Atsushi Nagayasu

881 total citations
28 papers, 712 citations indexed

About

Atsushi Nagayasu is a scholar working on Rheumatology, Molecular Biology and Immunology. According to data from OpenAlex, Atsushi Nagayasu has authored 28 papers receiving a total of 712 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Rheumatology, 9 papers in Molecular Biology and 8 papers in Immunology. Recurrent topics in Atsushi Nagayasu's work include Systemic Lupus Erythematosus Research (7 papers), Rheumatoid Arthritis Research and Therapies (7 papers) and Lipid Membrane Structure and Behavior (6 papers). Atsushi Nagayasu is often cited by papers focused on Systemic Lupus Erythematosus Research (7 papers), Rheumatoid Arthritis Research and Therapies (7 papers) and Lipid Membrane Structure and Behavior (6 papers). Atsushi Nagayasu collaborates with scholars based in Japan, China and Kazakhstan. Atsushi Nagayasu's co-authors include Hiroshi Kiwada, Kazuko Uchiyama, Yoshiya Tanaka, Hideyoshi Harashima, Kazuhiro Morimoto, Shingo Nakayamada, Katsuaki Morisaka, S. Iwata, Suong‐Hyu Hyon and Yoshito Ikada and has published in prestigious journals such as SHILAP Revista de lepidopterología, Advanced Drug Delivery Reviews and Frontiers in Immunology.

In The Last Decade

Atsushi Nagayasu

26 papers receiving 696 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Atsushi Nagayasu Japan 13 300 294 166 101 97 28 712
Parthapratim Chandaroy United States 7 537 1.8× 171 0.6× 142 0.9× 58 0.6× 140 1.4× 7 853
Ruchit Trivedi United States 9 218 0.7× 170 0.6× 93 0.6× 126 1.2× 47 0.5× 10 632
Sheryl Harvey United States 6 368 1.2× 177 0.6× 128 0.8× 45 0.4× 142 1.5× 7 682
Zoltán Székely United States 14 252 0.8× 90 0.3× 82 0.5× 44 0.4× 69 0.7× 38 620
Girish Kore India 6 276 0.9× 262 0.9× 185 1.1× 103 1.0× 33 0.3× 6 666
Hyeong Jun Byeon South Korea 12 339 1.1× 451 1.5× 290 1.7× 204 2.0× 51 0.5× 14 890
Antoni Kozłowski United States 9 200 0.7× 141 0.5× 130 0.8× 36 0.4× 41 0.4× 25 679
Kuo‐Hsiang Chuang Taiwan 14 321 1.1× 136 0.5× 126 0.8× 35 0.3× 72 0.7× 32 605
Dipak S. Pisal United States 8 342 1.1× 153 0.5× 70 0.4× 96 1.0× 68 0.7× 12 600

Countries citing papers authored by Atsushi Nagayasu

Since Specialization
Citations

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

Fields of papers citing papers by Atsushi Nagayasu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Atsushi Nagayasu

