Kaida Mu

402 total citations
22 papers, 306 citations indexed

About

Kaida Mu is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Genetics. According to data from OpenAlex, Kaida Mu has authored 22 papers receiving a total of 306 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Endocrinology, Diabetes and Metabolism, 7 papers in Molecular Biology and 7 papers in Genetics. Recurrent topics in Kaida Mu's work include Thyroid Disorders and Treatments (8 papers), Diabetes and associated disorders (5 papers) and Adipose Tissue and Metabolism (4 papers). Kaida Mu is often cited by papers focused on Thyroid Disorders and Treatments (8 papers), Diabetes and associated disorders (5 papers) and Adipose Tissue and Metabolism (4 papers). Kaida Mu collaborates with scholars based in China, Canada and United States. Kaida Mu's co-authors include Jin‐an Zhang, Qian Li, Jing Zhang, Qiuming Yao, Weiwei He, Chen Wang, Weiping Jia, Wei Yao, Xinming Li and Xiaoqing Shao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Biochemical and Biophysical Research Communications and Diabetologia.

In The Last Decade

Kaida Mu

21 papers receiving 303 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kaida Mu China 10 126 89 86 53 38 22 306
Maria Kalina Poland 9 113 0.9× 174 2.0× 39 0.5× 90 1.7× 37 1.0× 26 370
Naruhiro Fujita Japan 10 93 0.7× 58 0.7× 76 0.9× 115 2.2× 74 1.9× 21 293
M. Kacem Tunisia 10 109 0.9× 107 1.2× 56 0.7× 104 2.0× 37 1.0× 27 394
Anna Bossowska Poland 10 179 1.4× 60 0.7× 146 1.7× 104 2.0× 16 0.4× 24 380
Anna S. Wilhelmson Sweden 11 117 0.9× 117 1.3× 67 0.8× 55 1.0× 19 0.5× 19 364
Kristin G. Ardlie United States 7 49 0.4× 77 0.9× 77 0.9× 91 1.7× 24 0.6× 7 268
Maolian Gong Germany 10 75 0.6× 165 1.9× 79 0.9× 74 1.4× 61 1.6× 18 318
Ingrid Yao Mattisson Sweden 12 42 0.3× 126 1.4× 135 1.6× 25 0.5× 44 1.2× 18 370
Felipe Crispim Brazil 12 104 0.8× 153 1.7× 26 0.3× 66 1.2× 62 1.6× 21 364
Stefano Lavaroni Italy 9 180 1.4× 141 1.6× 39 0.5× 52 1.0× 36 0.9× 16 379

Countries citing papers authored by Kaida Mu

Since Specialization
Citations

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

Fields of papers citing papers by Kaida Mu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaida Mu

