Xiangmei Zhou

3.7k total citations · 1 hit paper
135 papers, 2.8k citations indexed

About

Xiangmei Zhou is a scholar working on Molecular Biology, Infectious Diseases and Epidemiology. According to data from OpenAlex, Xiangmei Zhou has authored 135 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 87 papers in Molecular Biology, 37 papers in Infectious Diseases and 36 papers in Epidemiology. Recurrent topics in Xiangmei Zhou's work include Prion Diseases and Protein Misfolding (50 papers), Tuberculosis Research and Epidemiology (30 papers) and Mycobacterium research and diagnosis (26 papers). Xiangmei Zhou is often cited by papers focused on Prion Diseases and Protein Misfolding (50 papers), Tuberculosis Research and Epidemiology (30 papers) and Mycobacterium research and diagnosis (26 papers). Xiangmei Zhou collaborates with scholars based in China, United States and Pakistan. Xiangmei Zhou's co-authors include Deming Zhao, Lifeng Yang, Yang Zhou, Xiaomin Yin, Danyan Zhang, Qiuyun Liu, Syed Zahid Ali Shah, Tariq Hussain, Naveed Sabir and Mohammed Kouadir and has published in prestigious journals such as Nature Communications, PLoS ONE and The FASEB Journal.

In The Last Decade

Xiangmei Zhou

133 papers receiving 2.8k citations

Hit Papers

The role of mitochondria ... 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
Xiangmei Zhou China 29 1.7k 664 624 504 379 135 2.8k
Vijay Kumar Australia 27 1.2k 0.7× 1.7k 2.5× 619 1.0× 300 0.6× 262 0.7× 85 3.5k
Haitao Guo United States 15 2.3k 1.4× 1.5k 2.2× 535 0.9× 249 0.5× 359 0.9× 20 3.7k
Takumi Kawasaki Japan 22 1.8k 1.1× 2.0k 3.1× 472 0.8× 394 0.8× 173 0.5× 32 4.3k
Roopali Gandhi United States 29 1.7k 1.0× 1.3k 1.9× 321 0.5× 266 0.5× 249 0.7× 47 3.6k
Karen V. Swanson United States 15 3.2k 1.9× 1.9k 2.8× 593 1.0× 344 0.7× 262 0.7× 24 4.9k
Jenny P.-Y. Ting United States 17 2.6k 1.6× 1.9k 2.9× 655 1.0× 248 0.5× 262 0.7× 21 4.3k
B Gajkowska Poland 28 1.5k 0.9× 292 0.4× 369 0.6× 240 0.5× 178 0.5× 149 2.7k
Arnaud Muller Luxembourg 20 2.3k 1.4× 340 0.5× 307 0.5× 318 0.6× 178 0.5× 42 3.3k
Bart Tummers United States 19 1.4k 0.8× 1.0k 1.5× 668 1.1× 140 0.3× 170 0.4× 26 2.6k
France Moreau Canada 26 1.3k 0.7× 373 0.6× 312 0.5× 528 1.0× 109 0.3× 59 2.3k

