Dian Fu

898 total citations
22 papers, 628 citations indexed

About

Dian Fu is a scholar working on Molecular Biology, Surgery and Cancer Research. According to data from OpenAlex, Dian Fu has authored 22 papers receiving a total of 628 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Surgery and 5 papers in Cancer Research. Recurrent topics in Dian Fu's work include Bladder and Urothelial Cancer Treatments (5 papers), Cancer-related molecular mechanisms research (4 papers) and SARS-CoV-2 and COVID-19 Research (3 papers). Dian Fu is often cited by papers focused on Bladder and Urothelial Cancer Treatments (5 papers), Cancer-related molecular mechanisms research (4 papers) and SARS-CoV-2 and COVID-19 Research (3 papers). Dian Fu collaborates with scholars based in China. Dian Fu's co-authors include Mingxiang Ye, Faxiang Wang, Yi Ren, Xinyi Xia, Fang Zhang, Dong Wang, Tangfeng Lv, Wen Cheng, Zhengyu Zhang and Feng Xu and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Letters and Critical Care.

In The Last Decade

Dian Fu

21 papers receiving 612 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dian Fu China 12 286 194 122 117 92 22 628
Zheyi Han United States 8 309 1.1× 317 1.6× 282 2.3× 151 1.3× 73 0.8× 14 749
Ze‐Xiao Lin China 11 234 0.8× 196 1.0× 126 1.0× 105 0.9× 181 2.0× 23 693
Weichen Lin China 8 355 1.2× 154 0.8× 91 0.7× 186 1.6× 89 1.0× 13 694
Liang Shao China 14 218 0.8× 208 1.1× 101 0.8× 141 1.2× 116 1.3× 32 645
Yuncheng Li China 14 171 0.6× 215 1.1× 136 1.1× 74 0.6× 120 1.3× 45 546
Jiarui Feng China 8 244 0.9× 149 0.8× 72 0.6× 118 1.0× 124 1.3× 11 497
Xiangqiong Liu China 11 121 0.4× 190 1.0× 142 1.2× 31 0.3× 45 0.5× 23 465
Song Tong China 11 205 0.7× 223 1.1× 64 0.5× 104 0.9× 70 0.8× 24 506
Hongying Guo China 13 151 0.5× 241 1.2× 189 1.5× 70 0.6× 71 0.8× 40 587
Guogang Xie China 11 117 0.4× 167 0.9× 50 0.4× 44 0.4× 69 0.8× 23 472

