Home | Register | Login | Inquiries | Alerts | Sitemap |  


Advanced Search
JKM > Volume 45(4); 2024 > Article
Lim, Oh, Noh, Yu, Kim, Kweon, and Bae: Exploring the Therapeutic Potential and Mechanisms of Zizyphus jujuba Miller in Chronic Pancreatitis: A Network Pharmacology and Molecular Docking Approach

Abstract

Objectives

This study employed a network pharmacology approach to explore the potential therapeutic effects and underlying molecular mechanisms of Zizyphus jujuba Miller var. inermis Rehder (Jujube) in the treatment of chronic pancreatitis (CP).

Methods

The bioactive compounds of Jujube and their target genes were identified from the HERB, OASIS databases. These putative target genes were then cross-referenced with CP-associated genes to identify potential correlations. A network was subsequently constructed using Cytoscape 3.10.2. To further investigate, functional enrichment analyses were conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway databases. Additionally, binding affinities between active compounds and key genes were assessed by CB-DOCK2.

Results

55 active compounds and 344 associated target genes were identified from Jujube. Among these, 156 genes overlapped with the CP gene set. After screening, 9 key genes were identified from this subset, further emphasizing the significant relationship between the Jujube and CP. GO and KEGG analyses revealed that the 'PI3K-Akt Signaling Pathway' is a significant pathway mediated by 9 key genes in the context of CP. Furthermore, molecular docking analysis confirmed the strong binding affinities between the active compounds and key genes.

Conclusions

Through the application of a network pharmacology approach, complemented by molecular docking studies, this research highlights a strong pharmacological relevance of Jujube in CP. These findings provide a valuable foundation for future investigations into the therapeutic potential of Jujube in mitigating CP, possibly through the modulation of the PI3K/Akt signaling pathway.

Introduction

Chronic pancreatitis (CP) is an irreversible disease characterized by the replacement of pancreatic parenchyma with fibrous connective tissue due to repeated episodes of inflammation1). This condition is marked by intermittent or continuous severe abdominal pain and, as it progresses, leads to both exocrine and endocrine pancreatic insufficiencies, severely impacting the quality of life2). Additionally, patients with CP have a 13.3-fold increased risk of developing pancreatic cancer3). The highest prevalence and incidence of pancreatitis are observed in East Asia, particularly in Korea, where a 13-year cohort study reported a significant increase in CP prevalence from 90 per 100,000 individuals in 2002 to 560 per 100,000 individuals in 20154,5). Although the overall incidence and prevalence of CP are relatively low, it is associated with considerable morbidity and poses a significant financial burden on both individuals and public health systems2). Despite its severity, CP currently lacks effective treatments, with existing medications providing only limited symptom relief610). For instance, paracetamol is frequently administered to manage pain in CP patients, while opioids may be considered in cases of more severe pain11). As a result, patients are encouraged to implement lifestyle modifications, including abstinence from alcohol and smoking, to help manage the disease7). Consequently, there is an urgent need for effective therapeutic interventions for CP.
The Zizyphus jujuba Miller var. inermis Rehder (Jujube) belongs to the Rhamnaceae family and has been widely utilized in traditional medicine across Asia, Europe, and the United States for the treatment of various ailments such as gastrointestinal disorders, liver diseases, obesity, skin infections, anemia, diarrhea, insomnia, and cancer12). Several studies have reported the anti-inflammatory and anti-fibrotic properties of Jujube and its varieties1317). However, research investigating the effects of Jujube on CP has not yet been conducted.
Network pharmacology encompasses various approaches, one of which involves linking active compounds to target genes, and target genes to diseases, thereby constructing a network to explore drug efficacy18,19). It has garnered attention as a novel approach to studying the efficacy of traditional herbal medicines with multiple components and multiple targets18,20). Additionally, network pharmacology research methods are being effectively used to uncover new effects of existing drugs21,22).
In this study, we aimed to explore the potential of jujube in improving CP through network pharmacology. Accordingly, we constructed a network based on the active compounds and key genes of jujube. Furthermore, using network pharmacology and blind molecular docking techniques, we sought to predict the potential ameliorative effects and mechanisms of jujube on CP.

Material and Methods

1. Screening the active compounds and targets of Jujube

The compounds of Jujube were obtained from HERB (http://herb.ac.cn/) and OASIS (https://oasis.kiom.re.kr/) databases, and 74 compounds were selected based on validation through published studies. After excluding compounds that violated two or more of Lipinski’s rules (MW≤500; HBA ≤10; HBD≤5; MLogP≤4.15) or had a topological polar surface area (TPSA) exceeding 140Å2, which indicates poor oral bioavailability, and included only those with a bioavailability score of ≥ 0.55, 62 compounds were retained for further analysis. Among these, the compounds for which target gene information was available in the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) were selected as the active compounds of Jujube.

2. Identification of target genes linking Jujube and CP

CP-related genes were collected from the human gene database GeneCards version 5.20 (https://www.genecards.org/) using the search term “Chronic pancreatitis”. A total of 1241 CP-related genes were collected. To verify the relationship between Jujube and CP, only the overlapping genes with Jujube's target genes were collected. The selected overlapping genes were analyzed for protein-protein interactions (PPI) using the STRING database (https://string-db.org/), under the conditions of ‘Homo sapiens’ and a combination score of 0.7 or higher (high confidence).

3. Identification and network analysis of key genes between Jujube and CP

To identify the key genes among the overlapping genes, a topological analysis of the proteins in the PPI network was conducted using Cytoscape 3.10.2 software. The analysis employed metrics such as Degree Centrality (DC), Betweenness Centrality (BC), and Closeness Centrality (CC). Genes exhibiting values above the mean for each metric were initially selected. This selection process was subsequently repeated, and only those genes that met the criteria in both rounds were designated as the key genes within the network.

