M.G. Chambers

3.7k total citations · 1 hit paper
46 papers, 2.6k citations indexed

About

M.G. Chambers is a scholar working on Pharmacology, Rheumatology and Molecular Biology. According to data from OpenAlex, M.G. Chambers has authored 46 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Pharmacology, 23 papers in Rheumatology and 14 papers in Molecular Biology. Recurrent topics in M.G. Chambers's work include Osteoarthritis Treatment and Mechanisms (22 papers), Inflammatory mediators and NSAID effects (22 papers) and Cell Adhesion Molecules Research (9 papers). M.G. Chambers is often cited by papers focused on Osteoarthritis Treatment and Mechanisms (22 papers), Inflammatory mediators and NSAID effects (22 papers) and Cell Adhesion Molecules Research (9 papers). M.G. Chambers collaborates with scholars based in United States, United Kingdom and Canada. M.G. Chambers's co-authors include W. B. Van Den Berg, Christopher B. Little, S.S. Glasson, Roger M. Mason, Michael T. Bayliss, J.L. Oskins, Kristen M. Clements, Chaohua Lin, A. Robin Poole and Denise M. Visco and has published in prestigious journals such as Analytical Biochemistry, Pain and Journal of Medicinal Chemistry.

In The Last Decade

M.G. Chambers

45 papers receiving 2.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The OARSI histopathology initiative – recommendations for histological assessments of osteoarthritis in the mouse

2010 1.3k citations S.S. Glasson, M.G. Chambers et al. Osteoarthritis and Cartilage profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M.G. Chambers United States	21	1.8k	952	749	450	426	46	2.6k
John Rediske United States	17	845 0.5×	490 0.5×	531 0.7×	182 0.4×	162 0.4×	28	1.9k
Shan‐Chi Liu Taiwan	30	712 0.4×	895 0.9×	291 0.4×	343 0.8×	143 0.3×	64	1.9k
Chen‐Ming Su Taiwan	25	329 0.2×	726 0.8×	127 0.2×	313 0.7×	98 0.2×	57	1.5k
Federica Ciregia Italy	22	327 0.2×	631 0.7×	104 0.1×	226 0.5×	237 0.6×	52	1.6k
Artur J. de Brum‐Fernandes Canada	24	356 0.2×	465 0.5×	281 0.4×	73 0.2×	84 0.2×	59	1.3k
I R Patel United States	8	305 0.2×	338 0.4×	405 0.5×	104 0.2×	65 0.2×	11	1.0k
J.R. Connor United States	16	322 0.2×	431 0.5×	135 0.2×	100 0.2×	67 0.2×	17	1.1k
Marsha L. Roach United States	13	87 0.0×	882 0.9×	483 0.6×	222 0.5×	613 1.4×	13	1.9k
Jean‐Michel Longpré Canada	21	83 0.0×	684 0.7×	347 0.5×	161 0.4×	325 0.8×	57	1.6k
Anna M. Gómèz‐Foix Spain	26	320 0.2×	1.7k 1.7×	66 0.1×	168 0.4×	734 1.7×	67	2.8k

Countries citing papers authored by M.G. Chambers

Since Specialization

Citations

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

Fields of papers citing papers by M.G. Chambers

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.G. Chambers. 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 M.G. Chambers. The network helps show where M.G. Chambers may publish in the future.

Co-authorship network of co-authors of M.G. Chambers

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

All Works

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20 of 20 papers shown

Lesage, R, Nicole Kops, Niamh Fahy, et al.. (2024). A multi-model approach identifies ALW-II-41-27 as a promising therapy for osteoarthritis-associated inflammation and endochondral ossification. Heliyon. 10(23). e40871–e40871. 1 indexed citations

Chandrasekhar, Srinivasan, Anita K. Harvey, J.L. Oskins, et al.. (2017). Analgesic and anti‐inflammatory properties of novel, selective, and potent EP4 receptor antagonists. Pharmacology Research & Perspectives. 5(3). e00316–e00316. 15 indexed citations

Stuart, Kate, Alan Chan, J.L. Oskins, et al.. (2017). Sustained efficacy of intra-articular SB-061, a novel bioconjugate inspired by aggrecan, in a rat model of osteoarthritis. Osteoarthritis and Cartilage. 25. S415–S415. 2 indexed citations

McDougall, Jason J., Niklas Schuelert, Chaohua Lin, et al.. (2016). Lysophosphatidic acid provides a missing link between osteoarthritis and joint neuropathic pain. Osteoarthritis and Cartilage. 25(6). 926–934. 54 indexed citations

