Koshi Hashimoto

4.7k total citations
142 papers, 3.6k citations indexed

About

Koshi Hashimoto is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery and Molecular Biology. According to data from OpenAlex, Koshi Hashimoto has authored 142 papers receiving a total of 3.6k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Endocrinology, Diabetes and Metabolism, 47 papers in Surgery and 47 papers in Molecular Biology. Recurrent topics in Koshi Hashimoto's work include Thyroid Disorders and Treatments (19 papers), Growth Hormone and Insulin-like Growth Factors (17 papers) and Adrenal and Paraganglionic Tumors (16 papers). Koshi Hashimoto is often cited by papers focused on Thyroid Disorders and Treatments (19 papers), Growth Hormone and Insulin-like Growth Factors (17 papers) and Adrenal and Paraganglionic Tumors (16 papers). Koshi Hashimoto collaborates with scholars based in Japan, United States and Brazil. Koshi Hashimoto's co-authors include Masatomo Mori, Fredric E. Wondisford, Masanobu Yamada, Masanobu Yamada, Yoshihiro Ogawa, Nobuyuki Shibusawa, Teturou Satoh, Shuichi Okada, Tetsurou Satoh and Takanobu Yoshimoto and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Koshi Hashimoto

134 papers receiving 3.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Koshi Hashimoto Japan 35 1.7k 1.1k 897 630 519 142 3.6k
Say Viengchareun France 33 1.7k 1.0× 1.1k 1.0× 650 0.7× 643 1.0× 327 0.6× 77 3.0k
Darlene E. Berryman United States 36 2.1k 1.3× 1.2k 1.1× 429 0.5× 2.0k 3.1× 657 1.3× 119 4.4k
Sandro Loche Italy 35 3.0k 1.8× 965 0.9× 547 0.6× 524 0.8× 376 0.7× 160 4.2k
Irina Kowalska Poland 32 921 0.5× 853 0.8× 386 0.4× 1.1k 1.7× 1.0k 2.0× 133 3.4k
Iwona Bujalska United Kingdom 35 3.6k 2.1× 945 0.9× 841 0.9× 1.0k 1.6× 465 0.9× 54 5.0k
Akihiko Taguchi Japan 20 1.0k 0.6× 1.4k 1.3× 370 0.4× 717 1.1× 337 0.6× 34 4.1k
Karsten Müssig Germany 30 1.0k 0.6× 698 0.6× 599 0.7× 731 1.2× 641 1.2× 202 2.9k
Alessandro Peri Italy 35 890 0.5× 1.2k 1.1× 814 0.9× 538 0.9× 345 0.7× 147 4.0k
Dora M. Berman United States 33 1.4k 0.9× 841 0.8× 2.1k 2.4× 1.1k 1.7× 680 1.3× 69 4.1k
Renzo Cordera Italy 32 687 0.4× 1.1k 1.0× 834 0.9× 670 1.1× 265 0.5× 116 2.6k

Countries citing papers authored by Koshi Hashimoto

Since Specialization
Citations

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

Fields of papers citing papers by Koshi Hashimoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Koshi Hashimoto

