scholarly journals Evaluating the Therapeutic Mechanisms of Selected Active Compounds in Cornus Officinalis and Paeonia Lactiflora in Rheumatoid Arthritis via Network Pharmacology Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Qinglin Li ◽  
Shaoqi Hu ◽  
Lichuang Huang ◽  
Jida Zhang ◽  
Gang Cao
Keyword(s):  
Rheumatoid Arthritis ◽  
Ursolic Acid ◽  
Network Pharmacology ◽  
Pharmacological Properties ◽  
Paeonia Lactiflora ◽  
Collagen Induced Arthritis ◽  
Active Compounds ◽  
Cornus Officinalis ◽  
Therapeutic Mechanisms ◽  
Compound Target

Cornus officinalis Sieb et. Zucc and Paeonia lactiflora Pall. have exhibited favorable therapeutic effects against rheumatoid arthritis (RA), but the specific mechanisms of their active compounds remain unclear. The aim of this study was to comprehensively analyze the therapeutic mechanisms of selected active compounds in Cornus officinalis (loganin, ursolic acid, and morroniside) and Paeonia lactiflora (paeoniflorin and albiflorin) via network pharmacology. The pharmacological properties of the five active compounds were evaluated and their potential target genes were identified by database screening. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional analysis were performed to determine the enriched molecular pathways associated with the active compounds. Using network pharmacology tools, eight genes (IL1β, VEGFA, STAT3, TP53, IL6, TNF, FOS, and LGALS3) were identified as common targets between RA and the five active compounds. Molecular docking simulation revealed the compound-target relationship between the five active compounds and three selected targets from the eight common ones (LGALS3, STAT3, and VEGFA). The compound-target relationships were subsequently validated via preliminary in vivo experiments in a rat model of collagen-induced arthritis. Rats subjected to collagen-induced arthritis showed increased protein expression of LGALS3, STAT3, and VEGFA in synovial tissues. However, treatment using Cornus officinalis or/and Paeonia lactiflora, as well as their most drug-like active compounds (ursolic acid or/and paeoniflorin, respectively, identified based on pharmacological properties), attenuated the expression of these three targets, as previously predicted. Collectively, network pharmacology allowed the pharmacological and molecular roles of Cornus officinalis and Paeonia lactiflora to be systematically revealed, further establishing them as important candidate drugs in the treatment and management of RA.

scholarly journals Identification of Active Compounds of Mahuang Fuzi Xixin Decoction and Their Mechanisms of Action by LC-MS/MS and Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xiao Liang ◽  
Chang-Shun Liu ◽  
Ting Xia ◽  
Qing-Fa Tang ◽  
Xiao-Mei Tan
Keyword(s):  
Signaling Pathways ◽  
Bioactive Compounds ◽  
Cell Receptor ◽  
Mechanisms Of Action ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Active Compounds ◽  
Beneficial Effects ◽  
T Cell Receptor Signaling ◽  
Therapeutic Mechanisms

The decoction is an important dosage form of traditional Chinese medicine (TCM) administration. The Mahuang Fuzi Xixin decoction (MFXD) is widely used to treat allergic rhinitis (AR) in China. However, its active compounds and therapeutic mechanisms are unclear. The aim of this study was to establish an integrative method to identify the bioactive compounds and reveal the mechanisms of action of MFXD. LC-MS/MS was used to identify the compounds in MFXD, followed by screening for oral bioavailability. TCMSP, BindingDB, STRING, DAVID, and KEGG databases and algorithms were used to gather information. Cytoscape was used to visualize the networks. Twenty-four bioactive compounds were identified, and thirty-seven predicted targets of these compounds were associated with AR. DAVID analysis suggested that these compounds exert their therapeutic effects by modulating the Fc epsilon RI, B-cell receptor, Toll-like receptor, TNF, NF-κB, and T-cell receptor signaling pathways. The PI3K/AKT and cAMP signaling pathways were also implicated. Ten of the identified compounds, quercetin, pseudoephedrine, ephedrine, β-asarone, methylephedrine, α-linolenic acid, cathine, ferulic acid, nardosinone, and higenamine, seemed to account for most of the beneficial effects of MFXD in AR. This study showed that LC-MS/MS followed by network pharmacology analysis is useful to elucidate the complex mechanisms of action of TCM formulas.

scholarly journals A Network Pharmacology-Based Approach for Exploring Key Active Compounds and Pharmacological Mechanisms of Tangshen Formula for Treatment of Diabetic Nephropathy

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Weie Zhou ◽  
Xuefeng Zhou ◽  
Yuan Zhang ◽  
Yuyang Wang ◽  
Wenjie Wu ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Synergistic Effects ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Promising Source ◽  
Tangshen Formula ◽  
Compound Target

