N. Chai

1.0k total citations
19 papers, 822 citations indexed

About

N. Chai is a scholar working on Immunology, Cancer Research and Genetics. According to data from OpenAlex, N. Chai has authored 19 papers receiving a total of 822 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Immunology, 6 papers in Cancer Research and 4 papers in Genetics. Recurrent topics in N. Chai's work include T-cell and B-cell Immunology (8 papers), Immune Cell Function and Interaction (7 papers) and Protease and Inhibitor Mechanisms (3 papers). N. Chai is often cited by papers focused on T-cell and B-cell Immunology (8 papers), Immune Cell Function and Interaction (7 papers) and Protease and Inhibitor Mechanisms (3 papers). N. Chai collaborates with scholars based in United States and China. N. Chai's co-authors include Tripathi B. Rajavashisth, Prediman K. Shah, Stefan Jovinge, Xiaoping Xu, Stanley C. Jordan, Gordon D. Wu, Andrew S. Klein, Irene Kim, Behrooz G. Sharifi and Michael C. Fishbein and has published in prestigious journals such as Journal of Biological Chemistry, Circulation and Biochemical and Biophysical Research Communications.

In The Last Decade

N. Chai

19 papers receiving 813 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
N. Chai United States 12 291 236 216 179 152 19 822
Christopher R. Longo United States 13 274 0.9× 265 1.1× 336 1.6× 202 1.1× 86 0.6× 14 904
Mathijs Groeneweg Netherlands 13 169 0.6× 322 1.4× 270 1.3× 107 0.6× 72 0.5× 30 753
K. S. Srinivasa Prasad United States 11 90 0.3× 369 1.6× 253 1.2× 156 0.9× 107 0.7× 12 1.2k
Sippie Huitema Netherlands 15 180 0.6× 194 0.8× 315 1.5× 123 0.7× 57 0.4× 24 977
Parmeet K. Manchanda India 19 102 0.4× 181 0.8× 496 2.3× 158 0.9× 197 1.3× 30 958
Annalisa Altimari Italy 20 255 0.9× 70 0.3× 380 1.8× 269 1.5× 389 2.6× 72 1.1k
Roberto Scorza Italy 15 361 1.2× 206 0.9× 204 0.9× 94 0.5× 316 2.1× 19 859
Kwang‐Sun Suh South Korea 15 235 0.8× 130 0.6× 235 1.1× 105 0.6× 183 1.2× 55 802
Ewelina Kulikowski United States 19 76 0.3× 86 0.4× 771 3.6× 169 0.9× 159 1.0× 49 1.2k
Hajnalka Andrikovics Hungary 21 86 0.3× 151 0.6× 463 2.1× 155 0.9× 272 1.8× 90 1.2k

Countries citing papers authored by N. Chai

Since Specialization
Citations

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

Fields of papers citing papers by N. Chai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of N. Chai

