PANG Xinxin,ZHU Qing,PENG Zining,ZHANG Yage,SHI Xiujie,HAN Jiarui
PANG Xinxin,ZHU Qing,PENG Zining,ZHANG Yage,SHI Xiujie,HAN Jiarui,Department of Nephropathy,Henan Provincial Hospital of Traditional Chinese Medicine,Zhengzhou 450002,China
Abstract OBJECTIVE:To explore the mechanism of hirudin in the treatment of diabetic kidney disease (DKD).METHOD:Cytoscape software was used to analyze the network between hirudin targets and active components in the treatment of DKD.The biological function and mechanism of effective targets of hirudin for DKD treatment were analyzed by the Database for Annotation,Visualization and Integrated Discovery (DAVID) database.Molecular docking technology was used to simulate the docking of key targets,and the DKD rat model was used to verify the first 4 key targets with high "Hydrogen number" among the top 10 targets verified by molecular docking.RESULTS:Total of 12334 DKD targets were screened in GeneCards,OMIM and other databases,Hirudin and DKD had 247 common target genes,and the protein interaction network got 2115 edges.The DAVID database was used for the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis,confirming that hirudin in treatment of DKD involves multiple signaling pathways such as the forkhead box O signaling pathway,the phosphatidylinositol 3-kinase-protein kinase B signaling pathway,the vascular endothelial-derived growth factor signaling pathway and other signaling pathways.The top ten key targets of hirudin in treatment of DKD were verified by molecular docking.Animal experiments showed that hirudin could decrease the expression of caspase-3 in renal tissue of DKD rats,and increase the expression of RAC-alpha serine/threonineprotein kinase,Catalase,and Heat shock protein HSP 90-alpha in renal tissue of DKD rats.CONCLUSION:This study preliminarily reveals that hirudin treats DKD through multiple targets and pathways,and molecular docking and animal experiments indicates the feasibility of this study.Hirudin may be directly or indirectly involved in the regulation of cell metabolism,oxidative stress and other mechanisms in the treatment of DKD,which will lay the foundation for future molecular biological experiments of hirudin in the treatment of DKD.
Keywords:hirudins;diabetic kidney disease;network pharmacology;molecular docking simulation
Diabetic kidney disease (DKD) is a common complication of diabetic microvascular,and its incidence has increased significantly in recent years.Research shows that approximately 20% of the 400 million diabetics worldwide have DKD.At present,modern medicine mainly treats DKD by regulating blood pressure,blood lipids,lowering glucose and other traditional methods,as well as developing new drugs such as Dapagliflozin and Linagliptin.However,DKD is still the primary reason for dialysis.1
In recent years,many scholars have found that Traditional Chinese Medicine plays an increasingly important role in the treatment of DKD.2Traditional Chinese Medicine believes blood stasis is the core pathogenesis of DKD throughout the course of the disease.Therefore,drugs for promoting blood circulation and eliminating stasis are often used to treat DKD.3Leech is a common clinical medicine for promoting blood circulation and eliminating stasis.Hirudin is a natural thrombin inhibitor extracted from leeches.It can resist blood clotting and reduce inflammation.4Our previous studies have shown that hirudin can play a therapeutic effect on DKD.5,6However,the potential mechanism involved in the treatment of DKD with hirudin remains to be further studied.
In this study,we aim to explore and verify the molecular mechanisms and pathways of hirudin in the treatment of DKD based on a network pharmacology with molecular docking and animal experiments validation,so as to provide references for further basic and clinical research of hirudin for the treatment of DKD.
The SDF file of hirudin was downloaded from the PubChem database and uploaded to the PharmMapper server,7where small molecular compounds were optimized to generate multiple conformations.The parameters were set as follows:Generate Conformers:Yes;Maximum Generated Conformations:300;Select Targets Se:All Targets (V2010,7302);Number of Reserved Matched Targets (Max 1000):300.All target prediction results were ranked according to Fit Score from high to low,and species were selected as "Homo sapiens" target for subsequent analysis.The naming of compound targets was retrieved through the UniProt database specification,the protein name was entered and the species was qualified as “human”.
GeneCards8is a public integrated database."Diabetic kidney disease" and "Diabetic nephropathy" were selected as the key words and all the targets related to DKD were screened in GeneCards,selected and supplemented appropriately in OMIM,9DisGeNET,10Drug Bank11and other databases.The venn diagram of the target and the effective target of hirudin was drawn.
