found that INS resistance and the resulting high glucose levels in Cushing syndrome can affect the proliferation and differentiation of osteoblasts and apoptosis, while excessive INS causes overexpression of IGF1, which not only affects cartilage synthesis but also aggravates hormonal disorders. STAT3 and VEGF, on the other hand, induce angiogenesis in pituitary adenomas and also play a positive role in bone growth and reconstruction. TNF, IL-6 and IL-17-mediated inflammatory responses can inhibit osteoprotegerin synthesis and promote osteoclast differentiation, in addition to having an effect on glucose and lipid metabolism. The neurological ligand recipient interaction pathway, JAK-STAT signaling pathway, Rap1 signaling pathway, and PI3K-Akt signaling pathway play direct or indirect roles in this. And the prediction of core genes and upstream miRNAs not only provides potential targets for simultaneous drug intervention in both diseases, but also provides a basis for pathological screening and genetic diagnosis. The results of these analyses not only provide theoretical support for subsequent experimental studies, but the analysis methods embodied also serve to save resources and improve efficiency. Since this study is only a database based analysis, and the reliability and accuracy of the data will continue to improve with the continuous development of bioinformatics and disease databases, studies from cellular and animal testing are still needed to make the conclusions more reliable.Conceptualization: Ding Wang, Jin-Song Li.Data curation: Chun-Xiao Dang, Ding Wang, Ying-Xin Hao.Formal analysis: Chun-Xiao Dang, Ding Wang.Funding acquisition: Peng-Fei Liu, Xiao Yu.Investigation: Ding Wang, Peng-Fei Liu.Methodology: Ding Wang, Xiao Yu, Ying-Xin Hao.Writing – original draft: Ding Wang, Chun-Xiao Dang, Ying-Xin Hao.Writing – review & editing: Peng-Fei Liu, Jin-Song Li.


The Xpaths algorithms are applied to predict developmental and reproductive toxicity (DART) and implemented into an https://github.com/Xpaths/dartpaths-app under Apache license 2.0, detailed overview with demo is available at https://www.vivaltes.com/dartpaths/.All code is available on GitHub Bioinformatics online. Caenorhabditis elegans (C.elegans-nematodes), Danio rerio (zebrafish) or Dictyostelium discoideum (D.discoideum-slime mold), as well as several in silico platforms.Regulatory compliance to address the human health risks of chemicals commonly still requires both rodents and non-rodents as test species. In addition to these species not always being reliable due to species-specific differences, they are not ethically sustainable in the current century. For this reason, a broad portfolio of new approach methods (NAMs) have been established over the last years, such as a wide diversity of cell- and organoid-based protocols, assays that use small organisms like D.discoideum , C.elegans (nematode), Drosophila melanogaster (fruitfly), D.rerio (zebrafish), Mus musculus (mouse) and Homo sapiens (human) form the foundation of the Xpaths model. In addition, the model can predict which assays in C.elegans, D.melanogaster or D.rerio are relevant for further validation of predictions of possible (adverse outcome) mechanisms. With Xpaths, we aimed to create a single data model for inter-species connection of test outcomes, with the overall goal to improve the reliability of compound effect predictions.The largest challenge remains how to integrate and combine the study data of all these different screening platforms into a single framework. Such a framework connects and enhances the predictivity of the scientific and regulatory framework for hazard and risk assessment. With Xpaths, we created a data model and algorithms for interspecies integration of test outcomes. The resulting cross-species profiles of compound mechanistic activity can support regulatory acceptance and approval of NAMs. To predict effects in higher organisms like humans, compound-affected evolutionary conserved molecular pathways are identified using multiple test methodologies. The goal is to test compound-induced effects in multiple (NAM and/or other) test methodologies, identify evolutionary conserved mechanistic pathways and combine this information to predict the effect of the same compound in humans and other mammals. Those pathways form a key to identify the most relevant and conserved toxicity endpoint effects. The ontology-linked approach of Xpaths allows translation of toxicity (phenotypic) endpoints of different studies in different species, into a mechanistical knowledge-based prediction output, using statistical pathway ranking. Data from a broad set of cell-based assays as well as six major model organisms: https://www.R-project.org/) and Python. Data are made interoperable using standard vocabularies  module takes as input a list of phenotype ontology identifiers observed in model organisms after exposure to a chemical . The algP-values in the phenotype enrichment module are computed from a hypergeometric distribution and are subsequentially adjusted by FDR-correction .The data model can be reused for other comparative pathways projects by providing all extraction, transformation and loading scripts and enrichment algorithms via a GitHub repository. At the same time the user-friendly interface makes the tool widely applicable. Future work might be able to make use of the Xpaths algorithms as a general data model. Currently, the Xpaths algorithms have been implemented in the DARTpaths platform.in silico platform to predict developmental and reproductive toxicity (DART). The DARTpaths platform is created as an R Shiny app. All code is available on GitHub.DARTpaths is designed as an D.discoideum, C.elegans, D.melanogaster, D.rerio and M.musculus) is integrated to predict which pathways are potentially affected by the chemical. An integrated P-value indicates the strength of evidence for that pathway. For example, when searching with DiEthylStilbestrol (DES), the top pathways predicted include: ‘Metbolism of steroids’; this is supported by two in vitro hits CYP19A1 and TSPO- these targets are both part of the pathway. In addition, the specific phenotypes caused by genetic variants in this pathway resemble the phenotypes induced by DES in zebrafish, nematodes (3 out of 8 overlap) and mammals (10 out of 20 overlap). DES, has indeed been shown to interfere with this pathway , phenotypes and regulatory information about the chemical.Users can start by searching for a single chemical or a complex substance (i.e. UVCB), either by name or by identifier . Endpoint data from different test methodologies  and D.rerio (zebrafish). The phenotype ‘neurite connectivity defective’ is observed in genetic variants of AHR in nematodes. One might expect dioxin-like chemicals to induce similar phenotypes. In this way, one can further validate pathway predictions.Users can also start by selecting a pathway. Pathway exploration shows the type of orthology relations  for each organism for all genes in this human pathway. For example, it is known that dioxin-like chemicals bind to the aryl hydrocarbon receptor (AHR). By starting from the pathway ‘Aryl Hydrocarbon Receptor Signaling’, a user can see which non-mammalian model organisms contain this pathway and might be used to study the toxicity of dioxin-like compounds. The AHR pathway is highly conserved in nematodes and thus, toxicity of these type of compounds can be studied in nematodes. This is particularly useful for testing mixtures as reported by EPA  using natural language processing with SpaCy (spacy.io; Currently, the DARTpaths database contains information on DART-related phenotypic endpoints for model organisms  and in vbtac767_Supplementary_DataClick here for additional data file.


