Hidehisa Shimizu

2.9k total citations
70 papers, 2.4k citations indexed

About

Hidehisa Shimizu is a scholar working on Molecular Biology, Immunology and Epidemiology. According to data from OpenAlex, Hidehisa Shimizu has authored 70 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 19 papers in Immunology and 13 papers in Epidemiology. Recurrent topics in Hidehisa Shimizu's work include Eicosanoids and Hypertension Pharmacology (8 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (7 papers) and Peroxisome Proliferator-Activated Receptors (7 papers). Hidehisa Shimizu is often cited by papers focused on Eicosanoids and Hypertension Pharmacology (8 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (7 papers) and Peroxisome Proliferator-Activated Receptors (7 papers). Hidehisa Shimizu collaborates with scholars based in Japan, Ghana and South Korea. Hidehisa Shimizu's co-authors include Toshimitsu Niwa, Fuyuhiko Nishijima, Dilinaer Bolati, Atsushi Enomoto, Hitoshi Miyazaki, Maimaiti Yisireyili, Yukihiro Higashiyama, Ayinuer Adijiang, Gulinuer Muteliefu and Shinichi Saito and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

Hidehisa Shimizu

67 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hidehisa Shimizu Japan 28 957 910 403 276 225 70 2.4k
Fuyuhiko Nishijima Japan 32 780 0.8× 1.2k 1.3× 397 1.0× 199 0.7× 233 1.0× 37 2.4k
Daniela Verzola Italy 30 961 1.0× 1.2k 1.3× 733 1.8× 310 1.1× 321 1.4× 109 3.1k
Jinn‐Yuh Guh Taiwan 30 718 0.8× 697 0.8× 257 0.6× 155 0.6× 212 0.9× 80 2.3k
Raúl R. Rodrigues-Díez Spain 31 1.2k 1.3× 746 0.8× 228 0.6× 504 1.8× 431 1.9× 72 3.1k
Sungjin Chung South Korea 30 792 0.8× 658 0.7× 388 1.0× 130 0.5× 399 1.8× 100 2.5k
Ya‐Long Feng China 23 1.5k 1.5× 579 0.6× 225 0.6× 220 0.8× 227 1.0× 33 3.0k
Victoria Ramírez Mexico 21 696 0.7× 957 1.1× 185 0.5× 139 0.5× 325 1.4× 48 2.5k
Liyu He China 27 1.3k 1.4× 1.2k 1.3× 234 0.6× 370 1.3× 250 1.1× 93 3.1k
Anna V. Mathew United States 23 1.3k 1.3× 434 0.5× 776 1.9× 302 1.1× 267 1.2× 51 2.6k
Na Liu China 37 1.9k 2.0× 1.3k 1.5× 178 0.4× 325 1.2× 478 2.1× 134 3.8k

Countries citing papers authored by Hidehisa Shimizu

Since Specialization
Citations

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

Fields of papers citing papers by Hidehisa Shimizu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hidehisa Shimizu