Based on the intersection target obtained from the Venn diagram,hirudin and DKD were introduced,and these data were made into a visual network diagram using Cytoscape 3.7.2 software.Among them,"rectangle"represented the target protein,"triangle" represented the compound,"diamond" represented the disease and"edges" represented the relationship between the compound,target and disease,so as to explore the relationship between them.Finally,the diseasecompound-target regulatory network diagram of hirudin treatment of DKD was obtained.
Protein-protein interaction (PPI) can help to explore the potential interactions between proteins,discover new drug targets.The STRING database was used to construct the PPI network of the intersection of hirudin target and DKD target to obtain the core target.The screening parameter settings mainly included:the biological organism was selected as human,and the minimum interaction score was set to the maximum confidence level of 0.4.
The RCSB PDB database was used to find the top 10 core targets of hirudin and hirudin treatment with the highest DKD degree.First,pymol was used to remove water and remove impurities.AutoDockTools 1.5.6 software was used to optimize ligands (hirudin) and receptors (top ten target proteins).Those data before molecular docking were processed,such as hydrogenation of the receptor,calculation of charge,addition of atom type,route determination of ligand,etc.and saved in PDB format.Auto DockTools were used to perform molecular docking for the best matching method.Pymol software was used to optimize the diagram.
The Database for Annotation,Visualization and Integrated Discovery (DAVID) database was used to annotate effective targets.The correlation between genes and diseases was discovered through the DAVID database.DAVID tool was used for GO enrichment analysis of hirudin-DKD mutual target genes.At the same time,enrichment analysis of the KEGG pathway of hirudin-DKD interaction target gene was performed by DAVID tool,and the main pathway of hirudin treatment of DKD was obtained.GO and KEGG enrichment analysis was conducted to investigate the biological functions that hirudin potential targets might have and the biological pathways involved. Statistical hypergeometric distribution quantification (Padjust value) was adjusted to assess the significance of the biological function and pathway enrichment of proteins present in each GO and KEGG annotation.The redder thePadjust value in the figure,the more significant it was.
A total of 21 specific pathogen free-grade Sprague-Dawley (SD) rats (male,6 weeks old,180-200 g) were used in this study,and 14 rats were used to established a DKD model by intraperitoneal injection of 100 mg/kg streptozotocin (STZ,V900890,Sigma-Aldrich,St.Louis,MO,USA).We measured the blood glucose of tail vein on the third day after STZ injection,and selected rats with the blood glucose of tail vein >16.7 mmol/L as the standard for the model of diabetic rats.5One week after STZ injection,we administered 5 U hirudin (cat# 94,581,Sigma-Aldrich,St.Louis,MO,USA) daily by subcutaneous injection for rats in DKD+Hirudin,and others DKD rats in DKD group and normal rats in Control group were given the same dose of physiological saline solution.We defined the first day of the study was the day that we injected STZ,and at 16th week,7 rats/group was sacrificed.
In addition,the animal experiment in this study has been approved by the Ethical review Committee of Experimental Animal welfare in Henan Hospital of Traditional Chinese Medicine.Because this article is a data class article,there is no reference number.The experiment was carried out in the central laboratory of Henan Provincial Hospital of Traditional Chinese Medicine.
After 16 weeks,the rats were sacrificed and one side of the kidney was quickly extracted under asepsis,and half of the kidney was fixed in 10% formaldehyde,embedded in paraffin,and finally made into 4 µm thin sections for Masson and PAS staining.Histopathological changes were observed under light microscope and photographed.
