Mari Dezawa

11.1k total citations · 1 hit paper
171 papers, 8.6k citations indexed

About

Mari Dezawa is a scholar working on Genetics, Molecular Biology and Developmental Neuroscience. According to data from OpenAlex, Mari Dezawa has authored 171 papers receiving a total of 8.6k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Genetics, 73 papers in Molecular Biology and 50 papers in Developmental Neuroscience. Recurrent topics in Mari Dezawa's work include Mesenchymal stem cell research (78 papers), Neurogenesis and neuroplasticity mechanisms (45 papers) and Nerve injury and regeneration (41 papers). Mari Dezawa is often cited by papers focused on Mesenchymal stem cell research (78 papers), Neurogenesis and neuroplasticity mechanisms (45 papers) and Nerve injury and regeneration (41 papers). Mari Dezawa collaborates with scholars based in Japan, United States and Egypt. Mari Dezawa's co-authors include Shohei Wakao, Masaaki Kitada, Chizuka Idé, Yutaka Itokazu, Hajime Sawada, Yasumasa Kuroda, Hiroto Ishikawa, Mikio Hoshino, Naoya Matsumoto and Yoshihiro Kushida and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.

In The Last Decade

Mari Dezawa

168 papers receiving 8.4k citations

Hit Papers

Specific induction of neu... 2004 2026 2011 2018 2004 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mari Dezawa Japan 48 4.1k 3.7k 2.6k 2.2k 2.0k 171 8.6k
Chizuka Idé Japan 49 2.3k 0.6× 3.8k 1.0× 4.5k 1.8× 1.9k 0.9× 2.1k 1.0× 189 9.9k
Osamu Honmou Japan 41 3.7k 0.9× 2.2k 0.6× 2.0k 0.8× 820 0.4× 2.2k 1.1× 119 6.5k
Fanie Barnabé‐Heider Sweden 26 1.4k 0.3× 4.3k 1.2× 1.7k 0.7× 1.7k 0.8× 2.2k 1.1× 33 7.7k
Alison E. Willing United States 42 3.3k 0.8× 2.6k 0.7× 1.5k 0.6× 1.0k 0.5× 2.1k 1.0× 130 7.1k
Masaaki Kitada Japan 35 2.0k 0.5× 2.0k 0.5× 1.7k 0.7× 1.0k 0.5× 1.3k 0.7× 89 4.6k
Cindi M. Morshead Canada 44 1.4k 0.3× 3.6k 1.0× 3.3k 1.3× 757 0.3× 4.4k 2.2× 127 8.8k
Yang D. Teng United States 37 1.3k 0.3× 2.1k 0.6× 2.3k 0.9× 901 0.4× 2.1k 1.0× 102 6.1k
Melissa K. Carpenter United States 33 1.3k 0.3× 9.4k 2.6× 1.6k 0.6× 4.8k 2.2× 1.6k 0.8× 48 12.8k
Samuel Saporta United States 37 2.0k 0.5× 2.0k 0.5× 1.7k 0.7× 827 0.4× 1.4k 0.7× 95 5.2k

Countries citing papers authored by Mari Dezawa

Since Specialization
Citations

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

Fields of papers citing papers by Mari Dezawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mari Dezawa