4. Functional enrichment analysis

To predict the functions and mechanisms of action of the key genes affecting CP, functional enrichment analysis was performed using Enrichr (https://maayanlab.cloud/Enrichr/). The analysis utilized databases including The Gene Ontology (GO) biological process, GO cellular component, GO molecular function, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) 2021 Human. Significant pathways were identified based on the p-value. Data was visualized by SRplot tools (https://www.bioinformatics.com.cn/srplot).

5. Construction of the Jujube-Active compound-Key gene-Pathway (JAKP) network

The active compounds of Jujube, key genes, and pathways collected through the above processes were analyzed in 3 stages using Cytoscape 3.10.2.

6. Molecular docking analysis

Molecular docking techniques were employed to study the binding strength and interaction modes between the active compounds of Jujube and the major proteins encoded by the key genes. Blind docking simulations were conducted using CB-Dock2 (https://cadd.labshare.cn/cb-dock2/index.php), with protein PDB format files obtained from AlphaFold protein structure database (https://alphafold.ebi.ac.uk/) and compound SDF format files sourced from PubChem database.

Results

1. Selection of active compounds among the constituents of Jujube

A total of 74 compounds constituting Jujube were collected from the HERB and OASIS databases. After excluding compounds with poor oral bioavailability and those without valid target gene information in the PubChem database, 55 compounds were predicted to be active compounds (Table 1). A total of 344 genes were associated with these compounds, and a PPI network was constructed using these genes, resulting in 344 nodes and 2237 edges (Figure 1A).

2. Exploring Key genes and Network analysis between Jujube and CP

To determine the association between CP-related genes and the target genes of Jujube, we identified common genes between the 1,241 CP-related genes collected from the GeneCards database and the target genes of Jujube. The analysis revealed a total of 156 overlapping genes (Figure 1B, Table 2). A PPI network of 9 nodes and 28 edges was constructed from 156 overlapping genes through topological analysis in Cytoscape 3.10.2 (Figure 2). The 9 nodes identified as key genes include TP53, IL6, AKT1, TNF, IL1B, INS, STAT3, BCL2, and TLR4. The respective DC, BC and CC values are presented in Table 3.
To investigate the potential mechanisms and effects of Jujube on CP, 9 key genes were analyzed through GO enrichment analysis and KEGG pathway analysis. The GO enrichment analysis identified 65 items in the Molecular Function (MF) category, 26 items in the Cellular Component (CC) category, and 822 items in the Biological Process (BP) category. From each category, the top 10 items with the lowest p-values were selected. The MF category was associated with ‘Cytokine Activity’ and ‘Cytokine Receptor binding’, the CC category with ‘Endoplasmic Reticulum Lumen’ and ‘Mitochondrial Outer Membrane’, and the BP category with ‘Positive Regulation Of NF-kappaB Transcription Factor Activity’, ‘Positive Regulation Of Cytokine Production Involved In Inflammatory Response’, and ‘Positive Regulation Of Interleukin-6 Production’ (Figure 3).
Additionally, KEGG pathway analysis identified 153 items associated with the 9 key genes. Among these, the top 30 items were selected based on p-value for further analysis. Ultimately, 4 top items related to the mechanism were identified: ‘HIF-1 signaling pathway’, ‘Toll-like receptor signaling pathway’, ‘PI3K-Akt signaling pathway’, and ‘NOD-like receptor signaling pathway’ (Figure 4, Table 4).

4. Exploring the Mechanism of Jujube’s Therapeutic Effects on CP through JAKP network analysis

DC in network pharmacology measures a node's influence based on its number of connections and is crucial for identifying potential drug targets23,24). In the JAKP network analysis of Jujube, compounds closely associated with CP were ranked by their DC. The top 5 active compounds were Apigenin, Caffeic acid, Ferulic acid, Quercetin, and Ursolic acid. They were found to be connected to all 9 key genes: IL6, TNF, INS, AKT1, BCL2, TP53, TLR4, STAT3, and IL1B. Among the 4 pathways identified through KEGG pathway analysis, ‘HIF-1 signaling pathway’ and ‘PI3K-Akt signaling pathway’ had a DC value of 6, while ‘Toll-like receptor signaling pathway’ and ‘NOD-like receptor signaling pathway’ had a DC value of 5 (Figure 5).

5. Molecular docking

In the JAKP network, the top 5 active compounds with the highest DC scores were analyzed for their binding energy with proteins coded by key genes. On average, these compounds exhibited a binding affinity of -6.91 Vina score. Notably, Ursolic acid showed a particularly strong binding affinity with the protein Akt1, coded by the AKT1 gene, with a Vina score of −9.0. Additionally, Ursolic acid also demonstrated strong binding with proteins Stat3 and Ins, coded by the STAT3 and INS genes, with Vina scores of −8.9 and −8.6, respectively (Figure 6).