We used an animal tissue/cell RNA extraction kit (cat#CW0580S,NuoYang Biological,Hangzhou,China) to extract total RNA from tissues and cells according to manufacturer’s instructions.cDNA was prepared using a real-time (RT) reagent kit (cat# RR047A,Takara,Kyoto,Japan) according to manufacturer’s instructions.We prepared 20 μL of the RT-qPCR system as described in the quantitative polymerase chain reaction (qPCR)master mix kit instructions (cat# A600A,Promega,Madison,WI,USA).The relative expression of genes was calculated by the 2–ΔΔCtmethod.The primers used were as follows:RAC-alpha serine/threonine-protein kinase (AKT1) forward:ATGAACGACGT-AGCCATTGTG,reverse:TTGTAGCCAATAA-AGGTGCCAT;Catalase (CAT) forward:CCTCCTCG-TTCAAG-ATGTGGTTTTC,reverse:CGTGGGTGA-CCTC-AAAGATCCAAA;Caspase-3 (CASP3) forward:AGAGCGGACTGCGGTATTGAG,reverse:GAAC-CATGACCCGTCCCTTG;Heat shock protein HSP 90-alpha(HSP90AA1) forward:ACAAGCA-CAT-ATGGCTGCAGCA,reverse:TTCAGTTACAGC-AGCACTGTATC;GAPDH forward:GTGCCA-GCCTCGTCCATAG,reverse:CTTTGTCACAA-GAGAAGGCAG.
Protein levels were analyzed by Western blotting.Briefly,we extracted total proteins from tissues using RIPA lysis buffer (Solarbio,Beijing,China) and isolated 40 micrograms of total proteins using SDS-PAGE and transferred them to PVDF membranes (Thermo Fisher Scientific,Waltham,MA,USA).Bolts were sealed with 5% no-fat milk-PBS buffer for 1 h at room temperature,followed by primary antibodies to CASP3 (AF6311,Affinity Biosciences,Columbus,OH,USA),AKT1(AF4718,Affinity Biosciences,Columbus,OH,USA),CAT (Ab217793,Abcam,Cambridge,UK),HSP90AA1(Ab2928,Abcam,Cambridge,UK),β-actin (Ab8227,Abcom,Cambridge,UK) were detected at 4 ℃ after three overnight washings with PBS-Tain,and the blots were then incubated with goat anti-mouse IgG and goat anti-rabbit IgG for 1 h at room temperature.Finally,ECL solution (WBKLS0100,Beijing New Jinko Biotechnology Co.,Ltd.,Beijing,China) was added for detection,and the gray value of protein bands was analyzed by IMAG J 3.0.
All experimental data were analyzed using SPSS 21.0 statistical software (IBM Corp.,Armonk,NY,USA),and measurement data was expressed as mean ± standard deviation ().One-way analysis of variance was used for comparison among groups,least significant difference test was used for homogeneity of variance,and Dunnett's T3 test was used for heterogeneity of variance.P<0.05 was considered statistically significant.
The structure of hirudin (PubChem CID:16131390) was obtained by searching the compound structure of hirudin in the PubChem database.The hirudin targets were predicted by PharmMapper and the Naming of compound targets was regularized from the UniProt database specification.In the end,a total of 286 hirudin target genes related to humans were obtained.
By screening DKD related targets in GeneCards,OMIM,DisGeNET,and other databases,after deleting duplicates,a total of 12 334 disease-related targets were obtained.The intersection of the effective targets of hirudin and DKD was taken to obtain 247 common target genes(Supplementary Figure 1).
Cytoscape software was used to visualize the diseasechemist-target interaction of hirudin in the DKD network.The 247 genes screened by effective target genes of the active component of hirudin and DKD related target genes were included,and the network visualization figure was got (Figure 1).
Figure 1 The network diagram of hirudin-diabetic kidney disease-target
PPI analysis was carried out on 247 interacting targets of hirudin-DKD using STRING database,and 247 nodes,2115 edges,and an average degree of freedom of 17.1(nodes represent targets and edges represent interaction relationships between targets) were obtained.The PPI diagram was obtained after hiding the discrete nodes(Figure 2).The more enrichment nodes there are,the closer the target position is to the center.The PPI relationship was analyzed to obtain the top 30 core targets of hirudin-DKD (Figure 3).The main targets are ALB,AKT1,epidermal growth factor receptor (EGFR),SRC,CAT,mitogen-activated protein kinase 8(MAPK8),CASP3,HRAS and other targets.