This figure shows the co-authorship network connecting the top 25 collaborators of Mari Dezawa. A scholar is included among the top collaborators of Mari Dezawa 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 Mari Dezawa. Mari Dezawa 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.
Dezawa, Mari. (2025). Comparison of MSCs and Muse cells: the possible use for healthspan optimization. Biogerontology. 26(4). 139–139.
2.
Toyoda, Shigeru, Masashi Sakuma, Kazuyuki Ishida, et al.. (2024). Accumulation of endogenous Muse cells in the myocardium and its pathophysiological role in patients with fulminant myocarditis. Clinical and Translational Science. 17(11). e70067–e70067. 2 indexed citations
3.
Kumagai, Gentaro, Ayako Sasaki, Taku Fujita, et al.. (2023). Comparison of the Anti-Inflammatory Effects of Mouse Adipose- and Bone-Marrow-Derived Multilineage-Differentiating Stress-Enduring Cells in Acute-Phase Spinal Cord Injury. Journal of Neurotrauma. 40(23-24). 2596–2609. 4 indexed citations
4.
Sato, Yoshiaki, Shinobu Shimizu, Toshihiko Suzuki, et al.. (2023). Systemic administration of clinical-grade multilineage-differentiating stress-enduring cells ameliorates hypoxic–ischemic brain injury in neonatal rats. Scientific Reports. 13(1). 14958–14958. 4 indexed citations
5.
Yamashita, Shinichi, Shinji Fujii, Yu Suzuki, et al.. (2023). Intravenously engrafted human multilineage‐differentiating stress‐enduring (Muse) cells rescue erectile function after rat cavernous nerve injury. British Journal of Urology. 133(3). 332–340. 1 indexed citations
6.
Wakao, Shohei, et al.. (2022). Phagocytosing differentiated cell-fragments is a novel mechanism for controlling somatic stem cell differentiation within a short time frame. Cellular and Molecular Life Sciences. 79(11). 542–542. 19 indexed citations
7.
Yamada, Yoshihisa, Shingo Minatoguchi, Hiromitsu Kanamori, et al.. (2021). Stem cell therapy for acute myocardial infarction - focusing on the comparison between Muse cells and mesenchymal stem cells. Journal of Cardiology. 80(1). 80–87. 27 indexed citations
9.
Kushida, Yoshihiro, Shohei Wakao, Yasumasa Kuroda, et al.. (2020). Protection of liver sinusoids by intravenous administration of human Muse cells in a rat extra-small partial liver transplantation model. American Journal of Transplantation. 21(6). 2025–2039. 17 indexed citations
10.
Kamei, Naosuke, Ryo Shimizu, Shohei Wakao, et al.. (2017). Therapeutic Potential of Multilineage-Differentiating Stress-Enduring Cells for Osteochondral Repair in a Rat Model. Stem Cells International. 2017. 1–8. 18 indexed citations
11.
Katagiri, Hirokatsu, Yoshihiro Kushida, Y Kuroda, et al.. (2015). A Distinct Subpopulation of Bone Marrow Mesenchymal Stem Cells, Muse Cells, Directly Commit to the Replacement of Liver Components. American Journal of Transplantation. 16(2). 468–483. 72 indexed citations
12.
Wakao, Shohei, Yasumasa Kuroda, Kenichiro Tsuchiyama, et al.. (2013). Human Adipose Tissue Possesses a Unique Population of Pluripotent Stem Cells with Nontumorigenic and Low Telomerase Activities: Potential Implications in Regenerative Medicine. Stem Cells and Development. 23(7). 717–728. 125 indexed citations
14.
Kitada, Masaaki, et al.. (2009). Practical Induction System for Dopamine-Producing Cells from Bone Marrow Stromal Cells Using Spermine-Pullulan-Mediated Reverse Transfection Method. Tissue Engineering Part A. 15(7). 1655–1665. 22 indexed citations
15.
Xu, Yi, Masaaki Kitada, Masahiro Yamaguchi, Mari Dezawa, & Chizuka Idé. (2006). Increase in bFGF-responsive neural progenitor population following contusion injury of the adult rodent spinal cord. Neuroscience Letters. 397(3). 174–179. 42 indexed citations
16.
Yamazaki, Hitoshi, Hiroshi Ohguro, Ikuyo Maruyama, et al.. (2002). Poster Program. The Keio Journal of Medicine. 51(supplement1). 76–85. 4 indexed citations
17.
Dezawa, Mari, et al.. (2002). Gene transfer into retinal ganglion cells by in vivo electroporation: a new approach. Micron. 33(1). 1–6. 72 indexed citations
18.
Kobayashi, Noriko, Mari Dezawa, Hiroshi Nagata, Shigeki Yuasa, & Akiyoshi Konno. (1998). Immunohistochemical Study of E–cadherin and ZO–1 in Allergic Nasal Epithelium of the Guinea Pig. International Archives of Allergy and Immunology. 116(3). 196–205. 10 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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