Yasuyo Urasaki

1.2k total citations
27 papers, 960 citations indexed

About

Yasuyo Urasaki is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Yasuyo Urasaki has authored 27 papers receiving a total of 960 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 7 papers in Oncology and 6 papers in Epidemiology. Recurrent topics in Yasuyo Urasaki's work include Liver Disease Diagnosis and Treatment (5 papers), Metabolomics and Mass Spectrometry Studies (3 papers) and Biochemical and Molecular Research (3 papers). Yasuyo Urasaki is often cited by papers focused on Liver Disease Diagnosis and Treatment (5 papers), Metabolomics and Mass Spectrometry Studies (3 papers) and Biochemical and Molecular Research (3 papers). Yasuyo Urasaki collaborates with scholars based in United States and Japan. Yasuyo Urasaki's co-authors include Thuc T. Le, Giuseppe Pizzorno, Nobuyuki Miyasaka, Toshihiro Nanki, Toshio Imai, Cheng Xu, Amy Ziemba, Kenzo Muramoto, Miyuki Nishimura and Tetsuo Kubota and has published in prestigious journals such as The Journal of Immunology, PLoS ONE and Stroke.

In The Last Decade

Yasuyo Urasaki

27 papers receiving 954 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yasuyo Urasaki United States 18 407 226 174 132 128 27 960
Xiaofei Zhu China 21 666 1.6× 284 1.3× 164 0.9× 216 1.6× 253 2.0× 78 1.4k
Carina L. Bos Netherlands 14 473 1.2× 212 0.9× 205 1.2× 60 0.5× 141 1.1× 17 1.4k
David C. Montrose United States 23 794 2.0× 248 1.1× 202 1.2× 109 0.8× 256 2.0× 40 1.5k
Shuibang Wang United States 19 667 1.6× 87 0.4× 202 1.2× 69 0.5× 119 0.9× 27 1.2k
Yuanyuan Weng China 20 677 1.7× 200 0.9× 162 0.9× 160 1.2× 297 2.3× 30 1.2k
Ho‐Shik Kim South Korea 20 721 1.8× 146 0.6× 184 1.1× 112 0.8× 170 1.3× 49 1.2k
Ke Feng China 22 460 1.1× 89 0.4× 222 1.3× 183 1.4× 197 1.5× 75 1.2k
Yukimi Kira Japan 14 436 1.1× 98 0.4× 86 0.5× 134 1.0× 57 0.4× 31 946
Randy Nelson Canada 15 551 1.4× 134 0.6× 156 0.9× 260 2.0× 97 0.8× 25 1.2k

Countries citing papers authored by Yasuyo Urasaki

Since Specialization
Citations

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

Fields of papers citing papers by Yasuyo Urasaki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yasuyo Urasaki