Figure 2 PPI relationship diagram of hirudin and DKD
The DAVID tool was used to analyze the core genes of the intersection of hirudin and DKD,and 151 kinds of biological functions of the targets that hirudin could treat DKD were obtained.After comprehensive analysis,the first 20 functional properties were selected to obtain the effective component targets of hirudin,and DKD was treated mainly through these biological functional properties,such as coenzyme binding,endopeptidase activity,amide binding,serine/threonine protein kinase activity,etc.(Figure 4).Then,KEGG signaling pathway analysis was performed with the DAVID tool to explore 78 signaling pathways of DKD treated with hirudin,and the first 20 signaling pathways were selected after comprehensive analysis.KEGG analysis showed that the effective target of hirudin in the treatment of DKD mainly acts on the phosphatidylinositol 3-kinase (PI3K)-protein kinase B (AKT) signaling pathway,MAPK signaling pathway,forkhead box O (FoxO) signaling pathway,vascular endothelial-derived growth factor(VEGF) signaling pathway,Ras signaling pathway and other signaling pathways (Figure 5).Among them,the redder the bubble color was,the more significant it was,and the larger the bubble was,the more targets were enriched in this biological function or this pathway (all results were in line withPadjust <0.05,which was significant).
Figure 3 Core target map of hirudin in the treatment of diabetic kidney disease
Figure 4 Related biological functions of hirudin in the treatment of diabetic kidney disease
Figure 5 Key signaling pathway of hirudin in the treatment of diabetic kidney disease
The ligand and receptor were optimized in Pymol and AutoDockTools 1.5.6.The PDB data of the receptor and the hydrogen bond results of molecular docking were shown in Table 1,and the optimal binding mode was verified by molecular docking.Three hydrogen bonds were formed between hirudin and amino acid residues of ALA-553,LYS-525 and LYS-402 on ALB for connection;six hydrogen bonds were formed between hirudin and amino acid residues of ARG-23,ARG-25,ARG-86,LYS-14 and GLN-79 on AKT1 for connection;three hydrogen bonds were formed between hirudin and amino acid residues of LYS-754,LYS-875 and THR-751 on EGFR for connection,etc.(Table 1,Figure 6).
Table 1 Molecular docking data of the core target of diabetic kidney disease treated by hirudin
In this study,we assessed differences in renal pathology between groups using PAS,and Masson staining.The glomeruli,renal tubules and interstitial structures of normal control group rats were normal,uniform and clear,without pathological changes,and the renal tissues were normal.PAS staining showed that,compared with normal control group,glomerular basement membrane in DKD group was thickened,and there were different degrees of positive reactions in renal tubular basement membrane,which was purple red.Compared with the DKD group,the PAS positive substance in the DKD+hirudin group decreased,and the purplish red distribution decreased.Masson staining showed that in DKD group,compared with normal control group,there were blue colloids deposits,collagen fibers in glomeruli,renal interstitial fibrosis,and purple red substance deposits in glomerular basement membrane and mesangial membrane.Compared with the DKD group,the color deposition of DKD+hirudin group was significantly reduced,the renal interstitial fibrosis was milder,and the glomerular collagen fibers were reduced (Supplementary Figure 2).
Figure 6 Optimal binding mode of the main active component of hirudin and the key target protein of diabetic kidney disease a-j of them correspond to the molecular docking diagrams of 1-10 proteins bound to hirudin in Table 1,respectively.
RT-PCR analysis and Western blot analysis were performed on the top 4 key targets with high "Hydrogen number" among the top 10 targets verified by molecular docking.RT-PCR analysis showed that compared with the normal control group,the mRNA expression level of CASP3 in DKD group was significantly increased (P<0.01),and the mRNA expression levels of AKT1,CAT and HSP90AA1 were significantly decreased(P<0.01 or <0.05).After 16 weeks of hirudin treatment,the mRNA levels of CASP3 in DKD+hirudin group were significantly decreased compared with DKD group (P<0.05),and the mRNA levels of AKT1,CAT and HSP90AA1 were significantly increased (P<0.05),as shown in Supplementary Figure 3.Western blot analysis showed that compared with normal control group,the protein expression level of CASP3 in DKD group was significantly increased (P<0.01),and the protein expression levels of AKT1,CAT and HSP90AA1 were significantly decreased (P<0.01 or <0.05).After 16 weeks of hirudin treatment,compared with DKD group,the protein expression of CASP3 in DKD+hirudin group was significantly decreased (P<0.05),and the protein expression levels of AKT1,CAT and HSP90AA1 were significantly increased (P<0.05) (Figure 7).
