Stephen J. DiMartino

478 total citations
17 papers, 344 citations indexed

About

Stephen J. DiMartino is a scholar working on Rheumatology, Pharmacology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Stephen J. DiMartino has authored 17 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Rheumatology, 4 papers in Pharmacology and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Stephen J. DiMartino's work include Osteoarthritis Treatment and Mechanisms (5 papers), Blood properties and coagulation (3 papers) and Erythrocyte Function and Pathophysiology (3 papers). Stephen J. DiMartino is often cited by papers focused on Osteoarthritis Treatment and Mechanisms (5 papers), Blood properties and coagulation (3 papers) and Erythrocyte Function and Pathophysiology (3 papers). Stephen J. DiMartino collaborates with scholars based in United States. Stephen J. DiMartino's co-authors include Richard R. Kew, Glenda Trujillo, Haitao Gao, Paula Dakin, Gregory P. Geba, George D. Yancopoulos, Neil Stahl, Alan Kivitz, Lionel B. Ivashkiv and Jennifer Maloney and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Immunology and Journal of the American Society of Nephrology.

In The Last Decade

Stephen J. DiMartino

15 papers receiving 339 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen J. DiMartino United States 9 88 83 80 80 75 17 344
Sibel Oğuzkan Balcı Türkiye 13 59 0.7× 40 0.5× 115 1.4× 53 0.7× 50 0.7× 48 404
Dong‐Hyuk Sheen South Korea 11 54 0.6× 32 0.4× 93 1.2× 111 1.4× 39 0.5× 17 358
Johanna Huhtakangas Finland 10 72 0.8× 248 3.0× 134 1.7× 104 1.3× 45 0.6× 24 520
T. Okano Japan 10 144 1.6× 30 0.4× 136 1.7× 114 1.4× 48 0.6× 36 422
Anders Ljungberg Sweden 8 191 2.2× 40 0.5× 26 0.3× 58 0.7× 93 1.2× 11 343
Nathália Batista Corrêa Brazil 9 45 0.5× 67 0.8× 75 0.9× 35 0.4× 32 0.4× 13 348
R. Schwendimann United States 10 28 0.3× 65 0.8× 73 0.9× 39 0.5× 30 0.4× 27 323
Yune-Jung Park South Korea 7 80 0.9× 27 0.3× 120 1.5× 116 1.4× 24 0.3× 14 399
Shota Miyake Japan 7 58 0.7× 50 0.6× 92 1.1× 59 0.7× 27 0.4× 15 314
Mamori Tani Japan 13 94 1.1× 92 1.1× 54 0.7× 79 1.0× 75 1.0× 30 462

Countries citing papers authored by Stephen J. DiMartino

Since Specialization
Citations

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

Fields of papers citing papers by Stephen J. DiMartino

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen J. DiMartino. 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 Stephen J. DiMartino. The network helps show where Stephen J. DiMartino may publish in the future.

Co-authorship network of co-authors of Stephen J. DiMartino

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen J. DiMartino. A scholar is included among the top collaborators of Stephen J. DiMartino 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 Stephen J. DiMartino. Stephen J. DiMartino 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.
DiMartino, Stephen J., Haitao Gao, Guillermo J. Valenzuela, et al.. (2025). Efficacy and safety of fasinumab in an NSAID-controlled study in patients with pain due to osteoarthritis of the knee or hip. BMC Musculoskeletal Disorders. 26(1). 192–192. 1 indexed citations
2.
Piret, Siân E., et al.. (2025). Krüppel-Like Factor 6 Induces RNA Polymerase II Subunit RPB1 to Promote Kidney Injury. Journal of the American Society of Nephrology. 36(10). 1914–1927.
3.
DiMartino, Stephen J., Mónica P. Revelo, Sandeep K. Mallipattu, & Siân E. Piret. (2024). Activation of branched chain amino acid catabolism protects against nephrotoxic acute kidney injury. American Journal of Physiology-Renal Physiology. 328(1). F152–F163.
4.
DiMartino, Stephen J., Haitao Gao, Tuhina Neogi, et al.. (2024). Prevalence of preexisting articular bone pathology in patients with osteoarthritis screened for fasinumab clinical trials identified by X-ray or magnetic resonance imaging. Osteoarthritis and Cartilage. 32(12). 1601–1609. 1 indexed citations
5.
DiMartino, Stephen J., Thomas J. Schnitzer, Haitao Gao, et al.. (2024). A phase III study to evaluate the long-term safety and efficacy of fasinumab in patients with pain due to osteoarthritis of the knee or hip. SHILAP Revista de lepidopterología. 6(4). 100533–100533. 2 indexed citations
6.
Chen, Shuang, et al.. (2024). Risk of carpal tunnel syndrome among patients with osteoarthritis: a US population-based study. BMC Musculoskeletal Disorders. 25(1). 468–468. 1 indexed citations
7.
Dakin, Paula, Alan Kivitz, Joseph Gimbel, et al.. (2020). Efficacy and safety of fasinumab in patients with chronic low back pain: a phase II/III randomised clinical trial. Annals of the Rheumatic Diseases. 80(4). 509–517. 26 indexed citations
8.
Dakin, Paula, Stephen J. DiMartino, Haitao Gao, et al.. (2019). The Efficacy, Tolerability, and Joint Safety of Fasinumab in Osteoarthritis Pain: A Phase IIb/III Double‐Blind, Placebo‐Controlled, Randomized Clinical Trial. Arthritis & Rheumatology. 71(11). 1824–1834. 71 indexed citations
9.
DiMartino, Stephen J., et al.. (2014). FRI0506 Total Joint Arthroplasty in Dermatomyositis and Polymyositis. Annals of the Rheumatic Diseases. 73. 570–571. 1 indexed citations
10.
DiMartino, Stephen J., et al.. (2010). Systemic lupus erythematosus monocytes are less responsive to interleukin‐10 in the presence of immune complexes. Arthritis & Rheumatism. 63(1). 212–218. 24 indexed citations
11.
DiMartino, Stephen J.. (2008). Idiopathic inflammatory myopathy: Treatment options. Current Rheumatology Reports. 10(4). 321–327. 4 indexed citations
12.
DiMartino, Stephen J., et al.. (2008). Insoluble immune complexes are most effective at triggering IL-10 production in human monocytes and synergize with TLR ligands and C5a. Clinical Immunology. 127(1). 56–65. 15 indexed citations
13.
DiMartino, Stephen J., et al.. (2006). Upregulation of Vitamin D binding protein (Gc-globulin) binding sites during neutrophil activation from a latent reservoir in azurophil granules. Molecular Immunology. 44(9). 2370–2377. 26 indexed citations
14.
DiMartino, Stephen J., et al.. (2005). Selective inhibition of the C5a chemotactic cofactor function of the Vitamin D binding protein by 1,25(OH)2 Vitamin D3. Molecular Immunology. 43(8). 1109–1115. 31 indexed citations
15.
DiMartino, Stephen J., et al.. (2001). Elastase Controls the Binding of the Vitamin D-Binding Protein (Gc-Globulin) to Neutrophils: A Potential Role in the Regulation of C5a Co-Chemotactic Activity. The Journal of Immunology. 166(4). 2688–2694. 43 indexed citations
16.
DiMartino, Stephen J. & Richard R. Kew. (1999). Initial Characterization of the Vitamin D Binding Protein (Gc-Globulin) Binding Site on the Neutrophil Plasma Membrane: Evidence for a Chondroitin Sulfate Proteoglycan. The Journal of Immunology. 163(4). 2135–2142. 39 indexed citations
17.

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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