Zhimei Lv

807 total citations · 1 hit paper
15 papers, 460 citations indexed

About

Zhimei Lv is a scholar working on Molecular Biology, Nephrology and Cancer Research. According to data from OpenAlex, Zhimei Lv has authored 15 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 7 papers in Nephrology and 4 papers in Cancer Research. Recurrent topics in Zhimei Lv's work include Renal Diseases and Glomerulopathies (4 papers), Cancer-related molecular mechanisms research (4 papers) and Chronic Kidney Disease and Diabetes (3 papers). Zhimei Lv is often cited by papers focused on Renal Diseases and Glomerulopathies (4 papers), Cancer-related molecular mechanisms research (4 papers) and Chronic Kidney Disease and Diabetes (3 papers). Zhimei Lv collaborates with scholars based in China. Zhimei Lv's co-authors include Rong Wang, Jiangong Lin, Qiang Wan, Mengsi Hu, Qun Wang, Junhui Zhen, Yi Liu, Junhui Zhen, Qiqi Ma and Minghua Fan and has published in prestigious journals such as PLoS ONE, Biochemical and Biophysical Research Communications and Kidney International.

In The Last Decade

Zhimei Lv

15 papers receiving 460 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Mitochondrial metabolic reprogramming in diabetic kidney disease

2024 42 citations Ying Gao, Zhimei Lv et al. Cell Death and Disease profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Zhimei Lv China	12	234	149	73	55	46	15	460
Xing Mao China	11	171 0.7×	159 1.1×	51 0.7×	67 1.2×	41 0.9×	18	446
Pengchao Du China	9	302 1.3×	162 1.1×	46 0.6×	74 1.3×	54 1.2×	18	537
Xianglan Quan South Korea	9	245 1.0×	149 1.0×	37 0.5×	70 1.3×	88 1.9×	15	497
Chakradhar Velagapudi United States	8	254 1.1×	77 0.5×	47 0.6×	50 0.9×	51 1.1×	11	463
Bridgit B. Bowskill Canada	10	237 1.0×	166 1.1×	44 0.6×	59 1.1×	68 1.5×	11	457
Shan Xiong China	10	153 0.7×	83 0.6×	57 0.8×	65 1.2×	42 0.9×	18	350
Shirley Wang United States	9	280 1.2×	115 0.8×	62 0.8×	65 1.2×	91 2.0×	16	591
Ranjan Das South Korea	11	236 1.0×	173 1.2×	25 0.3×	68 1.2×	84 1.8×	20	522
Steven D. Funk United States	13	282 1.2×	81 0.5×	48 0.7×	38 0.7×	77 1.7×	16	638
Xiujin Shen China	10	246 1.1×	136 0.9×	38 0.5×	29 0.5×	48 1.0×	17	419

Countries citing papers authored by Zhimei Lv

Since Specialization

Citations

This map shows the geographic impact of Zhimei Lv's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zhimei Lv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhimei Lv more than expected).

Fields of papers citing papers by Zhimei Lv

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhimei Lv. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zhimei Lv. The network helps show where Zhimei Lv may publish in the future.

Co-authorship network of co-authors of Zhimei Lv

This figure shows the co-authorship network connecting the top 25 collaborators of Zhimei Lv. A scholar is included among the top collaborators of Zhimei Lv based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zhimei Lv. Zhimei Lv is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Lv, Zhimei, et al.. (2024). LncRNA PVT1 induces mitochondrial dysfunction of podocytes via TRIM56 in diabetic kidney disease. Cell Death and Disease. 15(9). 697–697. 7 indexed citations

Gao, Ying, et al.. (2024). Mitochondrial metabolic reprogramming in diabetic kidney disease. Cell Death and Disease. 15(6). 442–442. 42 indexed citations breakdown →

Lv, Zhimei, et al.. (2024). TRAIL induces podocyte PANoptosis via death receptor 5 in diabetic kidney disease. Kidney International. 107(2). 317–331. 15 indexed citations

Zhen, Junhui, Cheng Wang, Huimin Chen, et al.. (2023). Long noncoding RNA ENST00000436340 promotes podocyte injury in diabetic kidney disease by facilitating the association of PTBP1 with RAB3B. Cell Death and Disease. 14(2). 130–130. 23 indexed citations

Zhao, Yanfang, Junhui Zhen, Xia Li, et al.. (2023). ROS promote hyper-methylation of NDRG2 promoters in a DNMTS-dependent manner: Contributes to the progression of renal fibrosis. Redox Biology. 62. 102674–102674. 34 indexed citations

Su, Hong, Bing Liu, Huimin Chen, et al.. (2022). LncRNA ANRIL mediates endothelial dysfunction through BDNF downregulation in chronic kidney disease. Cell Death and Disease. 13(7). 661–661. 25 indexed citations

Liu, Bing, Jiao Qiao, Minghua Fan, et al.. (2020). Leptin promotes endothelial dysfunction in chronic kidney disease by modulating the MTA1-mediated WNT/β-catenin pathway. Molecular and Cellular Biochemistry. 473(1-2). 155–166. 15 indexed citations

Su, Hong, Jiao Qiao, Yanmei Li, et al.. (2020). Podocyte-derived extracellular vesicles mediate renal proximal tubule cells dedifferentiation via microRNA-221 in diabetic nephropathy. Molecular and Cellular Endocrinology. 518. 111034–111034. 44 indexed citations

Hu, Mengsi, Minghua Fan, Junhui Zhen, et al.. (2016). FAK contributes to proteinuria in hypercholesterolaemic rats and modulates podocyte F‐actin re‐organization via activating p38 in response to ox‐LDL. Journal of Cellular and Molecular Medicine. 21(3). 552–567. 18 indexed citations

10.

Liu, Bing, et al.. (2016). Leptin promotes endothelial dysfunction in chronic kidney disease through AKT/GSK3β and β-catenin signals. Biochemical and Biophysical Research Communications. 480(4). 544–551. 21 indexed citations

11.

Lv, Zhimei, Mengsi Hu, Minghua Fan, et al.. (2016). Fyn Mediates High Glucose-Induced Actin Cytoskeleton Reorganization of Podocytes via Promoting ROCK Activation In Vitro. Journal of Diabetes Research. 2016. 1–13. 39 indexed citations

12.

Xu, Ying, Wei Xin, Liyong Chen, et al.. (2014). Lipid accumulation is ahead of epithelial-to-mesenchymal transition and therapeutic intervention by acetyl-CoA carboxylase 2 silence in diabetic nephropathy. Metabolism. 63(5). 716–726. 56 indexed citations

13.

Zhang, Pengju, Mingfeng Cao, Yi Liu, et al.. (2012). PDGF-induced airway smooth muscle proliferation is associated with Human antigen R activation and could be weakened by AMPK activation. Molecular Biology Reports. 39(5). 5819–5829. 8 indexed citations

14.

Lv, Zhimei, Yi Liu, Pengju Zhang, et al.. (2012). The Role of AMPKαin High-Glucose-Induced Dysfunction of Cultured Rat Mesangial Cells. Renal Failure. 34(5). 616–621. 10 indexed citations

15.

Lv, Zhimei, Qun Wang, Qiang Wan, et al.. (2011). The Role of the p38 MAPK Signaling Pathway in High Glucose-Induced Epithelial-Mesenchymal Transition of Cultured Human Renal Tubular Epithelial Cells. PLoS ONE. 6(7). e22806–e22806. 103 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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