Figure 7 Effects of hirudin on protein expression levels of CASP3,AKT1,CAT and HSP90AA1 in renal tissues of DKD rats
DKD is one of the most common chronic complications of diabetes.The clinical treatment is mainly to regulate blood glucose,blood lipids and control blood pressure.12Although it can relieve some of the symptoms,the most patients develop severely impaired renal function in the later stage and inevitably rely on renal replacement therapy.Therefore,we need to conduct in-depth research on DKD to find new treatment methods and targets.
The Traditional Chinese Medicine believed that blood stasis is the central link in the formation of DKD.2Professor Zhao Jinxi13believed that DKD is caused by damage to the kidneys based on the combined effects of phlegm-heat and blood stasis in diabetes.Tonget al14believed that blood stasis is the main cause of DKD.Therefore,drugs for promoting blood circulation and eliminating stasis are widely used in the treatment of DKD.
Leech is a traditional Chinese medicine commonly used to promote blood circulation and eliminate stasis.Studies have shown that the application of leeches can reduce renal damage in clinical.15Hirudin is the main active ingredient of leeches and has many pharmacological effects such as anticoagulation and anti-inflammatory reactions.In our previous study,we found that hirudin can inhibits inflammation through the P38 MAPK/NFκB pathway to prevent kidney damage in streptozotocin induced DKD rats.16Fanet al17also proved that hirudin can slow down the renal fibrosis of DKD.However,the current research on the pharmacological effects of hirudin in the treatment of DKD is not comprehensive enough.It is still necessary to further explore the potential mechanism of hirudin in the treatment of DKD and provide better guidance for clinical treatment.
Network pharmacology belongs to the branch of pharmacology,which can closely strengthen the connection between traditional Chinese medicine and contemporary pharmacology.18In this study,through the analysis of network pharmacology,it is concluded that hirudin can treat DKD mainly acts on ALB,AKT1,EGFR,CAT and other related target genes.Among them,AKT can participate in autophagy and is closely related to DKD.19EGFR may be involved in cardiovascular remodeling caused by renal blood flow,and it plays an important role in the early stage of renal compensation.20CAT deficiency can increase the kidney damage of DKD.21
GO analysis with DAVID tool showed that hirudin-DKD target genes act on DKD mainly through multiple biological functions such as coenzyme binding,endopeptidase activity,amide binding,etc.KEGG analysis showed that the signaling pathways related to the hirudin treatment of DKD mainly involved FoxO signaling pathway,PI3K-AKT signaling pathway,VEGF signaling pathway,MAPK signaling pathway,Ras signaling pathway,etc.In the FoxO signaling pathway,FoxO protein regulates the transcription of target genes involved in metabolism,22and its abnormal expression can lead to metabolic disease.23In the PI3KAKT signaling pathway,PI3K can activate AKT and regulate cell proliferation,movement and other functions.24Studies have shown that by stimulating the P13K-AKT pathway,it can reduce kidney damage.25MAPK can be divided into four subgroups.Among them,P38 is involved in the intracellular signal transduction in the process of inflammatory injury of kidney tissue.26VEGF promotes angiogenesis,inhibits endothelial cell apoptosis,increases their permeability,promotes cell migration,and protects the integrity of the glomerulus when it performs filtration function.27These pathways involve oxidative stress,inflammatory response,cell metabolism,and other mechanisms,so they may be an important mechanism for hirudin to treat DKD.
We further used molecular docking to show that the top ten target genes of hirudin in the treatment of DKD all have binding activity with hirudin molecules.We further conducted animal experiments on the top 4 key targets with high "hydrogen number" among the top 10 targets obtained by molecular docking verification,confirming that hirudin can reduce the expression of CASP3 and increase the expression of AKT1,CAT and HSP90AA1 in renal tissue of DKD rats.Among them,AKT1 is involved in a variety of cell signal transduction processes such as glucose metabolism,apoptosis,cell proliferation and migration.28It has been shown that in a mouse model of unilateral ureteral obstruction,AKT1 deficiency may lead to renal fibrosis by inducing the TGFβ1/ STAT3 pathway.29CAT is highly expressed in the liver,kidney,and lung,and its deficiency can sensitively sensitize the residual kidney to epithelial to mesenchymal transition leading to progressive renal fibrosis.30ASP3 is known as a representative effector of apoptosis and has recently been shown to be a mediator of pyroptosis.31Meanwhile,it has been shown that inhibition of NF-κB and CASP3 signaling pathway can reduce the kidney from gentamicin-induced nephrotoxicity in rats.32HSP90AA1 is a major cytoplasmic isomeric and one of the most abundant proteins in cells.Studies have shown that intrarenal transfection of HSP90AA1 can prevent ischemia/eperfusion injury.33These studies are consistent with our findings.