Countries citing papers authored by Dian Fu

Since Specialization
Citations

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

Fields of papers citing papers by Dian Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dian Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Dian Fu. A scholar is included among the top collaborators of Dian Fu 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 Dian Fu. Dian Fu 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.
Wu, Ding, Yulin Zhou, Xiuquan Shi, et al.. (2024). SLC11A1 promotes kidney renal clear cell carcinoma (KIRC) progression by remodeling the tumor microenvironment. Toxicology and Applied Pharmacology. 487. 116975–116975. 5 indexed citations
2.
3.
Tan, Xiaowen, Wenfang Chen, Huiyu Li, et al.. (2024). [Efficiency of different large language models in China in response to consultations about PCa-related perioperative nursing and health education].. PubMed. 30(2). 151–156. 1 indexed citations
4.
Fu, Dian, Bo Yang, Ming Yang, et al.. (2023). Misdiagnosis of renal pelvic unicentric Castleman disease: a case report. Frontiers in Surgery. 10. 1225890–1225890.
5.
Li, Ping, et al.. (2023). Cardamonin suppresses glycolysis and induces oxidative stress by inhibiting PI3K/AKT/mTOR pathway in bladder cancer cells. Tropical Journal of Pharmaceutical Research. 22(8). 1541–1546. 1 indexed citations
6.
Shen, Tianyi, Yulin Zhou, Xiaoming Yi, et al.. (2022). Exosomal AP000439.2 from clear cell renal cell carcinoma induces M2 macrophage polarization to promote tumor progression through activation of STAT3. Cell Communication and Signaling. 20(1). 152–152. 35 indexed citations
7.
Shen, Tianyi, Feng Xu, Jing Zhang, et al.. (2022). KCNN4 may weaken anti-tumor immune response via raising Tregs and diminishing resting mast cells in clear cell renal cell carcinoma. Cancer Cell International. 22(1). 211–211. 15 indexed citations
8.
Fu, Dian, Bo Yang, Jing Xu, et al.. (2020). COVID-19 Infection in a Patient with End-Stage Kidney Disease. ˜The œNephron journals/Nephron journals. 144(5). 245–247. 33 indexed citations
9.
Fu, Dian, Ruiyuan Cao, Lei Zhao, et al.. (2020). Oral favipiravir for patients with delayed SARS-CoV-2 viral RNA clearance: a case series. Critical Care. 24(1). 578–578. 8 indexed citations
10.
Fu, Dian, Ding Wu, Wen Cheng, et al.. (2020). Costunolide Induces Autophagy and Apoptosis by Activating ROS/MAPK Signaling Pathways in Renal Cell Carcinoma. Frontiers in Oncology. 10. 582273–582273. 30 indexed citations
11.
Fu, Dian, et al.. (2020). GSG2 (Haspin) promotes development and progression of bladder cancer through targeting KIF15 (Kinase-12). Aging. 12(10). 8858–8879. 15 indexed citations
12.
Xu, Zhenyu, Ding Wu, Dian Fu, et al.. (2020). Nobiletin inhibits viability of human renal carcinoma cells via the JAK2/STAT3 and PI3K/Akt pathway. Cellular and Molecular Biology. 66(5). 199–203. 11 indexed citations
13.
Cheng, Wen, Dian Fu, Feng Xu, & Zhengyu Zhang. (2018). Unwrapping the genomic characteristics of urothelial bladder cancer and successes with immune checkpoint blockade therapy. Oncogenesis. 7(1). 2–2. 65 indexed citations
14.
Xu, Xiaofeng, Ping Li, Dian Fu, et al.. (2018). Combined use of urinary Survivin detection and liquid-based cytology for the early diagnosis of bladder urothelial carcinoma. Oncology Letters. 15(5). 7739–7743. 8 indexed citations
15.
Fu, Dian, Kai Zhou, Jun Liu, et al.. (2018). Long non-coding RNA PlncRNA-1 regulates cell proliferation, apoptosis, and autophagy in septic acute kidney injury by regulating BCL2.. PubMed. 11(1). 314–323. 13 indexed citations
16.
Fu, Dian, Jie Dong, Ping Li, et al.. (2017). MiRNA-21 has effects to protect kidney injury induced by sepsis. Biomedicine & Pharmacotherapy. 94. 1138–1144. 32 indexed citations
17.
Fu, Dian, Ping Li, Wen Cheng, et al.. (2017). Impact of vascular endothelial growth factor gene-gene and gene-smoking interaction and haplotype combination on bladder cancer risk in Chinese population. Oncotarget. 8(14). 22927–22935. 17 indexed citations
18.
Wei, Zhifeng, Jie Dong, Dian Fu, et al.. (2017). [Efficacy of Lamiophlomis Rotata Capsule in the treatment of type ⅢB prostatitis].. PubMed. 23(12). 1107–1110. 1 indexed citations
19.
Wang, Longxin, Dian Fu, Feng Xu, et al.. (2014). Genome-wide screening and identification of long noncoding RNAs and their interaction with protein coding RNAs in bladder urothelial cell carcinoma. Cancer Letters. 349(1). 77–86. 33 indexed citations
20.
Cheng, Wen, Dian Fu, Zhifeng Wei, et al.. (2014). NRP-1 expression in bladder cancer and its implications for tumor progression. Tumor Biology. 35(6). 6089–6094. 25 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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