Michael D. Lovelace

924 total citations
22 papers, 708 citations indexed

About

Michael D. Lovelace is a scholar working on Molecular Biology, Physiology and Neurology. According to data from OpenAlex, Michael D. Lovelace has authored 22 papers receiving a total of 708 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 7 papers in Physiology and 4 papers in Neurology. Recurrent topics in Michael D. Lovelace's work include Adenosine and Purinergic Signaling (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers) and Stress Responses and Cortisol (3 papers). Michael D. Lovelace is often cited by papers focused on Adenosine and Purinergic Signaling (7 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers) and Stress Responses and Cortisol (3 papers). Michael D. Lovelace collaborates with scholars based in Australia, United States and Singapore. Michael D. Lovelace's co-authors include Bruce J. Brew, Gilles J. Guillemin, Matthew J. Lennon, Chai K. Lim, Bianca Varney, Gayathri Sundaram, Kelly R. Jacobs, Ben J. Gu, Saparna Pai and Tailoi Chan‐Ling and has published in prestigious journals such as Scientific Reports, The FASEB Journal and Neuroscience.

In The Last Decade

Michael D. Lovelace

22 papers receiving 705 citations

Peers

Michael D. Lovelace
Michael D. Lovelace
Citations per year, relative to Michael D. Lovelace Michael D. Lovelace (= 1×) peers Krzysztof Kolmus

Countries citing papers authored by Michael D. Lovelace

Since Specialization
Citations

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

Fields of papers citing papers by Michael D. Lovelace

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael D. Lovelace

This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. Lovelace. A scholar is included among the top collaborators of Michael D. Lovelace 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 D. Lovelace. Michael D. Lovelace 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.
Ng, Mah Lee, Monokesh K. Sen, Michael W. Weible, et al.. (2024). A Review of the Evidence for Tryptophan and the Kynurenine Pathway as a Regulator of Stem Cell Niches in Health and Disease. PubMed. 17. 944232991–944232991. 7 indexed citations
2.
Gautam, Vini, Martin Engel, Rachelle Balez, et al.. (2024). Visualization of incrementally learned projection trajectories for longitudinal data. Scientific Reports. 14(1). 13558–13558. 1 indexed citations
3.
Weible, Michael W., et al.. (2023). BMPRII+ neural precursor cells isolated and characterized from organotypic neurospheres: an in vitro model of human fetal spinal cord development. Neural Regeneration Research. 19(2). 447–457. 2 indexed citations
4.
Qin, Jim, Michael D. Lovelace, Andrew J. Mitchell, et al.. (2021). Perivascular macrophages create an intravascular niche for CD8+ T cell localisation prior to the onset of fatal experimental cerebral malaria. Clinical & Translational Immunology. 10(4). e1273–e1273. 17 indexed citations
5.
Skarratt, Kristen K., Ben J. Gu, Michael D. Lovelace, et al.. (2020). A P2RX7 single nucleotide polymorphism haplotype promotes exon 7 and 8 skipping and disrupts receptor function. The FASEB Journal. 34(3). 3884–3901. 14 indexed citations
6.
Gu, Ben J., et al.. (2019). P2X7 receptor signaling during adult hippocampal neurogenesis. Neural Regeneration Research. 14(10). 1684–1684. 26 indexed citations
7.
Leeson, Hannah C., Tailoi Chan‐Ling, Michael D. Lovelace, et al.. (2019). Real-time Live-cell Flow Cytometry to Investigate Calcium Influx, Pore Formation, and Phagocytosis by P2X7 Receptors in Adult Neural Progenitor Cells. Journal of Visualized Experiments. 2 indexed citations
8.
Cysique, Lucette A., Lauriane Jugé, Matthew J. Lennon, et al.. (2018). HIV brain latency as measured by CSF BcL11b relates to disrupted brain cellular energy in virally suppressed HIV infection. AIDS. 33(3). 433–441. 15 indexed citations
9.
Lennon, Matthew J., Simon Jones, Michael D. Lovelace, Gilles J. Guillemin, & Bruce J. Brew. (2017). Bcl11b—A Critical Neurodevelopmental Transcription Factor—Roles in Health and Disease. Frontiers in Cellular Neuroscience. 11. 89–89. 46 indexed citations
10.
Lovelace, Michael D., Paul Coleman, Yang Zhao, et al.. (2017). The RhoGAP protein ARHGAP18/SENEX localizes to microtubules and regulates their stability in endothelial cells. Molecular Biology of the Cell. 28(8). 1066–1078. 19 indexed citations
11.
Lovelace, Michael D., Bianca Varney, Gayathri Sundaram, et al.. (2016). Current Evidence for a Role of the Kynurenine Pathway of Tryptophan Metabolism in Multiple Sclerosis. Frontiers in Immunology. 7. 246–246. 120 indexed citations
12.
Lovelace, Michael D., Bianca Varney, Gayathri Sundaram, et al.. (2016). Recent evidence for an expanded role of the kynurenine pathway of tryptophan metabolism in neurological diseases. Neuropharmacology. 112(Pt B). 373–388. 274 indexed citations
13.
Lennon, Matthew J., Simon Jones, Michael D. Lovelace, Gilles J. Guillemin, & Bruce J. Brew. (2015). Bcl11b: A New Piece to the Complex Puzzle of Amyotrophic Lateral Sclerosis Neuropathogenesis?. Neurotoxicity Research. 29(2). 201–207. 13 indexed citations
14.
Gu, Ben J., Michael D. Lovelace, Michael W. Weible, et al.. (2015). P2X7 IS AN ARCHAIC SCAVENGER RECEPTOR RECOGNIZING APOPTOTIC NEUROBLASTS IN EARLY HUMAN NEUROGENESIS. Minerva Access (University of Melbourne). 6 indexed citations
15.
Lovelace, Michael D., Ben J. Gu, Steven S. Eamegdool, et al.. (2014). P2X7 Receptors Mediate Innate Phagocytosis by Human Neural Precursor Cells and Neuroblasts. Stem Cells. 33(2). 526–541. 43 indexed citations
16.
Lovelace, Michael D., et al.. (2013). Absence of Platelet Endothelial Cell Adhesion Molecule 1, PECAM-1/CD31,In VivoIncreases Resistance to Salmonella enterica Serovar Typhimurium in Mice. Infection and Immunity. 81(6). 1952–1963. 10 indexed citations
17.
Werry, Eryn L., Guo Jun Liu, Michael D. Lovelace, Rajini Nagarajah, & Max R. Bennett. (2012). Glutamate potentiates lipopolysaccharide–stimulated interleukin-10 release from neonatal rat spinal cord astrocytes. Neuroscience. 207. 12–24. 7 indexed citations
18.
Werry, Eryn L., Guo Jun Liu, Michael D. Lovelace, et al.. (2010). Lipopolysaccharide-stimulated interleukin-10 release from neonatal spinal cord microglia is potentiated by glutamate. Neuroscience. 175. 93–103. 29 indexed citations
19.
Lovelace, Michael D. & David M. Cahill. (2007). A rapid cell counting method utilising acridine orange as a novel discriminating marker for both cultured astrocytes and microglia. Journal of Neuroscience Methods. 165(2). 223–229. 19 indexed citations
20.
Lovelace, Michael D., et al.. (2003). Steroid 21-hydroxylase expression in cultured rat astrocytes. Brain Research Bulletin. 61(6). 609–615. 7 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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