Discussion

CP is a disease characterized by the progressive loss of the endocrine and exocrine compartments of the pancreas due to long-standing inflammation that results in atrophic, fibrotic, or a combination of both types of tissues25,26). In particular, the activation of pancreatic stellate cells (PSCs) plays a crucial role in pancreatic fibrosis, which is primarily triggered by exposure to various cytokines, growth factors, and reactive oxygen species (ROS) during tissue injury, repair, and inflammation27). Once activated, PSCs migrate to the site of injury, proliferate, and secrete excessive amounts of extracellular matrix (ECM), leading to fibrosis, while establishing a vicious cycle through autocrine stimulation28,29). These pathological changes eventually lead to structural alterations of the pancreas, contributing to clinical manifestations of CP, such as reduced secretion of digestive enzymes and endocrine dysfunction29,30). Although the pathophysiology of CP is highly complex, smoking and excessive alcohol consumption have been studied as major etiological factors for chronic pancreatitis, and particularly in cases of recurrent acute pancreatitis, it may progress to CP through a necrosis-fibrosis sequence6,3133).
In traditional Korean medicine, CP is categorized under the concepts of pain, epigastric pain, and the formation of abdominal masses(癥瘕)34). It can be classified into several patterns, including spleen-stomach weakness(脾胃虛弱), heat-dampness stagnation(濕熱鬱蒸), and excess heat with obstruction(實熱結滯)34). Due to the prolonged nature of the condition and the predominance of symptoms such as indigestion and abdominal pain, some perspectives consider spleen-stomach weakness (脾胃虛弱) as a primary pathophysiological mechanism35).
The fruit of Jujube has been used to alleviate symptoms related to weakened digestive function and insufficiency of middle qi (中氣不足), which weakens the spleen and stomach, leading to symptoms such as poor appetite, fatigue, weakness, unexplained palpitations, anxiety, and the passage of unformed stools36,37). Given these properties, Jujube may offer therapeutic potential for treating chronic pancreatitis, particularly in addressing spleen-stomach weakness. While experimental studies suggest that Ziziphus jujuba may have a fibrosis-preventing effect on cavernosal tissue, Jujube’s protective effects against CP have not yet been elucidated16).
A total of 55 active compounds from the collected Jujube were found to interact with 344 target genes. Among these, 156 genes overlapped with CP, showing a significant relevance of 45.35%. This overlap is relatively higher compared to previous network pharmacology studies, suggesting that Jujube may have a meaningful effect in improving CP38,39).
Functional enrichment analysis was conducted to investigate the biological functions associated with Jujube in CP. The results revealed that Jujube may play an important role in inflammatory responses, as indicated by functions such as ‘Cytokine Activity’, ‘Cytokine Receptor Binding’, and ‘Positive Regulation Of Cytokine Production Involved In Inflammatory Response’. Additionally, the KEGG 2021 Human database indicates that Jujube is related to CP through pathways such as the ‘HIF-1 signaling pathway’, ‘Toll-like receptor signaling pathway’, ‘PI3K-Akt signaling pathway’, and ‘NOD-like receptor signaling pathway’. Although all 4 pathways are involved in the regulation of inflammation, the PI3K/Akt signaling pathway, in particular, is closely associated with fibrosis, as several studies have highlighted its potential as a therapeutic target4042). For instance, in pancreatic fibrosis, a treatment has been shown to inhibit PSCs autophagy and reduce ECM formation and pancreatic damage through the PI3K/Akt pathway43). Therefore, regulation of the PI3K/Akt pathway could potentially prevent or alleviate fibrosis, a major pathological feature of CP.
The PI3K/Akt signaling pathway is involved in the migration and proliferation of PSCs44). The migration of PSCs is induced by platelet-derived growth factor (PDGF), which is upregulated during pancreatic injury and mediated through the downstream pathways of PI3K45,46). Additionally, PI3K interacts with the ERK pathway, which is involved in the proliferation of PSCs45). Indeed, it has been reported that the administration of the PI3K inhibitor wortmannin not only inhibits PSCs migration but also reduces ERK activation47). Since activated PSCs migrate to the site of injury, proliferate, and secrete extracellular matrix, thereby contributing to pancreatic fibrosis, targeting the PI3K/Akt pathway to regulate PSC activation could potentially reduce tissue damage and serve as a promising therapeutic approach for CP9,47,48). Several experimental studies have shown that PI3K/Akt signaling is elevated in CP, while inhibitors that reduce symptoms inhibit the phosphorylation of PI3K and Akt49,50). There is evidence that mixtures containing Ziziphus jujuba Mill. modulate the PI3K/Akt pathway, but no studies have yet demonstrated that Jujube regulates CP51). Given the critical role of the PI3K/Akt pathway in CP, Jujube may have the potential to alleviate the condition through the same mechanism.
Subsequently, using blind molecular docking, the binding affinities between the top 5 active compounds with the highest DC in the JAKP pathway and key genes were assessed. The analysis revealed that the binding energy between Akt1, a critical component of the PI3K/Akt pathway, and Ursolic acid was −9.0 vina score, indicating a notably strong interaction. In addition, compounds involved in the JAKP network have shown relevance in this context. In the JAKP network, Apigenin, Caffeic acid, Ferulic acid, Quercetin, and Ursolic acid exhibit high DC, suggesting their significant involvement in various biological processes related to CP. Notably, Ursolic acid, Quercetin, and Apigenin demonstrated strong binding affinities with key genes-coded proteins, with average binding energies below −7 vina score (Figure 6A). These active compounds have been reported to modulate various diseases through the PI3K/Akt signaling pathway5259). Particularly Ursolic acid, which stands out with its strong binding affinities to Akt1, has meaningful relevance to fibrosis. For instance, Ursolic acid ameliorates hepatic fibrosis in rats through the ERK, PI3K/Akt, and p38 MAPK pathways59). Furthermore, It has been demonstrated that Ursolic acid significantly suppresses the growth and induces apoptosis of resistant pancreatic cancer through activation of the c-Jun-terminal kinase pathway and inhibition of PI3K/Akt/NF-κ B pathway60). Such evidence suggests that Jujube has the potential to modulate CP through the PI3K/Akt signaling pathway, with Ursolic acid, in particular, playing a prominent role, alongside Quercetin and Apigenin.
However, this study is based on in silico analysis, and it remains unclear whether Jujube exhibits beneficial effects on CP in vivo. While the potential antifibrotic effects of the aforementioned compounds have been suggested, the precise mechanisms through which Jujube and its active compounds act on pancreatic tissue remain unclear. Additionally, research on the dosage of Jujube that can exhibit pharmacological efficacy is also needed.

