Masayo Ukita

1.4k total citations · 1 hit paper
47 papers, 936 citations indexed

About

Masayo Ukita is a scholar working on Pulmonary and Respiratory Medicine, Water Science and Technology and Molecular Biology. According to data from OpenAlex, Masayo Ukita has authored 47 papers receiving a total of 936 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Pulmonary and Respiratory Medicine, 7 papers in Water Science and Technology and 5 papers in Molecular Biology. Recurrent topics in Masayo Ukita's work include Ovarian cancer diagnosis and treatment (5 papers), Blood properties and coagulation (4 papers) and Wastewater Treatment and Nitrogen Removal (4 papers). Masayo Ukita is often cited by papers focused on Ovarian cancer diagnosis and treatment (5 papers), Blood properties and coagulation (4 papers) and Wastewater Treatment and Nitrogen Removal (4 papers). Masayo Ukita collaborates with scholars based in Japan, China and United States. Masayo Ukita's co-authors include Masahiko Sekine, Tsuyoshi Imai, Masaki Mandai, Takaya Higuchi, Junzo Hamanishi, Ken Yamaguchi, Kaoru Abiko, Mana Taki, Tsukasa Baba and Noriomi Matsumura and has published in prestigious journals such as The Lancet, Journal of Clinical Oncology and Water Research.

In The Last Decade

Masayo Ukita

42 papers receiving 903 citations

Hit Papers

Tumor Immune Microenvironment during Epithelial–Mesenchym... 2021 2026 2022 2024 2021 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Masayo Ukita Japan 16 282 230 191 152 144 47 936
Yiding Li China 20 138 0.5× 180 0.8× 262 1.4× 66 0.4× 74 0.5× 55 1.1k
Hebatallah Hassan Egypt 19 289 1.0× 147 0.6× 456 2.4× 260 1.7× 56 0.4× 44 1.5k
Enyu Liu China 21 246 0.9× 115 0.5× 468 2.5× 172 1.1× 64 0.4× 73 1.4k
Magdalena Barešová Czechia 11 119 0.4× 144 0.6× 251 1.3× 303 2.0× 100 0.7× 15 1.2k
David R. Simpson United States 9 158 0.6× 95 0.4× 571 3.0× 100 0.7× 153 1.1× 14 1.1k
Zuwei Wang China 15 110 0.4× 69 0.3× 331 1.7× 76 0.5× 292 2.0× 49 904
Chunhong Cui China 18 280 1.0× 90 0.4× 597 3.1× 66 0.4× 53 0.4× 38 1.1k
Xiaokai Zhang China 16 120 0.4× 200 0.9× 285 1.5× 29 0.2× 87 0.6× 44 755
Nathalie Steimberg Italy 18 178 0.6× 53 0.2× 293 1.5× 109 0.7× 240 1.7× 42 1.3k
Jing Du China 15 220 0.8× 69 0.3× 557 2.9× 88 0.6× 90 0.6× 48 1.1k

