Z. J. Shang

2.5k total citations
100 papers, 1.8k citations indexed

About

Z. J. Shang is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Z. J. Shang has authored 100 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 27 papers in Cancer Research and 22 papers in Oncology. Recurrent topics in Z. J. Shang's work include Cancer Cells and Metastasis (15 papers), Cancer, Hypoxia, and Metabolism (12 papers) and Reconstructive Surgery and Microvascular Techniques (12 papers). Z. J. Shang is often cited by papers focused on Cancer Cells and Metastasis (15 papers), Cancer, Hypoxia, and Metabolism (12 papers) and Reconstructive Surgery and Microvascular Techniques (12 papers). Z. J. Shang collaborates with scholars based in China, United Kingdom and United States. Z. J. Shang's co-authors include Erhui Jiang, Zhe Shao, Ke Liu, Xiaocheng Zhou, Tinglin Yan, Yang Chen, Hui Zhao, Lin Wang, Chunming Huang and Zhi Xu and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and Nano Letters.

In The Last Decade

Z. J. Shang

88 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Z. J. Shang China 25 832 593 457 253 209 100 1.8k
Laikui Liu China 27 1.1k 1.4× 506 0.9× 731 1.6× 247 1.0× 142 0.7× 72 2.2k
Fanglong Wu China 18 607 0.7× 411 0.7× 529 1.2× 146 0.6× 125 0.6× 42 1.4k
Lai‐ping Zhong China 24 667 0.8× 299 0.5× 461 1.0× 414 1.6× 79 0.4× 96 1.7k
Yuichiro Kuratomi Japan 24 731 0.9× 401 0.7× 669 1.5× 355 1.4× 138 0.7× 96 2.1k
Yuxian Song China 23 1.1k 1.3× 662 1.1× 328 0.7× 171 0.7× 67 0.3× 70 1.9k
Chenzhou Wu China 19 865 1.0× 355 0.6× 202 0.4× 161 0.6× 198 0.9× 48 1.8k
Patrícia P. Reis Brazil 27 1.2k 1.5× 828 1.4× 422 0.9× 269 1.1× 42 0.2× 80 2.1k
Kyoko Hida Japan 24 1.1k 1.3× 623 1.1× 672 1.5× 92 0.4× 140 0.7× 58 1.8k
Daisuke Uchida Japan 25 1.2k 1.4× 676 1.1× 1.2k 2.5× 261 1.0× 98 0.5× 84 2.7k
Xing Qin China 27 1.6k 1.9× 901 1.5× 367 0.8× 197 0.8× 177 0.8× 65 2.3k

Countries citing papers authored by Z. J. Shang

Since Specialization
Citations

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

Fields of papers citing papers by Z. J. Shang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Z. J. Shang. 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 Z. J. Shang. The network helps show where Z. J. Shang may publish in the future.