Chandrasekhar, S., Anita K. Harvey, M.G. Chambers, et al.. (2016). Identification and Characterization of Novel Microsomal Prostaglandin E Synthase-1 Inhibitors for Analgesia. Journal of Pharmacology and Experimental Therapeutics. 356(3). 635–644. 20 indexed citations

Blanco, María‐Jesús, Tatiana Vetman, Srinivasan Chandrasekhar, et al.. (2016). Identification and biological activity of 6-alkyl-substituted 3-methyl-pyridine-2-carbonyl amino dimethyl-benzoic acid EP4 antagonists. Bioorganic & Medicinal Chemistry Letters. 26(9). 2303–2307. 10 indexed citations

Benschop, Robert J., Emily C. Collins, Ryan J. Darling, et al.. (2014). Development of a novel antibody to calcitonin gene-related peptide for the treatment of osteoarthritis-related pain. Osteoarthritis and Cartilage. 22(4). 578–585. 100 indexed citations

Norman, Bryan H., Andrew G. Geiser, M.G. Chambers, et al.. (2013). Selective RAR gamma antagonist LY2813631 protects against retinoid induced cartilage degradation in preclinical models of arthritis. Osteoarthritis and Cartilage. 21. S287–S288. 1 indexed citations

Bar, Grégory, Paul Edwards, Reginald Brys, et al.. (2012). Discovery of a series of imidazopyrazine small molecule inhibitors of the kinase MAPKAPK5, that show activity using in vitro and in vivo models of rheumatoid arthritis. Bioorganic & Medicinal Chemistry Letters. 22(6). 2266–2270. 12 indexed citations

10.

Swearingen, Craig, M.G. Chambers, Chaohua Lin, et al.. (2010). A short-term pharmacodynamic model for monitoring aggrecanase activity: injection of monosodium iodoacetate (MIA) in rats and assessment of aggrecan neoepitope release in synovial fluid using novel ELISAs. Osteoarthritis and Cartilage. 18(9). 1159–1166. 21 indexed citations

11.

Glasson, S.S., M.G. Chambers, W. B. Van Den Berg, & Christopher B. Little. (2010). The OARSI histopathology initiative – recommendations for histological assessments of osteoarthritis in the mouse. Osteoarthritis and Cartilage. 18. S17–S23. 1292 indexed citations breakdown →

12.

Schuelert, Niklas, et al.. (2010). Local application of the endocannabinoid hydrolysis inhibitor URB597 reduces nociception in spontaneous and chemically induced models of osteoarthritis. Pain. 152(5). 975–981. 65 indexed citations

13.

Chambers, M.G., et al.. (2006). The role of adenosine in chondrocyte death in murine osteoarthritis and in a murine chondrocyte cell line. Osteoarthritis and Cartilage. 14(5). 486–495. 25 indexed citations

14.

Berna, Michael J., et al.. (2006). Online immunoaffinity liquid chromatography/tandem mass spectrometry determination of a type II collagen peptide biomarker in rat urine: Investigation of the impact of collision-induced dissociation fluctuation on peptide quantitation. Analytical Biochemistry. 356(2). 235–243. 42 indexed citations

15.

Howard, Michael J., M.G. Chambers, Roger M. Mason, & Clare M. Isacke. (2003). Distribution of Endo180 receptor and ligand in developing articular cartilage. Osteoarthritis and Cartilage. 12(1). 74–82. 22 indexed citations

16.

Chambers, M.G., et al.. (2003). Chondrocyte death during murine osteoarthritis. Osteoarthritis and Cartilage. 12(2). 131–141. 76 indexed citations

17.

Clements, Kristen M., et al.. (2003). Gene deletion of either interleukin‐1β, interleukin‐1β–converting enzyme, inducible nitric oxide synthase, or stromelysin 1 accelerates the development of knee osteoarthritis in mice after surgical transection of the medial collateral ligament and partial medial meniscectomy. Arthritis & Rheumatism. 48(12). 3452–3463. 173 indexed citations

18.

Chambers, M.G., et al.. (2002). Comparison of collagenase-cleaved articular cartilage collagen in mice in the naturally occurring STR/ort model of osteoarthritis and in collagen-induced arthritis. Osteoarthritis and Cartilage. 10(3). 172–179. 20 indexed citations

19.

Chambers, M.G., et al.. (2002). Expression of collagen and aggrecan genes in normal and osteoarthritic murine knee joints. Osteoarthritis and Cartilage. 10(1). 51–61. 45 indexed citations

20.

Flannelly, J., M.G. Chambers, Jayesh Dudhia, et al.. (2002). Metalloproteinase and tissue inhibitor of metalloproteinase expression in the murine STR/ort model of osteoarthritis. Osteoarthritis and Cartilage. 10(9). 722–733. 64 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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