Tomoyasu Fukui

2.6k total citations
81 papers, 1.8k citations indexed

About

Tomoyasu Fukui is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Molecular Biology. According to data from OpenAlex, Tomoyasu Fukui has authored 81 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Endocrinology, Diabetes and Metabolism, 33 papers in Surgery and 29 papers in Molecular Biology. Recurrent topics in Tomoyasu Fukui's work include Pancreatic function and diabetes (28 papers), Diabetes Management and Research (26 papers) and Diabetes and associated disorders (22 papers). Tomoyasu Fukui is often cited by papers focused on Pancreatic function and diabetes (28 papers), Diabetes Management and Research (26 papers) and Diabetes and associated disorders (22 papers). Tomoyasu Fukui collaborates with scholars based in Japan, United States and Argentina. Tomoyasu Fukui's co-authors include Tsutomu Hirano, Makoto Ohara, John M. Lowenstein, Takeshi Yamamoto, Leslie A. Serunian, Lewis C. Cantley, Martin T. Haber, Sue Goo Rhee, Toshiyuki Hayashi and Yusaku Mori and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Tomoyasu Fukui

79 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomoyasu Fukui Japan 20 742 606 431 235 229 81 1.8k
Zbigniew Pietrzkowski United States 23 1.1k 1.5× 574 0.9× 351 0.8× 98 0.4× 214 0.9× 60 2.8k
Kyoungmin Park United States 25 730 1.0× 405 0.7× 212 0.5× 201 0.9× 295 1.3× 48 1.7k
Shizhong Bu China 30 1.5k 2.1× 222 0.4× 270 0.6× 92 0.4× 193 0.8× 86 2.6k
Rafael Moreno‐Luna Spain 22 436 0.6× 164 0.3× 336 0.8× 189 0.8× 180 0.8× 56 1.5k
Hanne Scholz Norway 24 550 0.7× 320 0.5× 627 1.5× 98 0.4× 82 0.4× 90 1.6k
Louise Dunn Australia 20 729 1.0× 159 0.3× 201 0.5× 130 0.6× 162 0.7× 44 1.7k
Norifumi Urao United States 26 1.1k 1.5× 174 0.3× 301 0.7× 218 0.9× 324 1.4× 49 2.3k
Jian Zhu China 31 1.2k 1.6× 171 0.3× 311 0.7× 74 0.3× 259 1.1× 96 2.5k
Mary F. Walsh United States 25 595 0.8× 393 0.6× 204 0.5× 447 1.9× 391 1.7× 53 1.7k
Jianyun Yan China 26 1.2k 1.6× 93 0.2× 398 0.9× 385 1.6× 249 1.1× 52 2.1k

Countries citing papers authored by Tomoyasu Fukui

Since Specialization
Citations

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

Fields of papers citing papers by Tomoyasu Fukui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomoyasu Fukui