In this study,a combination of network pharmacological prediction,molecular docking and animal experiments were used to verify the target of hirudin and the mechanism in the treatment of DKD.We proved that hirudin can act on DKD through different signaling pathways,including PI3K-AKT signaling pathway and MAPK signaling pathway and other signaling pathways,as well as through multiple targets and biological functions.It is inferred that hirudin may be directly or indirectly involved in the regulation of cell metabolism,growth,differentiation and oxidative stress and play a therapeutic role in DKD.Based on this multidisciplinary strategy,the present study provided a promising approach for the treatment of DKD using Traditional Chinese Medicine.However,there are also some limitations existing in the current research.Firstly,the public databases investigated in the study are constantly updated,thus,some other target genes may not have been included in our analysis;In addition,the pathway of hirudin in DKD treatment were not further discussed in this paper,and furtherin vivo,in vitroexperiments and clinical trials are needed to verify it.
1.Ding XQ,Zhu JM.Research progress,existing problems and prospect of the diagnosis and treatment of diabetic nephropathy.Shanghai Yi Xue 2018;41:73-7.
2.Mu X,zhuang AW,Ma GL,et al.Cluster analysis of TCM syndromes in 237 patients with clinical stage diabetic nephropathy.Zhong Hua Zhong Yi Yao Xue Kan 2016;34:332-5.
3.Guo Q,Chen ZQ,Fang J,et al.Effect of Traditional Chinese Medicine for removing blood stasis and collaterals on laboratory indexes related to collaterals of diabetic nephropathy rats.Zhong Hua Zhong Yi Yao Za Zhi 2016;31:5188-91.
4.Yan YY,Pan SY,Lin BJ,et al.Effects of natural hirudin on the angiogenesis of ischemic flaps in rats.Zhong Guo Xiu Fu Chong Jian Wai Ke Za Zhi 2020;34:382-6.
5.Pang XX,Zhang YG,Peng ZN,et al.Hirudin reduces nephropathy microangiopathy in STZ-induced diabetes rats by inhibiting endothelial cell migration and angiogenesis.Life Sci 2020;255:117779.
6.Pang XX,Zhang YG,Shi XJ,et al.Hirudin reduces the expression of markers of the extracellular matrix in renal tubular epithelial cells in a rat model of diabetic kidney disease through the hypoxiainducible factor-1α (HIF-1α)/vascular endothelial growth factor(VEGF) signaling pathway.Med Sci Monit 2020;26:e921894.
7.Wang X,Shen Y,Wang S,et al.PharmMapper 2017 update:a web server for potential drug target identification with a comprehensive target pharmacophore database.Nucleic Acids Res 2017;45:356-60.
8.Stelzer G,Rosen N,Plaschkes I,et al.The genecards suite:from gene data mining to disease genome sequence analyses.Curr Protoc Bioinformatics 2016;54:1-30.
9.Amberger JS,Bocchini CA,Schiettecatte F,et al.OMIM.org:Online Mendelian Inheritance in Man (OMIM®),an online catalog of human genes and genetic disorders.Nucleic Acids Res 2015;43:789-98.
10.Piñero J,Ramírez-Anguita JM,Saüch-Pitarch J,et al.The DisGeNET knowledge platform for disease genomics:2019 update.Nucleic Acids Res 2020;48:845-55.
11.Law V,Knox C,Djoumbou Y,et al.DrugBank 4.0:shedding new light on drug metabolism.Nucleic Acids Res 2014;42:1091-7.
12.Thomas MC,Brownlee M,Susztak K,et al.Diabetic kidney disease.Nat Rev Dis Primers 2015;1:15018.
13.Xiao Y,Zhao JX.Zhao Jin-xi's experience in the treatment of diabetic nephropathy.Zhong Hua Zhong Yi Yao Za Zhi 2018;33:159-62.