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

All Works

19 of 19 papers shown
1.
Zheng, Wei, et al.. (2025). Paeoniflorin attenuates cisplatin induced ototoxicity by inhibiting ferroptosis mediated by HMGB1/NRF2/GPX4 pathway. Food and Chemical Toxicology. 202. 115550–115550. 1 indexed citations
2.
Kim, Irene, Gordon D. Wu, N. Chai, Andrew S. Klein, & Stanley C. Jordan. (2017). Ibrutinib suppresses alloantibody responses in a mouse model of allosensitization. Transplant Immunology. 45. 59–64. 6 indexed citations
3.
Kim, Irene, Gordon D. Wu, N. Chai, Andrew S. Klein, & Stanley C. Jordan. (2016). Immunological characterization of de novo and recall alloantibody suppression by CTLA4Ig in a mouse model of allosensitization. Transplant Immunology. 38. 84–92. 27 indexed citations
4.
Wu, Gordon D., et al.. (2015). Evidence That CTLA4Ig Attenuates Recall Alloantibody Responses By Interacting With Antibody Forming Cells. The Journal of Heart and Lung Transplantation. 34(4). S265–S266. 1 indexed citations
5.
Wu, Gordon D., et al.. (2014). CTLA4Ig Differentially Suppresses De Novo and Recall Alloantibody Responses in a Mouse Model of HLA.A2 Allosensitization.. Transplantation. 98. 674–674. 1 indexed citations
6.
Kim, Irene, Gordon D. Wu, N. Chai, Andrew S. Klein, & Stanley C. Jordan. (2014). Anti–Interleukin 6 Receptor Antibodies Attenuate Antibody Recall Responses in a Mouse Model of Allosensitization. Transplantation. 98(12). 1262–1270. 60 indexed citations
7.
Wu, Gordon D., N. Chai, Irene Kim, Andrew S. Klein, & Stanley C. Jordan. (2013). Monoclonal anti-interleukin-6 receptor antibody attenuates donor-specific antibody responses in a mouse model of allosensitization. Transplant Immunology. 28(2-3). 138–143. 43 indexed citations
8.
Wu, Gordon D., et al.. (2013). Anti-IL6R Attenuates Humoral Responses to Allograft in a Mouse Model of Allosensitization. The Journal of Heart and Lung Transplantation. 32(4). S245–S245. 1 indexed citations
9.
Ge, Shili, Ashley Vo, Joseph Kahwaji, et al.. (2010). Immunologic parameters and viral infections in patients desensitized with intravenous immunoglobulin and rituximab. Transplant Immunology. 24(3). 142–148. 13 indexed citations
10.
He, Yao, Tomohito Sadahiro, Hong Wang, et al.. (2009). Flow cytometric isolation and phenotypic characterization of two subsets of ED2+ (CD163) hepatic macrophages in rats. Hepatology Research. 39(12). 1208–1218. 10 indexed citations
11.
Wu, Gordon D., Yao He, N. Chai, et al.. (2008). Anti-CD20 antibody suppresses anti-HLA antibody formation in a HLA-A2 transgenic mouse model of sensitization. Transplant Immunology. 19(3-4). 178–186. 12 indexed citations
12.
Zhou, Shengmei, Offir Paz, Ji‐Min Cao, et al.. (2005). Differential β-adrenoceptor expression induced by nerve growth factor infusion into the canine right and left stellate ganglia. Heart Rhythm. 2(12). 1347–1355. 20 indexed citations
13.
Wang, Charles, Marjorie Chelly, N. Chai, et al.. (2004). Transcriptomic fingerprinting of bone marrow-derived hepatic β2m−/Thy-1+ stem cells. Biochemical and Biophysical Research Communications. 327(1). 252–260. 13 indexed citations
14.
Chelly, Marjorie, et al.. (2004). Transcriptomic fingerprints of Beta2m−/Thy1+ bone marrow stem cells derived from common bile duct-ligated rats. Journal of the American College of Surgeons. 199(3). 11–11. 1 indexed citations
15.
Uzui, Hiroyasu, Liu Ming, Terence M. Doherty, et al.. (2002). Increased Expression of Membrane Type 3-Matrix Metalloproteinase in Human Atherosclerotic Plaque. Circulation. 106(24). 3024–3030. 141 indexed citations
16.
Rajavashisth, Tripathi B., James K. Liao, Zorina S. Galis, et al.. (1999). Inflammatory Cytokines and Oxidized Low Density Lipoproteins Increase Endothelial Cell Expression of Membrane Type 1-Matrix Metalloproteinase. Journal of Biological Chemistry. 274(17). 11924–11929. 164 indexed citations
17.
Rajavashisth, Tripathi B., Xiaoping Xu, Stefan Jovinge, et al.. (1999). Membrane Type 1 Matrix Metalloproteinase Expression in Human Atherosclerotic Plaques. Circulation. 99(24). 3103–3109. 224 indexed citations
18.
19.
Chai, N.. (1997). A putative human male infertility gene DAZLA: genomic structure and methylation status. Molecular Human Reproduction. 3(8). 705–708. 36 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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