Diabetic nephropathy (DN) is one of the common and severe microvascular complications of diabetes mellitus (DM). The occurrence and development of DN are related to multiple factors in the human body, which makes DN a complex disease, and the pathogeneses of DN have not yet been fully illustrated. Furthermore, DN lacks effective drugs for treatment nowadays. Chinese herbal medicine (CHM) often shows the feature of multicomponents, multitargets, multipathways, and synergistic effects and shows a promising source of new therapeutic drugs for DN. As a CHM, Tangshen Formula (TSF) was used to treat DN patients in China. However, its bioactive compounds and holistic pharmacological mechanisms on DN are both unclear. A network pharmacology approach was firstly applied to explore multiple active compounds and multiple key pharmacological mechanisms for TSF treating DN by drug-targeted interaction databases, herb-compound-target network, protein-protein interaction network, compound-target-pathway network, and analysis methods. And the results showed that TSF have the characteristic of multicomponents, multitargets, multipathways, and synergistic effects for treating DN. The quercetin, naringenin, kaempferol, and isorhamnetin as key active compounds and the PI3K-Akt signaling pathway, TNF signaling pathway, nonalcoholic fatty liver disease (NAFLD), focal adhesion, rap1 signaling pathway, T cell receptor signaling pathway, MAPK signaling pathway, and insulin resistance as the key molecular mechanisms play important roles in TSF treating DN. Moreover, quercetin, naringenin, kaempferol, and isorhamnetin were successfully detected in TSF by the UHPLC-MS/MS analysis method. And their concentrations were 0.224, 8.295, 0.0564, and 0.0879 mg·kg-1, respectively. The present findings not only provide new insights for a deeper understanding of the constituent basis and pharmacology of TSF but also provide guidance for further pharmacological studies on TSF.

scholarly journals Study on the Multitarget Mechanism of Sanmiao Pill on Gouty Arthritis Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
Huiqin Qian ◽  
Qianqian Jin ◽  
Yichen Liu ◽  
Ning Wang ◽  
Yuru Chu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Gouty Arthritis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Regulation Of Transcription ◽  
Receptor Signaling ◽  
Active Compounds ◽  
Receptor Signaling Pathway ◽  
Compound Target

Sanmiao pill (SMP), a Chinese traditional formula, had been used to treat gouty arthritis (GA). However, the active compounds and underlying mechanism remained unclear. Hence, network pharmacology and molecular docking were utilized to explore bioactive compounds and potential mechanism of action of SMP in treating GA. In the study, the compounds of SMP, corresponding targets, and GA-related targets were mined from various pharmacological databases. Then, herb-compound-target, compound-target, PPI, and target-pathway networks were constructed. Ultimately, molecular docking was carried out to verify the predicted results. The results indicated that 47 active compounds, 338 targets, and 144 disease targets were collected. Network analysis implied that Phellodendron chinense Schneid. played a vital role in the whole formula. Moreover, 7 compounds (quercetin, kaempferol, wogonin, rutaecarpine, baicalein, beta-sitosterol, and stigmasterol) and 4 targets (NFKB1, RELA, MAPK1, and TNF) might be the kernel compounds and targets of SMP against GA. According to GOBP and KEGG pathway enrichment analysis and target-pathway network, SMP might exert a therapeutic role in GA by regulating numerous biological processes and pathways, including lipopolysaccharide-mediated signaling pathway, positive regulation of transcription, Toll-like receptor signaling pathway, JAK-STAT signaling pathway, NOD-like receptor signaling pathway, and MAPK signaling pathway. The results of molecular docking showcased that 11 pairs of compound with targets had tight binding strength. Thereinto, 4 compounds of MAPK1 and 5 compounds of NFKB1 possessed a better combination, suggesting that MAPK1 and NFKB1 might be considered as therapeutic targets in treatment of GA. This study verified that SMP had synergistic effect on GA by multicomponents, multitargets, and multipathways.

scholarly journals A Network Pharmacology Study on the Active Ingredients and Potential Targets ofTripterygium wilfordiiHook for Treatment of Rheumatoid Arthritis

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Wei Hu ◽  
Wanjin Fu ◽  
Xin Wei ◽  
Yang Yang ◽  
Chao Lu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanism ◽  
Rheumatic Diseases ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Disease Network ◽  
Rheumatoid Arthritis Disease ◽  
Compound Target