Bombus kashmirensis and B. waltoni—were studied through transcriptomics methods. For each species, enrichment analysis of the differentially expressed genes and gene set enrichment analysis were carried out between samples collected at different altitudes . The results indicate that these bumblebees tend to up-regulate energy metabolism-related genes when facing extremely high-altitude environments. Of the enriched pathways up-regulated in higher altitudes, the pentose and glucuronate interconversions pathway presented the most severe up-regulation in multiple comparisons of different altitudes for B. kashmirensis, as well as the AMPK signaling pathway, which was found to be up-regulated in both species. Notably, limited by the extreme high altitudes in this study, oxidative phosphorylation was found to be down-regulated with increasing altitude, which is uncommon in studies on bumblebee adaptation to high altitudes.Determining the adaptive mechanisms by which bumblebees adapt to high altitudes can help us to better understand their distribution, providing a basis for the future protection and utilization of bumblebee resources. For this study, the adaptive mechanisms of two dominant bumblebee species in the northeastern Qinghai-Tibet Plateau—Bombus kashmirensis and B. waltoni—were studied through transcriptomics methods. For each species, enrichment analysis of the differentially expressed genes and gene set enrichment analysis were carried out between samples collected at different altitudes . The results indicate that these bumblebees tend to up-regulate energy metabolism-related genes when facing extremely high-altitude environments. Of the enriched pathways up-regulated in higher altitudes, the pentose and glucuronate interconversions pathway presented the most severe up-regulation in multiple comparisons of different altitudes for B. kashmirensis, as well as the AMPK signaling pathway, which was found to be up-regulated in both species. Notably, limited by the extreme hypoxic conditions in this study, oxidative phosphorylation was found to be down-regulated with increasing altitude, which is uncommon in studies on bumblebee adaptation to high altitudes.Determining the adaptive mechanisms by which bumblebees adapt to high altitudes can help us to better understand their distribution, providing a basis for the future protection and utilization of bumblebee resources. For this study, the adaptive mechanisms of two dominant bumblebee species in the northeastern Qinghai-Tibet Plateau— Bombus spp.) play a critical role in maintaining the balance of various ecosystems [As one of the most important wild pollinators in both cultivated and natural ecosystems in the northern temperate world, bumblebees  was used to extract mRNA using Oligo (dT) magnetic beads . The extracted mRNA was used for synthesis of cDNA by reverse transcription and random hexamers, after treatment with fragmentation buffer . Then, the ends of the cDNA were repaired using End Repair Mix . During this process, a single A base and adapters were added to each end of the cDNA. Then, cDNA sequencing was carried out on an Illumina NovaSeq 6000 platform after PCR amplification. Raw data was gained from the Illumina platform by CASAVA, and has been deposited into the NCBI SRA database . Clean data were obtained from raw data by removing the adapter sequence and low-quality reads. Transcriptome assembly was accomplished by Trinity v2.8.5 (k-mer = 31) [www.majorbio.com (accessed on 10 March 2022)).Sampling sites were chosen in the northeastern QTP, as this region is next to the global biodiversity center of bumblebees and a large number of species are distributed. On the other hand, the study area is close to the plateau edge and rich in high mountains, with high average altitude and severe altitude changes over a small range, making it a good choice for the study of high-altitude adaptation. Based on a previous investigation in the QTP, two indicator species,  waltoni , were cht 2100 m , and itst 2100 m . In thishttps://cloud.majorbio.com/page/tools/ (accessed on 10 March 2022)). For each species, the transcriptomic differences of 4500 m vs. 4000 m, 5000 m vs. 4500 m, and 5000 m vs. 4000 m were explored through GSEA. In each comparison, the samples from the lower altitude were set as the control group and enriched GO terms were identified at the higher elevation. The enriched GO terms with the top 20 largest absolute normalized enrichment scores (NES) and p-values (adjusted by the Benjamini–Hochberg approach) lower than 0.05 were focused in the following analysis.According to the annotation results, genes involved in GO terms were used to perform the gene set enrichment analysis (GSEA) using the Majorbio Cloud Platform  less than 0.05 were considered as DEGs. The KEGG enrichment of differentially up- or down-regulated genes was assessed using a script developed by Majorbio (https://www.majorbiogroup.com (accessed on 10 March 2022)). The enriched KEGG pathways with p-values (corrected by the Benjamini–Hochberg approach) lower than 0.05 were considered as key pathways related to altitude adaptation.For each species, the KEGG enrichment of differentially expressed genes (DEGs) for 4500 m vs. 4000 m, 5000 m vs. 4500 m, and 5000 m vs. 4000 m was assessed, wherein we identified up- and down-regulated genes at the higher elevation. Differentially expressed genes (DEGs) in each analysis were screened using DESeq 2 v1.24.0 . The genB. kashmirensis and B. waltoni were qualified. Among these RNA, one of them presented an OD260/280 value of 1.98, and the others had OD260/280 values greater than two. The Q30 values of clean reads of all samples were above 90%, and the error rates were about 0.03%. The average GC content was 42.71% for B. kashmirensis samples and 46.32% for B. waltoni. The numbers of clean bases of B. kashmirensis and B. waltoni were 6.54 G and 6.74 G, respectively. The GC contents of unigenes for these two species were 40.55% and 41.67%, respectively. The mapping ratios of each B. kashmirensis sample computed by hisat2 v2.1.0 ranged from 69.74% to 83.32%, while that for B. waltoni ranged from 74.02% to 82.28%  were mainly enriched by down-regulated genes, except for protein lipidation and steroid dehydrogenase activity terms, which were mainly enriched by up-regulated genes. The protein lipidation term has a positive effect on effective protein processing. In samples from 5000 m, 120 and 50 enriched GO terms with adjusted p-values lower than 0.05 were discovered compared to samples from 4500 m and 4000 m, respectively. In the comparison of 5000 m vs. 4500 m, all terms with the top 20 largest absolute NES were mainly enriched by up-regulated genes while for 5000 m vs. 4000 m, only six of the terms with the top 20 largest absolute NES were mainly enriched by up-regulated genes  signaling pathways were enriched by up-regulated DEGs. These pathways play roles in carbohydrate metabolism, neuroprotection in hypoxic tissues [B. kashmirensis from 4000 m, in the transcriptomes of bumblebees from 5000 m, the amino acids metabolism, carbohydrate metabolism, and cellular energy homeostasis processes were all promoted, while aerobic respiration was weakened  differed. Compared to cospecies at 4000 m, B. kashmirensis at 5000 m showed up-regulated pentose and glucuronate interconversions pathway, arginine and proline metabolism pathway, and AMPK signaling pathway (B. waltoni at 5000 m showed a down-regulated pentose and glucuronate interconversions pathway and no up-regulated energy metabolism (B. kashmirensis enhanced its DNA repair function (B. waltoni strengthened the apoptosis process (B. kashmirensis, the gap junction and AMPK signaling pathways were up-regulated at the high altitude of 5000 m (B. waltoni (It can also be inferred that the mechanisms of extremely high-altitude adaptation for the two bumblebee species (i.e.,  pathway  while B.tabolism . This mafunction  while B. process . Furtherf 5000 m  while th waltoni . These rB. kashmirensis, while the AMPK signaling pathway was up-regulated in both species. However, due to the extreme hypoxia in this study, oxidative phosphorylation was detected to be down-regulated as the altitude kept increasing, which is uncommon in studies on bumblebee adaptation to high altitudes.We showed, according to the results of our study, that the considered bumblebees tend to up-regulate energy metabolism-related genes when adapting to extremely high-altitude environments. Of the enriched pathways up-regulated in higher altitudes, the pentose and glucuronate interconversions pathway presented the most severe up-regulation in multiple comparisons at different altitudes for


