Kai Nagasawa
- Cardiology and Cardiovascular Medicine
- Physiology
- Molecular Biology
- Endocrinology, Diabetes and Metabolism
- Epidemiology
- Co-authors
- Kohzo NagataToyoaki MuroharaNatsumi MatsuuraYuichiro YamadaShogo ItoTakuya HattoriShogo WatanabeAyako Uchinaka
- Topics
- Adipose Tissue and Metabolism (5 papers)Adipokines, Inflammation, and Metabolic Diseases (4 papers)Hormonal Regulation and Hypertension (4 papers)
- Cited by
- Behavioral NeuroscienceCardiology and Cardiovascular MedicineEndocrinology, Diabetes and Metabolism
- Journals
- Annals of the New York Academy of SciencesAmerican Journal of Physiology-Heart and Circulatory PhysiologyJournal of Hypertension
- Partner nations
- Japan
In The Last Decade
Kai Nagasawa
13 papers receiving 299 citations
Peers
Comparison fields: 5 of 79
- Cardiology and Cardiovascular Medicine 109
- Physiology 80
- Molecular Biology 77
- Endocrinology, Diabetes and Metabolism 68
- Epidemiology 64
Countries citing papers authored by Kai Nagasawa
This map shows the geographic impact of Kai Nagasawa'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 Kai Nagasawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Nagasawa more than expected).
Fields of papers citing papers by Kai Nagasawa
This network shows the impact of papers produced by Kai Nagasawa. 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 Kai Nagasawa. The network helps show where Kai Nagasawa may publish in the future.
Co-authorship network of co-authors of Kai Nagasawa
This figure shows the co-authorship network connecting the top 25 collaborators of Kai Nagasawa. A scholar is included among the top collaborators of Kai Nagasawa 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 Kai Nagasawa. Kai Nagasawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 34 | |
| 3 | 18 | |
| 4 | 54 | |
| 5 | 0 | |
| 6 | 7 | |
| 7 | 28 | |
| 8 | 32 | |
| 9 | Roles of oxidative stress and the mineralocorticoid receptor in cardiac pathology in a rat model of metabolic syndrome. | 6 |
| 10 | 14 | |
| 11 | 41 | |
| 12 | 38 | |
| 13 | 17 | |
| 14 | Environmental games made much more exciting by soft computing techniques | 4 |
About Kai Nagasawa
Kai Nagasawa is a scholar working on Behavioral Neuroscience, Endocrinology, Diabetes and Metabolism and Physiology, having authored 14 papers that have together received 303 indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (5 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers) and Hormonal Regulation and Hypertension (4 papers). The work is most often cited by research in Behavioral Neuroscience (18 citations), Cardiology and Cardiovascular Medicine (109 citations) and Endocrinology, Diabetes and Metabolism (68 citations). Kai Nagasawa has collaborated with scholars based in Japan. Frequent co-authors include Kohzo Nagata, Toyoaki Murohara, Natsumi Matsuura, Yuichiro Yamada, Shogo Ito, Takuya Hattori, Shogo Watanabe, Ayako Uchinaka, Miwa Takatsu and Keiji Takahashi. Their work appears in journals such as Annals of the New York Academy of Sciences, American Journal of Physiology-Heart and Circulatory Physiology and Journal of Hypertension.
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.