Mai Uesugi

2.5k total citations · 1 hit paper
17 papers, 1.5k citations indexed

About

Mai Uesugi is a scholar working on Molecular Biology, Epidemiology and Cell Biology. According to data from OpenAlex, Mai Uesugi has authored 17 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Epidemiology and 3 papers in Cell Biology. Recurrent topics in Mai Uesugi's work include Endoplasmic Reticulum Stress and Disease (3 papers), Neuroscience and Neural Engineering (2 papers) and Autophagy in Disease and Therapy (2 papers). Mai Uesugi is often cited by papers focused on Endoplasmic Reticulum Stress and Disease (3 papers), Neuroscience and Neural Engineering (2 papers) and Autophagy in Disease and Therapy (2 papers). Mai Uesugi collaborates with scholars based in Japan, United States and United Kingdom. Mai Uesugi's co-authors include Takashi Owa, Yoshihiko Kotake, Koji Sagane, Yasushi Ishihama, Masao Iwata, Hajime Shimizu, Yoshiharu Mizui, Yuko Mimori‐Kiyosue, Masayuki Kaneko and Yasuyuki Nomura and has published in prestigious journals such as Journal of Biological Chemistry, Cancer Research and FEBS Letters.

In The Last Decade

Mai Uesugi

17 papers receiving 1.5k citations

Hit Papers

Splicing factor SF3b as a target of the antitumor natural... 2007 2026 2013 2019 2007 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
Mai Uesugi Japan 12 1.0k 297 273 148 134 17 1.5k
Yongmun Choi South Korea 15 1.3k 1.2× 226 0.8× 150 0.5× 118 0.8× 106 0.8× 34 1.7k
Peter Canning United Kingdom 14 1.2k 1.2× 258 0.9× 145 0.5× 83 0.6× 126 0.9× 21 1.6k
Wooyoung Hur United States 19 1.3k 1.3× 253 0.9× 130 0.5× 91 0.6× 103 0.8× 35 1.9k
T F Franke United States 7 1.3k 1.3× 367 1.2× 124 0.5× 74 0.5× 223 1.7× 7 1.8k
Chunhua Lu China 23 1.0k 1.0× 443 1.5× 170 0.6× 78 0.5× 391 2.9× 67 1.7k
Robert te Poele United Kingdom 20 1.1k 1.1× 451 1.5× 206 0.8× 106 0.7× 292 2.2× 33 1.7k
William J. Placzek United States 19 947 0.9× 290 1.0× 101 0.4× 45 0.3× 199 1.5× 42 1.3k
Francesca Grespi Italy 16 1.4k 1.3× 458 1.5× 199 0.7× 191 1.3× 383 2.9× 20 1.7k
Daniela Spano Italy 22 757 0.7× 404 1.4× 213 0.8× 219 1.5× 184 1.4× 37 1.6k
Valérie Gouazé‐Andersson France 20 1.3k 1.2× 277 0.9× 271 1.0× 113 0.8× 124 0.9× 31 1.6k

Countries citing papers authored by Mai Uesugi

Since Specialization
Citations

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

Fields of papers citing papers by Mai Uesugi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mai Uesugi

