Ai Kushida

1.6k total citations
15 papers, 1.3k citations indexed

About

Ai Kushida is a scholar working on Biomedical Engineering, Surgery and Molecular Biology. According to data from OpenAlex, Ai Kushida has authored 15 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Biomedical Engineering, 5 papers in Surgery and 5 papers in Molecular Biology. Recurrent topics in Ai Kushida's work include 3D Printing in Biomedical Research (6 papers), Tissue Engineering and Regenerative Medicine (5 papers) and Hydrogels: synthesis, properties, applications (3 papers). Ai Kushida is often cited by papers focused on 3D Printing in Biomedical Research (6 papers), Tissue Engineering and Regenerative Medicine (5 papers) and Hydrogels: synthesis, properties, applications (3 papers). Ai Kushida collaborates with scholars based in Japan and Nepal. Ai Kushida's co-authors include Masayuki Yamato, Teruo Okano, Akihiko Kikuchi, Chie Konno, Yasuhisa Sakurai, M Utsumi, Motohiro Hirose, Yuki Isoi, Yoshikatsu Akiyama and Oh Hyeong Kwon and has published in prestigious journals such as Biomaterials, Biochemical and Biophysical Research Communications and Journal of Biomedical Materials Research.

In The Last Decade

Ai Kushida

15 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ai Kushida Japan	9	644	600	478	293	224	15	1.3k
Chie Konno Japan	7	705 1.1×	559 0.9×	426 0.9×	289 1.0×	250 1.1×	8	1.3k
Minako Okuhara Japan	7	575 0.9×	485 0.8×	257 0.5×	370 1.3×	291 1.3×	8	1.1k
M Utsumi Japan	6	417 0.6×	317 0.5×	210 0.4×	173 0.6×	151 0.7×	8	856
Iossif Strehin United States	12	380 0.6×	484 0.8×	411 0.9×	276 0.9×	177 0.8×	13	1.3k
Anirudha Singh United States	18	497 0.8×	422 0.7×	322 0.7×	114 0.4×	92 0.4×	29	1.3k
Colleen Irvin United States	9	419 0.7×	348 0.6×	311 0.7×	138 0.5×	351 1.6×	10	1.5k
Winnette McIntosh United States	7	585 0.9×	611 1.0×	287 0.6×	333 1.1×	64 0.3×	7	1.4k
Rachael Schmedlen United States	7	846 1.3×	821 1.4×	357 0.7×	363 1.2×	145 0.6×	12	1.5k
Yuki Isoi Japan	7	759 1.2×	982 1.6×	1.0k 2.2×	115 0.4×	93 0.4×	8	1.6k
Mara Macdonald United States	7	1.1k 1.7×	826 1.4×	632 1.3×	244 0.8×	323 1.4×	8	1.9k

Countries citing papers authored by Ai Kushida

Since Specialization

Citations

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

Fields of papers citing papers by Ai Kushida

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ai Kushida

This figure shows the co-authorship network connecting the top 25 collaborators of Ai Kushida. A scholar is included among the top collaborators of Ai Kushida 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 Ai Kushida. Ai Kushida is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Takagi, Ryo, Masayuki Yamato, Ai Kushida, Kohji Nishida, & Teruo Okano. (2012). Profiling of Extracellular Matrix and Cadherin Family Gene Expression in Mouse Feeder Layer Cells: Type VI Collagen Is a Candidate Molecule Inducing the Colony Formation of Epithelial Cells. Tissue Engineering Part A. 18(23-24). 2539–2548. 7 indexed citations

Kushida, Ai, Akira Kato, Keiko Fukushima, et al.. (2009). Neuroblastoma GOTO cells are hypersensitive to disruption of lipid rafts. Biochemical and Biophysical Research Communications. 389(1). 122–127. 2 indexed citations

Akiyama, Yoshikatsu, Ai Kushida, Masayuki Yamato, Akihiko Kikuchi, & Teruo Okano. (2007). Surface Characterization of Poly(N-isopropylacrylamide) Grafted Tissue Culture Polystyrene by Electron Beam Irradiation, Using Atomic Force Microscopy, and X-Ray Photoelectron Spectroscopy. Journal of Nanoscience and Nanotechnology. 7(3). 796–802. 38 indexed citations

Hasegawa, Go, et al.. (2005). Human neuroblastoma GOTO cells express CD44 and localize it into lipid rafts upon differentiation into Schwannian cells. Cell Biology International. 29(3). 193–202. 5 indexed citations

Kushida, Ai, Masayuki Yamato, Yuki Isoi, Akihiko Kikuchi, & Teruo Okano. (2005). A noninvasive transfer system for polarized renal tubule epithelial cell sheets using temperature-responsive culture dishes. European Cells and Materials. 10. 23–30. 54 indexed citations

Yamato, Masayuki, Ai Kushida, Chie Konno, et al.. (2002). Two-dimensional cell sheet manipulation of heterotypically co-cultured lung cells utilizing temperature-responsive culture dishes results in long-term maintenance of differentiated epithelial cell functions. Biomaterials. 23(4). 1121–1130. 80 indexed citations

Yamato, Masayuki, M Utsumi, Ai Kushida, et al.. (2001). Thermo-Responsive Culture Dishes Allow the Intact Harvest of Multilayered Keratinocyte Sheets without Dispase by Reducing Temperature. Tissue Engineering. 7(4). 473–480. 344 indexed citations

Kushida, Ai, et al.. (2000). Temperature-responsive culture dishes allow nonenzymatic harvest of differentiated Madin-Darby canine kidney (MDCK) cell sheets. Journal of Biomedical Materials Research. 51(2). 216–223. 112 indexed citations

Yamato, Masayuki, Chie Konno, Ai Kushida, et al.. (2000). Release of adsorbed fibronectin from temperature-responsive culture surfaces requires cellular activity. Biomaterials. 21(10). 981–986. 102 indexed citations

10.

Kushida, Ai, Masayuki Yamato, Akihiko Kikuchi, & Teruo Okano. (2000). Two-dimensional manipulation of differentiated Madin-Darby canine kidney (MDCK) cell sheets: The noninvasive harvest from temperature-responsive culture dishes and transfer to other surfaces. Journal of Biomedical Materials Research. 54(1). 37–46. 86 indexed citations

11.

Hirose, Motohiro, Masayuki Yamato, Oh Hyeong Kwon, et al.. (2000). Temperature-Responsive surface for novel co-culture systems of hepatocytes with endothelial cells: 2-D patterned and double layered co-cultures. Yonsei Medical Journal. 41(6). 803–803. 43 indexed citations

12.

Yamato, Masayuki, Ai Kushida, & Teruo Okano. (2000). [Cell adhesion and detachment control toward cell sheet engineering utilizing temperature-responsive intelligent culture dishes].. PubMed. 45(10). 1766–72. 3 indexed citations

13.

Yamato, Masayuki, Ai Kushida, Chie Konno, et al.. (1999). A Novel Tool of Temperature-Responsive Cell Culture Surfaces and Its Application to Matrix Biology. 31(1). 13–16. 2 indexed citations

14.

Kushida, Ai, Masayuki Yamato, Chie Konno, et al.. (1999). Decrease in culture temperature releases monolayer endothelial cell sheets together with deposited fibronectin matrix from temperature-responsive culture surfaces. Journal of Biomedical Materials Research. 45(4). 355–362. 402 indexed citations

15.

Kushida, Ai, et al.. (1998). Screening of Hybridoma Clones Producing Antibodies Against Plasma Membrane-Associated Materials. Hybridoma. 17(2). 209–213. 2 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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