Cassia fistula is popular for its anti-inflammatory and anticarcinogenic properties in conventional medications. Nevertheless, its molecular mechanisms are still unclear. The current study evaluated the potential of C. fistula for the treatment of EOC using network pharmacology approach integrated with molecular docking. Eight active constituents of C. fistula were obtained from two independent databases and the literature, and their targets were retrieved from the SwissTargetPrediction. In total, 1077 EOC associated genes were retrieved from DisGeNET and GeneCardsSuite databases, and 800 potential targets of eight active constituents of C. fistula were mapped to the 1077 EOC targets and intersected targets from two databases. Ultimately, 98 potential targets were found from C. fistula for EOC. Finally, the protein–protein interaction network (PPI) topological interpretation revealed AKT1, CTNNB1, ESR1, and CASP3 as key targets. This is the first time four genes have been found against EOC from C. fistula. The major enriched pathways of these candidate genes were established by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) investigations. To confirm the network pharmacology findings, the molecular docking approach demonstrated that active molecules have higher affinity for binding to putative targets for EOC suppression. More pharmacological and clinical research is required for the development of a drug to treat EOC.Epithelial ovarian cancer (EOC) is one of the deadliest reproductive tract malignancies that form on the external tissue covering of an ovary.  Ovarian cancer (OC) is the world’s seventh highest prevalent lethal gynecological malignancy and accounted for 2.5% of new cancers in women. In 2019, the number of new cases was predicted to be 222,240, while the death toll was estimated to be 14,170 . EOCs arThe use of plants and their components to control different diseases in humans has an age-old history. Several therapeutic plants have been demonstrated to be effective in the administration of quality of life through antioxidant, anti-inflammation, and antidiabetic biological effects ,10,11. TC. fistula belongs to the subfamily Caesalpinioideae of the legume family, Fabaceae popular as Amaltas. C. fistula is indigenous to the Indian subcontinent, Mauritius, Thailand, China, Brazil, Sri Lanka, and southern Pakistan. It plays a central role in disease prevention because of its valuable constituents such as flavonoids, anthraquinone, chromones, coumarins, alkaloids, phytosterols, long-chain hydrocarbons, phenolic, and triterpenes. Former research confirmed that C. fistula showed roles in antifertility [C. fistula also played a wide range of activities including hypoglycemic activities [C. fistula is prescribed against epidermis, hepatic, and lung problems as well as hematemesis, chronic itchy skin, hypopigmentation, and diabetes mellitus [C. fistula-target EOC network is constructed, from analysis of compound to the interaction of potential targets, integrated with pathway analysis to investigate the molecular mechanism of C. fistula in order to treat EOC.ertility , antimicertility , hepatopertility , improveertility ,20. C. ftivities ,22, antitivities , larvicitivities , anti-intivities , antioxitivities . C. fistmellitus . The exaC. fistula were acquired from the literature [http://www.knapsackfamily.com/, accessed on 8 August 2022) and Traditional Chinese Medicine System Pharmacology (TCMSP) , which was performed by using the plant name Cassia fistula as a search term in kNAPSAcK database [https://pubchem.ncbi.nlm.nih.gov/, accessed on 10 August 2022) to construct phytochemical library. Meanwhile, their SMILES were also collected in order to investigate the pharmacodynamics attributes. Active constituents of C. fistula were obtained from admetSAR  and TCMSP database, i.e., OB and DL greater than 30% and 0.18, respectively [Phyto-constituents of terature ,29, KNApterature   was used to find out prospective genes targeting active compounds via providing the SMILES, while Homo sapiens were selected as the species. SwissTargetPrediction is extensively used program for reverse screening of chemical compounds and predicting the bioactivity of the chemicals. Protein IDs were aligned with UniProtKB  [SwissTargetPrediction tool (st 2022) , performhttps://www.disgenet.org/, accessed on 20 August 2022) and GeneCards  using keyword “epithelial ovarian cancer” [C. fistula to the EOC-related targets [C. fistula to treat EOC. These mapped genes were chosen to advance the investigations.EOC-related Human targets were retrieved from DisGeNET  to construct a PPI network [To evaluate the interaction between the prospective genes of  network . The mul network . A plug- network . “Networ network .https://david.ncifcrf.gov/home.jsp, accessed on 26 August 2022). DAVID is a database of functional annotations that can be accessed online that helps researchers comprehends the biological meanings of a huge number of genes. The gene enrichment analysis categorized the gene functions that incorporate Biological Process (BP), Cellular Component (CC) and Molecular Function (MF). Moreover, enriched pathways were filtered out through KEGG analysis [Homo sapiens. The probability value was set to p < 0.05 to select enriched pathways. To illustrate the GO annotation and KEGG pathways, bubble plots were created in R via ggplot2 package.The gene and pathway enrichment investigation was performed through DAVID  was used to retrieve receptor protein data, and their PDB files were downloaded [Molecular docking makes it easier to figure out how ligands interact with their corresponding proteins. Finally, the results of this network pharmacological study were verified through molecular docking approach. For that, the 3D structures of active components were retrieved from the PubChem search in the .sdf format and optimized . The Reswnloaded . The inpAuto-dock Vina is used to carry out the protein–ligand docking for the prediction of predominant binding mode of the ligand with a protein . The actC. fistula such as leaves, fruit, bark, stem, as well as seeds , Ellagic Acid (32), Quercetin (30), Kaempferol (29), Gibberellin A3 (28), Licoisoflavone (26), β-Sitosterol (21), and Stigmasterol (19). They interacted with multiple targets .C. fistula which may be the potential targeting genes to treat EOC were copied to STRING v11.5to build a PPI network with a score of 0.4 confidence interaction. That was performed to predict the interactions of potential proteins with Homo sapiens proteins and their physiological functions. In that network, the nodes are representing the targets, and the lines connecting the nodes are edges that represent the intermolecular interactions between multiple targets during a disease development , 51 Cellular Components (CCs) and 85 Molecular Functions (MFs) as conformed screening criteria, with count ≥ 2 and p ≤ 0.05. Moreover, 133 enriched pathways were identified on the basis of criteria p < 0.05. A pathway–target network was constructed by using Cytoscape  structures of these target proteins (AKT1 (PDB id: 3QKK), CTNNB1 (PDB id: 1jdh), ESR1 (PDB id: 1pcg), CASP3 (PDB id: 3kjf) were retrieved through