Conclusion

In this study, we constructed a network based on the active compounds of Jujube and the associated key genes. By utilizing network pharmacology and molecular docking methods, we explored the potential of Jujube in improving CP and its underlying mechanisms of action. It is anticipated that the findings of this study could provide foundational data for future research on the use of Jujube in improving CP.

Acknowledgements

This research was funded by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MEST; contract/grant number (RS-2024-00351313/RS-2023-00261934/2021R1I1A2053285/RS-2024-00450002/RS-2024-00459946).

Fig. 1
(A) Network of Zizyphus jujuba Miller var. inermis Rehder (Jujube) with 344 nodes and 2237 edges. (B) Venn-diagram showing the relationship between Jujube and chronic pancreatitis (CP).
jkm-45-4-99f1.gif
Fig. 2
Process of topological screening: (A) Network illustrating the intersection of target genes from Jujube and gene sets associated with CP. (B) and (C) show the networks of the target genes during the initial and final screening, respectively.
jkm-45-4-99f2.gif
Fig. 3
GO enrichment analysis of the key genes. Top 10 biological processes, cellular components, and molecular functions were identified, ranked by the lowest p-values.
jkm-45-4-99f3.gif
Fig. 4
(A) KEGG pathway analysis of the key genes. Pathways were listed in order of significance based on their p-values. (B) SRPLOT was used to illustrate the association between the key genes and KEGG pathways.
jkm-45-4-99f4.gif
Fig. 5
The compound, target, and pathway network of Jujube in the treatment of CP. The blue represents Jujube, the sky blue represents active compounds, the green represents key genes and the yellow represents pathways.
jkm-45-4-99f5.gif
Fig. 6
(A) Results from molecular docking studies between the proteins encoded by the 9 key genes and the top 5 active compounds. (B)–(D) show the results of the top 3 structure-based blind docking poses with the lowest binding energies; (B) Ursolic acid-Akt1, (C) Ursolic acid-Stat3 and (D) Ursolic acid-Ins.
jkm-45-4-99f6.gif
Table 1
List of 55 active compounds of Jujube
Pubchem ID Compound Pubchem ID Compound
244 Benzyl Alcohol 135398638 Hypoxanthine
126 4-Hydroxybenzaldehyde 5283028 Traumatic acid
243 Benzoic Acid 21672700 Colubrinic acid
444539 Cinnamic acid 72 3,4-Dihydroxybenzoic acid
11005 Myristic Acid 689043 Caffeic acid
445638 Palmitoleic Acid 12305768 Alphitolic acid
985 Palmitic Acid 73659 Maslinic acid
5280450 Linoleic Acid 382831 Pomolic acid
445639 Oleic Acid 190 Adenine
5281 Stearic Acid 135191 D-Xylose
145742 Proline 25310 L-Rhamnose
122844 Betulonic acid 5280443 Apigenin
12313704 Oleanonic acid 525 Malic Acid
9890209 Ursonic acid 23631167 Epiceanothic Acid
338 Salicylic Acid 66308 (2S,3R,4R)-2,3,4,5-tetrahydroxypentanal
135 4-Hydroxybenzoic acid 370 Gallic acid
637542 p-Coumaric acid 135398634 Guanine
64971 Betulinic Acid 6267 Asparagine
10494 Oleanolic Acid 5793 D-glucose
64945 Ursolic Acid 18950 D-Mannose
73337 Magnoflorine 9064 Cianidanol
750 Glycine 73160 (−)-Catechin
5950 Alanine 72276 Epicatechin
6287 Valine 6029 Uridine
6106 Leucine 439215 D-Galacturonic Acid
1174 Uracil 5280343 Quercetin
8468 Vanillic Acid 60961 Adenosine
445858 Ferulic acid
Table 2
List of overlapping genes of Jujube and CP
Overlapping genes of Jujube and CP (156)
ABCB1, ABCC1, ACE, ADIPOQ, AKR1A1, AKT1, ALB, ALOX5, AMY2A, APOA1, APOB, APOE, ATF4, ATF6, BCL2, BCL2L1, BDNF, BECN1, BIRC5, CASP1, CASP3, CASP7, CASP8, CASP9, CAT, CCK, CCL2, CCNB1, CCND1, CD36, CD4, CD8A, CDH1, CDK4, CDKN1A, CHUK, COMT, CRP, CTNNB1, CXCL8, CXCR4, CYP1A1, CYP1A2, CYP2E1, DCN, DMD, EDN1, EGF, EGFR, EIF4EBP1, ELANE, FABP4, FAS, FASN, FGF21, FOS, G6PD, GCG, GCK, GIP, GLI1, GLO1, GPT, GSR, GUSB, HDAC2, HIF1A, HK2, HMGB1, HMGCR, HMOX1, HSP90B1, HSPA5, HSPB1, IAPP, ICAM1, IFI27, IFNG, IGF1, IL10, IL13, IL17A, IL18, IL1B, IL2, IL4, IL6, INS, INSR, IRS1, JAK2, JUN, LCN2, LEP, LPL, MAPK1, MAPK14, MAPK3, MAPK8, MCL1, MMP1, MMP9, MPO, MTOR, MTTP, MYC, NFE2L2, NFKB1, NLRP3, NOS2, NOX4, NQO1, PARP1, PCNA, PDX1, PIK3CA, PKM, PLA2G1B, PLAU, PNLIP, PNPLA2, POMC, PPARG, PRKCZ, PTCH1, PTEN, PTGS2, PTK2, PYY, RB1, RELA, RETN, RPS6KB1, SCT, SIRT1, SLC29A1, SLC2A1, SLC2A2, SLC2A4, SMAD3, SOD1, SOD2, SP1, SST, STAT3, TF, TGIF1, TLR4, TNF, TNFRSF10B, TP53, UGT1A1, UMPS, VIM, VIP, XDH
Table 3
The DC, BC and CC values of key genes
Key genes DC BC CC
TP53 77 0.081383665 0.645299145
IL6 75 0.045471407 0.645299145
AKT1 74 0.053877149 0.639830508
TNF 72 0.059863694 0.645299145
IL1B 69 0.0380407 0.631799163
INS 69 0.127863343 0.618852459
STAT3 68 0.044317805 0.616326531
BCL2 58 0.029624285 0.596837945
TLR4 49 0.032268605 0.569811321
Table 4
Top 4 items of KEGG pathway related to CP mechanism
Term log(p-value) Genes
HIF-1 signaling pathway −11.72372899 IL6;STAT3;BCL2;AKT1;TLR4;INS
Toll-like receptor signaling pathway −9.369048421 IL6;IL1B;AKT1;TNF;TLR4
PI3K-Akt signaling pathway −8.625714301 IL6;BCL2;AKT1;TLR4;TP53;INS
NOD-like receptor signaling pathway −8.153224401 IL6;IL1B;BCL2;TNF;TLR4

