Mayumi Nagashimada
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- Diet, Metabolism, and Disease 8
- Biochemistry top 2%
- Epidemiology top 5%
- Liver Disease Diagnosis and Treatment 18
- Adipokines, Inflammation, and Metabolic Diseases 7
- Hepatology top 5%
- Liver Disease and Transplantation 3
- Gastroenterology top 5%
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- Adipose Tissue and Metabolism 7
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- Congenital gastrointestinal and neural anomalies 5
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- Genomics, phytochemicals, and oxidative stress 4
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- Lipid metabolism and disorders 3
- Co-authors
- Tsuguhito OtaYinhua NiShuichi KanekoFen ZhugeNaoto NagataToshihiro UesakaHideki EnomotoLiang Xu
- Journals
- Journal of Clinical Investigation (2 papers)Journal of Neuroscience (2 papers)PLoS ONE (1 paper)
- Partner nations
- JapanChinaUnited States
In The Last Decade
Mayumi Nagashimada
35 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Endocrinology, Diabetes and Metabolism 602
- Biochemistry 203
- Epidemiology 962
- Hepatology 197
- Gastroenterology 133
Countries citing papers authored by Mayumi Nagashimada
This map shows the geographic impact of Mayumi Nagashimada'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 Mayumi Nagashimada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mayumi Nagashimada more than expected).
Fields of papers citing papers by Mayumi Nagashimada
This network shows the impact of papers produced by Mayumi Nagashimada. 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 Mayumi Nagashimada. The network helps show where Mayumi Nagashimada may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mayumi Nagashimada, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 2 | |
| 2 | 2023 | 2 | |
| 3 | 2022 | 52 | |
| 4 | 2021 | 41 | |
| 5 | 2021 | 56 | |
| 6 | 2020 | 57 | |
| 7 | 2019 | 53 | |
| 8 | 2019 | 29 | |
| 9 | SGLT2 Inhibition by Empagliflozin Promotes Fat Utilization and Browning and Attenuates Inflammation and Insulin Resistance by Polarizing M2 Macrophages in Diet-induced Obese Micebreakdown → | 2017 | 402 |
| 10 | 2016 | 67 | |
| 11 | 2016 | 73 | |
| 12 | 2015 | 212 | |
| 13 | 2015 | 173 | |
| 14 | 2014 | 63 | |
| 15 | 2013 | 65 | |
| 16 | CCR5はマクロファージ動員とM1/M2状態を調節することで,肥満による脂肪組織の炎症およびインスリン抵抗性に重要な役割を果たす | 2013 | 1 |
| 17 | 2012 | 240 | |
| 18 | 2012 | 83 | |
| 19 | 2008 | 132 | |
| 20 | 2006 | 56 |
About Mayumi Nagashimada
Mayumi Nagashimada is a scholar working on Epidemiology, Endocrinology, Diabetes and Metabolism and Hepatology, having authored 35 papers that have together received 2.6k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (18 papers), Diet, Metabolism, and Disease (8 papers), Adipose Tissue and Metabolism (7 papers), Adipokines, Inflammation, and Metabolic Diseases (7 papers), Congenital gastrointestinal and neural anomalies (5 papers), Genomics, phytochemicals, and oxidative stress (4 papers), Liver Disease and Transplantation (3 papers) and Lipid metabolism and disorders (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (602 citations), Biochemistry (203 citations) and Epidemiology (962 citations). Mayumi Nagashimada has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Tsuguhito Ota, Yinhua Ni, Shuichi Kaneko, Fen Zhuge, Naoto Nagata, Toshihiro Uesaka, Hideki Enomoto, Liang Xu, Guanliang Chen and Naofumi Mukaida. Their work appears in journals such as Journal of Clinical Investigation, Journal of Neuroscience and PLoS ONE.
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.