Hsin-Jung Wu

5.2k total citations · 4 hit papers
20 papers, 3.7k citations indexed

About

Hsin-Jung Wu is a scholar working on Immunology, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Hsin-Jung Wu has authored 20 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Immunology, 6 papers in Molecular Biology and 4 papers in Infectious Diseases. Recurrent topics in Hsin-Jung Wu's work include Immune Cell Function and Interaction (8 papers), Immunotherapy and Immune Responses (6 papers) and T-cell and B-cell Immunology (6 papers). Hsin-Jung Wu is often cited by papers focused on Immune Cell Function and Interaction (8 papers), Immunotherapy and Immune Responses (6 papers) and T-cell and B-cell Immunology (6 papers). Hsin-Jung Wu collaborates with scholars based in United States, United Kingdom and Japan. Hsin-Jung Wu's co-authors include Eric Wu, Diane Mathis, Christophe Benoıst, Dan R. Littman, Kimie Hattori, Tatsuichiro Shima, Jaime Darce, Yoshinori Umesaki, Ivaylo I. Ivanov and Esen Sefik and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and Immunity.

In The Last Decade

Hsin-Jung Wu

20 papers receiving 3.7k citations

Hit Papers

Gut-Residing Segmented Filamentous Bacteria Drive Autoimm... 2010 2026 2015 2020 2010 2012 2016 2021 250 500 750 1000

Peers

Hsin-Jung Wu
Martin Kriegel United States
Kristine A. Kuhn United States
Craig L. Maynard United States
Karin Allenspach United States
Joris van der Veeken United States
Suxia Yao United States
Martin Kriegel United States
Hsin-Jung Wu
Citations per year, relative to Hsin-Jung Wu Hsin-Jung Wu (= 1×) peers Martin Kriegel

Countries citing papers authored by Hsin-Jung Wu

Since Specialization
Citations

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

Fields of papers citing papers by Hsin-Jung Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsin-Jung Wu. 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 Hsin-Jung Wu. The network helps show where Hsin-Jung Wu may publish in the future.