This figure shows the co-authorship network connecting the top 25 collaborators of Tomoyasu Fukui. A scholar is included among the top collaborators of Tomoyasu Fukui 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 Tomoyasu Fukui. Tomoyasu Fukui 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.
Shimada, Akira, Eiji Kawasaki, Norio Abiru, et al.. (2024). New diagnostic criteria (2023) for slowly progressive type 1 diabetes (SPIDDM): Report from Committee on Type 1 Diabetes of the Japan Diabetes Society (English version). Journal of Diabetes Investigation. 15(2). 254–257. 8 indexed citations
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Shimada, Akira, Eiji Kawasaki, Norio Abiru, et al.. (2024). Practice guideline: Statement regarding treatment for suspected slowly progressive type 1 diabetes (SPIDDM; probable) cases (English version). Journal of Diabetes Investigation. 16(1). 163–168.
4.
Fukui, Tomoyasu, Tetsuro Kobayashi, Kaoru Aida, et al.. (2023). Bi-glandular and persistent enterovirus infection and distinct changes of the pancreas in slowly progressive type 1 diabetes mellitus. Scientific Reports. 13(1). 6977–6977. 11 indexed citations
5.
Terasaki, Michishige, Keita Shibata, Yusaku Mori, et al.. (2023). SMTP-44D Inhibits Atherosclerotic Plaque Formation in Apolipoprotein-E Null Mice Partly by Suppressing the AGEs-RAGE Axis. International Journal of Molecular Sciences. 24(7). 6505–6505. 8 indexed citations
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Kawasaki, Eiji, Akira Shimada, Akihisa Imagawa, et al.. (2023). Bivalent GAD autoantibody ELISA improves clinical utility and risk prediction for adult autoimmune diabetes. Journal of Diabetes Investigation. 14(4). 570–581. 7 indexed citations
8.
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Hiromura, Munenori, Yusaku Mori, Michishige Terasaki, et al.. (2021). Glucose-dependent insulinotropic polypeptide inhibits cardiac hypertrophy and fibrosis in diabetic mice via suppression of TGF-β2. Diabetes and Vascular Disease Research. 18(2). 3155060410–3155060410. 9 indexed citations
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Terasaki, Michishige, Takanori Matsui, Yusaku Mori, et al.. (2020). AGE-RAGE Axis Stimulates Oxidized LDL Uptake into Macrophages through Cyclin-Dependent Kinase 5-CD36 Pathway via Oxidative Stress Generation. International Journal of Molecular Sciences. 21(23). 9263–9263. 14 indexed citations
13.
Fukui, Tomoyasu, Munenori Hiromura, Michishige Terasaki, et al.. (2020). Pancreatic fat accumulation evaluated by multidetector computed tomography in patients with type 2 diabetes. Journal of Diabetes Investigation. 11(5). 1188–1196. 7 indexed citations
14.
Kushima, Hideki, Yusaku Mori, Tomomi Saito, et al.. (2020). Anti-inflammatory and atheroprotective properties of glucagon. Diabetes and Vascular Disease Research. 17(5). 3154026559–3154026559. 6 indexed citations
15.
Terasaki, Michishige, Yusaku Mori, Tomomi Saito, et al.. (2020). A Dipeptidyl Peptidase-4 Inhibitor Inhibits Foam Cell Formation of Macrophages in Type 1 Diabetes via Suppression of CD36 and ACAT-1 Expression. International Journal of Molecular Sciences. 21(13). 4811–4811. 25 indexed citations
16.
Fukui, Tomoyasu, Kaoru Aida, Akira Shimada, et al.. (2019). Unique Inflammatory Changes in Exocrine and Endocrine Pancreas in Enterovirus-Induced Fulminant Type 1 Diabetes. The Journal of Clinical Endocrinology & Metabolism. 104(10). 4282–4294. 13 indexed citations
17.
Fukui, Tomoyasu, Yusaku Mori, Toshiyuki Hayashi, et al.. (2019). Circulating anti‐glutamic acid decarboxylase‐65 antibody titers are positively associated with the capacity of insulin secretion in acute‐onset type 1 diabetes with short duration in a Japanese population. Journal of Diabetes Investigation. 10(6). 1480–1489. 6 indexed citations
18.
Fukui, Tomoyasu, Toshiyuki Hayashi, Takeshi Yamamoto, et al.. (2018). Analysis of pancreatic volume in acute‐onset, slowly‐progressive and fulminant type 1 diabetes in a Japanese population. Journal of Diabetes Investigation. 9(5). 1091–1099. 19 indexed citations
19.
Yamasaki, Masahiro, et al.. (2008). Ketone Body Utilization is Regulated by Male-specific Factors in Rat Subcutaneous Adipocytes. Experimental and Clinical Endocrinology & Diabetes. 117(4). 170–174. 4 indexed citations
20.
Shiraishi, Mitsuya, et al.. (1988). Pharmacological studies on anethole trithione.. PubMed. 38(10). 1460–5. 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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