Yushi Yao

2.1k total citations · 1 hit paper
38 papers, 1.3k citations indexed

About

Yushi Yao is a scholar working on Immunology, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Yushi Yao has authored 38 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Immunology, 13 papers in Molecular Biology and 7 papers in Infectious Diseases. Recurrent topics in Yushi Yao's work include Immune responses and vaccinations (10 papers), Immune Cell Function and Interaction (9 papers) and Immunotherapy and Immune Responses (8 papers). Yushi Yao is often cited by papers focused on Immune responses and vaccinations (10 papers), Immune Cell Function and Interaction (9 papers) and Immunotherapy and Immune Responses (8 papers). Yushi Yao collaborates with scholars based in China, Canada and United States. Yushi Yao's co-authors include Zhou Xing, Sam Afkhami, Mangalakumari Jeyanathan, Maryam Vaseghi‐Shanjani, Rocky Lai, Anna Dvorkin‐Gheva, Jihao Zhou, Siamak Haddadi, Daniela Damjanovic and Clinton S. Robbins and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Blood.

In The Last Decade

Yushi Yao

37 papers receiving 1.3k citations

Hit Papers

Induction of Autonomous Memory Alveolar Macrophages Requi... 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yushi Yao China 18 868 403 370 146 141 38 1.3k
Charlotte Viant United States 8 989 1.1× 226 0.6× 318 0.9× 136 0.9× 180 1.3× 11 1.4k
Jelle de Wit Netherlands 17 504 0.6× 349 0.9× 154 0.4× 166 1.1× 121 0.9× 42 1.1k
Julio C. C. Lorenzi United States 20 554 0.6× 380 0.9× 1.0k 2.7× 242 1.7× 53 0.4× 36 1.8k
Renoud J. Marijnissen Netherlands 15 604 0.7× 236 0.6× 285 0.8× 232 1.6× 130 0.9× 21 1.1k
Nicholas A. Gherardin Australia 16 1.9k 2.2× 250 0.6× 336 0.9× 358 2.5× 393 2.8× 29 2.3k
Hiroyuki Yamamoto Japan 19 458 0.5× 295 0.7× 161 0.4× 144 1.0× 187 1.3× 62 1.1k
Benjamin Israelow United States 13 295 0.3× 585 1.5× 556 1.5× 320 2.2× 54 0.4× 15 1.5k
Helen Baxendale United Kingdom 19 643 0.7× 224 0.6× 156 0.4× 540 3.7× 75 0.5× 45 1.4k
Lauren B. Rodda United States 9 707 0.8× 275 0.7× 181 0.5× 259 1.8× 159 1.1× 13 1.2k
Sharline Madera United States 11 1.2k 1.4× 123 0.3× 143 0.4× 216 1.5× 173 1.2× 19 1.5k