References

1. Beyer, G., Hoffmeister, A., Lorenz, P., Lynen, P., Lerch, M. M., & Mayerle, J. (2022). Clinical Practice Guideline—Acute and Chronic Pancreatitis. Dtsch Arztebl Int, 119(29–30), 495-501. DOI:https://doi.org/10.3238/arztebl.m2022.02231
crossref pmid pmc

2. Smith, S. R., Jajja, M. R., & Sarmiento, J. M. (2024). Long-term symptom resolution following the surgical management of chronic pancreatitis. The American Journal of Surgery, 115810. DOI:https://doi.org/10.1016/j.amjsurg.2024.115810
crossref pmid

3. Raimondi, S., Lowenfels, A. B., Morselli-Labate, A. M., Maisonneuve, P., & Pezzilli, R. (2010). Pancreatic cancer in chronic pancreatitis; aetiology, incidence, and early detection. Best practice & research Clinical gastroenterology, 24(3), 349-358. DOI:https://doi.org/10.1016/j.bpg.2010.02.007
crossref pmid

4. Han, M., Tran, T. P. T., & Oh, J.-K. (2022). Chronic pancreatitis and cancer risk in a matched cohort study using national claims data in South Korea. Scientific Reports, 12(1), 5545. DOI:https://doi.org/10.1038/s41598-022-09426-z
pmid pmc

5. Tong, G.-X., Geng, Q.-Q., Chai, J., Cheng, J., Chen, P.-L., & Liang, H., et al (2014). Association between pancreatitis and subsequent risk of pancreatic cancer: a systematic review of epidemiological studies. Asian Pacific Journal of Cancer Prevention, 15(12), 5029-5034. DOI:https://doi.org/10.7314/APJCP.2014.15.12.5029
crossref pmid

6. Hart, P. A., & Conwell, D. L. (2020). Chronic Pancreatitis: Managing a Difficult Disease. The American Journal of Gastroenterology, 115(1), 49-55. DOI:https://doi.org/10.14309/ajg.0000000000000421
crossref pmid pmc

7. Yin, H., Zhang, Z., Zhang, D., Peng, L., Xia, C., & Yang, X., et al (2023). A new method for treating chronic pancreatitis and preventing fibrosis using bioactive calcium silicate ion solution. Journal of Materials Chemistry B, 11(38), 9163-9178. DOI:https://doi.org/10.1039/D3TB01287E
crossref pmid

8. Mössner J.(2016). Conservative therapy of chronic pancreatitis. Pancreapedia. The Exocrine Pancreas Knowledge Base.


9. Kong, F., Pan, Y., & Wu, D. (2024). Activation and Regulation of Pancreatic Stellate Cells in Chronic Pancreatic Fibrosis: A Potential Therapeutic Approach for Chronic Pancreatitis. Biomedicines, 12(1), 108. DOI:https://doi.org/10.3390/biomedicines12010108
crossref pmid pmc

10. Han, C., Lv, Y.-W., & Hu, L.-H. (2024). Management of chronic pancreatitis: recent advances and future prospects. Therapeutic Advances in Gastroenterology, 17, 17562848241234480. DOI:https://doi.org/10.1177/17562848241234480
pmc

11. Nag, D. S., Swain, B. P., Anand, R., & Barman, T. K. (2024). Pain management in chronic pancreatitis. World Journal of Clinical Cases, 12(12), 2016. DOI:https://doi.org/10.12998/wjcc.v12.i12.2016
crossref pmid pmc

12. Tran, H. N. K., Cao, T. Q., Kim, J. A., Woo, M. H., & Min, B. S. (2019). Anti-inflammatory and cytotoxic activities of constituents isolated from the fruits of Ziziphus jujuba var. inermis Rehder. Fitoterapia, 137, 104261. DOI:https://doi.org/10.1016/j.fitote.2019.104261
crossref