This figure shows the co-authorship network connecting the top 25 collaborators of Hidehisa Shimizu. A scholar is included among the top collaborators of Hidehisa Shimizu 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 Hidehisa Shimizu. Hidehisa Shimizu 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.
Kawahara, Hideaki, Kohji Nishimura, Hideaki Maseda, et al.. (2024). Increased Prorenin Expression in the Kidneys May Be Involved in the Abnormal Renal Function Caused by Prolonged Environmental Exposure to Microcystin-LR. Toxics. 12(8). 547–547. 3 indexed citations
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Kobayashi, Jun, et al.. (2023). Activation of the TLR4-JNK but not the TLR4-ERK pathway induced by indole-3-acetic acid exerts anti-proliferative effects on Caco-2 cells. Bioscience Biotechnology and Biochemistry. 87(8). 839–849. 23 indexed citations
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Lee, Yeonmi, W. Iwasaki, Koji Tada, et al.. (2022). Dietary supplementation with okara and Bacillus coagulans lilac-01 improves hepatic lipid accumulation induced by cholic acids in rats. Journal of Functional Foods. 90. 104991–104991. 3 indexed citations
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Hori, Shota, et al.. (2020). A low coefficient of variation in hepatic triglyceride concentration in an inbred rat strain. Lipids in Health and Disease. 19(1). 137–137. 3 indexed citations
8.
Kawahara, Hideaki, et al.. (2019). Skatole regulates intestinal epithelial cellular functions through activating aryl hydrocarbon receptors and p38. Biochemical and Biophysical Research Communications. 510(4). 649–655. 60 indexed citations
9.
Nakayama, Kazuhiro, Shinichi Saito, Kazuhisa Watanabe, et al.. (2017). Influence of AHRR Pro189Ala polymorphism on kidney functions. Bioscience Biotechnology and Biochemistry. 81(6). 1120–1124. 3 indexed citations
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Imamura, Osamu, et al.. (2015). A novel strategy for selective gene delivery by using the inhibitory effect of blue light on jetPRIME‐mediated transfection. Biotechnology and Bioengineering. 113(7). 1560–1567. 3 indexed citations
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Bolati, Dilinaer, Hidehisa Shimizu, Maimaiti Yisireyili, Fuyuhiko Nishijima, & Toshimitsu Niwa. (2013). Indoxyl sulfate, a uremic toxin, downregulates renal expression of Nrf2 through activation of NF-κB. BMC Nephrology. 14(1). 56–56. 113 indexed citations
14.
Shimizu, Hidehisa, Dilinaer Bolati, Yukihiro Higashiyama, et al.. (2012). Indoxyl sulfate upregulates renal expression of MCP-1 via production of ROS and activation of NF-κB, p53, ERK, and JNK in proximal tubular cells. Life Sciences. 90(13-14). 525–530. 137 indexed citations
15.
Shimizu, Hidehisa, Maimaiti Yisireyili, Yukihiro Higashiyama, Fuyuhiko Nishijima, & Toshimitsu Niwa. (2012). Indoxyl sulfate upregulates renal expression of ICAM-1 via production of ROS and activation of NF-κB and p53 in proximal tubular cells. Life Sciences. 92(2). 143–148. 80 indexed citations
16.
Shimizu, Hidehisa, Maimaiti Yisireyili, Fuyuhiko Nishijima, & Toshimitsu Niwa. (2012). Stat3 Contributes to Indoxyl Sulfate-Induced Inflammatory and Fibrotic Gene Expression and Cellular Senescence. American Journal of Nephrology. 36(2). 184–189. 43 indexed citations
17.
Adijiang, Ayinuer, Hidehisa Shimizu, Yusuke Higuchi, Fuyuhiko Nishijima, & Toshimitsu Niwa. (2011). Indoxyl Sulfate Reduces Klotho Expression and Promotes Senescence in the Kidneys of Hypertensive Rats. Journal of Renal Nutrition. 21(1). 105–109. 53 indexed citations
18.
Adijiang, Ayinuer, Yusuke Higuchi, Fuyuhiko Nishijima, Hidehisa Shimizu, & Toshimitsu Niwa. (2010). Indoxyl sulfate, a uremic toxin, promotes cell senescence in aorta of hypertensive rats. Biochemical and Biophysical Research Communications. 399(4). 637–641. 62 indexed citations
19.
Shimizu, Hidehisa, et al.. (2010). Protein tyrosine phosphatase PTPεM negatively regulates PDGF β-receptor signaling induced by high glucose and PDGF in vascular smooth muscle cells. American Journal of Physiology-Cell Physiology. 299(5). C1144–C1152. 19 indexed citations
20.
Nakagawa, Yoshimi, Naohito Aoki, Koji Aoyama, et al.. (2005). Receptor-Type Protein Tyrosine Phosphatase ε (PTPεM) is a Negative Regulator of Insulin Signaling in Primary Hepatocytes and Liver. ZOOLOGICAL SCIENCE. 22(2). 169–175. 28 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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