Sayaka Tsuda

927 total citations
27 papers, 660 citations indexed

About

Sayaka Tsuda is a scholar working on Obstetrics and Gynecology, Immunology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Sayaka Tsuda has authored 27 papers receiving a total of 660 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Obstetrics and Gynecology, 16 papers in Immunology and 8 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Sayaka Tsuda's work include Pregnancy and preeclampsia studies (18 papers), Reproductive System and Pregnancy (16 papers) and Pregnancy and Medication Impact (8 papers). Sayaka Tsuda is often cited by papers focused on Pregnancy and preeclampsia studies (18 papers), Reproductive System and Pregnancy (16 papers) and Pregnancy and Medication Impact (8 papers). Sayaka Tsuda collaborates with scholars based in Japan and United States. Sayaka Tsuda's co-authors include Shigeru Saito, Tomoko Shima, Akitoshi Nakashima, Akemi Ushijima, Aiko Aoki, Shi‐Bin Cheng, Surendra Sharma, Hiroyuki Kishi, Tae Kusabiraki and Hiroshi Hamana and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Sayaka Tsuda

25 papers receiving 656 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sayaka Tsuda Japan 13 380 367 168 133 121 27 660
Akemi Ushijima Japan 13 318 0.8× 403 1.1× 181 1.1× 92 0.7× 101 0.8× 14 646
Monika Siwetz Austria 16 471 1.2× 314 0.9× 93 0.6× 278 2.1× 179 1.5× 33 780
Leena Kadam United States 14 320 0.8× 241 0.7× 119 0.7× 237 1.8× 143 1.2× 28 685
Esteban Grasso Argentina 17 211 0.6× 404 1.1× 119 0.7× 33 0.2× 80 0.7× 37 565
K. Orendi Austria 11 473 1.2× 244 0.7× 91 0.5× 283 2.1× 187 1.5× 13 700
Stefan Hutter Germany 17 305 0.8× 301 0.8× 70 0.4× 142 1.1× 171 1.4× 45 664
Tracy Niven‐Fairchild United States 11 184 0.5× 260 0.7× 222 1.3× 168 1.3× 228 1.9× 11 659
Jinfeng Qian China 12 180 0.5× 290 0.8× 107 0.6× 58 0.4× 69 0.6× 23 419
Katja Woidacki Germany 14 207 0.5× 469 1.3× 164 1.0× 91 0.7× 100 0.8× 18 731

Countries citing papers authored by Sayaka Tsuda

Since Specialization
Citations

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

Fields of papers citing papers by Sayaka Tsuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sayaka Tsuda

This figure shows the co-authorship network connecting the top 25 collaborators of Sayaka Tsuda. A scholar is included among the top collaborators of Sayaka Tsuda 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 Sayaka Tsuda. Sayaka Tsuda 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.
Metoki, Hirohito, Akitoshi Nakashima, Noriko Yoneda, et al.. (2026). Prediction Model of Hypertensive Disorders of Pregnancy Based on Home Blood Pressure Monitoring. Journal of the American Heart Association. 15(5). e047093–e047093.
2.
Lindgren, A., et al.. (2025). Natural microbial exposure populates the maternal fetal interface with diverse T cells. Frontiers in Immunology. 16. 1616491–1616491.
3.
Tsuda, Sayaka, Shigeyuki Shichino, Tamara Tilburgs, et al.. (2024). CD4+ T cell heterogeneity in gestational age and preeclampsia using single-cell RNA sequencing. Frontiers in Immunology. 15. 1401738–1401738. 5 indexed citations
4.
Nakashima, Akitoshi, et al.. (2024). Immunological regulation and the role of autophagy in preeclampsia. American Journal of Reproductive Immunology. 91(3). e13835–e13835. 3 indexed citations
5.
6.
Tanimura, Kenji, Shigeru Saito, Sayaka Tsuda, et al.. (2023). Anti-β2-glycoprotein I/HLA-DR Antibody and Adverse Obstetric Outcomes. International Journal of Molecular Sciences. 24(13). 10958–10958. 5 indexed citations
7.
Nakashima, Akitoshi, Masami Ito, Satoshi Yamashita, et al.. (2023). The Role of Autophagy in the Female Reproduction System: For Beginners to Experts in This Field. Biology. 12(3). 373–373. 7 indexed citations
8.
Saito, Shigeru, Sayaka Tsuda, & Akitoshi Nakashima. (2023). T cell immunity and the etiology and pathogenesis of preeclampsia. Journal of Reproductive Immunology. 159. 104125–104125. 13 indexed citations
9.
Yoneda, Satoshi, Noriko Yoneda, Mika Ito, et al.. (2022). Probiotics including Clostridium butyricum, Enterococcus faecium, and Bacillus subtilis may prevent recurrent spontaneous preterm delivery. Journal of obstetrics and gynaecology research. 48(3). 688–693. 8 indexed citations
10.
Shima, Tomoko, Sayaka Tsuda, Satoshi Yoneda, et al.. (2022). Chloroquine is a safe autophagy inhibitor for sustaining the expression of antioxidant enzymes in trophoblasts. Journal of Reproductive Immunology. 155. 103766–103766. 11 indexed citations
11.
12.
Yagi, Kunimasa, Sayaka Tsuda, Tsutomu Wada, et al.. (2021). Type 1 diabetes woman with repeated miscarriages successfully gave birth after introducing an insulin pump with a predictive low glucose suspend feature. Diabetology International. 12(3). 324–329. 1 indexed citations
13.
14.
Yoneda, Noriko, Satoshi Yoneda, Sayaka Tsuda, et al.. (2021). Pre-eclampsia Complicated With Maternal Renal Dysfunction Is Associated With Poor Neurological Development at 3 Years Old in Children Born Before 34 Weeks of Gestation. Frontiers in Pediatrics. 9. 624323–624323. 2 indexed citations
15.
Nakashima, Akitoshi, Tomoko Shima, Sayaka Tsuda, et al.. (2020). Disruption of Placental Homeostasis Leads to Preeclampsia. International Journal of Molecular Sciences. 21(9). 3298–3298. 20 indexed citations
16.
Shima, Tomoko, Akitoshi Nakashima, Akemi Ushijima, et al.. (2020). Uterine CD11c+ cells induce the development of paternal antigen-specific Tregs via seminal plasma priming. Journal of Reproductive Immunology. 141. 103165–103165. 18 indexed citations
17.
Nakashima, Akitoshi, Kazuma Higashisaka, Tae Kusabiraki, et al.. (2019). Autophagy is a new protective mechanism against the cytotoxicity of platinum nanoparticles in human trophoblasts. Scientific Reports. 9(1). 5478–5478. 31 indexed citations
18.
Nakashima, Akitoshi, Shi‐Bin Cheng, Tae Kusabiraki, et al.. (2019). Endoplasmic reticulum stress disrupts lysosomal homeostasis and induces blockade of autophagic flux in human trophoblasts. Scientific Reports. 9(1). 11466–11466. 80 indexed citations
19.
Tsuda, Sayaka, Akitoshi Nakashima, Tomoko Shima, & Shigeru Saito. (2019). New Paradigm in the Role of Regulatory T Cells During Pregnancy. Frontiers in Immunology. 10. 573–573. 138 indexed citations
20.
Tsuda, Sayaka, Xiaoxin Zhang, Hiroshi Hamana, et al.. (2018). Clonally Expanded Decidual Effector Regulatory T Cells Increase in Late Gestation of Normal Pregnancy, but Not in Preeclampsia, in Humans. Frontiers in Immunology. 9. 1934–1934. 76 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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