Mai Hazekawa

1.1k total citations
47 papers, 931 citations indexed

About

Mai Hazekawa is a scholar working on Molecular Biology, Nutrition and Dietetics and Biomedical Engineering. According to data from OpenAlex, Mai Hazekawa has authored 47 papers receiving a total of 931 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 10 papers in Nutrition and Dietetics and 9 papers in Biomedical Engineering. Recurrent topics in Mai Hazekawa's work include Biochemical Analysis and Sensing Techniques (10 papers), Advanced Chemical Sensor Technologies (7 papers) and Cannabis and Cannabinoid Research (6 papers). Mai Hazekawa is often cited by papers focused on Biochemical Analysis and Sensing Techniques (10 papers), Advanced Chemical Sensor Technologies (7 papers) and Cannabis and Cannabinoid Research (6 papers). Mai Hazekawa collaborates with scholars based in Japan, New Zealand and United States. Mai Hazekawa's co-authors include Michihiro Fujiwara, Nobuaki Egashira, Kazuhide Hayakawa, Kenichi Mishima, Miyako Yoshida, Takahiro Uchida, Katsunori Iwasaki, Kensuke Orito, Masayuki Fujioka and Masanori Nozako and has published in prestigious journals such as Stroke, Scientific Reports and Brain Research.

In The Last Decade

Mai Hazekawa

47 papers receiving 905 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mai Hazekawa Japan 15 367 225 173 123 99 47 931
Jin Fu China 11 557 1.5× 412 1.8× 153 0.9× 50 0.4× 44 0.4× 27 1.2k
Letizia Palomba Italy 19 242 0.7× 630 2.8× 111 0.6× 73 0.6× 119 1.2× 60 1.6k
Reni Kalfin Bulgaria 19 114 0.3× 371 1.6× 245 1.4× 60 0.5× 57 0.6× 86 1.3k
Huei-Yann Tsai Taiwan 15 170 0.5× 407 1.8× 108 0.6× 57 0.5× 56 0.6× 36 1.3k
Rodrigo Portes Ureshino Brazil 22 138 0.4× 401 1.8× 190 1.1× 102 0.8× 59 0.6× 44 1.3k
Yan Hou China 13 98 0.3× 481 2.1× 165 1.0× 154 1.3× 36 0.4× 32 1.1k
Zaijie Jim Wang United States 28 218 0.6× 571 2.5× 468 2.7× 65 0.5× 46 0.5× 63 1.8k
Mireille Alhouayek Belgium 25 915 2.5× 711 3.2× 186 1.1× 104 0.8× 134 1.4× 52 2.2k
Neveen A. Salem Egypt 19 186 0.5× 196 0.9× 91 0.5× 49 0.4× 116 1.2× 45 917
Amit Khairnar India 18 112 0.3× 332 1.5× 205 1.2× 80 0.7× 28 0.3× 43 999

Countries citing papers authored by Mai Hazekawa

Since Specialization
Citations

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

Fields of papers citing papers by Mai Hazekawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mai Hazekawa

