Shaoming Sang

521 total citations
22 papers, 316 citations indexed

About

Shaoming Sang is a scholar working on Neurology, Physiology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Shaoming Sang has authored 22 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Neurology, 9 papers in Physiology and 7 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Shaoming Sang's work include Alcoholism and Thiamine Deficiency (9 papers), Alzheimer's disease research and treatments (7 papers) and Neurological and metabolic disorders (7 papers). Shaoming Sang is often cited by papers focused on Alcoholism and Thiamine Deficiency (9 papers), Alzheimer's disease research and treatments (7 papers) and Neurological and metabolic disorders (7 papers). Shaoming Sang collaborates with scholars based in China and United States. Shaoming Sang's co-authors include Chunjiu Zhong, Xiaoli Pan, Guoqiang Fei, Huimin Liu, Lirong Jin, Lei Zhao, Changpeng Wang, Wenwen Cai, Linxi Li and Yun Wang and has published in prestigious journals such as PLoS ONE, Analytical Chemistry and Scientific Reports.

In The Last Decade

Shaoming Sang

20 papers receiving 310 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shaoming Sang China 10 118 102 95 40 39 22 316
Viruna Neergheen United Kingdom 11 88 0.7× 212 2.1× 45 0.5× 62 1.6× 60 1.5× 11 391
Chigumi Sato Japan 6 112 0.9× 154 1.5× 103 1.1× 39 1.0× 43 1.1× 6 358
Valérie Leduc Canada 10 175 1.5× 124 1.2× 42 0.4× 51 1.3× 22 0.6× 13 421
Hojin Kang South Korea 12 67 0.6× 168 1.6× 79 0.8× 53 1.3× 21 0.5× 14 377
Lisa Hahnefeld Germany 12 128 1.1× 229 2.2× 30 0.3× 21 0.5× 24 0.6× 41 457
Carolina Maso Viegas Brazil 14 96 0.8× 328 3.2× 37 0.4× 67 1.7× 71 1.8× 33 512
Geetanjali Murari India 6 158 1.3× 104 1.0× 29 0.3× 35 0.9× 63 1.6× 9 362
Carlos Alberto Yasin Wayhs Brazil 15 178 1.5× 294 2.9× 26 0.3× 54 1.4× 80 2.1× 31 597
Ampa Luangpirom Thailand 5 192 1.6× 206 2.0× 34 0.4× 77 1.9× 13 0.3× 15 395
Pei‐Chuan Ho Taiwan 10 185 1.6× 252 2.5× 61 0.6× 49 1.2× 31 0.8× 13 510

Countries citing papers authored by Shaoming Sang

Since Specialization
Citations

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

Fields of papers citing papers by Shaoming Sang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaoming Sang