the PDB. These structures were refined by the UCSF Chimera tool with 1000 decent steps of energy minimization . In orde targets . All com targets .The etiology and pathogenesis of EOC is very complex and not yet fully understood. It is characterized by sneaking symptoms. That is why individuals are examined at a later stage. Cyto-reduction surgeries (CRS) are used to treat this, followed by platinum-based chemotherapy . These tC. fistula is a versatile plant that has shown the antioxidant, anti-inflammatory, immunological, hepatoprotective, antipyretic, analgesic, and antitumor properties [C. fistula.Natural phytochemicals, especially plant-derived compounds, are widely employed as alternative therapeutics, such as taxol for cancers . The reaoperties . More thC. fistula’s bioactive compounds. That was a unique therapeutic idea for future research of C. fistula’s processes for EOC treatment. Anthraquinone, polyphenols, hormones, phytosterols, and flavonoids were the most abundant bioactive chemicals discovered in C. fistula. These played a critical role in the development of EOC. This is a strong indicator that a number of targets may work together to provide a synergistic impact.This study has provided a baseline for the screening of By PPI network topological analysis, the four key targets AKT1, CTNNB1, ESR1, and CASP3 were evaluated for anti-EOC activity. This is a strong indicator that a number of targets may work together to provide a synergistic impact. AKT1 promotes OC cell proliferation, immigration, epithelial transformation to mesenchyme (EMT), gluconeogenesis, and resistance to therapeutics and serves as a biomarker for OC therapy response ,49,50,51C. fistula were primarily involved in different molecular processes such as protein serine activity, protein serine/threonine kinase activity, transmembrane receptor protein tyrosine kinase activity, and transmembrane receptor protein kinase activity. The pathway enrichment analysis evaluate that genes were focused to EOC-associated signaling pathways: the ‘PI3K-Akt signaling pathway, proteoglycans in cancer, the TNF signaling pathway, and the IL-17 signaling pathway. The PI3K-Akt signaling pathway might boost tumor progression, amplification, and uncontrolled mitosis OC cells [Gene enrichment analysis reported that anti-EOC target genes of OC cells ,57,59. POC cells . TNF sigOC cells ,62. The OC cells .C. fistula. It exemplifies the expression of multiple targets, components, and pathways. In molecular docking, more negative the binding energy, the greater the expected affinity for binding of the ligand to the target [C. fistula has anti-EOC properties, inhibiting EOC main targeting genes. Network pharmacology integrated to molecular docking approach appeared to be effective for the identification of biologically active phytochemicals, associated potential genes, and linked signaling pathways to treat EOC. It provided a systematic framework for subsequent investigation of phytochemicals against a wide range of disorders.Through the network analysis, the four main targets AKT1, CTNNB1, ESR1, and CASP3 were evaluated for their binding energies to eight active components of e target . The β-SC. fistula to treat EOC. Furthermore, our data suggest that the AKT1, CTNNB1, ESR1, and CASP3 targets are intriguingly beneficial to slow down the prevalence of EOC, potentially resulting in therapeutic benefits in EOC. This is the first time four genes have been reported against the EOC from C. fistula. However, more pharmacological and clinical studies are required to confirm our findings. This method lays the framework for future research into C. fistula for EOC-protective mechanisms and the use of network pharmacology in drug development.This research set the foundation to establish the efficacy of multicomponent, multitarget chemical formulae and identification of genes that target to treat EOC. Network pharmacology and molecular docking approaches were incorporated in order to reveal the underlying mechanisms of


Orthopoxvirus of the family Poxviridae. Unlike smallpox with no animal reservoir identified and patients suffering from milder symptoms with less mortality, several animals were confirmed to serve as natural hosts of MPV. The reemergence of a recently reported monkeypox epidemic outbreak in nonendemic countries has raised concerns about a global outburst. Since the underlying mechanism of animal-to-human transmission remains largely unknown, comprehensive analyses to discover principal differences in gene signatures during disease progression have become ever more critical. In this study, two MPV-infected in vitro models, including human immortal epithelial cancer (HeLa) cells and rhesus monkey (Macaca mulatta) kidney epithelial (MK2) cells, were chosen as the two subjects to identify alterations in gene expression profiles, together with co-regulated genes and pathways that are affected during monkeypox disease progression. Using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and MetaCore analyses, we discovered that elevated expression of genes associated with interleukins (ILs), G protein-coupled receptors (GPCRs), heat shock proteins (HSPs), Toll-like receptors (TLRs), and metabolic-related pathways play major roles in disease progression of both monkeypox-infected monkey MK2 and human HeLa cell lines. Interestingly, our analytical results also revealed that a cluster of differentiation 40 (CD40), plasmin, and histamine served as major regulators in the monkeypox-infected monkey MK2 cell line model, while interferons (IFNs), macrophages, and neutrophil-related signaling pathways dominated the monkeypox-infected human HeLa cell line model. Among immune pathways of interest, apart from traditional monkeypox-regulated signaling pathways such as nuclear factor- (NF-κB), mitogen-activated protein kinases (MAPKs), and tumor necrosis factors (TNFs), we also identified highly significantly expressed genes in both monkey and human models that played pivotal roles during the progression of monkeypox infection, including CXCL1, TNFAIP3, BIRC3, IL6, CCL2, ZC3H12A, IL11, CSF2, LIF, PTX3, IER3, EGR1, ADORA2A, and DUOX1, together with several epigenetic regulators, such as histone cluster family gene members, HIST1H3D, HIST1H2BJ, etc. These findings might contribute to specific underlying mechanisms related to the pathophysiology and provide suggestions regarding modes of transmission, post-infectious sequelae, and vaccine development for monkeypox in the future.Monkeypox virus (MPV) is a smallpox-like virus belonging to the genus  Orthopoxvirus in the family Poxviridae [Orthopoxvirus have been recorded until recently, after a significant number of confirmed monkeypox cases were reported worldwide [Monkeypox virus (MPV/MPXV) is commonly known as one of the rare systemic infections caused by one specie of the genus xviridae , 2. Othexviridae –5. Afterorldwide . The firorldwide –9. As oforldwide –10. Furtorldwide , 12. Traorldwide , 14.To date, definite diagnoses of monkeypox are largely based on either a polymerase chain reaction (PCR) of skin lesion specimens or immunohistochemical (IHC) staining of biopsies taken from those infected, as misdiagnoses of other blister-like diseases such as smallpox and chickenpox may occur in cases where only a visual skin examination and/or dermoscopy are solely employed , 16. Altin vitro models, including human immortal epithelial cancer (HeLa) cells and rhesus monkey (Macaca mulatta) kidney epithelial (MK2) cells, together with co-regulated genes and pathways that are affected during disease progression. The Gene Expression Omnibus (GEO) database and bioinformatics approaches were employed to perform analyses of available samples related to these two models  cells and monkey Macaca mulatta kidney epithelial (MK2) cells to characterize the effects of physical monkeypox viral infection. Relevant microarray gene expression datasets from the GEO (http://www.ncbi.nlm.nih.gov/geo)—an international public functional genomics data repository affiliated with the National Center for Biotechnology Information —were retrieved for subsequent analyses. In particular, MPV-induced alterations in transcriptomic profiles of 7-hour monkeypox-infected Macaca mulatta kidney epithelial (MK2) cells were obtained from the GSE21001 dataset [In this study, we investigated an  dataset , whereas dataset . The folhttp://www.bioinformatics.com.cn/srplot. For subsequent discoveries of enriched functionally related gene groups, the Database for Annotation, Visualization, and Integrated Discovery (DAVID), which is maintained by the Laboratory of Human Retrovirology and Immunoinformatic (LHRI) [p value of <0.05 was set as the significance level. After biological networks and related pathways were constructed, a cut-off value of 0.05 was applied to select significantly enriched pathways or groups of annotated genes.Before being mapped onto Ensembl features using packages attached to the biomaRt tool vers. 2.26.1), the CLC Genomics Workbench vers. 10.1  was utilized to process and standardize the raw data –23. Sign.1, the Cc (LHRI) –29, was c (LHRI) –32, the c (LHRI) –35, whilp value of <0.05.MetaCore  was designed to identify biological processes related to gene microarray data. The top 5% of upregulated genes with substantial differences in transcriptome levels were processed as input to the MetaCore program to compare average levels of gene expressions in the two models. Signal transduction pathways were examined. A statistically significant difference was indicated by a https://string-db.org/) serves as a search engine and a protein information resource that provides a considerable number of proteins and known interaction activities upon which differentially expressed genes (DEGs) were examined [k-means clustering algorithm.The STRING database (vers. 11.0)  cell retrieved from the GSE21001 dataset were matched with a mock treatment group for a comparative analysis of DEGs. GO analytical results associated with monkeypox infection are depicted in For the monkey cell line model, transcriptomic data of the 7-hour monkeypox-infected For the 6-hour monkeypox-infected human cell line model, transcriptomic data of monkeypox-infected human HeLa cells were retrieved from the GSE36854 dataset. Pathways assigned to cluster 1 (c1) were those most highly correlated with monkeypox infection, whereas cluster 2 (c2) exerted an opposite trend. The GO analysis suggested that pathways within c1 were related to growth factor activities, leukocyte activation, responses to organic cyclic compounds, inflammatory responses, regulation of the extracellular signal-regulated kinase 1 (ERK1) and the extracellular signal-regulated kinase 2 (ERK2) cascade, chemokine activities, and regulation of nitric oxide biosynthetic processes. Pathways in c2 were related to nucleosome assembly, protein heterodimerization activities, telomere maintenance, extracellular regions, the actin cytoskeleton, responses to protozoans, and coagulation.Macaca mulatta kidney epithelial (MK2) cell model and the human immortal epithelial cancer (HeLa) counterpart were highly expressed compared to those within the mock control  signaling,” and “inflammatory mechanisms of pancreatic cancerogenesis” (Venn diagrams were employed to filter upregulated genes in common between the two models mentioned above. The top 5% of messenger (m)RNAs within the monkeypox-infected  control . In totagenesis” . Meanwhigenesis” , Supplemgenesis” .Macaca mulatta kidney epithelial (MK2) cell model, the top 5% of upregulated genes obtained compared to the mock treatment group were input into the MetaCore platform for a comprehensive map analysis. The “immune response_IL-1 signaling pathway,” “immune response_IL-33 signaling pathway,” “signal transduction_nonapoptotic FasR (CD95) signaling,” “immune response_histamine H1 receptor signaling in immune response,” “IL-1 signaling in melanoma,” “inflammatory mechanisms of pancreatic cancerogenesis,” “immune response_HSP60 and HSP70/TLR signaling pathway,” “G protein-coupled receptors signaling in lung cancer,” “TNF-alpha-induced inflammatory signaling in normal and asthmatic airway epithelium,” and “resistance of pancreatic cancer cells to death receptor signaling” were among the most significant maps detected  cells revealed that pathways associated with phospholipid biosynthesis and amino acid synthesis included the “phosphatidylethanolamine pathway,” “N-acyl-sphingosine phosphate pathway,” “lyso-phosphatidylserine pathway,” “1-alkyl-glycerol_3-phosphoethanolamine pathway,” “1-oleoyl-glycerol_3-phosphate pathway,” “2-oleoyl-glycerol_3-phosphate pathway,” and “aminoacid metabolism_asparagine, and aspartic acid metabolism and transport,” which are metabolic signaling pathways dominated by these genes within this model  cell model, the top 5% of upregulated genes compared to the mock treatment groups were input into the MetaCore platform for a comprehensive map analysis. The “immune response_IL-1 signaling pathway,” “inflammatory mechanisms of pancreatic cancerogenesis,” “G protein-coupled receptors signaling in lung cancer,” “immune response_plasmin signaling,” “immune response_CD40 signaling in dendritic cells, monocytes, and macrophages,” “interleukins-induced inflammatory response in asthmatic airway fibroblasts,” “TNF-alpha-induced inflammatory signaling in normal and asthmatic airway epithelium,” “NF-Macaca mulatta kidney epithelial (MK2) cell model and the human immortal epithelial cancer (HeLa) cell model, and pathways were ranked by p values  in common, which were highly expressed in both models . UpregulIST1H2BB . These 2IST1H2BB .Macaca mulatta kidney epithelial (MK2) cell model, these genes mostly functioned in apical plasma membranes, neuronal cell bodies, the cytosol, nucleoplasm cytoplasm, extracellular exosomes, an integral component of presynaptic membranes, postsynaptic membranes, cytoplasmic exosomes, and the perikaryon , tumor necrosis factors (TNFs), and interferons (IFNs), were reported to be involved in disease progression. The ILs superfamily  and TNF signaling-mediated immune responses are important for antiviral activity , 56; howκB, MAPKs, and TNF-R2 signaling (Our research findings were consistent with previous studies on monkeypox infection as mentioned above; the GO and pathway analyses revealed similar enriched pathways for both monkeypox-infected monkey and human models, including IL-1, IL-33, IL-17, IL-18, NF-ignaling . Howeverignaling , A2 thatin vitro models (γ in cynomolgus macaques after being infected with aerosolized MPV [α during acute lung injury, was recently found to serve as a reliable prognostic indicator in predicting short-term mortality from SARS-CoV-2 [Regarding 24 common genes that were highly expressed in both o models , when coized MPV . In myelized MPV . Both ZCized MPV . Infectiized MPV –69. PTX3RS-CoV-2 . ApoptosRS-CoV-2 . Two memRS-CoV-2 . PreviouRS-CoV-2 , 74. MosRS-CoV-2 . For exaRS-CoV-2 . HoweverRS-CoV-2  revealedRS-CoV-2 , our stuIn the current study, we focused on investigating genetic signatures and their related pathways in two different monkeypox-infected models. Our research findings revealed the critical roles of multiple genes and their regulatory pathways in both monkeypox-infected models, which not only directly in line with previous literature but also provided novel functions as well as highly expressed genes related to MPV infection that had been less well revealed in the past. In the context of widespread epidemics of viral infectious diseases that are prevalent today, this work may contribute to bridging the traditional gap between bench research and clinical applications. However, with attempts to validate and examine the potentials of these genes as novel antiviral therapies, further expanding research on disease basics may provide more-concrete perspectives.