13. Chen, J., Du, C. Y., Lam, K. Y., Zhang, W. L., Lam, C. T., & Yan, A. L., et al (2014). The standardized extract of Ziziphus jujuba fruit (jujube) regulates pro-inflammatory cytokine expression in cultured murine macrophages: suppression of lipopolysaccharide-stimulated NF-κB activity. Phytotherapy research, 28(10), 1527-1532. DOI:https://doi.org/10.1002/ptr.5160
pmid

14. Kim, Y., Oh, J., & Kim, J.-S. (2020). Anti-inflammatory Effect of Hydrolyzed Jujube Ethanolic Extract. The FASEB Journal, 34(S1), 1-1. DOI:https://doi.org/10.1096/fasebj.2020.34.s1.07063
crossref

15. Yu M.-H., Im H.-G., Lee H.-J., Ji Y.-J., Lee I.-S.2006. Components and their antioxidative activities of methanol extracts from sarcocarp and seed of Zizyphus jujuba var. inermis Rehder. Korean Journal of Food Science and Technology. 38:1. 128-134.


16. Resim, S., Koluş, E., Barut, O., Kucukdurmaz, F., Bahar, A. Y., & Dagli, H. (2020). Ziziphus jujube ameliorated cavernosal oxidative stress and fibrotic processes in cavernous nerve injury-induced erectile dysfunction in a rat model. Andrologia, 52(7), e13632. DOI:https://doi.org/10.1111/and.13632
pmid

17. Zhu, D., Jiang, N., Wang, N., Zhao, Y., & Liu, X. (2024). A Literature Review of the Pharmacological Effects of Jujube. Foods, 13(2), 193. DOI:https://doi.org/10.3390/foods13020193
crossref

18. Zhang, G. B., Li, Q. Y., Chen, Q. L., & Su, S. B. (2013). Network pharmacology: a new approach for chinese herbal medicine research. Evid Based Complement Alternat Med, (2013). 621423. DOI:https://doi.org/10.1155/2013/621423


19. Hopkins, A. L. (2008). Network pharmacology: the next paradigm in drug discovery. Nature chemical biology, 4(11), 682-690. DOI:https://doi.org/10.1038/nchembio.118
pmid

20. Li, L., Yang, L., Yang, L., He, C., He, Y., & Chen, L., et al (2023). Network pharmacology: a bright guiding light on the way to explore the personalized precise medication of traditional Chinese medicine. Chinese Medicine, 18(1), 146. DOI:https://doi.org/10.1186/s13020-023-00853-2
pmid pmc

21. de Anda-Jáuregui, G., Guo, K., McGregor, B. A., & Hur, J. (2018). Exploration of the anti-inflammatory drug space through network pharmacology: applications for drug repurposing. Frontiers in Physiology, 9, 151. DOI:https://doi.org/10.3389/fphys.2018.00151
pmid pmc

22. Nogales, C., Mamdouh, Z. M., List, M., Kiel, C., Casas, A. I., & Schmidt, H. H. (2022). Network pharmacology: curing causal mechanisms instead of treating symptoms. Trends in pharmacological sciences, 43(2), 136-150. DOI:https://doi.org/10.1016/j.tips.2021.11.004
crossref pmid

23. Faustino, R., & Terzic, A. (2008). Bioinformatic networks: molecular reticles for pinpointing pharmacological target selection. Clinical Pharmacology & Therapeutics, 84(5), 543-545. DOI:https://doi.org/10.1038/clpt.2008.181
crossref pmid

24. Md Aksam, V., Chandrasekaran, V., & Pandurangan, S. (2018). Topological alternate centrality measure capturing drug targets in the network of MAPK pathways. IET Systems Biology, 12(5), 226-232. DOI:https://doi.org/10.1049/iet-syb.2017.0058
pmid pmc

25. Esposito, I., Hruban, R. H., Verbeke, C., Terris, B., Zamboni, G., & Scarpa, A., et al (2020). Guidelines on the histopathology of chronic pancreatitis. Recommendations from the working group for the international consensus guidelines for chronic pancreatitis in collaboration with the International Association of Pancreatology, the American Pancreatic Association, the Japan Pancreas Society, and the European Pancreatic Club. Pancreatology, 20(4), 586-593. DOI:https://doi.org/10.1016/j.pan.2020.04.009
crossref pmid

26. Kleeff, J., Whitcomb, D. C., Shimosegawa, T., Esposito, I., Lerch, M. M., & Gress, T., et al (2017). Chronic pancreatitis. Nature reviews Disease primers, 3(1), 1-18. DOI:https://doi.org/10.1038/nrdp.2017.60


27. Jin, G., Hong, W., Guo, Y., Bai, Y., & Chen, B. (2020). Molecular mechanism of pancreatic stellate cells activation in chronic pancreatitis and pancreatic cancer. Journal of Cancer, 11(6), 1505.
crossref pmid pmc

28. Kurimoto, M., Watanabe, T., Kamata, K., Minaga, K., & Kudo, M. (2021). IL-33 as a critical cytokine for inflammation and fibrosis in inflammatory bowel diseases and pancreatitis. Frontiers in Physiology, 12, 781012. DOI:https://doi.org/10.3389/fphys.2021.781012
crossref pmid pmc

29. Chang, M., Chen, W., Xia, R., Peng, Y., Niu, P., & Fan, H. (2023). Pancreatic Stellate Cells and the Targeted Therapeutic Strategies in Chronic Pancreatitis. Molecules, 28(14), 5586. DOI:https://doi.org/10.3390/molecules28145586
crossref pmid pmc

