Fuko Matsuda

1.9k total citations · 1 hit paper
53 papers, 1.4k citations indexed

About

Fuko Matsuda is a scholar working on Reproductive Medicine, Molecular Biology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Fuko Matsuda has authored 53 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Reproductive Medicine, 27 papers in Molecular Biology and 17 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Fuko Matsuda's work include Hypothalamic control of reproductive hormones (22 papers), Reproductive Biology and Fertility (16 papers) and Ovarian function and disorders (14 papers). Fuko Matsuda is often cited by papers focused on Hypothalamic control of reproductive hormones (22 papers), Reproductive Biology and Fertility (16 papers) and Ovarian function and disorders (14 papers). Fuko Matsuda collaborates with scholars based in Japan, United States and Australia. Fuko Matsuda's co-authors include Naoko Inoue, Noboru MANABE, Satoshi Ohkura, Yasufumi Goto, Hiroko Tsukamura, Yoshihisa Uenoyama, Fumie Magata, Kei‐ichiro Maeda, Akihisa Maeda and Senkiti Sakai and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Endocrinology and Journal of Medicinal Chemistry.

In The Last Decade

Fuko Matsuda

51 papers receiving 1.4k citations

Hit Papers

Follicular Growth and Atresia in Mammalian Ovaries: Regul... 2012 2026 2016 2021 2012 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fuko Matsuda Japan 20 595 576 532 233 218 53 1.4k
C. Bellido Spain 23 335 0.6× 512 0.9× 342 0.6× 231 1.0× 311 1.4× 53 1.6k
Maria Słomczyńska Poland 22 388 0.7× 381 0.7× 483 0.9× 131 0.6× 454 2.1× 100 1.5k
Sheng Cui China 19 546 0.9× 278 0.5× 185 0.3× 144 0.6× 236 1.1× 103 1.3k
Haisheng Hao China 20 300 0.5× 543 0.9× 620 1.2× 76 0.3× 195 0.9× 62 1.0k
Sang‐Hwan Hyun South Korea 24 866 1.5× 452 0.8× 952 1.8× 127 0.5× 451 2.1× 110 1.8k
Ashutosh Pandey India 23 605 1.0× 500 0.9× 692 1.3× 171 0.7× 129 0.6× 46 1.6k
Emilia Middea Italy 15 458 0.8× 637 1.1× 367 0.7× 93 0.4× 299 1.4× 15 1.3k
Dalia Galiani Israel 21 661 1.1× 612 1.1× 945 1.8× 154 0.7× 135 0.6× 33 1.5k
Haitao Zeng China 23 712 1.2× 521 0.9× 716 1.3× 122 0.5× 133 0.6× 65 1.6k
Eliana Herminia Pellizzari Argentina 25 616 1.0× 792 1.4× 421 0.8× 82 0.4× 258 1.2× 54 1.6k

Countries citing papers authored by Fuko Matsuda

Since Specialization
Citations

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

Fields of papers citing papers by Fuko Matsuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fuko Matsuda

This figure shows the co-authorship network connecting the top 25 collaborators of Fuko Matsuda. A scholar is included among the top collaborators of Fuko Matsuda 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 Fuko Matsuda. Fuko Matsuda 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.
Magata, Fumie, et al.. (2024). Lipopolysaccharide-binding protein in follicular fluid is associated with the follicular inflammatory status and granulosa cell steroidogenesis in dairy cows. Journal of Reproduction and Development. 70(3). 169–176. 1 indexed citations
2.
Magata, Fumie, Hiroko Tsukamura, & Fuko Matsuda. (2023). The impact of inflammatory stress on hypothalamic kisspeptin neurons: Mechanisms underlying inflammation-associated infertility in humans and domestic animals. Peptides. 162. 170958–170958. 19 indexed citations
4.
Xiong, Yan, et al.. (2022). Analysis of PPP1R11 expression in granulosa cells during developmental follicles of yak and its effects on cell function. Reproduction in Domestic Animals. 58(1). 129–140. 2 indexed citations
7.
Magata, Fumie, Marimo Sato, James Chambers, et al.. (2022). Intrauterine LPS inhibited arcuate Kiss1 expression, LH pulses, and ovarian function in rats. Reproduction. 164(5). 207–219. 8 indexed citations
8.
Minabe, Shiori, Fuko Matsuda, Sheng‐Hsiang Li, et al.. (2021). Testosterone regulation on quiescin sulfhydryl oxidase 2 synthesis in the epididymis. Reproduction. 161(5). 593–602. 8 indexed citations
9.
Chambers, James, Kei Takahashi, Yoshiyuki Soeda, et al.. (2021). Amyloid β and tau pathology in brains of aged pinniped species (sea lion, seal, and walrus). Acta Neuropathologica Communications. 9(1). 10–10. 19 indexed citations
10.
Magata, Fumie, et al.. (2021). Glutathione ethyl ester improved the age-induced decline in the developmental competence of bovine oocytes. Theriogenology. 167. 37–43. 9 indexed citations
11.
Magata, Fumie, et al.. (2020). Developmental kinetics and viability of bovine embryos produced in vitro with sex-sorted semen. Theriogenology. 161. 243–251. 19 indexed citations
12.
Minabe, Shiori, Marimo Sato, Naoko Inoue, et al.. (2019). Neonatal Estrogen Causes Irreversible Male Infertility via Specific Suppressive Action on Hypothalamic Kiss1 Neurons. Endocrinology. 160(5). 1223–1233. 15 indexed citations
13.
Sasaki, Takuya, Daisuke Ito, Yasuhiro Morita, et al.. (2019). Peripheral administration of κ-opioid receptor antagonist stimulates gonadotropin-releasing hormone pulse generator activity in ovariectomized, estrogen-treated female goats. Domestic Animal Endocrinology. 68. 83–91. 16 indexed citations
14.
Magata, Fumie, et al.. (2019). Growth potential of bovine embryos presenting abnormal cleavage observed through time lapse cinematography. Theriogenology. 133. 119–124. 27 indexed citations
15.
Nakamura, Sho, Shosuke Ito, Koki Yamamoto, et al.. (2017). SB223412, a neurokinin-3 receptor-selective antagonist, suppresses testosterone secretion in male guinea pigs. Theriogenology. 102. 183–189. 11 indexed citations
16.
Uenoyama, Yoshihisa, Junko Tomikawa, Naoko Inoue, et al.. (2016). Molecular and Epigenetic Mechanism Regulating Hypothalamic <b><i>Kiss1</i></b> Gene Expression in Mammals. Neuroendocrinology. 103(6). 640–649. 21 indexed citations
17.
Matsuyama, Shuichi, Koji Kimura, Nahoko Ieda, et al.. (2016). Immunohistochemical characterization of the arcuate kisspeptin/neurokinin B/dynorphin (KNDy) and preoptic kisspeptin neuronal populations in the hypothalamus during the estrous cycle in heifers. Journal of Reproduction and Development. 62(5). 471–477. 45 indexed citations
18.
Takahashi, Yūji, et al.. (2003). Coactivator CBP in the regulation of conceptus IFNτ gene transcription. Molecular Reproduction and Development. 65(1). 23–29. 21 indexed citations
20.
Sakamoto, Yoichi, et al.. (1981). [Glycosylated hemoglobin concentration in diabetes mellitus and hyperthyroidism (author's transl)].. PubMed. 29(4). 451–5. 1 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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