Takeshi Imamura

9.4k total citations · 2 hit papers
85 papers, 7.7k citations indexed

About

Takeshi Imamura is a scholar working on Molecular Biology, Physiology and Surgery. According to data from OpenAlex, Takeshi Imamura has authored 85 papers receiving a total of 7.7k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Molecular Biology, 36 papers in Physiology and 18 papers in Surgery. Recurrent topics in Takeshi Imamura's work include Metabolism, Diabetes, and Cancer (28 papers), Nitric Oxide and Endothelin Effects (19 papers) and Protein Kinase Regulation and GTPase Signaling (19 papers). Takeshi Imamura is often cited by papers focused on Metabolism, Diabetes, and Cancer (28 papers), Nitric Oxide and Endothelin Effects (19 papers) and Protein Kinase Regulation and GTPase Signaling (19 papers). Takeshi Imamura collaborates with scholars based in Japan, United States and Egypt. Takeshi Imamura's co-authors include Jerrold M. Olefsky, Eun Ju Bae, Da Young Oh, Pingping Li, Steven M. Watkins, Saswata Talukdar, Wendell J. Lu, Hidetaka Morinaga, WuQiang Fan and Jennie L. Babendure and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Takeshi Imamura

84 papers receiving 7.6k citations

Hit Papers

GPR120 Is an Omega-3 Fatty Acid Receptor Mediating Potent... 2010 2026 2015 2020 2010 2013 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. GPR120 Is an Omega-3 Fatty Acid Receptor Mediating Potent Anti-inflammatory and Insulin-Sensitizing Effects
    2010 1.9k citations Da Young Oh, Saswata Talukdar et al. Cell profile →
  2. The gut microbiota suppresses insulin-mediated fat accumulation via the short-chain fatty acid receptor GPR43
    2013 1.2k citations Ikuo Kimura, Kentaro Ozawa et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Takeshi Imamura Japan 35 4.2k 2.8k 1.6k 1.3k 1.2k 85 7.7k
Robert M. O’Doherty United States 45 3.1k 0.7× 2.9k 1.0× 1.9k 1.2× 1.4k 1.1× 535 0.5× 83 6.9k
Peter J. Voshol Netherlands 53 3.4k 0.8× 2.6k 0.9× 2.0k 1.3× 1.8k 1.3× 704 0.6× 114 8.4k
Saswata Talukdar United States 32 3.2k 0.8× 2.3k 0.8× 2.5k 1.6× 1.1k 0.8× 1.2k 1.0× 48 7.3k
Manuel Vázquez‐Carrera Spain 51 5.0k 1.2× 3.1k 1.1× 2.3k 1.5× 1.3k 1.0× 521 0.4× 191 9.2k
Alexander S. Banks United States 42 3.6k 0.9× 3.8k 1.4× 2.5k 1.6× 755 0.6× 1.0k 0.8× 69 9.1k
Juan C. Laguna Spain 43 2.5k 0.6× 1.8k 0.7× 1.5k 1.0× 892 0.7× 697 0.6× 157 5.8k
Bei B. Zhang United States 38 3.9k 0.9× 2.9k 1.0× 2.1k 1.4× 2.2k 1.7× 579 0.5× 68 8.6k
Hang Shi United States 44 3.2k 0.8× 3.6k 1.3× 3.1k 2.0× 908 0.7× 802 0.7× 103 9.4k
Takeshi Nishikawa Japan 35 3.0k 0.7× 2.1k 0.7× 854 0.6× 1.1k 0.8× 453 0.4× 109 8.1k
Steven M. Watkins United States 42 4.6k 1.1× 3.1k 1.1× 2.8k 1.8× 1.5k 1.1× 1.8k 1.5× 77 10.2k

Countries citing papers authored by Takeshi Imamura

Since Specialization
Citations

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

Fields of papers citing papers by Takeshi Imamura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takeshi Imamura