30. Glaubitz, J., Asgarbeik, S., Lange, R., Mazloum, H., Elsheikh, H., & Weiss, F. U., et al (2023). Immune response mechanisms in acute and chronic pancreatitis: strategies for therapeutic intervention. Frontiers in Immunology, 14, 1279539. DOI:https://doi.org/10.3389/fimmu.2023.1279539
crossref pmid pmc

31. Klöppel, G., & Maillet, B. (1992). The morphological basis for the evolution of acute pancreatitis into chronic pancreatitis. Virchows Archiv A, 420, 1-4. DOI:https://doi.org/10.1007/BF01605976


32. Mariani, A., & Testoni, P. A. (2008). Is acute recurrent pancreatitis a chronic disease? World Journal of Gastroenterol, 14(7), 995-998. DOI:https://doi.org/10.3748/wjg.14.995
crossref pmid pmc

33. Shah, I., Bocchino, R., Ahmed, A., Freedman, S. D., Kothari, D. J., & Sheth, S. G. (2022). Impact of recurrent acute pancreatitis on the natural history and progression to chronic pancreatitis. Pancreatology, 22(8), 1084-1090. DOI:https://doi.org/10.1016/j.pan.2022.09.237
crossref

34. Song, C., Lee, S., Oh, S., Jeong, J., Kim, S., & Lee, S., et al (2007). A Case Report of Chronic Pancreatitis. The Journal of Korean Oriental Internal Medicine, 28(2), 391-398.


35. Moon S., Moon G., Won J. H.(1996). 新 脾系內科學. Korea. 圓光大學校韓醫科大學 脾系內科學敎室.


36. Seo, Bi, & Ro, J. H. (1999). The meaning on using decoction of Jujubae Fructus in taking herb medicines. The Korean Medicine Society for the Herbal Formula Study, 07(01), 89-98.


37. BuIl S., Dongyeul K., Hoyong C., Jehyun L., Ohmyung S., Minyoung B.(2012). Medicine Herbology. Korea. Younglim-sa.


38. Wang, L., Zhang, C., Pang, L., & Wang, Y. (2023). Integrated network pharmacology and experimental validation to explore the potential pharmacological mechanism of Qihuang Granule and its main ingredients in regulating ferroptosis in AMD. BMC Complement Med Ther, 23(1), 420. DOI:https://doi.org/10.1186/s12906-023-04205-3
pmid pmc

39. Zhao, Y., Li, H., Li, X., Sun, Y., Shao, Y., & Zhang, Y., et al (2022). Network pharmacology-based analysis and experimental in vitro validation on the mechanism of Paeonia lactiflora Pall. in the treatment for type I allergy. BMC Complement Med Ther, 22(1), 199. DOI:https://doi.org/10.1186/s12906-022-03677-z
pmid pmc

40. Wang, J., Hu, K., Cai, X., Yang, B., He, Q., & Wang, J., et al (2022). Targeting PI3K/AKT signaling for treatment of idiopathic pulmonary fibrosis. Acta Pharm Sin B, 12(1), 18-32. DOI:https://doi.org/10.1016/j.apsb.2021.07.023
crossref pmid pmc

41. Wu, Y., Wu, Y., Yu, J., Zhang, Y., Li, Y., & Fu, R., et al (2023). Irisin ameliorates D-galactose-induced skeletal muscle fibrosis via the PI3K/Akt pathway. European Journal of Pharmacology, 939, 175476. DOI:https://doi.org/10.1016/j.ejphar.2022.175476
crossref pmid

42. Qin, W., Cao, L., & Massey, I. Y. (2021). Role of PI3K/Akt signaling pathway in cardiac fibrosis. Molecular and cellular biochemistry, 476(11), 4045-4059. DOI:https://doi.org/10.1007/s11010-021-04219-w
pmid

43. Cui, L.-H., Li, C.-X., Zhuo, Y.-Z., Yang, L., Cui, N.-Q., & Zhang, S.-K. (2019). Saikosaponin d ameliorates pancreatic fibrosis by inhibiting autophagy of pancreatic stellate cells via PI3K/Akt/mTOR pathway. Chemico-Biological Interactions, 300, 18-26. DOI:https://doi.org/10.1016/j.cbi.2019.01.005
crossref pmid

44. Manohar, M., Verma, A. K., Venkateshaiah, S. U., Sanders, N. L., & Mishra, A. (2017). Pathogenic mechanisms of pancreatitis. World Journal of Gastrointestinal Pharmacology and Therapeutics, 8(1), 10-25. DOI:https://doi.org/10.4292/wjgpt.v8.i1.10
crossref pmid pmc

45. Apte, M., & Wilson, J. (2005). Mechanisms of pancreatic fibrosis. Digestive diseases, 22(3), 273-279. DOI:https://doi.org/10.1159/000082799


46. Bynigeri, R. R., Jakkampudi, A., Jangala, R., Subramanyam, C., Sasikala, M., & Rao, G. V., et al (2017). Pancreatic stellate cell: Pandora's box for pancreatic disease biology. World Journal of Gastroenterol, 23(3), 382-405. DOI:https://doi.org/10.3748/wjg.v23.i3.382
crossref pmid pmc

47. McCarroll, J. A., Phillips, P. A., Kumar, R. K., Park, S., Pirola, R. C., & Wilson, J. S., et al (2004). Pancreatic stellate cell migration: role of the phosphatidylinositol 3-kinase (PI3-kinase) pathway. Biochemical pharmacology, 67(6), 1215-1225. DOI:https://doi.org/10.1016/j.bcp.2003.11.013
crossref pmid

