Mitsutaka Yoshida

2.4k total citations
74 papers, 1.8k citations indexed

About

Mitsutaka Yoshida is a scholar working on Molecular Biology, Epidemiology and Endocrinology. According to data from OpenAlex, Mitsutaka Yoshida has authored 74 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 15 papers in Epidemiology and 12 papers in Endocrinology. Recurrent topics in Mitsutaka Yoshida's work include Neonatal Health and Biochemistry (9 papers), Heme Oxygenase-1 and Carbon Monoxide (9 papers) and Legionella and Acanthamoeba research (7 papers). Mitsutaka Yoshida is often cited by papers focused on Neonatal Health and Biochemistry (9 papers), Heme Oxygenase-1 and Carbon Monoxide (9 papers) and Legionella and Acanthamoeba research (7 papers). Mitsutaka Yoshida collaborates with scholars based in Japan, France and United States. Mitsutaka Yoshida's co-authors include Chihiro Sasakawa, Michinaga Ogawa, Motoshi Kitamura, Hitomi Mimuro, Minsoo Kim, Yuko Yoshikawa, Ichirô Nakagawa, Torsten Hain, Toru Yanagawa and Akira Kakizuka and has published in prestigious journals such as Journal of the American Chemical Society, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Mitsutaka Yoshida

71 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mitsutaka Yoshida Japan 20 793 637 312 224 156 74 1.8k
Dorothea Sesardic United Kingdom 32 963 1.2× 376 0.6× 449 1.4× 629 2.8× 54 0.3× 128 3.6k
Christine Laurent‐Winter France 23 1.4k 1.8× 339 0.5× 266 0.9× 386 1.7× 171 1.1× 39 2.7k
Travis B. Nielsen United States 20 776 1.0× 259 0.4× 517 1.7× 216 1.0× 81 0.5× 40 2.1k
Rosa Anna Siciliano Italy 33 1.3k 1.7× 328 0.5× 55 0.2× 177 0.8× 139 0.9× 81 2.7k
Yuji Sato Japan 32 1.6k 2.1× 863 1.4× 190 0.6× 664 3.0× 220 1.4× 96 4.1k
Lan Gong China 21 833 1.1× 625 1.0× 103 0.3× 214 1.0× 85 0.5× 73 1.9k
F. U. Schade Germany 19 825 1.0× 508 0.8× 108 0.3× 1.2k 5.4× 56 0.4× 38 2.5k
Gabriele Sass United States 32 1.5k 1.9× 611 1.0× 81 0.3× 505 2.3× 172 1.1× 88 3.0k
Sjoerd van der Post Sweden 20 1.5k 1.9× 255 0.4× 95 0.3× 438 2.0× 105 0.7× 29 2.6k
Ivar Lönnroth Sweden 27 1.1k 1.4× 243 0.4× 760 2.4× 610 2.7× 121 0.8× 89 2.7k

Countries citing papers authored by Mitsutaka Yoshida

Since Specialization
Citations

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

Fields of papers citing papers by Mitsutaka Yoshida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mitsutaka Yoshida