Co-authorship network of co-authors of Z. J. Shang

This figure shows the co-authorship network connecting the top 25 collaborators of Z. J. Shang. A scholar is included among the top collaborators of Z. J. Shang 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 Z. J. Shang. Z. J. Shang 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.
Tian, Mei, Long Yi, Z. J. Shang, et al.. (2025). Design, Synthesis, and Insecticidal Activity of Sulfonamide Structures Containing Methoxyamine as Potential Inhibitors of V‐ATPase. Chemistry & Biodiversity. 22(10). e00285–e00285.
2.
Feng, Chao, Shuren Li, Xiaojuan Xu, et al.. (2025). Single-Cell Insights into Unicystic and Solid Ameloblastoma Heterogeneity. Journal of Dental Research. 104(13). 1506–1516.
3.
Lin, Hao, Xuepeng Xiong, Zhe Shao, et al.. (2025). Vascularized iliac crest free flap in maxillofacial reconstruction: Pearls and pitfalls from 437 clinical application. Journal of Stomatology Oral and Maxillofacial Surgery. 126(3). 102318–102318.
4.
Liu, Hanzhe, Zhi Liu, Tong Wang, et al.. (2024). Tea leaf-derived nanovesicles for ferric-supply-amplified ICD and macrophage reprogramming to boost immunotherapy against head and neck squamous carcinoma. Chemical Engineering Journal. 503. 158469–158469. 3 indexed citations
5.
Shang, Z. J., et al.. (2024). Physics-guided TL-LSTM network for early-stage degradation trajectory prediction of lithium-ion batteries. Journal of Energy Storage. 106. 114736–114736. 22 indexed citations
6.
Chen, Yang, et al.. (2024). EphA2 promotes the transcription of KLF4 to facilitate stemness in oral squamous cell carcinoma. Cellular and Molecular Life Sciences. 81(1). 278–278. 5 indexed citations
7.
Liu, Pan, Yue Wang, Zhi Liu, et al.. (2024). Enhanced lipid biosynthesis in oral squamous cell carcinoma cancer‐associated fibroblasts contributes to tumor progression: Role of IL8/AKT/p‐ACLY axis. Cancer Science. 115(5). 1433–1445. 6 indexed citations
8.
Zhao, Hui, et al.. (2024). NNMT switches the proangiogenic phenotype of cancer-associated fibroblasts via epigenetically regulating ETS2/VEGFA axis. Oncogene. 43(35). 2647–2660. 6 indexed citations
9.
Yang, Xiao, et al.. (2024). Fibroblast regulates angiogenesis in assembled oral cancer organoid: A possible role of NNMT. Oral Diseases. 30(8). 4982–4992. 5 indexed citations
10.
Zhang, Shuzhen, Jingjing Wang, Yang Chen, et al.. (2024). CAFs-derived lactate enhances the cancer stemness through inhibiting the MST1 ubiquitination degradation in OSCC. Cell & Bioscience. 14(1). 144–144. 7 indexed citations
11.
12.
Shang, Z. J., et al.. (2022). Changing trend of oral cancer disease burden in China from 1990 to 2019 and the forecast for the next 20 years. Oral Diseases. 30(2). 195–206. 8 indexed citations
13.
Jiang, Erhui, et al.. (2022). Prognostic value of tumor–stroma ratio in oral carcinoma: Role of cancer‐associated fibroblasts. Oral Diseases. 29(5). 1967–1978. 13 indexed citations
14.
Luo, Xinyue, Yang Chen, Hui Wang, et al.. (2022). Melatonin inhibits EMT and PD‐L1 expression through the ERK1/2/FOSL1 pathway and regulates anti‐tumor immunity in HNSCC. Cancer Science. 113(7). 2232–2245. 37 indexed citations
15.
16.
Chen, Xu, Rui Li, Hui Zhao, et al.. (2021). Phenotype transition of fibroblasts incorporated into patient‐derived oral carcinoma organoids. Oral Diseases. 29(3). 913–922. 13 indexed citations
17.
Luo, Tingting, Xiaocheng Zhou, Erhui Jiang, et al.. (2021). Osteosarcoma Cell-Derived Small Extracellular Vesicles Enhance Osteoclastogenesis and Bone Resorption Through Transferring MicroRNA-19a-3p. Frontiers in Oncology. 11. 618662–618662. 12 indexed citations
18.
Bi, Hong‐Yan, et al.. (2020). Predictive Values of Preoperative Prognostic Nutritional Index and Systemic Immune-Inflammation Index for Long-Term Survival in High-Risk Non-Muscle-Invasive Bladder Cancer Patients: A Single-Centre Retrospective Study. SHILAP Revista de lepidopterología. 2 indexed citations
19.
Wang, Hui, Lin Wang, Xiaocheng Zhou, et al.. (2020). OSCC Exosomes Regulate miR‐210‐3p Targeting EFNA3 to Promote Oral Cancer Angiogenesis through the PI3K/AKT Pathway. BioMed Research International. 2020(1). 2125656–2125656. 71 indexed citations
20.
Yan, Tinglin, Meng Wang, Zhi Xu, et al.. (2017). Up-regulation of syncytin-1 contributes to TNF-α-enhanced fusion between OSCC and HUVECs partly via Wnt/β-catenin-dependent pathway. Scientific Reports. 7(1). 40983–40983. 34 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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