Qing Lu

2.4k total citations
47 papers, 1.9k citations indexed

About

Qing Lu is a scholar working on Genetics, Endocrinology, Diabetes and Metabolism and Molecular Biology. According to data from OpenAlex, Qing Lu has authored 47 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 15 papers in Endocrinology, Diabetes and Metabolism and 13 papers in Molecular Biology. Recurrent topics in Qing Lu's work include Estrogen and related hormone effects (15 papers), Hormonal Regulation and Hypertension (11 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (8 papers). Qing Lu is often cited by papers focused on Estrogen and related hormone effects (15 papers), Hormonal Regulation and Hypertension (11 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (8 papers). Qing Lu collaborates with scholars based in United States, China and Italy. Qing Lu's co-authors include Richard H. Karas, Richard F. Ludueña, Wendy Baur, Iris Z. Jaffe, Michael E. Mendelsohn, Howard K. Surks, David C. Pallas, Kazutaka Ueda, Qing‐Yuan Sun and Mark Aronovitz and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Circulation.

In The Last Decade

Qing Lu

45 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qing Lu United States 24 712 505 426 274 259 47 1.9k
Xiaodong Fu China 30 818 1.1× 386 0.8× 583 1.4× 162 0.6× 150 0.6× 92 2.2k
Koji Hisamoto Japan 16 684 1.0× 337 0.7× 483 1.1× 78 0.3× 86 0.3× 23 1.5k
Katrine Almind United States 22 1.1k 1.6× 692 1.4× 507 1.2× 174 0.6× 803 3.1× 27 2.3k
Thomas C. Resta United States 33 1.0k 1.4× 234 0.5× 502 1.2× 122 0.4× 255 1.0× 96 2.9k
Wendy Baur United States 21 725 1.0× 548 1.1× 461 1.1× 130 0.5× 313 1.2× 31 2.0k
Sabina Baumgartner‐Parzer Austria 32 1.2k 1.7× 752 1.5× 386 0.9× 99 0.4× 358 1.4× 94 2.7k
Josep A. Villena Spain 27 1.7k 2.5× 271 0.5× 492 1.2× 194 0.7× 348 1.3× 42 3.3k
Constantinos Christodoulides United Kingdom 20 1.1k 1.5× 190 0.4× 216 0.5× 111 0.4× 171 0.7× 38 2.0k
Richard S. Haber United States 28 978 1.4× 705 1.4× 210 0.5× 83 0.3× 559 2.2× 41 2.4k
Kazushi Watanabe Japan 23 536 0.8× 154 0.3× 124 0.3× 140 0.5× 89 0.3× 98 1.8k

