Kuniko Matsuda

2.0k total citations
55 papers, 1.6k citations indexed

About

Kuniko Matsuda is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology and Oncology. According to data from OpenAlex, Kuniko Matsuda has authored 55 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Pulmonary and Respiratory Medicine, 25 papers in Molecular Biology and 18 papers in Oncology. Recurrent topics in Kuniko Matsuda's work include Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (21 papers), Lung Cancer Treatments and Mutations (14 papers) and PI3K/AKT/mTOR signaling in cancer (6 papers). Kuniko Matsuda is often cited by papers focused on Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (21 papers), Lung Cancer Treatments and Mutations (14 papers) and PI3K/AKT/mTOR signaling in cancer (6 papers). Kuniko Matsuda collaborates with scholars based in Japan, United States and Singapore. Kuniko Matsuda's co-authors include Akihiko Gemma, Masahiro Seike, Rintaro Noro, Shoji Kudoh, Arata Azuma, Yuji Minegishi, Jiro Usuki, Tetsuya Okano, Akihiko Miyanaga and Shinji Abe and has published in prestigious journals such as The Journal of Experimental Medicine, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Kuniko Matsuda

52 papers receiving 1.6k citations

Peers

Kuniko Matsuda
Sheng Zhang China
Leena P. Desai United States
Korsa Khan United Kingdom
Jean‐Marie Tournier France
Yan Y. Sanders United States
Shigeru Ueshima Japan
Sara Lovisa Italy
Nathaniel M. Weathington United States
Changfu Yao United States
Sheng Zhang China
Kuniko Matsuda
Citations per year, relative to Kuniko Matsuda Kuniko Matsuda (= 1×) peers Sheng Zhang

Countries citing papers authored by Kuniko Matsuda

Since Specialization
Citations

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

Fields of papers citing papers by Kuniko Matsuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kuniko Matsuda