14.Tong XL,Zhou Q,Zhao LH,et al.Experience of differentiation and treatment of diabetic nephropathy in Chinese medicine.Zhong Hua Zhong Yi Yao Za Zhi 2014;29:144-6.
15.Pang XX,Tong Y,Li XP,et al.Research progress of leech and its extract in the treatment of diabetic nephropathy.Guang Ming Zhong Yi 2019;34:168-71.
16.Han JR,Pang XX,Zhang YG,et al.Hirudin protects against kidney damage in streptozotocin-induced diabetic nephropathy rats by inhibiting inflammationviaP38 MAPK/NF-κB pathway.Drug Des Devel Ther 2020;14:3223-34.
17.Fan L,Dong ZH,Yang HX,et al.Study on the mechanism of hirudin alleviating human renal tubular epithelial cell fibrosis through JAK/STAT3 signaling pathway.Zhong Yao Cai 2018;41:982-5.
18.Xie J,Gao S,Li L,et al.Research progress and application strategy of network pharmacology in Traditional Chinese Medicine.Zhong Cao Yao 2019;50:2257-65.
19.Wu DP,Xiao Y,Zhang YY,et al.Regulation of the PTEN/AKT/mTOR pathway on autophagy in diabetic rat renal tissue.Zhong Yi Sheng Li Bing Li Za Zhi 2016;32:2015-9.
20.Feng M,Teng WH,Jiang WW,et al.Role of epidermal growth factor receptor in cardiovascular remodeling in rats with renal vascular hypertension.Zhong Guo Yao Li Xue Tong Bao 2016;32:625-31.
21.Hwang I,Lee J,Huh JY,et al.Catalase deficiency accelerates diabetic renal injury through peroxisomal dysfunction.Diabetes 2012;61:728-38.
22.Wang M,Wang Q,Wang Z,et al.The molecular evolutionary patterns of the insulin/FOXO signaling pathway.Evol Bioinform Online 2013;9:1-16.
23.Lee S,Dong HH.FoxO integration of insulin signaling with glucose and lipid metabolism.J Endocrinol 2017;233:67-79.
24.Wang XM,Yao M,Liu SX,et al.Interplay between the Notch and PI3K/Akt pathways in high glucose-induced podocyte apoptosis.Am J Physiol Renal Physiol 2014;306:205-13.
25.Li CF,Cao YD,LI H,et al.Effect of combined treatment of senile diabetic nephropathy on inflammatory factors and pi3K-Akt pathay in mononuclear cells.Mian Yi Xue Za Zhi 2018;34:683-9.
26.Declèves AE,Sharma K.Novel targets of antifibrotic and anti-inflammatory treatment in CKD.Nat Rev Nephrol 2014;10:257-67.
27.Melincovici CS,Boşca AB,Şuşman S,et al.Vascular endothelial growth factor (VEGF) -key factor in normal and pathological angiogenesis.Rom J Morphol Embryol 2018;59:455-67.
28.Lan A,Du J.Potential role of Akt signaling in chronic kidney disease.Nephrol Dial Transplant 2015;30:385-94.
29.Kim IY,Lee MY,Park MW,et al.Deletion of Akt1 promotes kidney fibrosis in a murine model of unilateral ureteral obstruction.Biomed Res Int 2020;2020:6143542.
30.Irazabal MV,Torres VE.Reactive oxygen species and redox signaling in chronic kidney disease.Cells 2020;9:1342.
31.Jin L,Luo ZY,Lu A.Piperlongumine induces apoptosis and pyroptosis of NCI-H460 lung cancer cellsviaincreasing ROS.Zhong Guo Yao Xue Za Zhi 2020;55:1002-1007.
32.Abdelrahman RS,Abdelmageed ME.Renoprotective effect of celecoxib against gentamicin-induced nephrotoxicity through suppressing NFκB and caspase-3 signaling pathways in rats.Chem Biol Interact 2020;315:108863.
33.Barrera-Chimal J,Pérez-Villalva R,Ortega JA,et al.Intra-renal transfection of heat shock protein 90 alpha or beta (Hsp90αor Hsp90β) protects against ischemia/reperfusion injury.Nephrol Dial Transplant 2014;29:301-12.
Journal of Traditional Chinese Medicine2022年4期