This figure shows the co-authorship network connecting the top 25 collaborators of Yasuyo Urasaki. A scholar is included among the top collaborators of Yasuyo Urasaki 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 Yasuyo Urasaki. Yasuyo Urasaki 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.
Urasaki, Yasuyo & Thuc T. Le. (2022). Functional Complementation of Anti-Adipogenic Phytonutrients for Obesity Prevention and Management. Nutrients. 14(20). 4325–4325. 8 indexed citations
2.
Urasaki, Yasuyo, et al.. (2020). Potency Assessment of CBD Oils by Their Effects on Cell Signaling Pathways. Nutrients. 12(2). 357–357. 16 indexed citations
3.
Urasaki, Yasuyo, et al.. (2020). Fast-Acting and Receptor-Mediated Regulation of Neuronal Signaling Pathways by Copaiba Essential Oil. International Journal of Molecular Sciences. 21(7). 2259–2259. 23 indexed citations
4.
Urasaki, Yasuyo, Chi Zhang, Ji‐Xin Cheng, & Thuc T. Le. (2018). Quantitative Assessment of Liver Steatosis and Affected Pathways with Molecular Imaging and Proteomic Profiling. Scientific Reports. 8(1). 3606–3606. 34 indexed citations
5.
Urasaki, Yasuyo, Ronald R. Fiscus, & Thuc T. Le. (2018). Detection of the Cell Cycle-Regulated Negative Feedback Phosphorylation of Mitogen-Activated Protein Kinases in Breast Carcinoma using Nanofluidic Proteomics. Scientific Reports. 8(1). 9991–9991. 11 indexed citations
6.
Urasaki, Yasuyo, Giuseppe Pizzorno, & Thuc T. Le. (2016). Chronic Uridine Administration Induces Fatty Liver and Pre-Diabetic Conditions in Mice. PLoS ONE. 11(1). e0146994–e0146994. 55 indexed citations
7.
Johlfs, Mary G., et al.. (2015). Capillary Isoelectric Focusing Immunoassay for Fat Cell Differentiation Proteomics. PLoS ONE. 10(7). e0132105–e0132105. 13 indexed citations
8.
Le, Thuc T., Yasuyo Urasaki, & Giuseppe Pizzorno. (2014). Uridine prevents tamoxifen-induced liver lipid droplet accumulation. BMC Pharmacology and Toxicology. 15(1). 27–27. 36 indexed citations
9.
Le, Thuc T., Yasuyo Urasaki, & Giuseppe Pizzorno. (2014). Uridine Prevents Fenofibrate-Induced Fatty Liver. PLoS ONE. 9(1). e87179–e87179. 31 indexed citations
10.
Urasaki, Yasuyo, Giuseppe Pizzorno, & Thuc T. Le. (2014). Uridine Affects Liver Protein Glycosylation, Insulin Signaling, and Heme Biosynthesis. PLoS ONE. 9(6). e99728–e99728. 29 indexed citations
11.
Le, Thuc T., et al.. (2013). Disruption of uridine homeostasis links liver pyrimidine metabolism to lipid accumulation. Journal of Lipid Research. 54(4). 1044–1057. 93 indexed citations
12.
Mitra, Ranjana, et al.. (2012). Detection of Lipid-Rich Prostate Circulating Tumour Cells with Coherent Anti-Stokes Raman Scattering Microscopy. BMC Cancer. 12(1). 540–540. 61 indexed citations
13.
Urasaki, Yasuyo, et al.. (2012). Coupling of Glucose Deprivation with Impaired Histone H2B Monoubiquitination in Tumors. PLoS ONE. 7(5). e36775–e36775. 81 indexed citations
14.
Le, Thuc T., et al.. (2012). Label-free Evaluation of Hepatic Microvesicular Steatosis with Multimodal Coherent Anti-Stokes Raman Scattering Microscopy. PLoS ONE. 7(11). e51092–e51092. 36 indexed citations
15.
Abe, Masako, Pamela A. Havre, Yasuyo Urasaki, et al.. (2011). Mechanisms of confluence-dependent expression of CD26 in colon cancer cell lines. BMC Cancer. 11(1). 51–51. 23 indexed citations
16.
Havre, Pamela A., Masako Abe, Yasuyo Urasaki, et al.. (2009). CD26 expression on T cell lines increases SDF-1-α-mediated invasion. British Journal of Cancer. 101(6). 983–991. 17 indexed citations
17.
Inamoto, Sakiko, Satoshi Iwata, Teruo Inamoto, et al.. (2006). Crk-associated substrate lymphocyte type regulates transforming growth factor-β signaling by inhibiting Smad6 and Smad7. Oncogene. 26(6). 893–904. 21 indexed citations
18.
Sasaki, Takahiro, Satoshi Iwata, Hirotaka James Okano, et al.. (2005). Nedd9 Protein, a Cas-L Homologue, Is Upregulated After Transient Global Ischemia in Rats. Stroke. 36(11). 2457–2462. 31 indexed citations
19.
Nanki, Toshihiro, Yasuyo Urasaki, Toshio Imai, et al.. (2004). Inhibition of Fractalkine Ameliorates Murine Collagen-Induced Arthritis. The Journal of Immunology. 173(11). 7010–7016. 119 indexed citations
20.
Nanki, Toshihiro, Toshio Imai, Kenji Nagasaka, et al.. (2002). Migration of CX3CR1‐positive T cells producing type 1 cytokines and cytotoxic molecules into the synovium of patients with rheumatoid arthritis. Arthritis & Rheumatism. 46(11). 2878–2883. 134 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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