Jaegwon Chung

1.2k total citations
17 papers, 709 citations indexed

About

Jaegwon Chung is a scholar working on Neurology, Physiology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Jaegwon Chung has authored 17 papers receiving a total of 709 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Neurology, 7 papers in Physiology and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Jaegwon Chung's work include Neuroinflammation and Neurodegeneration Mechanisms (11 papers), Alzheimer's disease research and treatments (5 papers) and Parkinson's Disease Mechanisms and Treatments (4 papers). Jaegwon Chung is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (11 papers), Alzheimer's disease research and treatments (5 papers) and Parkinson's Disease Mechanisms and Treatments (4 papers). Jaegwon Chung collaborates with scholars based in United States, Sweden and Denmark. Jaegwon Chung's co-authors include Jae‐Kyung Lee, Malú G. Tansey, Kelly B. Menees, Claire‐Anne Gutekunst, Jianjun Chang, George T. Kannarkat, Fiona E McAlpine, Christopher J. Barnum, Hyun Joon Lee and James Barber and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Jaegwon Chung

16 papers receiving 698 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jaegwon Chung United States 13 274 262 205 153 144 17 709
Xinling Yang China 14 201 0.7× 273 1.0× 313 1.5× 111 0.7× 154 1.1× 67 784
Merja Jaronen Finland 14 249 0.9× 180 0.7× 246 1.2× 147 1.0× 123 0.9× 17 834
Margarita Zoga Greece 14 248 0.9× 280 1.1× 127 0.6× 202 1.3× 117 0.8× 24 663
L.-W. Fan United States 11 273 1.0× 98 0.4× 217 1.1× 77 0.5× 102 0.7× 14 804
Jessica Dalsing-Hernandez United States 6 266 1.0× 120 0.5× 137 0.7× 197 1.3× 70 0.5× 6 577
Nithi Asavapanumas Thailand 17 241 0.9× 329 1.3× 283 1.4× 104 0.7× 141 1.0× 31 940
Paul Felten Luxembourg 9 248 0.9× 116 0.4× 367 1.8× 149 1.0× 79 0.5× 10 711
Alerie Guzman de la Fuente United Kingdom 14 322 1.2× 65 0.2× 288 1.4× 165 1.1× 119 0.8× 22 808
Yuen Ling Lee United States 10 273 1.0× 131 0.5× 285 1.4× 95 0.6× 196 1.4× 11 740
Shenbin Xu China 14 495 1.8× 259 1.0× 373 1.8× 90 0.6× 109 0.8× 21 1.1k

Countries citing papers authored by Jaegwon Chung

Since Specialization
Citations

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

Fields of papers citing papers by Jaegwon Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaegwon Chung

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

All Works

17 of 17 papers shown
1.
2.
Chung, Jaegwon, et al.. (2024). RGS10 mitigates high glucose-induced microglial inflammation via the reactive oxidative stress pathway and enhances synuclein clearance in microglia. Frontiers in Cellular Neuroscience. 18. 1374298–1374298. 1 indexed citations
3.
Menees, Kelly B., et al.. (2021). Sex- and age‐dependent alterations of splenic immune cell profile and NK cell phenotypes and function in C57BL/6J mice. Immunity & Ageing. 18(1). 3–3. 44 indexed citations
4.
Schank, Jesse R., Soo-Jung Lee, Carlos Gonzalez‐Islas, et al.. (2020). Increased Alcohol Consumption in Mice Lacking Sodium Bicarbonate Transporter NBCn1. Scientific Reports. 10(1). 11017–11017. 8 indexed citations
5.
Menees, Kelly B., Jaegwon Chung, Claire‐Anne Gutekunst, et al.. (2020). NK cells clear α-synuclein and the depletion of NK cells exacerbates synuclein pathology in a mouse model of α-synucleinopathy. Proceedings of the National Academy of Sciences. 117(3). 1762–1771. 97 indexed citations
6.
Menees, Kelly B., et al.. (2019). Intrastriatal injection of preformed alpha-synuclein fibrils alters central and peripheral immune cell profiles in non-transgenic mice. Journal of Neuroinflammation. 16(1). 250–250. 97 indexed citations
7.
8.
Eidson, Lori N., George T. Kannarkat, Christopher J. Barnum, et al.. (2017). Candidate inflammatory biomarkers display unique relationships with alpha-synuclein and correlate with measures of disease severity in subjects with Parkinson’s disease. Journal of Neuroinflammation. 14(1). 164–164. 69 indexed citations
9.
Lee, Jae‐Kyung, George T. Kannarkat, Jaegwon Chung, et al.. (2016). RGS10 deficiency ameliorates the severity of disease in experimental autoimmune encephalomyelitis. Journal of Neuroinflammation. 13(1). 24–24. 21 indexed citations
10.
Kannarkat, George T., Jae‐Kyung Lee, Chenere P. Ramsey, et al.. (2015). Age-related changes in regulator of G-protein signaling (RGS)-10 expression in peripheral and central immune cells may influence the risk for age-related degeneration. Neurobiology of Aging. 36(5). 1982–1993. 18 indexed citations
11.
Barnum, Christopher J., Xi Chen, Jaegwon Chung, et al.. (2014). Peripheral Administration of the Selective Inhibitor of Soluble Tumor Necrosis Factor (TNF) XPro®1595 Attenuates Nigral Cell Loss and Glial Activation in 6-OHDA Hemiparkinsonian Rats. Journal of Parkinson s Disease. 4(3). 349–360. 85 indexed citations
12.
Lee, Jae‐Kyung, Jaegwon Chung, George T. Kannarkat, & Malú G. Tansey. (2013). Critical Role of Regulator G-Protein Signaling 10 (RGS10) in Modulating Macrophage M1/M2 Activation. PLoS ONE. 8(11). e81785–e81785. 39 indexed citations
13.
Chen, Xi, Jianjun Chang, Qiudong Deng, et al.. (2013). Progranulin Does Not Bind Tumor Necrosis Factor (TNF) Receptors and Is Not a Direct Regulator of TNF-Dependent Signaling or Bioactivity in Immune or Neuronal Cells. Journal of Neuroscience. 33(21). 9202–9213. 74 indexed citations
14.
Lee, Jae‐Kyung, Jaegwon Chung, Kirk M. Druey, & Malú G. Tansey. (2012). RGS10 exerts a neuroprotective role through the PKA/c‐AMP response‐element (CREB) pathway in dopaminergic neuron‐like cells. Journal of Neurochemistry. 122(2). 333–343. 30 indexed citations
15.
Lee, Jae‐Kyung, Jaegwon Chung, Fiona E McAlpine, & Malú G. Tansey. (2011). Regulator of G-Protein Signaling-10 Negatively Regulates NF-κB in Microglia and Neuroprotects Dopaminergic Neurons in Hemiparkinsonian Rats. Journal of Neuroscience. 31(33). 11879–11888. 58 indexed citations
16.
Kim, Myoung Hwa & Jaegwon Chung. (2008). Synergistic cell death by EGCG and ibuprofen in DU-145 prostate cancer cell line.. PubMed. 27(6B). 3947–56. 23 indexed citations
17.
Yi, Kun, et al.. (2005). Role of Protein Phosphatases in Estrogen-Mediated Neuroprotection. Journal of Neuroscience. 25(31). 7191–7198. 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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