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

All Works

17 of 17 papers shown
1.
Uesugi, Mai, Takashi Obara, Yoshihisa Arita, et al.. (2021). Serum APOA4 Pharmacodynamically Represents Administered Recombinant Human Hepatocyte Growth Factor (E3112). International Journal of Molecular Sciences. 22(9). 4578–4578. 3 indexed citations
2.
Minami, Manabu, et al.. (2020). Administration of mulberry leaves maintains pancreatic β-cell mass in obese/type 2 diabetes mellitus mouse model. BMC Complementary Medicine and Therapies. 20(1). 19 indexed citations
3.
Kimura, Takayuki, Mai Uesugi, Kazuma Takase, Norimasa Miyamoto, & Kohei Sawada. (2017). Hsp90 inhibitor geldanamycin attenuates the cytotoxicity of sunitinib in cardiomyocytes via inhibition of the autophagy pathway. Toxicology and Applied Pharmacology. 329. 282–292. 29 indexed citations
4.
Uehara, Taisuke, Yukinori Minoshima, Koji Sagane, et al.. (2017). Selective degradation of splicing factor CAPERα by anticancer sulfonamides. Nature Chemical Biology. 13(6). 675–680. 279 indexed citations
5.
Funahashi, Yasuhiro, Kiyoshi Okamoto, Yusuke Adachi, et al.. (2014). Eribulin mesylate reduces tumor microenvironment abnormality by vascular remodeling in preclinical human breast cancer models. Cancer Science. 105(10). 1334–1342. 212 indexed citations
6.
Shikata, Kohdoh, Mai Uesugi, Hiroyuki Katayama, et al.. (2013). Prediction of relaxin-3-induced downstream pathway resulting in anxiolytic-like behaviors in rats based on a microarray and peptidome analysis. Journal of Receptors and Signal Transduction. 33(4). 224–233. 21 indexed citations
7.
Uesugi, Mai, Atsuko Ojima, Tomohiko Taniguchi, Norimasa Miyamoto, & Kohei Sawada. (2013). Low-density plating is sufficient to induce cardiac hypertrophy and electrical remodeling in highly purified human iPS cell-derived cardiomyocytes. Journal of Pharmacological and Toxicological Methods. 69(2). 177–188. 31 indexed citations
8.
Agoulnik, Sergei, Judith Oestreicher, Noël Taylor, et al.. (2013). Abstract 3830: Eribulin and Paclitaxel differentially affect gene expression profiling of blood vessel cells and in vitro angiogenesis in co-cultures of human endothelial cells with pericytes.. Cancer Research. 73(8_Supplement). 3830–3830. 2 indexed citations
10.
11.
Tsujioka, Takayuki, et al.. (2012). Effects of DNA methyltransferase inhibitors (DNMTIs) on MDS-derived cell lines. Experimental Hematology. 41(2). 189–197. 25 indexed citations
12.
Taniguchi, Tomohiko, Mai Uesugi, Toru Arai, et al.. (2011). Chronic Probucol Treatment Decreases the Slow Component of the Delayed-Rectifier Potassium Current in CHO Cells Transfected With KCNQ1 and KCNE1. Journal of Cardiovascular Pharmacology. 59(4). 377–386. 14 indexed citations
13.
Tokuhara, Naoki, Kana Namiki, Mai Uesugi, et al.. (2010). N-type Calcium Channel in the Pathogenesis of Experimental Autoimmune Encephalomyelitis*. Journal of Biological Chemistry. 285(43). 33294–33306. 30 indexed citations
14.
Miyamoto, Norimasa, Kana Namiki, Naoki Tokuhara, et al.. (2009). The Utilization of Gene Targeting Models During in Preclinical Study of Drug Discovery Process - Example of Phenotypic and Functional Analysis of Cacna1 βGene Product. Current Pharmaceutical Biotechnology. 10(2). 261–267. 2 indexed citations
15.
Kotake, Yoshihiko, Koji Sagane, Takashi Owa, et al.. (2007). Splicing factor SF3b as a target of the antitumor natural product pladienolide. Nature Chemical Biology. 3(9). 570–575. 500 indexed citations breakdown →
16.
Kubota, Kyoko, Yoshifumi Niinuma, Masayuki Kaneko, et al.. (2006). Suppressive effects of 4‐phenylbutyrate on the aggregation of Pael receptors and endoplasmic reticulum stress. Journal of Neurochemistry. 97(5). 1259–1268. 156 indexed citations
17.
Kaneko, Masayuki, et al.. (2002). Human HRD1 protects against ER stress‐induced apoptosis through ER‐associated degradation1. FEBS Letters. 532(1-2). 147–152. 188 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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