48. Xue, R., Yang, J., Wu, J., Meng, Q., & Hao, J. (2017). Coenzyme Q10 inhibits the activation of pancreatic stellate cells through PI3K/AKT/ mTOR signaling pathway. Oncotarget, 8(54), 92300-92311. DOI:https://doi.org/10.18632/oncotarget.21247
crossref pmid pmc

49. Mehra, S., Srinivasan, S., Singh, S., Zhou, Z., Garrido, V., & Silva, I. D. C., et al (2022). Urolithin A attenuates severity of chronic pancreatitis associated with continued alcohol intake by inhibiting PI3K/AKT/mTOR signaling. American Journal of Physiology-Gastrointestinal and Liver Physiology, 323(4), G375-G386. DOI:https://doi.org/10.1152/ajpgi.00159.2022
crossref pmid pmc

50. Xu, X., Yu, H., Sun, L., Zheng, C., Shan, Y., & Zhou, Z., et al (2020). Adipose-derived mesenchymal stem cells ameliorate dibutyltin dichloride-induced chronic pancreatitis by inhibiting the PI3K/AKT/mTOR signaling pathway. Molecular Medicine Reports, 21(4), 1833-1840. DOI:https://doi.org/10.3892/mmr.2020.10995
crossref pmid pmc

51. Ma, L., Chen, Z., Feng, M., Liu, Q., Sun, Y., & Wang, W., et al (2022). A diverse treatment with the extract of Euphorbia fischeriana Steud. and Ziziphus jujuba Mill. for breast cancer nude mice of MCF-7 (ER+) cells or MDA-MB-453 (ER-) cells via modulation of the PI3k/Akt signalling pathway. Pharmacological Research - Modern Chinese Medicine, 5, 100198. DOI:https://doi.org/10.1016/j.prmcm.2022.100198
crossref

52. Tu, H., Ma, D., Luo, Y., Tang, S., Li, Y., & Chen, G., et al (2021). Quercetin alleviates chronic renal failure by targeting the PI3k/Akt pathway. Bioengineered, 12(1), 6538-6558. DOI:https://doi.org/10.1080/21655979.2021.1973877
crossref pmid pmc

53. Wu, W., Wu, X., Qiu, L., Wan, R., Zhu, X., & Chen, S., et al (2024). Quercetin influences intestinal dysbacteriosis and delays alveolar epithelial cell senescence by regulating PTEN/PI3K/AKT signaling in pulmonary fibrosis. Naunyn-Schmiedeberg's Archives of Pharmacology, 397(7), 4809-4822. DOI:https://doi.org/10.1007/s00210-023-02913-8


54. Wu, L., Zhang, Q., Mo, W., Feng, J., Li, S., & Li, J., et al (2017). Quercetin prevents hepatic fibrosis by inhibiting hepatic stellate cell activation and reducing autophagy via the TGF-β1/Smads and PI3K/Akt pathways. Scientific Reports, 7(1), 9289. DOI:https://doi.org/10.1038/s41598-017-09673-5
pmid pmc

55. Qiao, M., Yang, J., Zhu, Y., Zhao, Y., & Hu, J. (2020). Transcriptomics and proteomics analysis of system-level mechanisms in the liver of apigenin-treated fibrotic rats. Life sciences, 248, 117475. DOI:https://doi.org/10.1016/j.lfs.2020.117475
crossref pmid

56. Meng, Y., Lin, Z. M., Ge, N., Zhang, D. L., Huang, J., & Kong, F. (2015). Ursolic Acid Induces Apoptosis of Prostate Cancer Cells via the PI3K/Akt/mTOR Pathway. The American Journal of Chinese Medicine, 43(7), 1471-1486. DOI:https://doi.org/10.1142/S0192415X15500834
crossref pmid

57. Zheng, S., Ma, M., Chen, Y., & Li, M. (2022). Effects of quercetin on ovarian function and regulation of the ovarian PI3K/Akt/FoxO3a signalling pathway and oxidative stress in a rat model of cyclophosphamide-induced premature ovarian failure. Basic Clin Pharmacol Toxicol, 130(2), 240-253. DOI:https://doi.org/10.1111/bcpt.13696
pmid

58. Yu, W., Sun, H., Zha, W., Cui, W., Xu, L., & Min, Q., et al (2017). Apigenin Attenuates Adriamycin-Induced Cardiomyocyte Apoptosis via the PI3K/AKT/mTOR Pathway. Evid Based Complement Alternat Med, (2017). 2590676. DOI:https://doi.org/10.1155/2017/2590676


59. He, W., Shi, F., Zhou, Z.-W., Li, B., Zhang, K., & Zhang, X., et al (2015). A bioinformatic and mechanistic study elicits the antifibrotic effect of ursolic acid through the attenuation of oxidative stress with the involvement of ERK, PI3K/Akt, and p38 MAPK signaling pathways in human hepatic stellate cells and rat liver. Drug Design, Development and Therapy, 3989-4104. DOI:http://dx.doi.org/10.2147/DDDT.S85426


60. Li, J., Liang, X., & Yang, X. (2012). Ursolic acid inhibits growth and induces apoptosis in gemcitabine-resistant human pancreatic cancer via the JNK and PI3K/Akt/NF-κB pathways. Oncology reports, 28(2), 501-510. DOI:https://doi.org/10.3892/or.2012.1827
crossref pmid

Editorial office contact information
3F, #26-27 Gayang-dong, Gangseo-gu Seoul, 157-200 Seoul, Korea
The Society of Korean Medicine
Tel : +82-2-2658-3627   Fax : +82-2-2658-3631   E-mail : skom1953.journal@gmail.com
About |  Browse Articles |  Current Issue |  For Authors and Reviewers
Developed in M2PI