Jiawei-Huang Lian-Gan Jiang decoction (JWHLGJD) was developed to treat and prevent the patients with colorectal adenomas (CRA) in China. This study is aimed to discover JWHLGJD's active compounds and demonstrate mechanisms of JWHLGJD against CRA through network pharmacology and molecular docking techniques.  All the components of JWHLGJD were retrieved from the pharmacology database of Traditional Chinese Medicine Systems Pharmacology (TCMSP). The GeneCards database, the Online Mendelian Inheritance in Man database (OMIM), the DrugBank database, and PharmGKB were used to obtain the genes matching the targets. Cytoscape created the compound-target network. The network of target protein-protein interactions (PPI) was constructed using the STRING database. Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways involved in the targets were analyzed by using the DAVID database. Cytoscape created the component-target-pathway (C-T-P) network. AutoDock Vina software was used to verify the molecular docking of JWHLGJD components and key targets. Core genes linked with survival and tumor microenvironment were analyzed through the Kaplan–Meier plotter and TIMER 2.0 databases, respectively.  Compound-target network mainly contained 38 compounds and 130 targets of the JWHLGJD associated with CRA. TP53, MAPK1, JUN, HSP90AA1, and AKT1 were identified as core targets by the PPI network. KEGG pathway shows that the pathways in cancer, lipids, and atherosclerosis, PI3K-Akt signaling pathway and MAPK signaling pathway, are the most relevant pathways to CRA. The C-T-P network suggests that the active component in JWHLGJD is capable of regulating target genes of these related pathways. The results of molecular docking showed that berberine and stigmasterol were the top two compounds of JWHLGJD, which had high affinity with TP53 and MAPK1, respectively. And, MAPK1 exerted a more significant effect on the prognosis of adenocarcinoma, for it was highly associated with various immune cells.  Findings in this study provided light on JWHLGJD's active components, prospective targets, and molecular mechanism. It also gave a potential way to uncovering the scientific underpinning and therapeutic mechanism of traditional Chinese medicine (TCM) formulas. Colorectal cancer (CRC) is the world's third most common cancer and the second major cause of death from cancer . AdenomaComplementary and alternative medicine (CAM) is important in the treatment of complex and serious diseases . TraditiIn silico techniques, such as virtual screening and network analysis, have become increasingly popular in efforts to understand the pharmacological foundation of traditional medicinal plant actions . In parthttps://tcmspw.com/tcmsp.php) [https://www.UniProt.org/) [The Traditional Chinese Medicine Systems Pharmacology database   was usedot.org/) , with thhttps://www.genecards.org/) [https://www.omim.org/) [https://www.drugbank.ca/) [https://www.pharmgkb.org) [The GeneCards database (ds.org/) , Online im.org/) , the Druank.ca/) , and Phagkb.org)  were useThe target prediction findings of the JWHLGJD's active ingredients are compared to the search results of CRA-related targets, and the overlapping target is chosen as the JWHLGJD's core target for CRA therapy. The active ingredient target of the JWHLGJD and CRA target was mapped using “Venn package” in R software. The Venn diagram was drawn. Cytoscape (version 3.7.2)  was usedhttps://string-db.org/) [The potential target genes of JWHLGJD and CRA were compared in this work to determine the common target genes for JWHLGJD to treat CRA. To create the protein-protein interaction (PPI) network, these common putative target genes were entered into the Search Tool for the retrieval of interacting genes (STRING) 11.0 database (db.org/) . The scrdb.org/) . The topdb.org/) .https://david.ncifcrf.gov/) [Homo Sapiens.” The P value for the screening criterion was set at 0.05. The results were visualized using the “ggplot2 package” in R software to obtain a bubble map of the results of the GO and KEGG enrichment analyses. Biological process (BP), cellular component (CC), and molecular function (MF) are all included in the GO functional analysis.The common gene target of JWHLGJD and CRA acquired by the aforesaid screening was imported into the DAVID6.8 database (rf.gov/) . The genIn order to analyze the association among JWHLGJD, the candidate targets and CRA-related pathways, the component-target-pathway (C-T-P) network, was constructed and visualized via Cytoscape . The inthttps://pubchem.ncbi.nlm.nih.gov/) and saved in “SDF” format. Chem 3D was used to convert “SDF” format into mol2 structures, which were then used to create small molecule ligands. The receptor protein coded by the selected gene was searched in the UniProt database. We downloaded the 3D structure of the protein in RCSB PDB database (https://www.rcsb.org/) [x = −27.253, center y = −21.535, center z = 19.46, size x = 60, size y = 126, size z = 74; TP53 (PDB ID6WQX), target center x = 11.896, center y = −0.498, center z = −16.077, size x = 74, size y = 46, size z = 94; MAPK1 (PDB ID7NR9), target center x = −0.724, center y = −3.547, center z = 37.875, size x = 42, size y = 38, size z = 46; JUN (PDB ID1A02), target center x = 28.223, center y = 28.762, center z = 60.016, size x = 56, size y = 38, size z = 68; and HSP90AA1 (PDB ID7LT0), target center x = −32.969, center y = −14.726, center z = −20.5, size x = 40, size y = 40, size z = 40. The PDBQT format is used to save both ligands and protein receptors. Molecular docking was executed out using the software AutoDock Vina 1.1.2 [The 2D structures of the top 8 compounds in terms of degrees of the active components of JWHLGJD were obtained from the PubChem database (sb.org/)  and savesb.org/)  to perfosb.org/) , with thna 1.1.2 . The dochttps://cistrome.shinyapps.io/timer/) [https://cistrome.shinyapps.io/timer/) provides immune infiltrates' abundances estimated by multiple immune deconvolution methods, to explore tumor immunological, clinical, and genomic features comprehensively. We investigated the correlation between the expression of core targets and tumor-infiltrating immune cells  in adenocarcinoma (COAD).Use the online tool Tumor Immune Estimation Resource (TIMER) (/timer/) , which ihttps://kmplot.com/analysis/) [The Kaplan–Meier plotter (KM-Plotter)  , a tool JWHLGJD obtained a total of 67 chemical components after searching the TCMSP database, with 5 compounds from Gan Jiang, 2 compounds from Danggui, 8 compounds from Wumei, 37 compounds from Huangbo, 14 compounds from Huang Lian, and 1 compound from Wubeizi , molecular function (MF), and cellular component (CC). The top 10 BP, MF, and CC enrichment findings are shown in The KEGG pathway enrichment analysis yielded a total of 166 findings, and the top 30 pathways were identified as core pathways, as seen in A “C-T-P” network was constructed based on the 30 most relevant signaling pathways obtained in To further analyze and verify the target-compound interactions, the top five core targets of TP53, MAPK1, JUN, HSP90AA1, and AKT1, which had higher degrees, were selected for molecular docking with the 8 major active compounds of JWHLGJD. The binding energy between drug component ligands and target receptors is an important indicator to evaluate the binding capacity. It is generally considered that the docking affinity is stronger when the binding energy is less than −5.0 kcal/mol . In thisTP53 with berberine and MAPK1 with stigmasterol have the greatest binding affinity. The lowest binding free energy of berberine and TP53 was −10 kcal/mol. It can be seen from The tumor microenvironment includes cancer cells, matrix cells, and