This figure shows the co-authorship network connecting the top 25 collaborators of Takeshi Imamura. A scholar is included among the top collaborators of Takeshi Imamura 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 Takeshi Imamura. Takeshi Imamura 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.
Miake, Junichiro, et al.. (2024). Mitochondrial Responses to Sublethal Doxorubicin in H9c2 Cardiomyocytes: The Role of Phosphorylated CaMKII. Yonago acta medica. 67(1). 41–51. 1 indexed citations
2.
Imamura, Takeshi. (2023). The mechanisms of glucose transporter type 4 translocation regulated by insulin receptor signaling. Folia Pharmacologica Japonica. 158(2). 169–172. 3 indexed citations
3.
Okura, Tsuyoshi, Risa Nakamura, Yuichi Ito, et al.. (2023). Fasting hepatic insulin clearance reflects postprandial hepatic insulin clearance: a brief report. Diabetology & Metabolic Syndrome. 15(1).
4.
Rahman, Asadur, Akram Hossain, Hideki Kobara, et al.. (2021). Cardioprotective Effects of a Nonsteroidal Mineralocorticoid Receptor Blocker, Esaxerenone, in Dahl Salt-Sensitive Hypertensive Rats. International Journal of Molecular Sciences. 22(4). 2069–2069. 14 indexed citations
5.
Lemecha, Mengistu, Katsutaro Morino, Takeshi Imamura, et al.. (2018). Improved glucose metabolism by Eragrostis tef potentially through beige adipocyte formation and attenuating adipose tissue inflammation. PLoS ONE. 13(8). e0201661–e0201661. 8 indexed citations
6.
Okura, Tsuyoshi, Risa Nakamura, Yuichi Ito, et al.. (2018). CPR-IR is an insulin resistance index that is minimally affected by hepatic insulin clearance—A preliminary research. PLoS ONE. 13(5). e0197663–e0197663. 10 indexed citations
7.
Lemecha, Mengistu, Katsutaro Morino, Takeshi Imamura, et al.. (2018). miR-494 Regulates Mitochondrial Biogenesis and Thermogenesis through PGC1-α Signaling in Beige Adipocytes. Diabetes. 67(Supplement_1). 1 indexed citations
8.
Li, Pingping, Shuainan Liu, Min Lü, et al.. (2016). Hematopoietic-Derived Galectin-3 Causes Cellular and Systemic Insulin Resistance. Cell. 167(4). 973–984.e12. 240 indexed citations
9.
Morino, Katsutaro, Osamu Sekine, Fumiyuki Nakagawa, et al.. (2015). Duality of n-3 Polyunsaturated Fatty Acids on Mcp-1 Expression in Vascular Smooth Muscle: A Potential Role of 4-Hydroxy Hexenal. Nutrients. 7(9). 8112–8126. 7 indexed citations
10.
Kimura, Ikuo, Kentaro Ozawa, Daisuke Inoue, et al.. (2013). The gut microbiota suppresses insulin-mediated fat accumulation via the short-chain fatty acid receptor GPR43. Nature Communications. 4(1). 1829–1829. 1164 indexed citations breakdown →
11.
Oh, Da Young, Saswata Talukdar, Eun Ju Bae, et al.. (2010). GPR120 Is an Omega-3 Fatty Acid Receptor Mediating Potent Anti-inflammatory and Insulin-Sensitizing Effects. Cell. 142(5). 687–698. 1921 indexed citations breakdown →
12.
Geddawy, Ayman, et al.. (2010). Comparison of Endothelium-Related Responses to Nucleotides of Dog and Monkey Cerebral Arteries. Journal of Pharmacological Sciences. 112(3). 378–381. 4 indexed citations
13.
Iwata, Takahiro, Hiroyuki Minamino, Mina Ogawa, et al.. (2009). Mission Outline of Selenodesy by KAGUYA (SELENE) and Developments and On-orbit Properties of Sub-satellites : OKINA and OUNA (Rstar and Vstar). 55(2). 135–150. 1 indexed citations
14.
Liao, Wei, Matthew Nguyen, Takeshi Imamura, et al.. (2006). Lentiviral Short Hairpin Ribonucleic Acid-Mediated Knockdown of GLUT4 in 3T3-L1 Adipocytes. Endocrinology. 147(5). 2245–2252. 53 indexed citations
15.
Satoh, Hiroaki, Matthew Nguyen, Philip D.G. Miles, et al.. (2004). Adenovirus-mediated chronic “hyper-resistinemia” leads to in vivo insulin resistance in normal rats. Journal of Clinical Investigation. 114(2). 224–231. 214 indexed citations
16.
Ugi, Satoshi, Prem M. Sharma, William Ricketts, Takeshi Imamura, & Jerrold M. Olefsky. (2002). Phosphatidylinositol 3-Kinase Is Required for Insulin-stimulated Tyrosine Phosphorylation of Shc in 3T3-L1 Adipocytes. Journal of Biological Chemistry. 277(21). 18592–18597. 8 indexed citations
17.
Dalle, Stéphane, William Ricketts, Takeshi Imamura, Péter Vollenweider, & Jerrold M. Olefsky. (2001). Insulin and Insulin-like Growth Factor I Receptors Utilize Different G Protein Signaling Components. Journal of Biological Chemistry. 276(19). 15688–15695. 131 indexed citations
18.
Janež, Andrej, Dorothy Sears Worrall, Takeshi Imamura, Prem M. Sharma, & Jerrold M. Olefsky. (2000). The Osmotic Shock-induced Glucose Transport Pathway in 3T3-L1 Adipocytes Is Mediated by Gab-1 and Requires Gab-1-associated Phosphatidylinositol 3-Kinase Activity for Full Activation. Journal of Biological Chemistry. 275(35). 26870–26876. 27 indexed citations
19.
Imamura, Takeshi, Tetsuro Haruta, Yasumitsu Takata, et al.. (1998). Involvement of Heat Shock Protein 90 in the Degradation of Mutant Insulin Receptors by the Proteasome. Journal of Biological Chemistry. 273(18). 11183–11188. 73 indexed citations
20.
Ishihara, Hajime, Toshiyasu Sasaoka, Manabu Ishiki, et al.. (1997). Functional Importance of Shc Tyrosine 317 on Insulin Signaling in Rat1 Fibroblasts Expressing Insulin Receptors. Journal of Biological Chemistry. 272(14). 9581–9586. 26 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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