Shenglian Gan

731 total citations
13 papers, 150 citations indexed

About

Shenglian Gan is a scholar working on Endocrinology, Diabetes and Metabolism, Cardiology and Cardiovascular Medicine and Epidemiology. According to data from OpenAlex, Shenglian Gan has authored 13 papers receiving a total of 150 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Endocrinology, Diabetes and Metabolism, 4 papers in Cardiology and Cardiovascular Medicine and 4 papers in Epidemiology. Recurrent topics in Shenglian Gan's work include Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Cardiovascular Health and Disease Prevention (4 papers) and Adipokines, Inflammation, and Metabolic Diseases (2 papers). Shenglian Gan is often cited by papers focused on Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Cardiovascular Health and Disease Prevention (4 papers) and Adipokines, Inflammation, and Metabolic Diseases (2 papers). Shenglian Gan collaborates with scholars based in China, United States and Russia. Shenglian Gan's co-authors include Shijun Gong, Yuhua Zhang, Yi Zhang, Xiaolin Dong, Quan Zhou, Liyin Zhang, Jianfeng Luo, Juan Zhang, Ting Sun and Hongwei� Jiang and has published in prestigious journals such as Scientific Reports, Medicine and Diabetes Obesity and Metabolism.

In The Last Decade

Shenglian Gan

10 papers receiving 145 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shenglian Gan China 5 94 54 25 18 16 13 150
Xiafei Lyu China 5 53 0.6× 36 0.7× 57 2.3× 21 1.2× 16 1.0× 7 138
Kalyan Kumar Gangopadhyay India 9 121 1.3× 42 0.8× 55 2.2× 14 0.8× 16 1.0× 25 180
Aline M.E. Stades Netherlands 6 203 2.2× 81 1.5× 85 3.4× 12 0.7× 18 1.1× 11 249
Christine P. Limonte United States 8 63 0.7× 38 0.7× 24 1.0× 22 1.2× 22 1.4× 18 171
Alfio Edoardo Giuffrida Italy 5 54 0.6× 30 0.6× 13 0.5× 20 1.1× 22 1.4× 9 179
Richard Chudleigh United Kingdom 10 139 1.5× 67 1.2× 33 1.3× 19 1.1× 35 2.2× 18 257
Sanam Ebtehaj United States 6 94 1.0× 27 0.5× 69 2.8× 48 2.7× 36 2.3× 9 200
Agnes Jumar Germany 9 124 1.3× 36 0.7× 43 1.7× 11 0.6× 80 5.0× 16 239
Guixia Wang China 3 38 0.4× 26 0.5× 18 0.7× 26 1.4× 8 0.5× 6 134
Kerri P. Howard United States 8 37 0.4× 41 0.8× 22 0.9× 37 2.1× 33 2.1× 15 289

Countries citing papers authored by Shenglian Gan

Since Specialization
Citations

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

Fields of papers citing papers by Shenglian Gan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shenglian Gan

This figure shows the co-authorship network connecting the top 25 collaborators of Shenglian Gan. A scholar is included among the top collaborators of Shenglian Gan 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 Shenglian Gan. Shenglian Gan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
2.
Ji, Linong, Yujin Ma, Shenglian Gan, et al.. (2025). Berberine Ursodeoxycholate for the Treatment of Type 2 Diabetes. JAMA Network Open. 8(3). e2462185–e2462185. 8 indexed citations
3.
4.
Gan, Shenglian, et al.. (2024). Visceral fat area is more strongly associated with arterial stiffness than abdominal subcutaneous fat area in Chinese patients with type 2 diabetes. Diabetology & Metabolic Syndrome. 16(1). 123–123. 2 indexed citations
5.
Yu, Fang, et al.. (2024). AST/ALT ratio is an independent risk factor for diabetic retinopathy: A cross-sectional study. Medicine. 103(26). e38583–e38583.
6.
Gan, Shenglian, et al.. (2023). Optimal Anthropometric Indicators and Cut Points for Predicting Metabolic Syndrome in Chinese Patients with Type 2 Diabetes Mellitus by Gender. Diabetes Metabolic Syndrome and Obesity. Volume 16. 505–514. 4 indexed citations
7.
Gan, Shenglian, Quan Zhou, Fang Yu, et al.. (2023). Positive correlation between lipid accumulation product index and arterial stiffness in Chinese patients with type 2 diabetes. Frontiers in Endocrinology. 14. 1277162–1277162. 3 indexed citations
8.
9.
Gan, Shenglian, Yunfeng Liu, Xiaofei Su, et al.. (2023). Diabetes remission in drug‐naïve patients with type 2 diabetes after dorzagliatin treatment: A prospective cohort study. Diabetes Obesity and Metabolism. 25(10). 2878–2887. 7 indexed citations
10.
Yu, Fang, Huilin Lu, Jianbin Luo, et al.. (2022). INSR novel mutations identified in a Chinese family with severe INSR-related insulin resistance syndromes: A case report. Medicine. 101(49). e32266–e32266. 4 indexed citations
11.
12.
Zhang, Liyin, et al.. (2022). Metabolic syndrome associated with higher glycemic variability in type 1 diabetes: A multicenter cross-sectional study in china. Frontiers in Endocrinology. 13. 972785–972785. 5 indexed citations
13.
Gan, Shenglian. (1992). Biguanide-associated lactic acidosis. Case report and review of the literature. Archives of Internal Medicine. 152(11). 2333–2336. 105 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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2026