David J. Nikolic‐Paterson

21.5k total citations · 4 hit papers
244 papers, 17.6k citations indexed

About

David J. Nikolic‐Paterson is a scholar working on Nephrology, Immunology and Molecular Biology. According to data from OpenAlex, David J. Nikolic‐Paterson has authored 244 papers receiving a total of 17.6k indexed citations (citations by other indexed papers that have themselves been cited), including 119 papers in Nephrology, 81 papers in Immunology and 73 papers in Molecular Biology. Recurrent topics in David J. Nikolic‐Paterson's work include Renal Diseases and Glomerulopathies (72 papers), Chronic Kidney Disease and Diabetes (65 papers) and Macrophage Migration Inhibitory Factor (35 papers). David J. Nikolic‐Paterson is often cited by papers focused on Renal Diseases and Glomerulopathies (72 papers), Chronic Kidney Disease and Diabetes (65 papers) and Macrophage Migration Inhibitory Factor (35 papers). David J. Nikolic‐Paterson collaborates with scholars based in Australia, United States and China. David J. Nikolic‐Paterson's co-authors include Hui Y. Lan, Xiao‐Ming Meng, Robert C. Atkins, Greg H. Tesch, R. C. Atkins, Elyce Ozols, Y. Frank, Patrick Ming‐Kuen Tang, Robert C. Atkins and Prudence A. Hill and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

David J. Nikolic‐Paterson

238 papers receiving 17.4k citations

Hit Papers

4 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.

TGF-β: the master regulator of fibrosis

2016 2.7k citations Xiao‐Ming Meng, David J. Nikolic‐Paterson et al. Nature Reviews Nephrology profile →
Macrophages: versatile players in renal inflammation and fibrosis

2019 737 citations Patrick Ming‐Kuen Tang, David J. Nikolic‐Paterson et al. Nature Reviews Nephrology profile →
Inflammatory processes in renal fibrosis

2014 571 citations Xiao‐Ming Meng, David J. Nikolic‐Paterson et al. Nature Reviews Nephrology profile →
Macrophage-to-Myofibroblast Transition Contributes to Interstitial Fibrosis in Chronic Renal Allograft Injury

2017 323 citations Xiao-Ru Huang, Ka‐Fai To et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David J. Nikolic‐Paterson Australia	70	6.0k	5.9k	4.7k	2.5k	2.2k	244	17.6k
Marta Ruiz‐Ortega Spain	70	4.7k 0.8×	6.9k 1.2×	2.7k 0.6×	2.0k 0.8×	1.8k 0.8×	265	18.2k
Ariela Benigni Italy	77	5.6k 0.9×	5.8k 1.0×	2.2k 0.5×	3.1k 1.3×	2.0k 0.9×	335	18.9k
Detlef Schlöndorff Germany	70	3.7k 0.6×	4.6k 0.8×	5.3k 1.1×	1.5k 0.6×	1.5k 0.7×	237	14.9k
Katalin Suszták United States	61	6.1k 1.0×	8.2k 1.4×	1.6k 0.4×	1.8k 0.7×	1.5k 0.7×	190	16.1k
Stuart J. Shankland United States	70	8.4k 1.4×	6.8k 1.2×	1.8k 0.4×	1.5k 0.6×	1.5k 0.7×	229	15.2k
Yashpal S. Kanwar United States	59	3.7k 0.6×	6.3k 1.1×	1.6k 0.3×	1.6k 0.6×	1.0k 0.5×	234	13.8k
Carla Zoja Italy	69	4.8k 0.8×	3.4k 0.6×	2.4k 0.5×	2.0k 0.8×	1.2k 0.5×	192	13.3k
Benjamin D. Humphreys United States	71	4.9k 0.8×	8.6k 1.5×	2.0k 0.4×	2.6k 1.1×	2.9k 1.3×	184	16.9k
Rolf A.K. Stahl Germany	59	4.8k 0.8×	2.9k 0.5×	3.4k 0.7×	865 0.3×	1.9k 0.9×	257	12.2k
Karl A. Nath United States	72	3.8k 0.6×	7.0k 1.2×	1.6k 0.3×	1.8k 0.7×	1.9k 0.9×	219	15.7k

Countries citing papers authored by David J. Nikolic‐Paterson

Since Specialization

Citations

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

Fields of papers citing papers by David J. Nikolic‐Paterson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Nikolic‐Paterson. 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 David J. Nikolic‐Paterson. The network helps show where David J. Nikolic‐Paterson may publish in the future.

Co-authorship network of co-authors of David J. Nikolic‐Paterson

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

All Works

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20 of 20 papers shown

Ozols, Elyce, et al.. (2025). Spleen tyrosine kinase signaling in myeloid cells promotes macrophage infiltration, glomerulosclerosis, and interstitial fibrosis in diabetic kidney disease. American Journal of Physiology-Renal Physiology. 329(6). F872–F882.

