Anping Xu

1.8k total citations
42 papers, 1.3k citations indexed

About

Anping Xu is a scholar working on Nephrology, Immunology and Molecular Biology. According to data from OpenAlex, Anping Xu has authored 42 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Nephrology, 15 papers in Immunology and 11 papers in Molecular Biology. Recurrent topics in Anping Xu's work include Chronic Kidney Disease and Diabetes (10 papers), Acute Kidney Injury Research (7 papers) and Systemic Lupus Erythematosus Research (5 papers). Anping Xu is often cited by papers focused on Chronic Kidney Disease and Diabetes (10 papers), Acute Kidney Injury Research (7 papers) and Systemic Lupus Erythematosus Research (5 papers). Anping Xu collaborates with scholars based in China, Hong Kong and United States. Anping Xu's co-authors include Ying Tang, Hui Y. Lan, Junzhe Chen, Patrick Ming‐Kuen Tang, Min Feng, Erik Fung, Xiao‐Ru Huang, Sheng Nie, Yan Zha and Gang Xu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Kidney International and Frontiers in Immunology.

In The Last Decade

Anping Xu

40 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anping Xu China 21 489 397 221 174 167 42 1.3k
Shuangxin Liu China 21 587 1.2× 450 1.1× 181 0.8× 186 1.1× 168 1.0× 97 1.5k
Ka‐Bik Lai Hong Kong 23 927 1.9× 556 1.4× 303 1.4× 132 0.8× 167 1.0× 56 1.8k
Belinda Jim United States 22 707 1.4× 593 1.5× 341 1.5× 178 1.0× 151 0.9× 57 2.3k
Jianwei Tian China 24 605 1.2× 506 1.3× 109 0.5× 146 0.8× 191 1.1× 66 1.5k
Chun‐Gyoo Ihm South Korea 23 561 1.1× 421 1.1× 264 1.2× 137 0.8× 211 1.3× 56 1.5k
Yi Tang China 21 564 1.2× 220 0.6× 104 0.5× 114 0.7× 168 1.0× 102 1.2k
María C. Izquierdo Spain 17 765 1.6× 643 1.6× 287 1.3× 170 1.0× 60 0.4× 26 1.8k
Maria R. Wing United States 15 426 0.9× 445 1.1× 101 0.5× 161 0.9× 145 0.9× 18 1.3k
Meixiao Sheng China 10 295 0.6× 356 0.9× 167 0.8× 252 1.4× 180 1.1× 19 1.3k
Wei Ren China 18 290 0.6× 334 0.8× 122 0.6× 302 1.7× 124 0.7× 71 1.2k

Countries citing papers authored by Anping Xu

Since Specialization
Citations

This map shows the geographic impact of Anping Xu'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 Anping Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anping Xu more than expected).

Fields of papers citing papers by Anping Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anping Xu. 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 Anping Xu. The network helps show where Anping Xu may publish in the future.