Co-authorship network of co-authors of Hsin-Jung Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Hsin-Jung Wu. A scholar is included among the top collaborators of Hsin-Jung Wu 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 Hsin-Jung Wu. Hsin-Jung Wu 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, Anna, et al.. (2021). Gut Commensal Segmented Filamentous Bacteria Fine-Tune T Follicular Regulatory Cells to Modify the Severity of Systemic Autoimmune Arthritis. The Journal of Immunology. 206(5). 941–952. 15 indexed citations
2.
Zaiss, Mario M., Hsin-Jung Wu, Daniele Mauro, Georg Schett, & Francesco Ciccia. (2021). The gut–joint axis in rheumatoid arthritis. Nature Reviews Rheumatology. 17(4). 224–237. 246 indexed citations breakdown →
3.
Wu, Hsin-Jung, et al.. (2019). Preparation of CuCrO2 Hollow Nanotubes from an Electrospun Al2O3 Template. Nanomaterials. 9(9). 1252–1252. 7 indexed citations
4.
Bradley, Caroline, Fei Teng, Krysta M. Felix, et al.. (2017). Segmented Filamentous Bacteria Provoke Lung Autoimmunity by Inducing Gut-Lung Axis Th17 Cells Expressing Dual TCRs. Cell Host & Microbe. 22(5). 697–704.e4. 147 indexed citations
5.
Naskar, Debdut, Fei Teng, Krysta M. Felix, Caroline Bradley, & Hsin-Jung Wu. (2017). Synthetic Retinoid AM80 Ameliorates Lung and Arthritic Autoimmune Responses by Inhibiting T Follicular Helper and Th17 Cell Responses. The Journal of Immunology. 198(5). 1855–1864. 26 indexed citations
6.
Tan, Tze Guan, Esen Sefik, Naama Geva‐Zatorsky, et al.. (2016). Identifying species of symbiont bacteria from the human gut that, alone, can induce intestinal Th17 cells in mice. Proceedings of the National Academy of Sciences. 113(50). E8141–E8150. 324 indexed citations breakdown →
7.
Wu, Hsin-Jung, et al.. (2015). Expansion of specialized epidermis induced by hormonal state and mechanical strain. Mechanisms of Development. 136. 73–86. 2 indexed citations
8.
Koyama, Sachiko, et al.. (2013). The Nipple: A Simple Intersection of Mammary Gland and Integument, but Focal Point of Organ Function. Journal of Mammary Gland Biology and Neoplasia. 18(2). 121–131. 20 indexed citations
9.
Mill, Christopher P., et al.. (2013). Autocrine-Derived Epidermal Growth Factor Receptor Ligands Contribute to Recruitment of Tumor-Associated Macrophage and Growth of Basal Breast Cancer Cells In Vivo. Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics. 20(7). 303–317. 20 indexed citations
10.
Wu, Hsin-Jung & Eric Wu. (2012). The role of gut microbiota in immune homeostasis and autoimmunity. Gut Microbes. 3(1). 4–14. 1009 indexed citations breakdown →
11.
Kriegel, Martin, Esen Sefik, Jonathan A. Hill, et al.. (2011). Naturally transmitted segmented filamentous bacteria segregate with diabetes protection in nonobese diabetic mice. Proceedings of the National Academy of Sciences. 108(28). 11548–11553. 340 indexed citations
12.
Wu, Hsin-Jung, Ivaylo I. Ivanov, Jaime Darce, et al.. (2010). Gut-Residing Segmented Filamentous Bacteria Drive Autoimmune Arthritis via T Helper 17 Cells. Immunity. 32(6). 815–827. 1198 indexed citations breakdown →
13.
Jacobs, Jonathan P., Hsin-Jung Wu, Christophe Benoıst, & Diane Mathis. (2009). IL-17-producing T cells can augment autoantibody-induced arthritis. Proceedings of the National Academy of Sciences. 106(51). 21789–21794. 59 indexed citations
14.
Wu, Hsin-Jung & Subbarao Bondada. (2008). CD72, a Coreceptor with Both Positive and Negative Effects on B Lymphocyte Development and Function. Journal of Clinical Immunology. 29(1). 12–21. 38 indexed citations
15.
Wu, Hsin-Jung, Heloisa Sawaya, Bryce A. Binstadt, et al.. (2007). Inflammatory arthritis can be reined in by CpG-induced DC–NK cell cross talk. The Journal of Experimental Medicine. 204(8). 1911–1922. 83 indexed citations
16.
Monach, Paul A., Kimie Hattori, Haochu Huang, et al.. (2007). The K/BxN Mouse Model of Inflammatory Arthritis. Methods in molecular medicine. 136. 269–282. 77 indexed citations
17.
Sen, Goutam, Hsin-Jung Wu, Gabriel Bikah, et al.. (2002). Defective CD19-dependent signaling in B-1a and B-1b B lymphocyte subpopulations. Molecular Immunology. 39(1-2). 57–68. 25 indexed citations
18.
Hempen, Paula M., et al.. (2002). Transcriptional Regulation of the Human Polymeric Ig Receptor Gene: Analysis of Basal Promoter Elements. The Journal of Immunology. 169(4). 1912–1921. 17 indexed citations
19.
Wu, Hsin-Jung & Subbarao Bondada. (2002). Positive and Negative Roles of CD72 in B Cell Function. Immunologic Research. 25(2). 155–166. 21 indexed citations
20.
Bondada, Subbarao, Hsin-Jung Wu, Darrell A. Robertson, & R. Lakshman Chelvarajan. (2000). Accessory cell defect in unresponsiveness of neonates and aged to polysaccharide vaccines. Vaccine. 19(4-5). 557–565. 42 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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