Countries citing papers authored by Masayo Ukita

Since Specialization
Citations

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

Fields of papers citing papers by Masayo Ukita

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masayo Ukita

This figure shows the co-authorship network connecting the top 25 collaborators of Masayo Ukita. A scholar is included among the top collaborators of Masayo Ukita 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 Masayo Ukita. Masayo Ukita 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.
Yamaguchi, Ken, Koji Yamanoi, Shiro Takamatsu, et al.. (2024). YAP1 Suppression by ZDHHC7 Is Associated with Ferroptosis Resistance and Poor Prognosis in Ovarian Clear Cell Carcinoma. Molecular Cancer Therapeutics. 23(11). 1652–1665. 7 indexed citations
2.
Komatsu, Hiroaki, Koji Matsumoto, Mitsunori Morita, et al.. (2024). A survey of carboplatin desensitization therapy in Japan: A multicenter retrospective study. Cancer Medicine. 13(5). e6968–e6968. 3 indexed citations
4.
Sumi, Eriko, Taito Miyamoto, Ryuji Uozumi, et al.. (2022). Safety of the cyclin dependent kinase 9 (CDK9) inhibitor FIT039 for cervical intraepithelial neoplasia (CIN) 1 or 2 in a phase I/II trial.. Journal of Clinical Oncology. 40(16_suppl). 3022–3022. 1 indexed citations
5.
Yamaguchi, Ken, Yosuke Yamamoto, Akihiko Ueda, et al.. (2022). Development of healthy lifestyle consciousness index for gynecological cancer patients. Supportive Care in Cancer. 30(9). 7569–7574. 1 indexed citations
6.
Ukita, Masayo, Junzo Hamanishi, Hiroyuki Yoshitomi, et al.. (2022). CXCL13-producing CD4+ T cells accumulate in the early phase of tertiary lymphoid structures in ovarian cancer. JCI Insight. 7(12). 119 indexed citations
7.
Hamanishi, Junzo, Masayo Ukita, Koji Yamanoi, et al.. (2021). Tertiary lymphoid structures are associated with favorable survival outcomes in patients with endometrial cancer. Cancer Immunology Immunotherapy. 71(6). 1431–1442. 38 indexed citations
8.
Yamaguchi, Ken, Ryusuke Murakami, Koji Yamanoi, et al.. (2021). Acquired Evolution of Mitochondrial Metabolism Regulated by HNF1B in Ovarian Clear Cell Carcinoma. Cancers. 13(10). 2413–2413. 15 indexed citations
9.
Horikawa, Naoki, Kaoru Abiko, Noriomi Matsumura, et al.. (2020). Anti-VEGF therapy resistance in ovarian cancer is caused by GM-CSF-induced myeloid-derived suppressor cell recruitment. British Journal of Cancer. 122(6). 778–788. 72 indexed citations
10.
Murakami, Kayo, et al.. (2017). Ultrasonic scalpel ablation for vaginal intraepithelial neoplasia occurring after hysterectomy. European Journal of Gynaecological Oncology. 38(4). 541–546. 2 indexed citations
11.
Sakai, Kazuko, Masayo Ukita, Jeanette P. Schmidt, et al.. (2017). Clonal composition of human ovarian cancer based on copy number analysis reveals a reciprocal relation with oncogenic mutation status. Cancer Letters. 405. 22–28. 17 indexed citations
12.
Ikeda, Yuji, Ryo Kitagawa, Fuminori Ito, et al.. (2016). Practice patterns of adjuvant therapy for intermediate/high recurrence risk cervical cancer patients in Japan. Journal of Gynecologic Oncology. 27(3). e29–e29. 23 indexed citations
13.
Ukita, Masayo, Hidekatsu Nakai, Yasushi Kotani, et al.. (2014). Long-term survival in metastatic malignant struma ovarii treated with oral chemotherapy: A case report. Oncology Letters. 8(6). 2458–2462. 12 indexed citations
14.
Zhu, Huaiyong, et al.. (2007). Enhancement of Oxygen Transfer Efficiency in Diffused Aeration Systems using Liquid-Film-Forming Apparatus. Environmental Technology. 28(5). 511–519. 13 indexed citations
15.
Ukita, Masayo, et al.. (2004). Compost Stability Assessment Using a Secondary Metabolite: Geosmin. Environmental Technology. 25(11). 1305–1312. 16 indexed citations
16.
Lu, Shuguang, Tsuyoshi Imai, Masayo Ukita, et al.. (2001). A model for membrane bioreactor process based on the concept of formation and degradation of soluble microbial products. Water Research. 35(8). 2038–2048. 105 indexed citations
17.
Sekine, Masahiko, Masayo Ukita, & Hiroshi Nakanishi. (1992). Determination of nutrient transformation pathways in rivers using a mathematical programming method. Journal of Contaminant Hydrology. 9(1-2). 189–206. 3 indexed citations
18.
Nakanishi, Hiroshi, Masayo Ukita, & Masahiko Sekine. (1991). Evaluation of primary production loads and their control in enclosed seas. Marine Pollution Bulletin. 23. 25–29. 4 indexed citations
19.
Ukita, Masayo. (1978). ANTITHROMBIN III AND HEPARIN. The Lancet. 311(8063). 538–539. 3 indexed citations
20.
Ukita, Masayo, Akira Furuya, Hozumi Tanaka, & Masanaru Misawa. (1973). 5′-Phosphodiesterase Formation by Cultured Plant Cells. Agricultural and Biological Chemistry. 37(12). 2849–2854. 2 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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