Countries citing papers authored by Qing Lu

Since Specialization
Citations

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

Fields of papers citing papers by Qing Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qing Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Qing Lu. A scholar is included among the top collaborators of Qing 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 Qing Lu. Qing 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.
Travers, Richard J., et al.. (2024). Abstract 110: Pro-thrombotic BCR-ABL Tyrosine Kinase Inhibitors Ponatinib And Nilotinib, But Not The Novel Agent Asciminb, Impair Endothelial Cell Wound Healing. Arteriosclerosis Thrombosis and Vascular Biology. 44(Suppl_1). 1 indexed citations
2.
Turner, Casey G., Qing Lu, Ayan R. Patel, et al.. (2024). Microvascular angiotensin II type 2 receptor function is enhanced in young females and declines in a model of murine aging. PubMed. 4(2). 2 indexed citations
3.
Ibarrola, Jaime, Seung Kyum Kim, Qing Lu, et al.. (2022). Smooth muscle mineralocorticoid receptor as an epigenetic regulator of vascular ageing. Cardiovascular Research. 118(17). 3386–3400. 16 indexed citations
4.
Biwer, Lauren A., et al.. (2021). Mineralocorticoid and Estrogen Receptors in Endothelial Cells Coordinately Regulate Microvascular Function in Obese Female Mice. Hypertension. 77(6). 2117–2126. 14 indexed citations
5.
Xue, Yan, Jing Zhao, Jian Lei, et al.. (2021). 144P Tislelizumab combined with chemotherapy as neoadjuvant therapy for surgically resectable esophageal cancer (TD-NICE): A single arm, phase II study. Annals of Oncology. 32. S1442–S1442. 3 indexed citations
6.
Man, Joshua J., Qing Lu, M. Elizabeth Moss, et al.. (2021). Myeloid Mineralocorticoid Receptor Transcriptionally Regulates P-Selectin Glycoprotein Ligand-1 and Promotes Monocyte Trafficking and Atherosclerosis. Arteriosclerosis Thrombosis and Vascular Biology. 41(11). 2740–2755. 13 indexed citations
7.
Ueda, Kazutaka, Eiki Takimoto, Qing Lu, et al.. (2018). Membrane-Initiated Estrogen Receptor Signaling Mediates Metabolic Homeostasis via Central Activation of Protein Phosphatase 2A. Diabetes. 67(8). 1524–1537. 22 indexed citations
8.
Gopal, Srila, Qing Lu, Joshua J. Man, et al.. (2018). A phosphoproteomic signature in endothelial cells predicts vascular toxicity of tyrosine kinase inhibitors used in CML. Blood Advances. 2(14). 1680–1684. 11 indexed citations
9.
Gopal, Srila, Qing Lu, Wendy Baur, et al.. (2017). Impact of Tyrosine Kinase Inhibitors Used in Chronic Myeloid Leukemia on Signaling and Epigenetics in Endothelial Cells. Blood. 130. 2296–2296. 1 indexed citations
10.
Liu, Haixin, Yu Wang, Qing Lu, et al.. (2016). Bidirectional regulation of angiogenesis by phytoestrogens through estrogen receptor-mediated signaling networks. Chinese Journal of Natural Medicines. 14(4). 241–254. 14 indexed citations
11.
Lu, Qing, et al.. (2016). ER Alpha Rapid Signaling Is Required for Estrogen Induced Proliferation and Migration of Vascular Endothelial Cells. PLoS ONE. 11(4). e0152807–e0152807. 42 indexed citations
12.
Wu, Yanting, et al.. (2015). Vegetarian diet and reduced uterine fibroids risk: A case–control study in Nanjing, China. Journal of obstetrics and gynaecology research. 42(1). 87–94. 17 indexed citations
13.
Li, Hui, et al.. (2007). Steroid receptor coactivator 3 is a coactivator for myocardin, the regulator of smooth muscle transcription and differentiation. Proceedings of the National Academy of Sciences. 104(10). 4065–4070. 31 indexed citations
15.
Lu, Qing, David C. Pallas, Howard K. Surks, et al.. (2004). Striatin assembles a membrane signaling complex necessary for rapid, nongenomic activation of endothelial NO synthase by estrogen receptor α. Proceedings of the National Academy of Sciences. 101(49). 17126–17131. 216 indexed citations
16.
Rämet, Maria E., et al.. (2003). High-density lipoprotein increases the abundance of eNOS protein in human vascular endothelial cells by increasing its half-life. Journal of the American College of Cardiology. 41(12). 2288–2297. 104 indexed citations
17.
Lu, Qing, et al.. (2002). Regulation of Spindle Formation by Active Mitogen-Activated Protein Kinase and Protein Phosphatase 2A During Mouse Oocyte Meiosis1. Biology of Reproduction. 66(1). 29–37. 46 indexed citations
19.
Lu, Qing, et al.. (1999). EXPRESSION AND PHOSPHORYLATION OF MITOGEN-ACTIVATED PROTEIN KINASES DURING SPERMATOGENESIS AND EPIDIDYMAL SPERM MATURATION IN MICE. Archives of Andrology. 43(1). 55–66. 46 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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