Countries citing papers authored by Yushi Yao

Since Specialization
Citations

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

Fields of papers citing papers by Yushi Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yushi Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Yushi Yao. A scholar is included among the top collaborators of Yushi Yao 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 Yushi Yao. Yushi Yao 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.
2.
Wang, Tao, Yanling Wang, Jinjing Zhang, & Yushi Yao. (2024). Role of trained innate immunity against mucosal cancer. Current Opinion in Virology. 64. 101387–101387. 2 indexed citations
3.
Wang, Tao, Yanling Wang, & Yushi Yao. (2024). Gut microbe guides alveolar macrophages to fight flu. Cell Host & Microbe. 32(3). 296–298. 3 indexed citations
5.
Wang, Tao, et al.. (2023). Influenza-trained mucosal-resident alveolar macrophages confer long-term antitumor immunity in the lungs. Nature Immunology. 24(3). 423–438. 98 indexed citations
6.
Dai, Min, Wei Ouyang, Tao Wang, et al.. (2023). IFP35 aggravates Staphylococcus aureus infection by promoting Nrf2-regulated ferroptosis. Journal of Advanced Research. 62. 143–154. 11 indexed citations
7.
Jeyanathan, Mangalakumari, Maryam Vaseghi‐Shanjani, Sam Afkhami, et al.. (2022). Parenteral BCG vaccine induces lung-resident memory macrophages and trained immunity via the gut–lung axis. Nature Immunology. 23(12). 1687–1702. 101 indexed citations
8.
Haddadi, Siamak, Maryam Vaseghi‐Shanjani, Yushi Yao, et al.. (2019). Mucosal-Pull Induction of Lung-Resident Memory CD8 T Cells in Parenteral TB Vaccine-Primed Hosts Requires Cognate Antigens and CD4 T Cells. Frontiers in Immunology. 10. 2075–2075. 28 indexed citations
9.
Afkhami, Sam, Rocky Lai, Michael R. D’Agostino, et al.. (2019). Single-Dose Mucosal Immunotherapy With Chimpanzee Adenovirus-Based Vaccine Accelerates Tuberculosis Disease Control and Limits Its Rebound After Antibiotic Cessation. The Journal of Infectious Diseases. 220(8). 1355–1366. 10 indexed citations
10.
Yao, Yushi, Mangalakumari Jeyanathan, Siamak Haddadi, et al.. (2018). Induction of Autonomous Memory Alveolar Macrophages Requires T Cell Help and Is Critical to Trained Immunity. Cell. 175(6). 1634–1650.e17. 341 indexed citations breakdown →
11.
Jeyanathan, Mangalakumari, Yushi Yao, Sam Afkhami, Fiona Smaill, & Zhou Xing. (2018). New Tuberculosis Vaccine Strategies: Taking Aim at Un-Natural Immunity. Trends in Immunology. 39(5). 419–433. 47 indexed citations
12.
Yao, Yushi, Lei Wang, Jihao Zhou, & Xinyou Zhang. (2017). HIF-1α inhibitor echinomycin reduces acute graft-versus-host disease and preserves graft-versus-leukemia effect. Journal of Translational Medicine. 15(1). 28–28. 25 indexed citations
13.
Yao, Yushi, et al.. (2017). Progesterone impairs antigen-non-specific immune protection by CD8 T memory cells via interferon-γ gene hypermethylation. PLoS Pathogens. 13(11). e1006736–e1006736. 23 indexed citations
14.
Afkhami, Sam, Yushi Yao, & Zhou Xing. (2016). Methods and clinical development of adenovirus-vectored vaccines against mucosal pathogens. Molecular Therapy — Methods & Clinical Development. 3. 16030–16030. 81 indexed citations
15.
Zhou, Jihao, Yushi Yao, Lixin Wang, et al.. (2013). Demethylating agent decitabine induces autologous cancer testis antigen specific cytotoxic T lymphocytes in vivo. Chinese Medical Journal. 126(23). 4552–4556. 5 indexed citations
16.
Gao, Xiaoning, Ji Lin, Li Gao, et al.. (2013). A Histone Acetyltransferase p300 Inhibitor C646 Induces Cell Cycle Arrest and Apoptosis Selectively in AML1-ETO-Positive AML Cells. PLoS ONE. 8(2). e55481–e55481. 75 indexed citations
18.
Wang, Lixin, Jihao Zhou, Yushi Yao, et al.. (2013). Low Dose Decitabine Treatment Induces CD80 Expression in Cancer Cells and Stimulates Tumor Specific Cytotoxic T Lymphocyte Responses. PLoS ONE. 8(5). e62924–e62924. 92 indexed citations
19.
Xu, Xiongfei, Zhenhong Guo, Yushi Yao, et al.. (2010). Regulatory dendritic cells program generation of interleukin-4–producing alternative memory CD4 T cells with suppressive activity. Blood. 117(4). 1218–1227. 17 indexed citations
20.
Xia, Sheng, Zhenhong Guo, Yushi Yao, et al.. (2008). Liver stroma enhances activation of TLR3-triggered NK cells through fibronectin. Molecular Immunology. 45(10). 2831–2838. 5 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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