Michael Q. Jiang

832 total citations
17 papers, 602 citations indexed

About

Michael Q. Jiang is a scholar working on Cellular and Molecular Neuroscience, Neurology and Developmental Neuroscience. According to data from OpenAlex, Michael Q. Jiang has authored 17 papers receiving a total of 602 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cellular and Molecular Neuroscience, 7 papers in Neurology and 6 papers in Developmental Neuroscience. Recurrent topics in Michael Q. Jiang's work include Neuroinflammation and Neurodegeneration Mechanisms (7 papers), Neuroscience and Neuropharmacology Research (5 papers) and Neurogenesis and neuroplasticity mechanisms (5 papers). Michael Q. Jiang is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (7 papers), Neuroscience and Neuropharmacology Research (5 papers) and Neurogenesis and neuroplasticity mechanisms (5 papers). Michael Q. Jiang collaborates with scholars based in United States, China and Netherlands. Michael Q. Jiang's co-authors include Ling Wei, Shan Ping Yu, Zheng Wei, Xiaohuan Gu, Osama Mohamad, Seong S. Shim, Weiwei Zhong, Yingying Zhao, Ken Berglund and Mingke Song and has published in prestigious journals such as The FASEB Journal, Progress in Neurobiology and Cell Reports.

In The Last Decade

Michael Q. Jiang

15 papers receiving 599 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Q. Jiang United States	11	273	175	169	133	85	17	602
Roza Lagoudaki Greece	16	283 1.0×	218 1.2×	135 0.8×	145 1.1×	90 1.1×	33	822
Eva M. Pérez-Villegas Spain	17	422 1.5×	203 1.2×	118 0.7×	267 2.0×	107 1.3×	25	758
Bhuvaneish T. Selvaraj United Kingdom	15	354 1.3×	164 0.9×	130 0.8×	93 0.7×	55 0.6×	30	709
Meiling Tian China	16	348 1.3×	148 0.8×	109 0.6×	187 1.4×	39 0.5×	56	730
Michael P. Fatt Canada	10	257 0.9×	118 0.7×	112 0.7×	179 1.3×	41 0.5×	11	618
Sang-Hyun Choi South Korea	13	353 1.3×	180 1.0×	55 0.3×	102 0.8×	41 0.5×	21	745
Qionglan Yuan China	15	310 1.1×	196 1.1×	143 0.8×	147 1.1×	32 0.4×	29	652
Xinjiang Kang China	12	404 1.5×	312 1.8×	95 0.6×	112 0.8×	31 0.4×	26	763
Аnton N. Shuvaev Russia	13	350 1.3×	325 1.9×	123 0.7×	76 0.6×	35 0.4×	40	618
Haviryaji S. G. Kalluri United States	14	308 1.1×	322 1.8×	180 1.1×	144 1.1×	33 0.4×	21	777

Countries citing papers authored by Michael Q. Jiang

Since Specialization

Citations

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

Fields of papers citing papers by Michael Q. Jiang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Q. Jiang. 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 Michael Q. Jiang. The network helps show where Michael Q. Jiang may publish in the future.

Co-authorship network of co-authors of Michael Q. Jiang

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

All Works

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17 of 17 papers shown

Jiang, Michael Q., et al.. (2025). Plasma H3.1 nucleosomes as biomarkers of infection, inflammation and organ failure. Critical Care. 29(1). 198–198. 4 indexed citations

Gu, Xiaohuan, et al.. (2025). Preventive Memantine Treatment at the Preclinical Stage in the Alzheimer’s Disease Model of the 5xFAD Mouse. Neuroscience Bulletin.