Countries citing papers authored by Xiangmei Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Xiangmei Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiangmei Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Xiangmei Zhou. A scholar is included among the top collaborators of Xiangmei Zhou 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 Xiangmei Zhou. Xiangmei Zhou 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
2.
Ge, Xin, et al.. (2024). Impact of Hypoxia-Inducible Factor-1α on Host Immune Metabolism and Tissue Damage During Mycobacterium bovis Infection. The Journal of Infectious Diseases. 231(2). 355–365. 1 indexed citations
3.
Liu, Chunfa, Jie Wang, Naveed Sabir, et al.. (2021). Caspase-1 inhibits IFN-β production via cleavage of cGAS during M. bovis infection. Veterinary Microbiology. 258. 109126–109126. 8 indexed citations
4.
Zhang, Kai, Tariq Hussain, Jie Wang, et al.. (2020). Sodium Butyrate Abrogates the Growth and Pathogenesis of Mycobacterium bovis via Regulation of Cathelicidin (LL37) Expression and NF-κB Signaling. Frontiers in Microbiology. 11. 433–433. 19 indexed citations
5.
Hussain, Tariq, Deming Zhao, Syed Zahid Ali Shah, et al.. (2019). PP2Ac Modulates AMPK-Mediated Induction of Autophagy in Mycobacterium bovis-Infected Macrophages. International Journal of Molecular Sciences. 20(23). 6030–6030. 6 indexed citations
6.
Yang, Dongming, Deming Zhao, Syed Zahid Ali Shah, et al.. (2019). The Role of the Gut Microbiota in the Pathogenesis of Parkinson's Disease. Frontiers in Neurology. 10. 1155–1155. 109 indexed citations
7.
Liu, Qiuyun, et al.. (2018). The role of mitochondria in NLRP3 inflammasome activation. Molecular Immunology. 103. 115–124. 364 indexed citations breakdown →
8.
9.
Zhao, Deming, et al.. (2016). The endoplasmic reticulum stress response: A link with tuberculosis?. Tuberculosis. 97. 52–56. 18 indexed citations
10.
Zhao, Deming, Srinand Sreevatsan, Chunfa Liu, et al.. (2016). Mycobacterium bovis Induces Endoplasmic Reticulum Stress Mediated-Apoptosis by Activating IRF3 in a Murine Macrophage Cell Line. Frontiers in Cellular and Infection Microbiology. 6. 182–182. 51 indexed citations
11.
Liu, He, Xiangmei Zhou, Xiaomin Yin, et al.. (2014). Comparative Study of the Growth and Survival of Recombinant Mycobacterium smegmatis Expressing Mce4A and Mce4E from Mycobacterium bovis. DNA and Cell Biology. 34(2). 125–132. 4 indexed citations
12.
Zhou, Xiangmei, Yun Lu, Yun Peng, et al.. (2014). Mycobacterium Bovis Ornithine Carbamoyltransferase, MB1684, Induces Proinflammatory Cytokine Gene Expression by Activating NF-κB in Macrophages. DNA and Cell Biology. 33(5). 311–319. 4 indexed citations
13.
Wang, Min, Deming Zhao, Yang Yang, et al.. (2014). The Cellular Prion Protein Negatively Regulates Phagocytosis and Cytokine Expression in Murine Bone Marrow-Derived Macrophages. PLoS ONE. 9(7). e102785–e102785. 13 indexed citations
14.
Wang, Jin, Xiangmei Zhou, Bo Pan, et al.. (2013). Expression Pattern of Interferon-Inducible Transcriptional Genes in Neutrophils During Bovine Tuberculosis Infection. DNA and Cell Biology. 32(8). 480–486. 6 indexed citations
15.
Yang, Lifeng, Mohammed Kouadir, Jin Wang, et al.. (2013). Expression and Distribution of Laminin Receptor Precursor/Laminin Receptor in Rabbit Tissues. Journal of Molecular Neuroscience. 51(2). 591–601. 3 indexed citations
16.
Yang, Lifeng, Xiangmei Zhou, Xiaomin Yin, et al.. (2013). Using Protein Misfolding Cyclic Amplification Generates a Highly Neurotoxic PrP Dimer Causing Neurodegeneration. Journal of Molecular Neuroscience. 51(3). 655–662. 4 indexed citations
17.
Kouadir, Mohammed, Lifeng Yang, Jian Cheng Tu, et al.. (2011). Comparison of mRNA Expression Patterns of Class B Scavenger Receptors in BV2 Microglia upon Exposure to Amyloidogenic Fragments of Beta-Amyloid and Prion Proteins. DNA and Cell Biology. 30(11). 893–897. 12 indexed citations
18.
Lu, Yun, Ailing Liu, Xiangmei Zhou, et al.. (2011). Prion Peptide PrP106-126 Induces Inducible Nitric Oxide Synthase and Proinflammatory Cytokine Gene Expression Through the Activation of NF-κB in Macrophage Cells. DNA and Cell Biology. 31(5). 833–838. 10 indexed citations
20.
Pang, Wanyong, et al.. (2006). Amino acid sequence of the Pekingese dog prion protein gene. Xenotransplantation. 13(5). 471–474. 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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