This figure shows the co-authorship network connecting the top 25 collaborators of Kaida Mu. A scholar is included among the top collaborators of Kaida Mu 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 Kaida Mu. Kaida Mu 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.
Jiang, Yanfei, et al.. (2025). Th17-associated cytokine gene hypomethylation reflects epigenetic dysregulation in graves’ disease. Frontiers in Immunology. 16. 1635883–1635883.
2.
Mu, Kaida, Xiaofei An, Jing Zhang, et al.. (2023). Proteomic analysis of urinary exosomes reveals ferroptosis-associated proteins are involved in diabetic nephropathy. Genes & Diseases. 11(5). 101138–101138. 2 indexed citations
3.
He, Weiwei, Jing Zhao, Xuerong Liu, et al.. (2021). Associations between CD160 polymorphisms and autoimmune thyroid disease: a case-control study. BMC Endocrine Disorders. 21(1). 148–148. 7 indexed citations
4.
Li, Qian, et al.. (2021). Hepatic nNOS impaired hepatic insulin sensitivity through the activation of p38 MAPK. Journal of Endocrinology. 248(3). 265–275. 5 indexed citations
5.
Jiang, Yanfei, et al.. (2021). Psoriasis Susceptibility 1 Candidate 1 (PSORS1C1) Polymorphism is Associated with Autoimmune Thyroid Disease in a Chinese Han Population. Immunological Investigations. 51(5). 1222–1231. 6 indexed citations
6.
Yao, Wei, et al.. (2020). Resveratrol Attenuates High Glucose‐Induced Vascular Endothelial Cell Injury by Activating the E2F3 Pathway. BioMed Research International. 2020(1). 6173618–6173618. 18 indexed citations
7.
Yao, Qiuming, Xiaofei An, Jing Zhang, et al.. (2019). IRF7 Gene Variations Confer Susceptibility to Autoimmune Thyroid Diseases and Graves’ Ophthalmopathy. International Journal of Endocrinology. 2019. 1–7. 4 indexed citations
8.
Yao, Qiuming, Zhenyu Song, Bin Wang, Jin‐an Zhang, & Kaida Mu. (2019). Thyroid disorders in patients with systemic sclerosis: A systematic review and meta-analysis. Autoimmunity Reviews. 18(6). 634–636. 12 indexed citations
9.
Li, Qian, Bin Wang, Kaida Mu, et al.. (2019). Increased Risk of Thyroid Dysfunction Among Patients With Rheumatoid Arthritis. Frontiers in Endocrinology. 9. 799–799. 23 indexed citations
10.
11.
Jia, Xi, Tianyu Zhai, Bing Wang, et al.. (2019). Decreased number and impaired function of type 1 regulatory T cells in autoimmune diseases. Journal of Cellular Physiology. 234(8). 12442–12450. 16 indexed citations
12.
Ni, Yan, Kaida Mu, Xiaofei An, et al.. (2019). Aberrant Histone Methylation in Patients with Graves’ Disease. International Journal of Endocrinology. 2019. 1–7. 8 indexed citations
13.
He, Weiwei, Bin Wang, Kaida Mu, et al.. (2019). Association of single-nucleotide polymorphisms in the IL27 gene with autoimmune thyroid diseases. Endocrine Connections. 8(3). 173–181. 15 indexed citations
14.
He, Weiwei, Bin Wang, Kaida Mu, et al.. (2018). Dose–response relationship between thyroid stimulating hormone and hypertension risk in euthyroid individuals. Journal of Hypertension. 37(1). 144–153. 18 indexed citations
15.
He, Weiwei, et al.. (2018). Effect of Levothyroxine on Blood Pressure in Patients With Subclinical Hypothyroidism: A Systematic Review and Meta-Analysis. Frontiers in Endocrinology. 9. 454–454. 22 indexed citations
16.
Shao, Xiaoqing, Bin Wang, Kaida Mu, et al.. (2018). Key gene co-expression modules and functional pathways involved in the pathogenesis of Graves’ disease. Molecular and Cellular Endocrinology. 474. 252–259. 6 indexed citations
17.
Li, Qian, et al.. (2018). The pathogenesis of thyroid autoimmune diseases: New T lymphocytes – Cytokines circuits beyond the Th1−Th2 paradigm. Journal of Cellular Physiology. 234(3). 2204–2216. 91 indexed citations
18.
Lin, Ziwei, Yu Zhao, Kaida Mu, et al.. (2016). Deletion of β-Arrestin2 in Mice Limited Pancreatic β-Cell Expansion under Metabolic Stress through Activation of the JNK Pathway. Molecular Medicine. 22(1). 74–84. 2 indexed citations
19.
Zhang, Mingliang, Yunxia Zhu, Kaida Mu, et al.. (2013). Loss of β-arrestin2 mediates pancreatic-islet dysfunction in mice. Biochemical and Biophysical Research Communications. 435(3). 345–349. 15 indexed citations
20.
Wang, Chen, Xiaowen Li, Kaida Mu, et al.. (2013). Deficiency of APPL1 in mice impairs glucose-stimulated insulin secretion through inhibition of pancreatic beta cell mitochondrial function. Diabetologia. 56(9). 1999–2009. 20 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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