Ming Lu

8.3k total citations · 3 hit papers
136 papers, 6.5k citations indexed

About

Ming Lu is a scholar working on Molecular Biology, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ming Lu has authored 136 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Molecular Biology, 30 papers in Neurology and 29 papers in Cellular and Molecular Neuroscience. Recurrent topics in Ming Lu's work include Neuroinflammation and Neurodegeneration Mechanisms (25 papers), Tryptophan and brain disorders (18 papers) and Parkinson's Disease Mechanisms and Treatments (18 papers). Ming Lu is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (25 papers), Tryptophan and brain disorders (18 papers) and Parkinson's Disease Mechanisms and Treatments (18 papers). Ming Lu collaborates with scholars based in China, Singapore and United States. Ming Lu's co-authors include Gang Hu, Jianhua Ding, Jin‐Song Bian, Li‐Fang Hu, Ren‐Hong Du, Qiao Chen, Chi Xin Tiong, Yiming Sun, Nanshan Song and Ming Xiao and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Nature Neuroscience.

In The Last Decade

Ming Lu

129 papers receiving 6.5k citations

Hit Papers

Small molecule-driven NLRP3 inflammation inhibition via i... 2019 2026 2021 2023 2019 2019 2021 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
Ming Lu China 42 2.6k 1.7k 1.2k 1.2k 942 136 6.5k
Simon Heales United Kingdom 54 4.7k 1.8× 1.4k 0.8× 1.2k 1.0× 3.5k 3.1× 1.6k 1.7× 180 10.6k
Li‐Fang Hu China 43 1.6k 0.6× 2.2k 1.3× 553 0.5× 1.0k 0.9× 544 0.6× 79 5.0k
Noel Y. Calingasan United States 54 4.5k 1.8× 891 0.5× 1.1k 0.9× 2.2k 1.9× 1.9k 2.0× 111 8.3k
John M. Land United Kingdom 42 4.2k 1.6× 914 0.5× 743 0.6× 2.4k 2.1× 1.0k 1.1× 111 7.9k
Hyman M. Schipper Canada 53 5.2k 2.0× 424 0.2× 1.3k 1.1× 2.1k 1.8× 737 0.8× 180 9.7k
Sang Won Suh South Korea 45 2.8k 1.1× 384 0.2× 1.4k 1.2× 1.9k 1.7× 2.1k 2.2× 149 9.0k
Ignacio Lizasoaín Spain 60 3.8k 1.5× 690 0.4× 3.6k 3.0× 2.8k 2.4× 1.9k 2.0× 208 12.4k
Simonetta Camandola United States 43 3.5k 1.4× 273 0.2× 1.3k 1.1× 2.3k 2.0× 1.1k 1.1× 77 8.1k
Luisa Minghetti Italy 56 3.0k 1.2× 491 0.3× 3.0k 2.5× 1.5k 1.3× 1.5k 1.5× 138 8.2k
Ryszard Pluta Poland 49 1.9k 0.7× 504 0.3× 1.9k 1.6× 4.0k 3.5× 1.0k 1.1× 240 8.4k

