145 related articles for article (PubMed ID: 38053423)
21. Seven basement membrane-specific expressed genes are considered potential biomarkers for the diagnosis and treatment of diabetic nephropathy.
Gui H; Chen X; Ye L; Ma H
Acta Diabetol; 2023 Apr; 60(4):493-505. PubMed ID: 36627452
[TBL] [Abstract][Full Text] [Related]
22. An integrated network pharmacology and transcriptomic method to explore the mechanism of the total Rhizoma Coptidis alkaloids in improving diabetic nephropathy.
Xiao Y; Liu Y; Lai Z; Huang J; Li C; Zhang Y; Gong X; Deng J; Ye X; Li X
J Ethnopharmacol; 2021 Apr; 270():113806. PubMed ID: 33444721
[TBL] [Abstract][Full Text] [Related]
23. Exploring the mechanisms underlying the therapeutic effect of Salvia miltiorrhiza in diabetic nephropathy using network pharmacology and molecular docking.
Zhang L; Han L; Wang X; Wei Y; Zheng J; Zhao L; Tong X
Biosci Rep; 2021 Jun; 41(6):. PubMed ID: 33634308
[TBL] [Abstract][Full Text] [Related]
24. Identification of Lipotoxicity-Related Biomarkers in Diabetic Nephropathy Based on Bioinformatic Analysis.
Nie H; Yang H; Cheng L; Yu J
J Diabetes Res; 2024; 2024():5550812. PubMed ID: 38774257
[No Abstract] [Full Text] [Related]
25. Identification of Key Genes of Human Advanced Diabetic Nephropathy Independent of Proteinuria by Transcriptome Analysis.
Cai F; Zhou X; Jia Y; Yao W; Lv J; Liu G; Yang L
Biomed Res Int; 2020; 2020():7283581. PubMed ID: 32685522
[TBL] [Abstract][Full Text] [Related]
26. Identification of co-expressed central genes and transcription factors in acute myocardial infarction and diabetic nephropathy.
Li B; Zhao X; Xie W; Hong Z; Cao Y; Zhang Y; Ding Y
BMC Med Genomics; 2024 May; 17(1):134. PubMed ID: 38764052
[TBL] [Abstract][Full Text] [Related]
27. Whole Transcriptomic Analysis of Key Genes and Signaling Pathways in Endogenous ARDS.
Xie Y; Luo J; Hu W; Ye C; Ren P; Wang Y; Li X
Dis Markers; 2022; 2022():1614208. PubMed ID: 36246560
[TBL] [Abstract][Full Text] [Related]
28. Microarray analysis reveals long non‑coding RNA SOX2OT as a novel candidate regulator in diabetic nephropathy.
Zhang X; Shang J; Wang X; Cheng G; Jiang Y; Liu D; Xiao J; Zhao Z
Mol Med Rep; 2018 Dec; 18(6):5058-5068. PubMed ID: 30320339
[TBL] [Abstract][Full Text] [Related]
29. Integrative analyses of biomarkers and pathways for diabetic nephropathy.
Li B; Zhao X; Xie W; Hong Z; Zhang Y
Front Genet; 2023; 14():1128136. PubMed ID: 37113991
[No Abstract] [Full Text] [Related]
30. Identification of pyroptosis-related genes and potential drugs in diabetic nephropathy.
Yan M; Li W; Wei R; Li S; Liu Y; Huang Y; Zhang Y; Lu Z; Lu Q
J Transl Med; 2023 Jul; 21(1):490. PubMed ID: 37480090
[TBL] [Abstract][Full Text] [Related]
31. PTGER3 and MMP-2 play potential roles in diabetic nephropathy via competing endogenous RNA mechanisms.
Yu Y; Jia YY; Wang M; Mu L; Li HJ
BMC Nephrol; 2021 Jan; 22(1):27. PubMed ID: 33435900
[TBL] [Abstract][Full Text] [Related]
32. Weighted gene co-expression network analysis of key targets and interventional mechanism of Milkvetch root in diabetic nephropathy.
Zeng SN; Li Y; Li YM; Wang SR
Eur Rev Med Pharmacol Sci; 2023 Oct; 27(20):9614-9627. PubMed ID: 37916327
[TBL] [Abstract][Full Text] [Related]
33. Identification of potential crosstalk genes and mechanisms between periodontitis and diabetic nephropathy through bioinformatic analysis.
Lu H; Sun J; Sun J
Medicine (Baltimore); 2023 Dec; 102(52):e36802. PubMed ID: 38206700
[TBL] [Abstract][Full Text] [Related]
34. LINC01018 and SMIM25 sponged miR-182-5p in endometriosis revealed by the ceRNA network construction.
Jiang L; Zhang M; Wang S; Xiao Y; Wu J; Zhou Y; Fang X
Int J Immunopathol Pharmacol; 2020; 34():2058738420976309. PubMed ID: 33237828
[TBL] [Abstract][Full Text] [Related]
35. Apoptosis and NETotic cell death affect diabetic nephropathy independently: An study integrative study encompassing bioinformatics, machine learning, and experimental validation.
Cai H; Zeng Y; Luo D; Shao Y; Liu M; Wu J; Gao X; Zheng J; Zhou L; Liu F
Genomics; 2024 Jul; 116(4):110879. PubMed ID: 38851464
[TBL] [Abstract][Full Text] [Related]
36. Prediction of the molecular mechanisms and potential therapeutic targets for diabetic nephropathy by bioinformatics methods.
Wang WN; Zhang WL; Zhou GY; Ma FZ; Sun T; Su SS; Xu ZG
Int J Mol Med; 2016 May; 37(5):1181-8. PubMed ID: 26986014
[TBL] [Abstract][Full Text] [Related]
37. Revealing the underlying mechanism of diabetic nephropathy viewed by microarray analysis.
Qu W; Han C; Li M; Zhang J; Li L
Exp Clin Endocrinol Diabetes; 2015 Jun; 123(6):353-9. PubMed ID: 25918880
[TBL] [Abstract][Full Text] [Related]
38. Identification of novel targets of diabetic nephropathy and PEDF peptide treatment using RNA-seq.
Rubin A; Salzberg AC; Imamura Y; Grivitishvilli A; Tombran-Tink J
BMC Genomics; 2016 Nov; 17(1):936. PubMed ID: 27855634
[TBL] [Abstract][Full Text] [Related]
39. Identification and prediction of novel non-coding and coding RNA-associated competing endogenous RNA networks in colorectal cancer.
Liang Y; Zhang C; Ma MH; Dai DQ
World J Gastroenterol; 2018 Dec; 24(46):5259-5270. PubMed ID: 30581274
[TBL] [Abstract][Full Text] [Related]
40. The whole profiling and competing endogenous RNA network analyses of noncoding RNAs in adipose-derived stem cells from diabetic, old, and young patients.
Ren S; Xiong H; Chen J; Yang X; Liu Y; Guo J; Jiang T; Xu Z; Yuan M; Liu Y; Zhou N; Chen H; Li W; Machens HG; Chen Z
Stem Cell Res Ther; 2021 May; 12(1):313. PubMed ID: 34051854
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]