infiltrating immune cells. Infiltrating immune cells are an independent predictor of sentinel lymph node status and survival of cancer patients. Tumor purity plays a role in analyzing immune infiltration in clinical tumor samples by genomics methods. The expressions of MAPK1 were significantly negatively correlated with tumor purity via TIMER platform, while TP53 were not associated with tumor purity and infiltrating immune cells. Interestingly, we found the expression of MAPK1 was positively correlated with the infiltration level of B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells. Figures KM-Plotter analysis revealed that increased MAPK1 expression levels resulted in a higher overall survival rate. TP53, on the other hand, exhibited a worse overall survival rate in individuals with COAD Figures . As a reCRC progresses in a multistep process from normal epithelium to a premalignant lesion (adenoma), then to a malignant lesion (carcinoma) that invades adjacent tissues and can finally spread systemically (metastasis) . TherefoIn this study, we found that active components of JWHLGJD could act on 130 targets related to CRA. Further analysis showed that JWHLGJD could act on many biological processes of CRA and had an influence on the outcome of CRA through pathways in cancer, lipid and atherosclerosis, PI3K-Akt signaling pathway, and MAPK signaling pathway. It further confirmed that active components of JWHLGJD can treat CRA through multitarget and multipathway.Active components with the highest degree in compound-target network were considered to be responsible for anti-CRA effect, including quercetin, kaempferol, beta-sitosterol, stigmasterol, palmatine, isocorypalmine, berlambine, and berberine.β-catenin [Quercetin can inhibit intestinal epithelial-mesenchymal transition by affecting Akt phosphorylation and downregulating Akt kinase, which in turn can regulate the PI3K-Akt pathway to inhibit intestinal adenoma cancer progression . In huma-catenin . Kaempfe-catenin , 40. Sti-catenin . Palmati-catenin , 43. Ber-catenin . A meta--catenin . These iWe obtained 130 intersection targets between JWHLGJD and CRA and further screened out 13 core targets of JWHLGJD in the treatment of CRA. The targets are mainly associated with gene expression, cell proliferation, apoptosis, metabolism, and cell cycle. The top 5 targets of JWHLGJD against CRA including TP53, MAPK1, JUN, HSP90AA1, and AKT1 are the five main molecular targets associated with cancer . TP53 isGO enrichment analysis showed that the BP involved in JWHLGJD is mainly focused on the transcription, gene expression, and apoptotic process. Studies have found that adenomas occur when there is an imbalance in DNA repair and dysregulation of cell proliferation . DysreguThis study elaborated the mechanisms of JWHLGJD against CRA using network pharmacology and molecular docking by constructing a “C-T-P” network. In compound-target network, a total of 38 bioactive compounds were found, with quercetin, kaempferol, beta-sitosterol, stigmasterol, palmatine, isocorypalmine, berlambine, and berberine as main active compounds. 130 key target genes were identified, with TP53, MAPK1, JUN, HSP90AA1, and AKT1 recognized as core targets. The main molecular mechanisms of JWHLGJD for CRA consisted of 30 signaling pathways, and the key pathways that were closely related to CRA were found to be related to cell proliferation, apoptosis, and metabolic dysregulation through the pathways in cancer, lipid and atherosclerosis, PI3K-Akt signaling pathway, and MAPK signaling pathway. In addition, we discovered important genes that are critical in influencing prognosis through immunomodulation during the cancer stage. In a nutshell, this study provided an insight on the cellular and pathway mechanism of JWHLGJD in the treatment of CRA, as well as a new vision for the exploration of the mechanisms of TCM for precancerous lesions. However, there was no corresponding experimental validation of this study, which is something we need to do in the future.


To reveal the potential targets and signaling pathways of dasatinib in the treatment of radiation ulcers through network pharmacology and molecular docking technology.Pathological targets of radiation ulcers were screened using GeneCards database. At the same time, the pharmacological targets of dasatinib were obtained through SwissTargetPrediction (STP), Binding DB and Drugbank databases. Subsequently, the potential targets of dasatinib for anti-radiation ulcers were obtained after intersection by Venn diagram. Next, a protein-protein interaction (PPI) network was constructed through the STRING database and core targets were screened. Finally, the identified core targets were subjected to GO and KEGG enrichment analysis, co-expression network analysis, and molecular docking technology to verify the reliability of the core targets.A total of 76 potential targets for anti-radiation ulcer with dasatinib were obtained, and 6 core targets were screened, including EGFR, ERBB2, FYN, JAK2, KIT, and SRC. These genes were mainly enriched in Adherens junction, EGFR tyrosine kinase inhibitor resistance, Focal adhesion, Bladder cancer and PI3K-Akt signaling pathway. Molecular docking results showed that dasatinib binds well to the core target.Dasatinib may play a role in the treatment of radiation ulcers by regulating EGFR, ERBB2, FYN, JAK2, KIT, and SRC. These core targets may provide new insights for follow-up studies of radiation ulcers. Radiation ulcers are the result of skin damage in excess of the cumulative radiation dose during radiation therapy or accidental exposure to radiation sources , 2, and Tissue reconstruction of radiation skin ulcers presents a great challenge for plastic surgeons. Anti-inflammatory drugs, growth factors, and local anesthetics are commonly used clinically to relieve radiation skin ulcers, but the effect is not good . Hyperbahttps://pubchem.ncbi.nlm.nih.gov/) database with the search term “Dasatinib,” which is an ASCII string that explicitly describes the three-dimensional chemistry of molecules structure. Import the retrieved SMILES into the SwissTargetPrediction (http://www.swisstargetprediction.ch/) database and the Binding DB (http://www.bindingdb.org/bind/index.jsp) database, with the respective filter conditions set as Probability > 0 and Similarity > 0.85. Subsequently, in the Drugbank (https://go.drugbank.com/) database, its potential targets were searched with the keyword “Dasatinib,” and all its drug target sources were supported by corresponding experimental verifications. The above search species are all set to “homo sapiens.” Finally, the final dasatinib pharmacological targets were obtained after screening and deduplication of the targets obtained from the three databases. The pathological targets were obtained by searching with “radiation skin ulcer” as the keyword, and setting the target with score > 1 form GeneCards database (https://www.genecards.org/). This is a database that provides detailed information on all currently annotated and predictable genes in humans.The SMILES (Simplified Molecular Linear Input Specification) is obtained from the PubChem (https://bioinfogp.cnb.csic.es/tools/venny/index.html), and then the intersection targets were imported into the STRING (https://cn.string-db.org/) (Version 11.5) data analysis platform for PPI analysis . Subsequently, the PPI network was visualized by Cytoscape (version 3.9.0) software. KEGG and GO analyses were performed on the intersection targets by using the online analysis tool Kobas 3.0. Subsequently, its results were visualized by R software.The intersection targets of Dasatinib against radiation skin ulcer