Kyosuke Takeshita

5.7k total citations
141 papers, 4.4k citations indexed

About

Kyosuke Takeshita is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Epidemiology. According to data from OpenAlex, Kyosuke Takeshita has authored 141 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Cardiology and Cardiovascular Medicine, 34 papers in Molecular Biology and 17 papers in Epidemiology. Recurrent topics in Kyosuke Takeshita's work include Cardiovascular Function and Risk Factors (15 papers), Cardiac Imaging and Diagnostics (13 papers) and Protease and Inhibitor Mechanisms (10 papers). Kyosuke Takeshita is often cited by papers focused on Cardiovascular Function and Risk Factors (15 papers), Cardiac Imaging and Diagnostics (13 papers) and Protease and Inhibitor Mechanisms (10 papers). Kyosuke Takeshita collaborates with scholars based in Japan, United States and China. Kyosuke Takeshita's co-authors include Toyoaki Murohara, James K. Liao, Takahisa Kondo, Minoru Satoh, Yasuya Inden, Xian Wu Cheng, Mutsuharu Hayashi, Yasushi Mukai, Freddy Radtke and Florian P. Limbourg 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

Kyosuke Takeshita

140 papers receiving 4.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kyosuke Takeshita Japan 35 1.7k 981 615 517 506 141 4.4k
Takahisa Kondo Japan 33 1.5k 0.8× 1.2k 1.2× 431 0.7× 642 1.2× 457 0.9× 121 4.1k
Anders Gabrielsen Sweden 32 964 0.6× 1.1k 1.1× 526 0.9× 528 1.0× 391 0.8× 89 3.3k
Takeshi Marumo Japan 30 1.5k 0.9× 565 0.6× 872 1.4× 482 0.9× 408 0.8× 59 3.7k
Erik Øie Norway 34 1.6k 0.9× 1.3k 1.3× 449 0.7× 551 1.1× 692 1.4× 82 4.1k
Hui Peng China 35 1.4k 0.8× 597 0.6× 522 0.8× 781 1.5× 534 1.1× 205 4.2k
Masashi Akaike Japan 35 1.3k 0.8× 1.3k 1.3× 623 1.0× 820 1.6× 453 0.9× 116 4.4k
Tadashi Yamakawa Japan 35 1.3k 0.7× 718 0.7× 630 1.0× 542 1.0× 609 1.2× 95 3.9k
Praveen Chander United States 36 1.5k 0.9× 828 0.8× 444 0.7× 646 1.2× 237 0.5× 96 4.1k
Yanqing Zhu United States 34 1.7k 1.0× 664 0.7× 580 0.9× 417 0.8× 503 1.0× 74 4.1k
Li Yan China 34 1.3k 0.7× 466 0.5× 495 0.8× 612 1.2× 722 1.4× 269 4.8k