This figure shows the co-authorship network connecting the top 25 collaborators of Shaoming Sang. A scholar is included among the top collaborators of Shaoming Sang 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 Shaoming Sang. Shaoming Sang 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.
Sang, Shaoming, et al.. (2025). Glucose-lipid metabolic index reflects cognitive impairment of non-diabetic elderly individuals. Journal of Alzheimer s Disease. 106(4). 1629–1640.
2.
Fei, Guoqiang, et al.. (2023). Identification of diagnostic biomarkers in Alzheimer’s disease by integrated bioinformatic analysis and machine learning strategies. Frontiers in Aging Neuroscience. 15. 1169620–1169620. 6 indexed citations
3.
4.
Cai, Wenwen, et al.. (2023). The Dynamic SUMOylation Changes and Their Potential Role in the Senescence of APOE4 Mice. Biomedicines. 12(1). 16–16.
5.
Cai, Wenwen, Linxi Li, Shaoming Sang, Xiaoli Pan, & Chunjiu Zhong. (2022). Physiological Roles of β-amyloid in Regulating Synaptic Function: Implications for AD Pathophysiology. Neuroscience Bulletin. 39(8). 1289–1308. 42 indexed citations
6.
Qian, Ting, Lei Zhao, Xiaoli Pan, et al.. (2022). Association Between Blood Biochemical Factors Contributing to Cognitive Decline and B Vitamins in Patients With Alzheimer's Disease. Frontiers in Nutrition. 9. 823573–823573. 7 indexed citations
7.
Pan, Xiaoli, Shaoming Sang, & Chunjiu Zhong. (2021). Brain Energy Improvement as an Emerging Approach for Alzheimer’s Disease Treatment. Neuroscience Bulletin. 37(6). 892–893. 2 indexed citations
8.
Zhao, Lei, et al.. (2021). The impact of thiamine deficiency and benfotiamine treatment on Nod-like receptor protein-3 inflammasome in microglia. Neuroreport. 32(12). 1041–1048. 5 indexed citations
9.
Zhao, Ruoqi, Guoqiang Fei, Xiaoli Pan, et al.. (2021). Dynamic Change of Intracellular Metabolism of Microglia Evaluated by Transcriptomics in an Alzheimer’s Mouse Model. Journal of Alzheimer s Disease. 81(2). 517–531. 5 indexed citations
10.
Wang, Changpeng, Donglang Jiang, Shaoming Sang, et al.. (2020). A novel PET tracer 18F-deoxy-thiamine: synthesis, metabolic kinetics, and evaluation on cerebral thiamine metabolism status. EJNMMI Research. 10(1). 126–126. 2 indexed citations
12.
Wang, Lijun, Xiaoli Pan, Guoqiang Fei, et al.. (2019). Decreased Function of Delayed Recall in Non-demented Elderly Subjects With Apolipoprotein E ε4 Allele. Frontiers in Aging Neuroscience. 11. 71–71. 2 indexed citations
13.
Fang, Pan, Juanjuan Xie, Shaoming Sang, et al.. (2019). Multilayered N-Glycoproteome Profiling Reveals Highly Heterogeneous and Dysregulated Protein N-Glycosylation Related to Alzheimer’s Disease. Analytical Chemistry. 92(1). 867–874. 42 indexed citations
14.
Liu, Huimin, et al.. (2018). Thiamine deficiency contributes to synapse and neural circuit defects. Biological Research. 51(1). 35–35. 25 indexed citations
15.
Sang, Shaoming, Xiaoli Pan, Zhichun Chen, et al.. (2018). Thiamine diphosphate reduction strongly correlates with brain glucose hypometabolism in Alzheimer’s disease, whereas amyloid deposition does not. Alzheimer s Research & Therapy. 10(1). 26–26. 48 indexed citations
16.
Wang, Changpeng, Guoqiang Fei, Xiaoli Pan, et al.. (2018). High thiamine diphosphate level as a protective factor for Alzheimer’s disease. Neurological Research. 40(8). 1–8. 18 indexed citations
17.
Pan, Xiaoli, Shaoming Sang, Guoqiang Fei, et al.. (2017). Enhanced Activities of Blood Thiamine Diphosphatase and Monophosphatase in Alzheimer's Disease. PLoS ONE. 12(1). e0167273–e0167273. 16 indexed citations
18.
Liu, Huimin, Shaoming Sang, Yuan Lü, et al.. (2017). Thiamine metabolism is critical for regulating correlated growth of dendrite arbors and neuronal somata. Scientific Reports. 7(1). 5342–5342. 15 indexed citations
19.
Pan, Xiaoli, Guoqiang Fei, Changpeng Wang, et al.. (2015). Correlat ion of thiamine metabolite levels with cognitive function in the non-demented elderly. Neuroscience Bulletin. 31(6). 676–684. 18 indexed citations
20.
Zhao, Lei, Neng Gong, Meng Liu, et al.. (2014). Beneficial synergistic effects of microdose lithium with pyrroloquinoline quinone in an Alzheimer's disease mouse model. Neurobiology of Aging. 35(12). 2736–2745. 36 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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