Mulley, William R., Kevan R. Polkinghorne, Greg H. Tesch, et al.. (2025). A randomized controlled trial of intravenous immunoglobulin vs standard of care for the treatment of chronic active antibody-mediated rejection in kidney transplant recipients. Kidney International. 108(3). 470–480. 1 indexed citations

Santos, Leilani L., et al.. (2025). Comparative Analysis of Human Kidney Organoid and Tubuloid Models. Kidney360. 6(7). 1073–1084. 1 indexed citations

Meng, Xiao‐Ming, Li Wang, David J. Nikolic‐Paterson, & Hui Y. Lan. (2025). Innate immune cells in acute and chronic kidney disease. Nature Reviews Nephrology. 21(7). 464–482. 11 indexed citations

Haruhara, Kotaro, David J. Nikolic‐Paterson, Peter G. Kerr, et al.. (2024). Podocyte number and glomerulosclerosis indices are associated with the response to therapy for primary focal segmental glomerulosclerosis. Frontiers in Medicine. 11. 1343161–1343161.

Zhong, Yu, Biao Wei, Wenbiao Wang, et al.. (2024). Single-Cell RNA-Sequencing Identifies Bone Marrow-Derived Progenitor Cells as a Main Source of Extracellular Matrix-Producing Cells Across Multiple Organ-Based Fibrotic Diseases. International Journal of Biological Sciences. 20(13). 5027–5042. 7 indexed citations

Tian, Lifang, Greg H. Tesch, Elyce Ozols, et al.. (2021). Mice with Established Diabetes Show Increased Susceptibility to Renal Ischemia/Reperfusion Injury. American Journal Of Pathology. 192(3). 441–453. 5 indexed citations

Ozols, Elyce, William R. Mulley, Roger J. Davis, et al.. (2021). JUN Amino-Terminal Kinase 1 Signaling in the Proximal Tubule Causes Cell Death and Acute Renal Failure in Rat and Mouse Models of Renal Ischemia/Reperfusion Injury. American Journal Of Pathology. 191(5). 817–828. 12 indexed citations

Andrikopoulos, Sofianos, Richard J. MacIsaac, Laura K. Mackay, et al.. (2021). Role of the adaptive immune system in diabetic kidney disease. Journal of Diabetes Investigation. 13(2). 213–226. 46 indexed citations

10.

Tang, Patrick Ming‐Kuen, Patrick Ming‐Kuen Tang, Yingying Zhang, et al.. (2020). Neural transcription factor Pou4f1 promotes renal fibrosis via macrophage–myofibroblast transition. Proceedings of the National Academy of Sciences. 117(34). 20741–20752. 120 indexed citations

11.

Meng, Xiao‐Ming, David J. Nikolic‐Paterson, & Hui Y. Lan. (2016). TGF-β: the master regulator of fibrosis. Nature Reviews Nephrology. 12(6). 325–338. 2651 indexed citations breakdown →

12.

Sun, Yu, Xinli Qu, Victor Howard, et al.. (2015). Smad3 deficiency protects mice from obesity-induced podocyte injury that precedes insulin resistance. Kidney International. 88(2). 286–298. 44 indexed citations

13.

Qu, Xinli, Mengjie Jiang, Yu Sun, et al.. (2015). The Smad3/Smad4/CDK9 complex promotes renal fibrosis in mice with unilateral ureteral obstruction. Kidney International. 88(6). 1323–1335. 17 indexed citations

14.

Tesch, Greg H., Karly C. Sourris, Shaun A. Summers, et al.. (2014). Deletion of bone-marrow-derived receptor for AGEs (RAGE) improves renal function in an experimental mouse model of diabetes. Diabetologia. 57(9). 1977–1985. 26 indexed citations

15.

Tesch, Greg H., Scott A. Summers, D M McCarthy, et al.. (2014). Deficiency of rage in bone marrow cells reduces renal injury in diabetic mice. Queensland's institutional digital repository (The University of Queensland). 1 indexed citations

16.

Assis, David N., Lin Leng, Xin Du, et al.. (2013). The Role of Macrophage Migration Inhibitory Factor in Autoimmune Liver Disease. Hepatology. 59(2). 580–591. 89 indexed citations

17.

Nikolic‐Paterson, David J.. (2003). A role for macrophages in mediating tubular cell apoptosis?. Kidney International. 63(4). 1582–1583. 5 indexed citations

18.

Jinde, Kiichiro, David J. Nikolic‐Paterson, Hideto Sakai, et al.. (2001). Tubular phenotypic change in progressive tubulointerstitial fibrosis in human glomerulonephritis. American Journal of Kidney Diseases. 38(4). 761–769. 127 indexed citations

19.

Hattori, Motoshi, David J. Nikolic‐Paterson, Hui Y. Lan, et al.. (1999). Mechanisms of glomerular macrophage infiltration in lipid-induced renal injury. Kidney International. 56. S47–S50. 58 indexed citations

20.

Hayes, Richard B., et al.. (1996). Secretion of Bioactive Interleukin 1 by Rat Testicular Macrophages In Vitro. Journal of Andrology. 17(1). 41–49. 53 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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