This figure shows the co-authorship network connecting the top 25 collaborators of Kuniko Matsuda. A scholar is included among the top collaborators of Kuniko 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 Kuniko Matsuda. Kuniko 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.
Miyanaga, Akihiko, et al.. (2024). Exploring effective biomarkers and potential immune related gene in small cell lung cancer. Scientific Reports. 14(1). 7604–7604. 1 indexed citations
2.
Kato, Yasuhiro, Masaru Matsumoto, Kuniko Matsuda, et al.. (2024). Induction of resistance to neurotrophic tropomyosin‐receptor kinase inhibitors by HMGCS2 via a mevalonate pathway. Cancer Medicine. 13(12). e7393–e7393. 1 indexed citations
3.
Nakamichi, Shinji, Kuniko Matsuda, Masaru Matsumoto, et al.. (2024). Afatinib plus PEM and CBDCA overcome osimertinib resistance in EGFR‐mutated NSCLC with high thrombospondin‐1 expression. Cancer Science. 115(8). 2718–2728. 2 indexed citations
4.
Saito, Yoshinobu, Kuniko Matsuda, Toru Tanaka, et al.. (2023). Increased CTGF expression in alveolar epithelial cells by cyclic mechanical stretch: Its mechanism and the therapeutic effect of pirfenidone. Respiratory Physiology & Neurobiology. 317. 104142–104142. 1 indexed citations
5.
Seike, Masahiro, Teppei Sugano, Kuniko Matsuda, et al.. (2022). A Novel Molecular Target in EGFR-mutant Lung Cancer Treated With the Combination of Osimertinib and Pemetrexed. Anticancer Research. 42(2). 709–722. 5 indexed citations
6.
Inomata, Minoru, Koichiro Kamio, Arata Azuma, et al.. (2020). Rictor-targeting exosomal microRNA-16 ameliorates lung fibrosis by inhibiting the mTORC2-SPARC axis. Experimental Cell Research. 398(2). 112416–112416. 14 indexed citations
7.
Nakamichi, Shinji, Masahiro Seike, Akihiko Miyanaga, et al.. (2017). RT-PCR for Detecting ALK Translocations in Cytology Samples from Lung Cancer Patients. Anticancer Research. 37(6). 3295–3299. 8 indexed citations
8.
Kamio, Koichiro, Jiro Usuki, Arata Azuma, et al.. (2015). Nintedanib modulates surfactant protein-D expression in A549 human lung epithelial cells via the c-Jun N-terminal kinase-activator protein-1 pathway. Pulmonary Pharmacology & Therapeutics. 32. 29–36. 14 indexed citations
9.
Noro, Rintaro, Masahiro Seike, Chie Soeno, et al.. (2015). MET FISH-positive status predicts short progression-free survival and overall survival after gefitinib treatment in lung adenocarcinoma with EGFR mutation. BMC Cancer. 15(1). 31–31. 20 indexed citations
10.
Inomata, Minoru, Koichiro Kamio, Arata Azuma, et al.. (2014). Pirfenidone inhibits fibrocyte accumulation in the lungs in bleomycin-induced murine pulmonary fibrosis. Respiratory Research. 15(1). 16–16. 101 indexed citations
11.
Kitamura, Kazuhiro, Masahiro Seike, Tetsuya Okano, et al.. (2013). MiR-134/487b/655 Cluster Regulates TGF-β–Induced Epithelial–Mesenchymal Transition and Drug Resistance to Gefitinib by Targeting MAGI2 in Lung Adenocarcinoma Cells. Molecular Cancer Therapeutics. 13(2). 444–453. 161 indexed citations
12.
13.
Abe, Shinji, Hiroki Hayashi, Kuniko Matsuda, et al.. (2010). Neutrophil Adsorption by Polymyxin B-Immobilized Fiber Column for Acute Exacerbation in Patients with Interstitial Pneumonia: A Pilot Study. Blood Purification. 29(4). 321–326. 54 indexed citations
14.
Mizutani, Hideaki, Tetsuya Okano, Yuji Minegishi, et al.. (2010). HSP27 modulates epithelial to mesenchymal transition of lung cancer cells in a Smad-independent manner. Oncology Letters. 1(6). 1011–1016. 27 indexed citations
15.
Miyanaga, Akihiko, Akihiko Gemma, Rintaro Noro, et al.. (2008). Antitumor activity of histone deacetylase inhibitors in non-small cell lung cancer cells: development of a molecular predictive model. Molecular Cancer Therapeutics. 7(7). 1923–1930. 81 indexed citations
16.
Azuma, Arata, Yingji Li, Chunyan Wang, et al.. (2008). EM703, A NEW DERIVATIVE OF ERYTHROMYCIN, INHIBITS TRANSFORMING GRWTH FACTOR-β SIGNALING IN HUMAN LUNG FIBROBLASTS. Experimental Lung Research. 34(6). 343–354. 13 indexed citations
17.
Gemma, Akihiko, Li Cai, Yuka Sugiyama, et al.. (2006). Anticancer drug clustering in lung cancer based on gene expression profiles and sensitivity database. BMC Cancer. 6(1). 174–174. 39 indexed citations
18.
Gemma, Akihiko, Rintaro Noro, Masahiro Seike, et al.. (2005). Reduction of PTEN protein and loss of epidermal growth factor receptor gene mutation in lung cancer with natural resistance to gefitinib (IRESSA). British Journal of Cancer. 92(9). 1711–1719. 115 indexed citations
19.
Gemma, Akihiko, Yoko Hosoya, Kuniko Matsuda, et al.. (2003). Reduced transcription of the RB2/p130 gene in human lung cancer. Molecular Carcinogenesis. 38(3). 124–129. 13 indexed citations
20.
Uematsu, Kazutsugu, Akihiko Gemma, Hiroshi Mochimaru, et al.. (2001). Aberrations in the fragile histidine triad (FHIT) gene in idiopathic pulmonary fibrosis.. PubMed. 61(23). 8527–33. 49 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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