Traditional Chinese medicine has specific effect on some chronic diseases in clinic, especially in rheumatic diseases.Tripterygium wilfordiiHook (TWH) is a traditional Chinese medicine commonly used in the treatment of rheumatoid arthritis (RA); the unique therapeutic effect has been confirmed by a large number of research papers. TWH has many compounds that lead to its active compounds. However, the potential targets and pharmacological and molecular mechanism of its action treatment of rheumatic diseases are not entirely clear. Therefore, the network pharmacology approach is needed to further study and explore its treatment mechanism. We have successfully set up 10 networks, including four major networks and other networks. Four major networks include rheumatoid arthritis disease network, compound-compound target network of TWH, TWH compound target-rheumatoid arthritis disease network, and TWH-rheumatoid arthritis disease-mechanism network. Other networks consist of RA disease and TWH related targets clusters, biological processes, and pathways network. Our study successfully predicted, explained, and confirmed the TWH of RA disease molecular synergy and found the potential of RA related targets, cluster, biological process, and pathways. This study not only provides prompts to the researcher who explores pharmacological and biological molecular mechanism of TWH applying to RA disease, but also proves a feasible method for discovering potential activated compounds from Chinese herbs.

scholarly journals Network Pharmacology Strategy to Investigate the Pharmacological Mechanism of Siwu Decoction on Primary Dysmenorrhea and Molecular Docking Verification

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dandan Jiang ◽  
Xiaoyan Wang ◽  
Lijun Tian ◽  
Yufeng Zhang
Keyword(s):  
Molecular Docking ◽  
Target Genes ◽  
Network Pharmacology ◽  
Primary Dysmenorrhea ◽  
Ppi Network ◽  
Active Compounds ◽  
Docking Simulations ◽  
Active Target ◽  
Target Network ◽  
Compound Target

Objective. To study the pharmacological mechanisms of Siwu decoction (SWD) on primary dysmenorrhea (PDM) and verify with molecular docking. Methods. The  Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was utilized to acquire the active compounds and their corresponding target genes. The GeneCards database was utilized in the search for target genes that were associated with PDM. The intersection genes from the active target genes of SWD and those associated with PDM represented the active target genes of SWD that act on PDM. The Gene Ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were both carried out by RGUI 3.6.1 and Cytoscape 3.6.0 software. Cytoscape was also utilized for creating a compound-target network, and a protein-protein interaction (PPI) network was created through the STRING database. Molecular docking simulations of the macromolecular protein target receptors and their corresponding compounds were performed using AutoDockTool 1.5.6 and AutoDock Vina software. Results. We identified 14 active compounds as well as 97 active target genes of SWD by using the TCMSP. We compared the 97 active target genes of SWD to the 299 target genes related to PDM, and 23 active target genes for SWD that act on PDM which correlated with 11 active compounds were detected. The compound-target network as well as the PPI network were created, in addition to selecting the most essential compounds and their targets in order to create a key compound-target network. The most essential compounds were kaempferol, beta-sitosterol, stigmasterol, and myricanone. The key targets were AKT1, PTGS2, ESR1, AHR, CASP3, and PGR. Lastly, molecular docking was used to confirm binding of the target with its corresponding compound. Conclusion. The pharmacological mechanisms of SWD that act on PDM were investigated, and the active compounds in the SWD for treating PDM were further verified.

scholarly journals Exploring Molecular Mechanism of Traditional Chinese Medicine Euphorbiae Semen on Reversing of Multidrug Resistance in Leukemia Based on Network Pharmacology Strategy and Molecular Docking Technology

2020 ◽  
Author(s):  
Xiao Song ◽  
Fei Guo ◽  
Xiao-Chen Sun ◽  
Shu-Yue Wang ◽  
Yao-Hui Yuan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Biological Functions ◽  
Active Compounds ◽  
The Core ◽  
The World ◽  
Target Network ◽  
Compound Target