Co-authorship network of co-authors of Anping Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Anping Xu. A scholar is included among the top collaborators of Anping Xu 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 Anping Xu. Anping Xu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Jie, et al.. (2022). MALDI-TOF-MS for rapid screening analysis of M-protein in serum. Frontiers in Oncology. 12. 1073479–1073479. 6 indexed citations
2.
Tang, Ying, Qiuyan Huang, Sha Fu, et al.. (2021). Systematic review and subgroup analysis of the incidence of acute kidney injury (AKI) in patients with COVID-19. BMC Nephrology. 22(1). 52–52. 37 indexed citations
3.
Chen, Junzhe, Honghui Zeng, Mingsheng Zhu, et al.. (2020). The incidence, risk factors, and long-term outcomes of acute kidney injury in hospitalized diabetic ketoacidosis patients. BMC Nephrology. 21(1). 48–48. 38 indexed citations
4.
Dang, Junlong, Anping Xu, Yan Liu, et al.. (2020). Human gingiva-derived mesenchymal stem cells are therapeutic in lupus nephritis through targeting of CD39−CD73 signaling pathway. Journal of Autoimmunity. 113. 102491–102491. 36 indexed citations
5.
Liao, Weitang, Bo Liu, Lili Zhang, et al.. (2020). MicroRNA-140-5p Mediates Renal Fibrosis Through TGF-β1/Smad Signaling Pathway by Directly Targeting TGFBR1. Frontiers in Physiology. 11. 1093–1093. 28 indexed citations
6.
Fu, Sha, Junzhe Chen, Bo Liu, et al.. (2020). Systemic inflammation modulates the ability of serum ferritin to predict all-cause and cardiovascular mortality in peritoneal dialysis patients. BMC Nephrology. 21(1). 237–237. 12 indexed citations
7.
Li, Jinhong, Ying Tang, Patrick Ming‐Kuen Tang, et al.. (2018). Blocking Macrophage Migration Inhibitory Factor Protects Against Cisplatin-Induced Acute Kidney Injury in Mice. Molecular Therapy. 26(10). 2523–2532. 52 indexed citations
8.
Tang, Ying, Junzhe Chen, Sha Fu, et al.. (2018). The baseline levels and risk factors for high-sensitive C-reactive protein in Chinese healthy population. Immunity & Ageing. 15(1). 21–21. 34 indexed citations
9.
Tang, Ying, Junzhe Chen, Kai Huang, et al.. (2017). The incidence, risk factors and in-hospital mortality of acute kidney injury in patients after abdominal aortic aneurysm repair surgery. BMC Nephrology. 18(1). 184–184. 41 indexed citations
10.
Feng, Min, Patrick Ming‐Kuen Tang, Xiao‐Ru Huang, et al.. (2017). TGF-β Mediates Renal Fibrosis via the Smad3-Erbb4-IR Long Noncoding RNA Axis. Molecular Therapy. 26(1). 148–161. 128 indexed citations
11.
Tang, Ying, Lin Liu, Hui Yang, et al.. (2017). Low level of circulating basophil counts in biopsy-proven active lupus nephritis. Clinical Rheumatology. 37(2). 459–465. 16 indexed citations
12.
Lai, Weiyan, Ying Tang, Xiao Ru Huang, et al.. (2016). C-reactive protein promotes acute kidney injury via Smad3-dependent inhibition of CDK2/cyclin E. Kidney International. 90(3). 610–626. 60 indexed citations
13.
Ge, Shuwang, Sheng Nie, Zhangsuo Liu, et al.. (2016). Epidemiology and outcomes of acute kidney injury in elderly chinese patients: a subgroup analysis from the EACH study. BMC Nephrology. 17(1). 136–136. 41 indexed citations
14.
Chen, Junzhe, Ying Tang, Mingsheng Zhu, & Anping Xu. (2016). Heart involvement in systemic lupus erythematosus: a systemic review and meta-analysis. Clinical Rheumatology. 35(10). 2437–2448. 68 indexed citations
15.
Feng, Min, Philip Chiu‐Tsun Tang, Yong‐Ke You, et al.. (2015). Long Non-coding RNA_5318 is a Novel Therapeutic Target for Renal Fibrosis in Obstructive Nephropathy. Hong Kong Journal of Nephrology. 17(2). S62–S63. 1 indexed citations
16.
17.
Feng, Min, Jun Lv, Sha Fu, et al.. (2014). Clinical features and mortality in Chinese with lupus nephritis and neuropsychiatric lupus: A 124-patient study. SHILAP Revista de lepidopterología. 8 indexed citations
18.
Tang, Ying, Sha Fu, Jun Lv, et al.. (2014). Basophil count, a marker for disease activity in systemic lupus erythematosus. Clinical Rheumatology. 34(5). 891–896. 20 indexed citations
19.
Tang, Ying, Xiao Ru Huang, Jun Lv, et al.. (2013). C-reactive protein promotes acute kidney injury by impairing G1/S-dependent tubular epithelium cell regeneration. Clinical Science. 126(9). 645–659. 60 indexed citations
20.
Xu, Anping, et al.. (2007). Osteopontin gene polymorphism in association with systemic lupus erythematosus in Chinese patients. Chinese Medical Journal. 120(23). 2124–2128. 28 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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