This figure shows the co-authorship network connecting the top 25 collaborators of Mitsutaka Yoshida. A scholar is included among the top collaborators of Mitsutaka Yoshida 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 Mitsutaka Yoshida. Mitsutaka Yoshida 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.
Yamamoto, Satoshi, et al.. (2017). Isolation of Extracellular Vesicles in Saliva Using Density Gradient Ultracentrifugation. Methods in molecular biology. 1660. 343–350. 24 indexed citations
2.
3.
Yamazaki, Tomohiro, Shinji Nakamura, Junji Matsuo, et al.. (2015). Amoebal Endosymbiont Parachlamydia acanthamoebae Bn9 Can Grow in Immortal Human Epithelial HEp-2 Cells at Low Temperature; An In Vitro Model System to Study Chlamydial Evolution. PLoS ONE. 10(2). e0116486–e0116486. 9 indexed citations
4.
Sekizuka, Tsuyoshi, Kyoko Hayashida, Junji Matsuo, et al.. (2014). Amoebal Endosymbiont Neochlamydia Genome Sequence Illuminates the Bacterial Role in the Defense of the Host Amoebae against Legionella pneumophila. PLoS ONE. 9(4). e95166–e95166. 38 indexed citations
5.
Matsuo, Junji, Shinji Nakamura, Atsushi Ito, et al.. (2013). Protochlamydia Induces Apoptosis of Human HEp-2 Cells through Mitochondrial Dysfunction Mediated by Chlamydial Protease-Like Activity Factor. PLoS ONE. 8(2). e56005–e56005. 12 indexed citations
6.
Kobayashi, T., Michinaga Ogawa, Takahito Sanada, et al.. (2013). The Shigella OspC3 Effector Inhibits Caspase-4, Antagonizes Inflammatory Cell Death, and Promotes Epithelial Infection. Cell Host & Microbe. 13(5). 570–583. 158 indexed citations
7.
Matsuo, Junji, Shinji Nakamura, Yasuhiro Hayashi, et al.. (2012). Chlamydia trachomatis serovar L2 infection model using human lymphoid Jurkat cells. Microbial Pathogenesis. 53(1). 1–11. 8 indexed citations
8.
Matsuo, Junji, Yimin, Shinji Nakamura, et al.. (2012). Chlamydophila pneumoniae in human immortal Jurkat cells and primary lymphocytes uncontrolled by interferon-γ. Microbes and Infection. 15(3). 192–200. 5 indexed citations
9.
Ezaki, Junji, Naomi Matsumoto, Mitsue Takeda‐Ezaki, et al.. (2011). Liver autophagy contributes to the maintenance of blood glucose and amino acid levels. Autophagy. 7(7). 727–736. 225 indexed citations
10.
Ogawa, Michinaga, Yuko Yoshikawa, T. Kobayashi, et al.. (2011). A Tecpr1-Dependent Selective Autophagy Pathway Targets Bacterial Pathogens. Cell Host & Microbe. 9(5). 376–389. 122 indexed citations
11.
Ueno, Takashi, Wataru Sato, Yasuo Horie, et al.. (2008). Loss of Pten, a tumor suppressor, causes the strong inhibition of autophagy without affecting LC3 lipidation. Autophagy. 4(5). 692–700. 77 indexed citations
12.
Ihara, Hiroshi, Naotaka Hashizume, Toshio Hasegawa, & Mitsutaka Yoshida. (2004). Antioxidant capacities of ascorbic acid, uric acid, α‐tocopherol, and bilirubin can be measured in the presence of another antioxidant, serum albumin. Journal of Clinical Laboratory Analysis. 18(1). 45–49. 21 indexed citations
13.
Tanaka, Yuriko, Hideki Nakano, Fumio Ishikawa, et al.. (1999). Cholera toxin increases intracellular pH in B lymphoma cells and decreases their antigen-presenting ability. European Journal of Immunology. 29(5). 1561–1570. 2 indexed citations
14.
Tanaka, Yuriko, Hideki Nakano, Fumio Ishikawa, et al.. (1999). Cholera toxin increases intracellular pH in B lymphoma cells and decreases their antigen-presenting ability. European Journal of Immunology. 29(5). 1561–1570. 9 indexed citations
15.
Koike, Michiaki, et al.. (1996). Apoptosis of T Cells in Multicentric Castleman's Disease. Clinical Immunology and Immunopathology. 79(3). 271–277. 6 indexed citations
16.
Yoshida, Mitsutaka, et al.. (1994). Sustained Release of hCG Minipellet for Newt Experiment in Space.. Biological Sciences in Space. 8(4). 226–230. 6 indexed citations
17.
Aoki, Yutaka, et al.. (1992). Rates of Oxidation of Bilirubin Species by Peroxidase With or Without Serum Albumin. 21(4). 245–248. 1 indexed citations
18.
Aoki, Yutaka, et al.. (1992). Delta Bilirubin: Its Isolation by Precipitation with Ammonium Sulfate and Properties. 21(1). 1–5. 4 indexed citations
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20.

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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