This figure shows the co-authorship network connecting the top 25 collaborators of Mai Hazekawa. A scholar is included among the top collaborators of Mai Hazekawa 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 Mai Hazekawa. Mai Hazekawa 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.
Hazekawa, Mai, et al.. (2023). RCAS1 increases cell morphological changes in murine fibroblasts by reducing p38 phosphorylation. Molecular Medicine Reports. 27(3). 1 indexed citations
2.
Mori, Takeshi, Miyako Yoshida, Mai Hazekawa, et al.. (2021). Antimicrobial Activities of LL-37 Fragment Mutant-Poly (Lactic-Co-Glycolic) Acid Conjugate against Staphylococcus aureus, Escherichia coli, and Candida albicans. International Journal of Molecular Sciences. 22(10). 5097–5097. 9 indexed citations
3.
Mori, Takeshi, Miyako Yoshida, Mai Hazekawa, et al.. (2021). Targeted Delivery of Miconazole Employing LL37 Fragment Mutant Peptide CKR12-Poly (Lactic-Co-Glycolic) Acid Polymeric Micelles. International Journal of Molecular Sciences. 22(21). 12056–12056. 4 indexed citations
4.
Hazekawa, Mai, et al.. (2021). Enhancing the anticancer efficacy of a LL-37 peptide fragment analog using peptide-linked PLGA conjugate micelles in tumor cells. International Journal of Pharmaceutics. 606. 120891–120891. 17 indexed citations
5.
Shimada, Yasuhito & Mai Hazekawa. (2020). Developing a Model for a siRNA Delivery System by Cancer Implantation into Zebrafish Circulation. Methods in molecular biology. 2174. 263–275. 3 indexed citations
6.
Kawakubo‐Yasukochi, Tomoyo, Kenji Ohe, Atsushi Yasukochi, et al.. (2019). Maternal folic acid depletion during early pregnancy increases sensitivity to squamous tumor formation in the offspring in mice. Journal of Developmental Origins of Health and Disease. 10(6). 683–691. 6 indexed citations
7.
Hazekawa, Mai, et al.. (2019). Glypican-3 gene silencing for ovarian cancer using siRNA-PLGA hybrid micelles in a murine peritoneal dissemination model. Journal of Pharmacological Sciences. 139(3). 231–239. 16 indexed citations
8.
Hazekawa, Mai, et al.. (2017). Assessment of Cytotoxicity of Imatinib for Oral Squamous CellCarcinoma by a Real-Time Cell Analysis System.. Electronic journal of biology. 13(1). 1 indexed citations
9.
Hazekawa, Mai, et al.. (2016). Effect of Collagen Type I or Human Fibronectin on Imatinib Cytotoxicity in Oral Squamous Cell Carcinoma. Pharmacology & Pharmacy. 7(7). 255–263. 2 indexed citations
10.
Kawakubo‐Yasukochi, Tomoyo, Yoshikazu Hayashi, Mai Hazekawa, et al.. (2016). Exosomes from oral squamous carcinoma cell lines, SQUU-A and SQUU-B, define the tropism of lymphatic dissemination. Journal of Oral Biosciences. 58(4). 180–184. 8 indexed citations
11.
Hazekawa, Mai, et al.. (2014). ヤマブシタケ子実体食品「山伏乃賜玉」のアルツハイマー病に対する薬理学的検討と臨床効果. 29(9). 920–926. 1 indexed citations
12.
Ito, Masanori, Koichi Wada, Miyako Yoshida, et al.. (2013). Quantitative Evaluation of Bitterness of H1-Receptor Antagonists and Masking Effect of Acesulfame Potassium, an Artificial Sweetener, Using a Taste Sensor. Sensors and Materials. 17–17. 12 indexed citations
13.
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15.
Uchida, Takahiro, et al.. (2012). Effect of antioxidants on the stability of ONO-1301, a novel long-acting prostacyclin agonist, loaded in PLGA microspheres. Journal of Microencapsulation. 30(3). 245–256. 8 indexed citations
16.
Uchida, Takahiro, et al.. (2012). Factors Affecting the Bitterness Intensities of Ten Commercial Formulations of Ambroxol. Chemical and Pharmaceutical Bulletin. 60(8). 949–954. 6 indexed citations
17.
Hazekawa, Mai, et al.. (2010). Predicting Bitterness of Clarithromycin Dry Syrups When in Mouth with Acidic Sports Drink or Taken Together with Mucodyne Dry Syrup. Iryo Yakugaku (Japanese Journal of Pharmaceutical Health Care and Sciences). 36(4). 262–269. 2 indexed citations
18.
Hayakawa, Kazuhide, Kenichi Mishima, Mai Hazekawa, et al.. (2007). Cannabidiol potentiates pharmacological effects of Δ9-tetrahydrocannabinol via CB1 receptor-dependent mechanism. Brain Research. 1188. 157–164. 113 indexed citations
19.
Hayakawa, Kazuhide, Kenichi Mishima, Masanori Nozako, et al.. (2007). Δ9-tetrahydrocannabinol (Δ9-THC) prevents cerebral infarction via hypothalamic-independent hypothermia. Life Sciences. 80(16). 1466–1471. 25 indexed citations
20.
Hayakawa, Kazuhide, Kenichi Mishima, Masanori Nozako, et al.. (2007). Repeated treatment with cannabidiol but not Δ9-tetrahydrocannabinol has a neuroprotective effect without the development of tolerance. Neuropharmacology. 52(4). 1079–1087. 74 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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