Abstract Background: Leukemia was listed by the World Health Organization as one of the five most intractable diseases in the world. The multi-drug resistance (MDR) of leukemia cells limits the efficacy of anti-tumor drugs and is the major reason for the chemotherapy failure and recurrence of leukemia chemotherapy. Some studies have shown that Euphorbiae semen (ES) possesses the characteristics of new therapeutic drugs for MDR. However, the molecular mechanisms and active compounds have not yet been fully clarified. Therefore, there is a need for explore its active compounds and demonstrate its mechanisms through network pharmacology and molecular docking technology.Method: First, the TCMSP database was searched and screened the active compounds of the ES, supplemented with compounds verified by literature, so as to further identify the core compounds in the active ingredient. Simultaneously, the TCMSP and Swiss database were searched to the targets of active compounds, and the targets of reverses leukemia multidrug resistance (RL-MDR) were screened in the relevant databases, such as GeneCards and DrugBank. Then, the targets of active compounds were intersected with RL-MDR targets to obtain potential targets of ES acting on MDR. The compound–target network was constructed by Cytoscape. The target protein–protein interaction network was built using STRING and Cytoscape database. Second, the R language and DAVID database were used to analyse Gene Ontology (GO) biological functions analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways enrichment. Finally, molecular docking method was utilized to investigate the binding activity between the core targets and the active compounds of ES.Results: Compound–target network mainly contained 22 compounds and 81 corresponding targets. Finally, seven components in ES were selected and 10 core targets were identified; Key targets contained JUN, CASP3, MAOA, AR, PPARG, DRD2, ADRA2A, CHRM2, PTGS2 and MAPK14. GO enrichment analysis indicated the main biological functions of potential genes of ES in the treatment of MDR. KEGG pathway enrichment analysis showed the main pathways, mainly including apoptosis, pathways in cancer, p53 signaling pathway, VEGF signaling pathway, TNF signaling pathway and PI3K–Akt signaling pathway. Finally, we chose the top 10 common targets for molecular docking with the 7 active compounds of ES. The results of molecular docking indicated that the compounds of ES, which had good affinity with targets. Conclusion: The molecular mechanism of ES in the treatment of MDR showed the synergistic reaction of multi-compound, multi-target, and multi-pathway of traditional Chinese medicine, which provided ideas for further clinical research.

scholarly journals Combined Cornus Officinalis and Paeonia Lactiflora Pall Therapy Alleviates Rheumatoid Arthritis by Regulating Synovial Apoptosis via AMPK-Mediated Mitochondrial Fission

2021 ◽  
Vol 12 ◽  
Author(s):  
Lichuang Huang ◽  
Shaoqi Hu ◽  
Meiyu Shao ◽  
Xin Wu ◽  
Jida Zhang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Bone Erosion ◽  
Mitochondrial Dynamics ◽  
Mitochondrial Fission ◽  
Cartilage Destruction ◽  
Paeonia Lactiflora ◽  
Active Components ◽  
Cornus Officinalis ◽  
Medicinal Value ◽  
Underlying Mechanisms

Rheumatoid arthritis (RA) is a chronic autoimmune disease that leads to cartilage destruction and bone erosion. In-depth exploration of the pathogenesis of RA and the development of effective therapeutic drugs are of important clinical and social value. Herein, we explored the medicinal value of Cornus officinalis Sieb. and Paeonia lactiflora Pall. in RA treatment using a rat model of collagen-induced arthritis (CIA). We compared the therapeutic effect of Cornus officinalis and Paeonia lactiflora with that of their main active compounds, ursolic acid and paeoniflorin, respectively. We demonstrated that the combination of Cornus officinalis and Paeonia lactiflora effectively inhibited the release of factors associated with oxidative stress and inflammation during RA, therein ameliorating the symptoms and suppressing the progression of RA. We further showed that the underlying mechanisms may be related to the regulation of apoptosis in synovial tissues, and we investigated the potential involvement of AMPK-mediated mitochondrial dynamics in the therapeutic action of the two drugs and their active components.

scholarly journals Antitumor Mechanisms of Curcumae Rhizoma Based on Network Pharmacology

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yan-Hua Bi ◽  
Li-hua Zhang ◽  
Shao-jun Chen ◽  
Qing-zhi Ling
Keyword(s):  
Target Genes ◽  
Clinical Care ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Protein Targets ◽  
Manual Search ◽  
Anticancer Effects ◽  
Pubmed Database ◽  
Materials Used ◽  
Compound Target

Curcumae Rhizoma, a traditional Chinese medication, is commonly used in both traditional treatment and modern clinical care. Its anticancer effects have attracted a great deal of attention, but the mechanisms of action remain obscure. In this study, we screened for the active compounds of Curcumae Rhizoma using a drug-likeness approach. Candidate protein targets with functions related to cancer were predicted by reverse docking and then checked by manual search of the PubMed database. Potential target genes were uploaded to the GeneMANIA server and DAVID 6.8 database for analysis. Finally, compound-target, target-pathway, and compound-target-pathway networks were constructed using Cytoscape 3.3. The results revealed that the anticancer activity of Curcumae Rhizoma potentially involves 13 active compounds, 33 potential targets, and 31 signaling pathways, thus constituting a “multiple compounds, multiple targets, and multiple pathways” network corresponding to the concept of systematic actions in TCM. These findings provide an overview of the anticancer action of Curcumae Rhizoma from a network perspective, as well as setting an example for future studies of other materials used in TCM.