Jiang, Michael Q., et al.. (2024). Reprogramming Glioblastoma Cells into Non-Cancerous Neuronal Cells as a Novel Anti-Cancer Strategy. Cells. 13(11). 897–897. 2 indexed citations

Yu, Shan Ping, et al.. (2024). Acute and chronic excitotoxicity in ischemic stroke and late-onset Alzheimer’s disease. Neural Regeneration Research. 20(7). 1981–1988. 4 indexed citations

Yu, Shan Ping, et al.. (2023). Extrasynaptic NMDA receptors in acute and chronic excitotoxicity: implications for preventive treatments of ischemic stroke and late-onset Alzheimer’s disease. Molecular Neurodegeneration. 18(1). 43–43. 74 indexed citations

Jiang, Michael Q., Xiaohuan Gu, Meghan Logun, et al.. (2022). Glycosaminoglycan scaffolding and neural progenitor cell transplantation promotes regenerative immunomodulation in the mouse ischemic brain. Experimental Neurology. 357. 114177–114177. 10 indexed citations

Yu, Shan Ping, Weiwei Zhong, Ken Berglund, et al.. (2022). Deficiency of NMDA receptor subunit GluN3A as a pathogenic factor for endogenous amyloid deposition and sporadic Alzheimer’s disease. Alzheimer s & Dementia. 18(S4).

Jiang, Michael Q., Shan Ping Yu, Zheng Wei, et al.. (2021). Conversion of Reactive Astrocytes to Induced Neurons Enhances Neuronal Repair and Functional Recovery After Ischemic Stroke. Frontiers in Aging Neuroscience. 13. 612856–612856. 37 indexed citations

Zhong, Weiwei, Ken Berglund, Xiaohuan Gu, et al.. (2021). Pathogenesis of sporadic Alzheimer's disease by deficiency of NMDA receptor subunit GluN3A. Alzheimer s & Dementia. 18(2). 222–239. 33 indexed citations

10.

Wei, Zheng, Meghan Logun, Stephen Tan, et al.. (2020). Cortical Transplantation of Brain‐Mimetic Glycosaminoglycan Scaffolds and Neural Progenitor Cells Promotes Vascular Regeneration and Functional Recovery after Ischemic Stroke in Mice. Advanced Healthcare Materials. 9(5). e1900285–e1900285. 35 indexed citations

11.

Zou, Shan–Shan, Zheng Wei, Yun Yue, et al.. (2019). Desflurane and Surgery Exposure During Pregnancy Decrease Synaptic Integrity and Induce Functional Deficits in Juvenile Offspring Mice. Neurochemical Research. 45(2). 418–427. 15 indexed citations

12.

Jiang, Michael Q., Michelle M. Giddens, James Y. Zhang, et al.. (2019). Protective effects of GPR37 via regulation of inflammation and multiple cell death pathways after ischemic stroke in mice. The FASEB Journal. 33(10). 10680–10691. 49 indexed citations

13.

Zhang, Chengjie, Yanbing Zhu, Song Wang, et al.. (2018). Temporal Gene Expression Profiles after Focal Cerebral Ischemia in Mice. Aging and Disease. 9(2). 249–249. 25 indexed citations

14.

Wei, Ling, Zheng Wei, Michael Q. Jiang, Osama Mohamad, & Shan Ping Yu. (2017). Stem cell transplantation therapy for multifaceted therapeutic benefits after stroke. Progress in Neurobiology. 157. 49–78. 115 indexed citations

15.

Song, Mingke, Shan Ping Yu, Osama Mohamad, et al.. (2016). Optogenetic stimulation of glutamatergic neuronal activity in the striatum enhances neurogenesis in the subventricular zone of normal and stroke mice. Neurobiology of Disease. 98. 9–24. 57 indexed citations

16.

Jiang, Michael Q., Yingying Zhao, Zheng Wei, et al.. (2016). Long‐term survival and regeneration of neuronal and vasculature cells inside the core region after ischemic stroke in adult mice. Brain Pathology. 27(4). 480–498. 53 indexed citations

17.

Groß, Christina, Seth M. Kelly, Aditi Bhattacharya, et al.. (2015). Increased Expression of the PI3K Enhancer PIKE Mediates Deficits in Synaptic Plasticity and Behavior in Fragile X Syndrome. Cell Reports. 11(5). 727–736. 89 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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