Countries citing papers authored by Ming Lu

Since Specialization
Citations

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

Fields of papers citing papers by Ming Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Lu. A scholar is included among the top collaborators of Ming Lu 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 Ming Lu. Ming Lu 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.
Chen, Chongyang, Yujie Zhao, Xinyu Wang, et al.. (2025). Mitochondrial Dysfunction in Neurodegenerative Diseases. MedComm. 6(9).
2.
Zhu, Rongxin, Xian Xia, Ting Liu, et al.. (2024). Formation of CSE-YAP complex drives FOXD3-mediated transition of neurotoxic astrocytes in Parkinson’s disease. Pharmacological Research. 210. 107507–107507. 1 indexed citations
3.
Meng, Qing‐Hao, Jiayu Chen, Hong Zhu, et al.. (2024). Antagonism of β-arrestins in IL-4–driven microglia reactivity via the Samd4/mTOR/OXPHOS axis in Parkinson’s disease. Science Advances. 10(34). eadn4845–eadn4845. 11 indexed citations
4.
Huang, Xiaofang, et al.. (2024). Gray matter volume alterations in de novo Parkinson's disease: A mediational role in the interplay between sleep quality and anxiety. CNS Neuroscience & Therapeutics. 30(7). e14867–e14867. 3 indexed citations
5.
Song, Nanshan, et al.. (2024). Focusing on mitochondria in the brain: from biology to therapeutics. Translational Neurodegeneration. 13(1). 23–23. 31 indexed citations
6.
Yang, Pei, Yang Liu, Qianhui Huang, et al.. (2024). The marine-derived compound TAG alleviates Parkinson’s disease by restoring RUBCN-mediated lipid metabolism homeostasis. Acta Pharmacologica Sinica. 45(7). 1366–1380. 5 indexed citations
8.
Yao, Wei, Shiyu Mao, Mengke Li, et al.. (2023). Aerobic glycolysis is the predominant means of glucose metabolism in neuronal somata, which protects against oxidative damage. Nature Neuroscience. 26(12). 2081–2089. 73 indexed citations
9.
Jiang, Siyuan, Tian Tian, Hang Yao, et al.. (2023). The cGAS-STING-YY1 axis accelerates progression of neurodegeneration in a mouse model of Parkinson’s disease via LCN2-dependent astrocyte senescence. Cell Death and Differentiation. 30(10). 2280–2292. 61 indexed citations
10.
Fang, Yinquan, Xiao Ding, Yihe Zhang, et al.. (2022). Fluoxetine inhibited the activation of A1 reactive astrocyte in a mouse model of major depressive disorder through astrocytic 5-HT2BR/β-arrestin2 pathway. Journal of Neuroinflammation. 19(1). 23–23. 61 indexed citations
11.
Song, Qiqi, Liping Lin, Yali Chen, et al.. (2022). Characterization of LTr1 derived from cruciferous vegetables as a novel anti-glioma agent via inhibiting TrkA/PI3K/AKT pathway. Acta Pharmacologica Sinica. 44(6). 1262–1276. 7 indexed citations
12.
Wang, Ting Ting, Ming Lu, Rui Jiao, et al.. (2021). Acautalides A–C, Neuroprotective Diels–Alder Adducts from Solid-State Cultivated Acaulium sp. H-JQSF. Organic Letters. 23(14). 5587–5591. 14 indexed citations
13.
Li, Shanshan, Yiming Sun, Mengmeng Song, et al.. (2021). NLRP3/caspase-1/GSDMD–mediated pyroptosis exerts a crucial role in astrocyte pathological injury in mouse model of depression. JCI Insight. 6(23). 205 indexed citations breakdown →
14.
15.
Chen, Qiao, Qian Zhang, Qingling Jiang, et al.. (2018). Inhibition of the hepatic Nlrp3 protects dopaminergic neurons via attenuating systemic inflammation in a MPTP/p mouse model of Parkinson’s disease. Journal of Neuroinflammation. 15(1). 193–193. 75 indexed citations
16.
Lu, Ming, et al.. (2016). Uncoupling protein 2 modulation of the NLRP3 inflammasome in astrocytes and its implications in depression. Redox Biology. 9. 178–187. 76 indexed citations
17.
Chen, Yahong, Chun‐Chin Chang, Jian Kang, et al.. (2015). [Present status of medical treatment for patients with chronic obstructive pulmonary disease based upon different severity classifications].. PubMed. 95(8). 570–6. 1 indexed citations
18.
Liu, Yi‐Hong, Ming Lu, Li‐Fang Hu, et al.. (2012). Hydrogen Sulfide in the Mammalian Cardiovascular System. Antioxidants and Redox Signaling. 17(1). 141–185. 227 indexed citations
19.
Huang, Xu‐Feng, et al.. (2012). d‐Serine Regulates Proliferation and Neuronal Differentiation of Neural Stem Cells from Postnatal Mouse Forebrain. CNS Neuroscience & Therapeutics. 18(1). 4–13. 33 indexed citations
20.
Hu, Li‐Fang, Ming Lu, Chi Xin Tiong, et al.. (2009). Neuroprotective effects of hydrogen sulfide on Parkinson’s disease rat models. Aging Cell. 9(2). 135–146. 315 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026