Countries citing papers authored by Kyosuke Takeshita

Since Specialization
Citations

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

Fields of papers citing papers by Kyosuke Takeshita

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kyosuke Takeshita

This figure shows the co-authorship network connecting the top 25 collaborators of Kyosuke Takeshita. A scholar is included among the top collaborators of Kyosuke Takeshita 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 Kyosuke Takeshita. Kyosuke Takeshita 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.
Takeshita, Kyosuke, Yuki Kitamura, Zhenlie Huang, et al.. (2023). In Vitro Exposure to Glucose Alters the Expression of Phosphorylated Proteins in Platelets. Biomedicines. 11(2). 543–543. 2 indexed citations
2.
3.
Hamrah, Mohammad Shoaib, Hideki Ishii, Susumu Suzuki, et al.. (2018). Anxiety and Depression among Hypertensive Outpatients in Afghanistan: A Cross-Sectional Study in Andkhoy City. International Journal of Hypertension. 2018. 1–8. 42 indexed citations
4.
Hiraiwa, Hiroaki, Takahiro Okumura, Akinori Sawamura, et al.. (2017). The Selvester QRS score as a predictor of cardiac events in nonischemic dilated cardiomyopathy. Journal of Cardiology. 71(3). 284–290. 14 indexed citations
5.
Varshney, Shweta, Mitsutaka Ogawa, Yuta Sakaidani, et al.. (2017). O-GlcNAc on NOTCH1 EGF repeats regulates ligand-induced Notch signaling and vascular development in mammals. eLife. 6. 67 indexed citations
6.
Zhu, Enbo, Lina Hu, Hongxian Wu, et al.. (2017). Dipeptidyl Peptidase‐4 Regulates Hematopoietic Stem Cell Activation in Response to Chronic Stress. Journal of the American Heart Association. 6(7). 38 indexed citations
7.
Kikuchi, Ryosuke, Yoshinari Yasuda, Masahiro Nakatochi, et al.. (2017). Urinary and circulating levels of the anti-angiogenic isoform of vascular endothelial growth factor-A in patients with chronic kidney disease. Clinica Chimica Acta. 475. 102–108. 5 indexed citations
8.
Honda, Kazunori, Kyosuke Takeshita, Kenta Murotani, et al.. (2016). Assessment of left ventricular diastolic function during trastuzumab treatment in patients with HER2-positive breast cancer. Breast Cancer. 24(2). 312–318. 7 indexed citations
9.
Jiang, Haiying, Xian Wu Cheng, Guo‐Ping Shi, et al.. (2014). Cathepsin K-mediated notch1 activation contributes to neovascularization in response to hypoxia. Nature Communications. 5(1). 3838–3838. 75 indexed citations
10.
Kobayashi, Masayoshi, Kyosuke Takeshita, Akio Kodama, et al.. (2013). Possible involvement of notch signaling in the pathogenesis of Buerger’s disease. Surgery Today. 44(2). 307–313. 8 indexed citations
11.
Yamada, Takashi, Akihiro Hirashiki, Xian Wu Cheng, et al.. (2013). Relationship of Myocardial Fibrosis to Left Ventricular and Mitochondrial Function in Nonischemic Dilated Cardiomyopathy—A Comparison of Focal and Interstitial Fibrosis. Journal of Cardiac Failure. 19(8). 557–564. 8 indexed citations
12.
13.
Li, Yuxin, Kyosuke Takeshita, Ping‐Yen Liu, et al.. (2009). Smooth Muscle Notch1 Mediates Neointimal Formation After Vascular Injury. Circulation. 119(20). 2686–2692. 95 indexed citations
14.
Takeshita, Kyosuke, Minoru Satoh, Masaaki Ii, et al.. (2006). Critical Role of Endothelial Notch1 Signaling in Postnatal Angiogenesis. Circulation Research. 100(1). 70–78. 200 indexed citations
15.
Takeshita, Kyosuke, Mutsuharu Hayashi, Shigeo Iino, et al.. (2004). Increased Expression of Plasminogen Activator Inhibitor-1 in Cardiomyocytes Contributes to Cardiac Fibrosis after Myocardial Infarction. American Journal Of Pathology. 164(2). 449–456. 101 indexed citations
16.
Kondo, Takahisa, Mutsuharu Hayashi, Kyosuke Takeshita, et al.. (2004). Smoking Cessation Rapidly Increases Circulating Progenitor Cells in Peripheral Blood in Chronic Smokers. Arteriosclerosis Thrombosis and Vascular Biology. 24(8). 1442–1447. 343 indexed citations
17.
Kondo, Takahisa, Miyoshi Ohno, Kyosuke Takeshita, et al.. (2002). Effects of coagulation Factor VII polymorphisms on the coronary artery disease in Japanese. Thrombosis Research. 105(6). 493–498. 12 indexed citations
18.
19.
Itoh, Masayuki, Kinji Ohno, Yutaka Tomita, & Kyosuke Takeshita. (1993). Abnormal short‐latency somatosensory evoked potentials in two patients with carbohydrate‐deficient glycoprotein syndrome. Acta Paediatrica. 82(6-7). 607–608. 5 indexed citations
20.
Mulley, B A, et al.. (1978). INTERACTIONS BETWEEN DIAZEPAM AND PARACETAMOL. Journal of Clinical Pharmacy and Therapeutics. 3(1). 25–35. 3 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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