scholarly journals Deciphering the Molecular Targets and Mechanisms of HGWD in the Treatment of Rheumatoid Arthritis via Network Pharmacology and Molecular Docking

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Wei Liu ◽  
Yihua Fan ◽  
Chunying Tian ◽  
Yue Jin ◽  
Shaopeng Du ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Target Genes ◽  
Differentially Expressed ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Target Proteins ◽  
Target Network

Background. Huangqi Guizhi Wuwu Decoction (HGWD) has been applied in the treatment of joint pain for more than 1000 years in China. Currently, most physicians use HGWD to treat rheumatoid arthritis (RA), and it has proved to have high efficacy. Therefore, it is necessary to explore the potential mechanism of action of HGWD in RA treatment based on network pharmacology and molecular docking methods. Methods. The active compounds of HGWD were collected, and their targets were identified from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and DrugBank database, respectively. The RA-related targets were retrieved by analyzing the differentially expressed genes between RA patients and healthy individuals. Subsequently, the compound-target network of HGWD was constructed and visualized through Cytoscape 3.8.0 software. Protein-protein interaction (PPI) network was constructed to explore the potential mechanisms of HGWD on RA using the plugin BisoGenet of Cytoscape 3.8.0 software. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed in R software (Bioconductor, clusterProfiler). Afterward, molecular docking was used to analyze the binding force of the top 10 active compounds with target proteins of VCAM1, CTNNB1, and JUN. Results. Cumulatively, 790 active compounds and 1006 targets of HGWD were identified. A total of 4570 differentially expressed genes of RA with a p value <0.05 and log 2fold change > 0.5 were collected. Moreover, 739 GO entries of HGWD on RA were identified, and 79 pathways were screened based on GO and KEGG analysis. The core target gene of HGWD in RA treatment was JUN. Other key target genes included FOS, CCND1, IL6, E2F2, and ICAM1. It was confirmed that the TNF signaling pathway and IL-17 signaling pathway are important pathways of HGWD in the treatment of RA. The molecular docking results revealed that the top 10 active compounds of HGWD had a strong binding to the target proteins of VCAM1, CTNNB1, and JUN. Conclusion. HGWD has important active compounds such as quercetin, kaempferol, and beta-sitosterol, which exert its therapeutic effect on multiple targets and multiple pathways.

scholarly journals A Network Pharmacology Approach to Reveal the Underlying Mechanisms of Paeonia lactiflora Pall. On the Treatment of Alzheimer’s Disease

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Qiang Zeng ◽  
Longfei Li ◽  
Yu Jin ◽  
Zongzheng Chen ◽  
Lihong Duan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Inflammatory Response ◽  
Signaling Pathway ◽  
Cell Apoptosis ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Paeonia Lactiflora ◽  
Active Compounds ◽  
Target Proteins ◽  
Underlying Mechanisms

Objective. To investigate the potential active compounds and underlying mechanisms of Paeonia lactiflora Pall. (PLP) on the treatment of Alzheimer’s disease (AD) based on network pharmacology. Methods. The active components of PLP were collected from Traditional Chinese Medicine System Pharmacology (TCMSP) database, and their possible target proteins were predicted using TCMSP, SwissTargetPrediction, and STITCH databases. The putative AD-related target proteins were identified from Therapeutic Target Database (TTD), GeneCards, and MalaCards database. The compound-target-disease network interactions were established to obtain the key targets about PLP acting on AD by network topology analysis. Then, the function annotation and signaling pathways of key targets were performed by GO and KEGG enrichment analysis using DAVID tools. Finally, the binding capacity between active ingredients and key targets was validated by molecular docking using SystemsDock tools. Results. There were 7 active compounds involving in 151 predicted targets identified in PLP. Besides, a total of 160 AD-related targets were identified. Among these targets, 30 shared targets of PLP and AD were acquired. After topological analysis of the PLP potential target-AD target network, 33 key targets that were highly responsible for the therapeutic effects of PLP on AD were obtained. Further GO and KEGG enrichment analysis showed that these key targets were significantly involved in multiple biological processes and pathways which participated in cell apoptosis and inflammatory response and maintained the function of neurons to accomplish the anti-AD activity. The molecular docking analysis verified that the 7 active compounds had definite affinity with the key targets. Conclusions. The ameliorative effects of PLP on AD were predicted to be associated with regulating neural cell apoptosis, inflammatory response, and neurotrophy via various pathways such as PI3K-Akt signaling pathway, MAPK signaling pathway, and neurotrophin signaling pathway.

Sign in / Sign up

Export Citation Format

Share Document