Wataru Nishida

3.2k total citations
61 papers, 2.6k citations indexed

About

Wataru Nishida is a scholar working on Molecular Biology, Epidemiology and Physiology. According to data from OpenAlex, Wataru Nishida has authored 61 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 18 papers in Epidemiology and 14 papers in Physiology. Recurrent topics in Wataru Nishida's work include Adipokines, Inflammation, and Metabolic Diseases (18 papers), Regulation of Appetite and Obesity (11 papers) and Adipose Tissue and Metabolism (10 papers). Wataru Nishida is often cited by papers focused on Adipokines, Inflammation, and Metabolic Diseases (18 papers), Regulation of Appetite and Obesity (11 papers) and Adipose Tissue and Metabolism (10 papers). Wataru Nishida collaborates with scholars based in Japan, United States and Ireland. Wataru Nishida's co-authors include Kenji Sobue, Ken’ichiro Hayashi, Kunio Hiwada, Katsuhiko Kohara, Haruhiko Osawa, Hiroshi Onuma, Motofumi Maguchi, Masanori Takahashi, Hideichi Makino and Masaaki Ochi and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Circulation.

In The Last Decade

Wataru Nishida

61 papers receiving 2.6k citations

Peers

Wataru Nishida
Anja Köster Netherlands
Anjali K. Nath United States
Yazmín Macotela Mexico
Jonathan M. Peterson United States
Bethel Stannard United States
Scott R. Johnstone United States
Kenneth Longo United States
Jianping Jin United States
Takeshige Kunieda Japan
Laurie Erb United States
Anja Köster Netherlands
Wataru Nishida
Citations per year, relative to Wataru Nishida Wataru Nishida (= 1×) peers Anja Köster

Countries citing papers authored by Wataru Nishida

Since Specialization
Citations

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

Fields of papers citing papers by Wataru Nishida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wataru Nishida

This figure shows the co-authorship network connecting the top 25 collaborators of Wataru Nishida. A scholar is included among the top collaborators of Wataru Nishida 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 Wataru Nishida. Wataru Nishida 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.
Maruyama, Koutatsu, Takeshi Tanigawa, Eri Eguchi, et al.. (2019). Effect of non-surgical periodontal therapy on insulin resistance and insulin sensitivity among individuals with borderline diabetes: A randomized controlled trial. Journal of Dentistry. 85. 18–24. 11 indexed citations
2.
Tanigawa, Takeshi, Isao Saito, Wataru Nishida, et al.. (2014). Sleep-related intermittent hypoxemia and glucose intolerance: a community-based study. Sleep Medicine. 15(10). 1212–1218. 33 indexed citations
3.
Tabara, Yasuharu, Michiya Igase, Isao Saito, et al.. (2013). Association of hematological parameters with insulin resistance, insulin sensitivity, and asymptomatic cerebrovascular damage: The J-SHIP and Toon Health Study. Clinical Hemorheology and Microcirculation. 55(3). 297–311. 7 indexed citations
4.
Tabara, Yasuharu, Isao Saito, Wataru Nishida, et al.. (2011). Relatively lower central aortic pressure in patients with impaired insulin sensitivity and resistance. Journal of Hypertension. 29(10). 1948–1954. 19 indexed citations
5.
Onuma, Hiroshi, Yasuharu Tabara, Ryuichi Kawamoto, et al.. (2010). The GCKR rs780094 polymorphism is associated with susceptibility of type 2 diabetes, reduced fasting plasma glucose levels, increased triglycerides levels and lower HOMA-IR in Japanese population. Journal of Human Genetics. 55(9). 600–604. 60 indexed citations
6.
Onuma, Hiroshi, Yasuharu Tabara, Ryoichi Kawamura, et al.. (2010). A at Single Nucleotide Polymorphism-358 Is Required for G at -420 to Confer the Highest Plasma Resistin in the General Japanese Population. PLoS ONE. 5(3). e9718–e9718. 41 indexed citations
7.
Tabara, Yasuharu, Haruhiko Osawa, Haiyan Guo, et al.. (2009). Prognostic significance of FTO genotype in the development of obesity in Japanese: the J-SHIPP study. International Journal of Obesity. 33(11). 1243–1248. 34 indexed citations
8.
Yamauchi, Junko, Haruhiko Osawa, Masaaki Ochi, et al.. (2008). Serum resistin is reduced by glucose and meal loading in healthy human subjects. Metabolism. 57(2). 149–156. 21 indexed citations
9.
10.
Nishida, Wataru, Yuya Yamada, Daisuke Chujo, et al.. (2007). Insulin administration may trigger pancreatic β-cell destruction in patients with type 2 diabetes. Diabetes Research and Clinical Practice. 79(2). 220–229. 8 indexed citations
11.
Osawa, Haruhiko, Masaaki Ochi, Kenichi Kato, et al.. (2007). Serum resistin is associated with the severity of microangiopathies in type 2 diabetes. Biochemical and Biophysical Research Communications. 355(2). 342–346. 20 indexed citations
12.
Onuma, Hiroshi, et al.. (2005). A newly identified 50 kDa protein, which is associated with phosphodiesterase 3B, is phosphorylated by insulin in rat adipocytes. Biochemical and Biophysical Research Communications. 337(3). 976–982. 7 indexed citations
13.
Osawa, Haruhiko, Hiroshi Onuma, Masaaki Ochi, et al.. (2005). Resistin SNP-420 determines its monocyte mRNA and serum levels inducing type 2 diabetes. Biochemical and Biophysical Research Communications. 335(2). 596–602. 77 indexed citations
14.
Osawa, Haruhiko, Kazuya Yamada, Hiroshi Onuma, et al.. (2004). The G/G Genotype of a Resistin Single-Nucleotide Polymorphism at −420 Increases Type 2 Diabetes Mellitus Susceptibility by Inducing Promoter Activity through Specific Binding of Sp1/3. The American Journal of Human Genetics. 75(4). 678–686. 199 indexed citations
15.
Hayashi, Ken’ichiro, Kazuhiro Kimura, Wataru Nishida, et al.. (2000). Phenotype‐dependent expression of cadherin 6B in vascular and visceral smooth muscle cells. FEBS Letters. 469(1). 67–71. 5 indexed citations
16.
Kitami, Yutaka, Motofumi Maguchi, Wataru Nishida, et al.. (1999). The Unique 5'-Flanking Region of the Human Basic Calponin Gene.. Hypertension Research. 22(3). 187–193. 8 indexed citations
17.
Nakamura, Mako, Wataru Nishida, Shunsuke Mori, Masanori Takahashi, & Kenji Sobue. (1998). A homeodomain protein, Barx and serum response factor (SRF) regulate transcription of β-tropomyosin gene in the smooth muscle cells.. 21. 429. 1 indexed citations
18.
Sobue, Kenji, Ken’ichiro Hayashi, & Wataru Nishida. (1998). Molecular Mechanism of Phenotypic Modulation of Smooth Muscle Cells. Hormone Research in Paediatrics. 50(Suppl. 2). 15–24. 43 indexed citations
19.
Nishida, Wataru, Yutaka Kitami, & Kunio Hiwada. (1993). cDNA cloning and mRNA expression of calponin and SM22 in rat aorta smooth muscle cells. Gene. 130(2). 297–302. 66 indexed citations
20.
Nishida, Wataru, et al.. (1990). Do thin filaments of smooth muscle contain calponin?. FEBS Letters. 268(1). 165–168. 50 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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