were obtained through the venn diagram (http://www.genemania.org/) database, which is mainly used to generate hypotheses about gene functions and analyze gene lists. KEGG and GO analyses were performed on the core targets by Kobas 3.0. Subsequently, its results were visualized by R software. Finally, the Drug-target-disease network was drawn by Cytoscape software.The six commonly used topological analysis methods  in Cytohubba, a plug-in of Cytoscape software, were used to identify the core targets of Dasatinib activity against radiation skin ulcer. Subsequently, the co-expression network and functional analysis of core targets were constructed through the GeneMANIA (https://www.rcsb.org/) database to obtain the protein structure crystal. In order to accurately obtain the PDB ID of the core target, the screening conditions are set as: Experimental method is set to X- ray diffraction, Refinement resolution is set to ≤ 2A, PH is selected to be 7.35–7.50, and chemical components are selected to have Ligand. We downloaded the 3D crystal structure of the core target from PDB database, selected to be saved in PDB format, served as the protein receptor. At the same time, download the 2D structure of Quercetin from the PubChem database, choose to save it as “SDF” format, and use OpenBabel (version 2.4.1) software to convert it to PDB format as a small molecule ligand. Using PyMOL software to remove water molecules and original ligands from protein molecules. Then, AutoDockTools (version 1.5.6) software was used to convert the PDB format files of proteins and small molecules into PDBQT format, including some operations: hydrogenation, charge calculation, atom type addition, determination of torque center (root), etc. Finally, the protein receptor and the small molecule ligand are docked by AutoDock vina (version 1.1.2). The size of the docking binding energy of the two indicates the strength of the binding activity. Small molecule ligands can bind spontaneously, and the smaller the binding energy, the better the binding activity and the stronger the binding stability. Pymol (version 2.2.0) software was used to visualize the docking results with minimal receptor-ligand binding energy.We enter the gene symbol of the core target in the PDB  to remove water molecules, hydrogenation, apply forcefield, clean protein and other operations on the core targets, and then obtain macromolecular receptors. Hydrogenation and apply forcefield are performed on the active ligand of the core target. The macromolecular receptor is molecularly docked with the treated active ligand, and the RMSD value is obtained , a smaller value indicates a more accurate docking method). After the reliability verification of the docking software, we began to do molecular docking between the core target and the drug. Before molecular docking, we performed operations such as removing water molecules, deleting ligand groups, hydrogenation, and cleaning proteins for the core targets, and preparing ligands for small molecule drugs.https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE193564), which has been previously uploaded by our team. Then we analyzed the expression changes of these core targets at different time points after irradiation in rats.Single cell sequencing data GSE193564 was downloaded from GEO database (http://sangerbox.com/home.html). Sangerbox is an online analysis tool developed based on R language, which has been widely recognized by peers . The binding energies of EGFR, ERBB2, FYN, JAK2, KIT, and SRC were all ≤ −5 kcal/mol, indicating good protein-ligand binding. See Compared with the original crystal structures, the RSMD values of EGFR, ERBB2, FYN, JAK2, KIT, and SRC were 1.4574, 1.1103, 1.4139, 0.5710, 0.5868, 1.1455A. The ligand conformation in the original crystal structure of the core protein basically overlaps with the docked ligand conformation, and RMSD <2A indicates that the calculation method can accurately predict the binding mode of the original ligand. The molecular docking results of EGFR, ERBB2, FYN, JAK2, KIT, and SRC with Dasatinib are shown in T-test was used to verify whether there was a significant difference between the groups. The results showed that the six core targets had significant expression changes at different time points after irradiation , early (2–8 weeks), mid-term (6–52 weeks), and late (over 40 weeks) according to the time after exposure. In addition, radiation damage response is dose-dependent, and the National Cancer Institute has identified four skin toxicity grades for radiation dermatitis. The most common immediate reaction (dose as low as 2 Gy) is transient erythema (grade 1), which is an inflammatory response with changes in cellular permeability and histamine release –25. Earlin vitro upon thrombin stimulation .EGFR is widely expressed in normal skin tissues, such as epidermis, sebaceous glands, glands, eccrine glands, and dendritic cells , and plain vivo and in vitro models, which will be the focus of our future research. Secondly, whether the pharmacological effects of dasatinib are as helpful to human patients as in animal and cell experimental models is also a problem that we need to solve. In follow-up studies, we will further verify the feasibility of treating radiation ulcers with core targets in animal and clinical trials.Few studies have been performed on other core targets related to radiation ulcers and deserve further consideration in future studies. Given that radiation ulcers are still a major problem facing the global medical system, our study is the first to use network pharmacology to explore the potential core targets and mechanisms of action of dasatinib against radiation ulcers. Their feasibility and possible docking sites are verified by molecular docking technology, which will provide a reference for the study of the molecular mechanism of dasatinib in the treatment of radiation ulcers. However, our study also has certain limitations. First, the core targets and pharmacological mechanisms of dasatinib in the treatment of radiation ulcers need to be verified Overall, this is the first time that bioinformatics methods such as network pharmacology and molecular docking have been applied to systematically explore the pharmacological and molecular mechanisms of dasatinib in the treatment of radiation skin ulcers. Dasatinib may promote the healing of radiation skin ulcers through EGFR tyrosine kinase inhibitor resistance, PI3K-Akt signaling pathway and ErbB signaling pathway. During treatment, EGFR, ERBB2, FYN, JAK2, KIT, and SRC were its main potential pharmacological targets, and the molecular docking results confirmed our conclusion. The identified potential targets and pathways may be validated in preclinical studies before being used in clinical therapy.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The animal study was reviewed and approved by Ethics Committee of the Second Affiliated Hospital of Chengdu Medical College.WS and DY: conceptualization. XiC, XuC, and WZ: data curation. WS, DL, and XiC: formal analysis and methodology. DY, DL, and XuC: supervision. WS, XuC, and DL: writing (review and editing). The final manuscript read and approved by all authors. All authors contributed to the article and approved the submitted version.This work was supported by the National Natural Science Foundation of China (32071238), the Fundamental Research Funds for the Central Universities and Young Talent Program of China National Nuclear Corporation (CNNC2021136), the Natural Science Project of Chengdu Medical College (CYZYB21-07), and the Medical Research Project of Chengdu 2021 (2021085).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.