This figure shows the co-authorship network connecting the top 25 collaborators of Atsushi Nagayasu. A scholar is included among the top collaborators of Atsushi Nagayasu 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 Atsushi Nagayasu. Atsushi Nagayasu 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.
Nagayasu, Atsushi, Yusuke Miyazaki, Koshiro Sonomoto, et al.. (2025). Influence of Rheumatoid Factors on the Efficacy of TNF Inhibitor Therapy in Patients with Rheumatoid Arthritis. Rheumatology and Therapy. 12(4). 641–662.
2.
Sonomoto, Koshiro, et al.. (2025). Real-World Safety and Efficacy of Targeted Therapies in Rheumatoid Arthritis: A 5-Year, 5130-Case Follow-Up from FIRST Registry. Rheumatology and Therapy. 12(3). 561–580. 2 indexed citations
3.
Miyazaki, Yusuke, Shingo Nakayamada, Shunsuke Fukuyo, et al.. (2025). Effective Second-Line b/tsDMARDs for Patients with Rheumatoid Arthritis Unresponsive to First-Line b/tsDMARDs from the FIRST Registry. Rheumatology and Therapy. 12(2). 353–369. 2 indexed citations
4.
Sonomoto, Koshiro, et al.. (2024). A Machine Learning Approach for Prediction of CDAI Remission with TNF Inhibitors: A Concept of Precision Medicine from the FIRST Registry. Rheumatology and Therapy. 11(3). 709–736. 7 indexed citations
5.
Iwata, S., Kaoru Yamagata, Yasuyuki Todoroki, et al.. (2024). Induction of interleukin 21 receptor expression via enhanced intracellular metabolism in B cells and its relevance to the disease activity in systemic lupus erythematosus. RMD Open. 10(4). e004567–e004567. 1 indexed citations
6.
Kubo, Satoshi, Yusuke Miyazaki, Yasuyuki Todoroki, et al.. (2023). Generation-Dependent Retention Rates and Reasons for Discontinuation of Molecular Targeted Therapies in Patients with Rheumatoid Arthritis: From FIRST Registry. Rheumatology and Therapy. 10(6). 1705–1723. 2 indexed citations
7.
Nawata, Masao, et al.. (2022). Usefulness of ultrasound as a predictor of elderly-onset rheumatoid arthritis with polymyalgia rheumatica-like onset. Modern Rheumatology. 33(2). 318–322. 9 indexed citations
8.
9.
Iwata, S., Mingzeng Zhang, Hao He, et al.. (2020). Enhanced Fatty Acid Synthesis Leads to Subset Imbalance and IFN-γ Overproduction in T Helper 1 Cells. Frontiers in Immunology. 11. 593103–593103. 24 indexed citations
10.
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12.
Kinoshita, Masahiro, et al.. (2003). Highly Stabilized Amorphous 3-bis(4-Methoxyphenyl)methylene-2-indolinone (TAS-301) in Melt-Adsorbed Products with Silicate Compounds. Drug Development and Industrial Pharmacy. 29(5). 523–529. 12 indexed citations
13.
Urakami, Yumiko, Hideyoshi Harashima, Shinya Iida, Atsushi Nagayasu, & Hiroshi Kiwada. (1997). Kinetic study on the optimization of tumor delivery of antitumor agents by liposomes: Simulation study based on the physiological modeling.. Drug Delivery System. 12(6). 403–408. 3 indexed citations
14.
Nagayasu, Atsushi, et al.. (1996). Is control of distribution of liposomes between tumors and bone marrow possible?. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1278(1). 29–34. 25 indexed citations
15.
Nagayasu, Atsushi, et al.. (1995). Effect of Vesicle Size on in vivo Release of Daunorubicin from Hydrogenated Egg Phosphatidylcholine-Based Liposomes into Blood Circulation.. Biological and Pharmaceutical Bulletin. 18(7). 1020–1023. 17 indexed citations
16.
Nagayasu, Atsushi, et al.. (1994). Solubilization by Triton X-100 makes possible complete recovery of lipids from liposomes in enzymatic assay. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1194(1). 12–16. 2 indexed citations
17.
Nagayasu, Atsushi, et al.. (1994). Effects of Fluidity and Vesicle Size on Antitumor Activity and Myelosuppressive Activity of Liposomes Loaded with Daunorubicin.. Biological and Pharmaceutical Bulletin. 17(7). 935–939. 21 indexed citations
18.
Morimoto, Kazuhiro, et al.. (1990). Design of a polyvinyl alcohol hydrogel containing phospholipid as controlled-release vehicle for rectal administration of (±)-propranolol HCl. Journal of Pharmacy and Pharmacology. 42(10). 720–722. 10 indexed citations
19.
Morimoto, Kazuhiro, et al.. (1990). Evaluation of Polyvinyl Alcohol Hydrogel as Sustained-Release Vehicle for Transdermal Sytem of Bunitrolol-HCL. Drug Development and Industrial Pharmacy. 16(1). 13–29. 16 indexed citations
20.
Morimoto, Kazuhiro, et al.. (1989). Evaluation of Polyvinyl Alcohol Hydrogel as a Sustained-Release Vehicle for Rectal Administration of Indomethacin. Pharmaceutical Research. 6(4). 338–341. 35 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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