This figure shows the co-authorship network connecting the top 25 collaborators of Koshi Hashimoto. A scholar is included among the top collaborators of Koshi Hashimoto 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 Koshi Hashimoto. Koshi Hashimoto 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.
Matsumoto, Shunichi, Satoshi Yoshino, Shuichi Okada, et al.. (2025). Thyroid Hormones Regulate Postprandial Glucose Metabolism by Regulating SGLT1 Expression in the Small Intestine in Rats and Mice. International Journal of Molecular Sciences. 26(18). 8854–8854.
2.
Tanaka, Satoshi, et al.. (2024). High prevalence of copy number variations in the Japanese participants with suspected MODY. Clinical Genetics. 106(3). 293–304. 2 indexed citations
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Takebayashi, Kohzo, et al.. (2024). Circulating Angiopoietin-like Protein 6 Levels and Clinical Features in Patients with Type 2 Diabetes. Internal Medicine. 64(5). 643–649.
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Hara, Kenji, Takenori Okumura, Takafumi Tsuchiya, et al.. (2023). Analysis of five cases showing false-high Hemoglobin A1c due to reduced catalase activity. Endocrine Journal. 71(1). 39–44.
8.
Takebayashi, Kohzo, et al.. (2022). Seasonal variations and the influence of COVID-19 pandemic on hemoglobin A1c, glycoalbumin, and low-density lipoprotein cholesterol. Diabetology International. 13(4). 599–605. 7 indexed citations
9.
Hashimoto, Koshi, Xunmei Yuan, Kazutaka Tsujimoto, et al.. (2020). Targeted DNA demethylation of the Fgf21 promoter by CRISPR/dCas9-mediated epigenome editing. Scientific Reports. 10(1). 5181–5181. 26 indexed citations
10.
Nakano, Yujiro, Koshi Hashimoto, Isao Minami, et al.. (2019). A Case of Refractory Hypothyroidism due to Poor Compliance Treated with the Weekly Intravenous and Oral Levothyroxine Administration. Case Reports in Endocrinology. 2019. 1–6. 8 indexed citations
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Hashimoto, Koshi, Eijun Nishihara, Masako Matsumoto, et al.. (2017). Sialic Acid-Binding Immunoglobulin-Like Lectin1 as a Novel Predictive Biomarker for Relapse in Graves' Disease: A Multicenter Study. Thyroid. 28(1). 50–59. 5 indexed citations
13.
Bouchi, Ryotaro, Takato Takeuchi, Masanori Murakami, et al.. (2017). Suppression of Extrapancreatic Glucagon by Octreotide May Reduce the Fasting and Postprandial Glucose Levels in a Diabetic Patient after Total Pancreatectomy. Internal Medicine. 56(22). 3061–3066. 3 indexed citations
14.
Okamura, Takashi, Yasuyo Nakajima, Nobuyuki Shibusawa, et al.. (2017). Pituitary NR4A1 is negatively regulated by thyroid hormone without direct binding of thyroid hormone receptors on the gene. Molecular and Cellular Endocrinology. 461. 32–42. 4 indexed citations
15.
Bouchi, Ryotaro, Takato Takeuchi, Yujiro Nakano, et al.. (2015). High visceral fat with low subcutaneous fat accumulation as a determinant of atherosclerosis in patients with type 2 diabetes. Cardiovascular Diabetology. 14(1). 136–136. 65 indexed citations
16.
Nakajima, Yasuyo, Masanobu Yamada, Ryo Taguchi, et al.. (2012). NR4A1 (Nur77) Mediates Thyrotropin-Releasing Hormone-Induced Stimulation of Transcription of the Thyrotropin β Gene: Analysis of TRH Knockout Mice. PLoS ONE. 7(7). e40437–e40437. 21 indexed citations
17.
Osaki, Aya, Atsuko Miura, Shuichi Okada, et al.. (2012). Secreted Nucleobindin-2 Inhibits 3T3-L1 Adipocyte Differentiation. Protein and Peptide Letters. 19(9). 997–1004. 16 indexed citations
18.
Horiguchi, Kazuhiko, Masanobu Yamada, Tetsurou Satoh, et al.. (2009). Transcriptional Activation of the Mixed Lineage Leukemia–p27Kip1 Pathway by a Somatostatin Analogue. Clinical Cancer Research. 15(8). 2620–2629. 30 indexed citations
19.
Shibusawa, Nobuyuki, Koshi Hashimoto, & Masanobu Yamada. (2008). Thyrotropin-releasing hormone (TRH) in the cerebellum. The Cerebellum. 7(1). 84–95. 25 indexed citations
20.
Yamada, Masanobu, et al.. (2002). A Novel TRH-PFTAIRE Protein Kinase 1 Pathway in the Cerebellum: Subtractive Hybridization Analysis of TRH-Deficient Mice. Endocrinology. 143(7). 2808–2811. 5 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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