Shawn A. Mahmud

2.1k total citations · 1 hit paper
19 papers, 1.4k citations indexed

About

Shawn A. Mahmud is a scholar working on Immunology, Rheumatology and Hematology. According to data from OpenAlex, Shawn A. Mahmud has authored 19 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Immunology, 6 papers in Rheumatology and 6 papers in Hematology. Recurrent topics in Shawn A. Mahmud's work include T-cell and B-cell Immunology (5 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (4 papers) and Immune Cell Function and Interaction (4 papers). Shawn A. Mahmud is often cited by papers focused on T-cell and B-cell Immunology (5 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (4 papers) and Immune Cell Function and Interaction (4 papers). Shawn A. Mahmud collaborates with scholars based in United States, Japan and Italy. Shawn A. Mahmud's co-authors include Michael A. Farrar, Luke S. Manlove, Arne Slungaard, Kieng B. Vang, Jianying Yang, Amanda L. Vegoe, Matthew A. Burchill, Jianguo Wang, Bryce A. Binstadt and David L. Owen and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Experimental Medicine and Blood.

In The Last Decade

Shawn A. Mahmud

17 papers receiving 1.4k citations

Hit Papers

On the Alert for Cytokine... 2020 2026 2022 2024 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shawn A. Mahmud United States 12 711 360 250 210 176 19 1.4k
Ramadan A. Ali United States 12 365 0.5× 377 1.0× 273 1.1× 183 0.9× 123 0.7× 23 1.1k
W. Winn Chatham United States 13 458 0.6× 343 1.0× 213 0.9× 165 0.8× 64 0.4× 30 1.2k
Zongwen Shuai China 19 388 0.5× 209 0.6× 446 1.8× 116 0.6× 100 0.6× 81 1.5k
Heather A. Corkrey United States 7 269 0.4× 226 0.6× 282 1.1× 89 0.4× 221 1.3× 8 1.3k
Chenxi Liu China 18 161 0.2× 366 1.0× 267 1.1× 207 1.0× 199 1.1× 94 1.5k
Shinjiro Todo Japan 21 444 0.6× 355 1.0× 258 1.0× 102 0.5× 236 1.3× 79 1.4k
Giacomo Cafaro Italy 19 228 0.3× 246 0.7× 161 0.6× 105 0.5× 102 0.6× 60 1.1k
Lauren Clancy United States 8 337 0.5× 182 0.5× 370 1.5× 66 0.3× 238 1.4× 13 1.2k
Martin F. Sprinzl Germany 25 300 0.4× 179 0.5× 237 0.9× 62 0.3× 266 1.5× 69 1.6k
Irina Portier United States 12 327 0.5× 525 1.5× 294 1.2× 246 1.2× 178 1.0× 22 1.2k

Countries citing papers authored by Shawn A. Mahmud

Since Specialization
Citations

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

Fields of papers citing papers by Shawn A. Mahmud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shawn A. Mahmud. 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 Shawn A. Mahmud. The network helps show where Shawn A. Mahmud may publish in the future.

Co-authorship network of co-authors of Shawn A. Mahmud

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

All Works

19 of 19 papers shown
1.
Mahmud, Shawn A., et al.. (2023). HLADRB1*15 and Eosinophilia Are Common Among Patients With Systemic Juvenile Idiopathic Arthritis. Arthritis Care & Research. 75(10). 2082–2087. 11 indexed citations
2.
McElwee, Matthew K., Thamotharampillai Dileepan, Shawn A. Mahmud, & Marc K. Jenkins. (2023). The CD4+ T cell repertoire specific for citrullinated peptides shows evidence of immune tolerance. The Journal of Experimental Medicine. 220(12). 11 indexed citations
3.
Binstadt, Bryce A., C. Correll, Patricia M. Hobday, et al.. (2022). Capturing critical data elements in Juvenile Idiopathic Arthritis: initiatives to improve data capture. Pediatric Rheumatology. 20(1). 83–83. 2 indexed citations
4.
Mahmud, Shawn A., C. Correll, Patricia M. Hobday, et al.. (2022). Non-criteria antiphospholipid antibodies and pediatric rheumatic disease: a case series. Pediatric Rheumatology. 20(1). 70–70. 4 indexed citations
5.
Boucher, Alexander A., Luke Young, Michael D. Evans, et al.. (2022). Prolonged Elevations of Factor VIII and von Willebrand Factor Antigen After Multisystem Inflammatory Syndrome in Children. Journal of Pediatric Hematology/Oncology. 45(4). e427–e432. 2 indexed citations
6.
Garay, Bayardo I., Bryce A. Binstadt, C. Correll, et al.. (2021). Using quality improvement methodology and tools to reduce patient wait time in a paediatric subspecialty rheumatology clinic. BMJ Open Quality. 10(4). e001550–e001550.
7.
Henderson, Lauren A., Scott Canna, Grant S. Schulert, et al.. (2020). On the Alert for Cytokine Storm: Immunopathology in COVID‐19. Arthritis & Rheumatology. 72(7). 1059–1063. 475 indexed citations breakdown →
8.
Mahmud, Shawn A. & Bryce A. Binstadt. (2019). Autoantibodies in the Pathogenesis, Diagnosis, and Prognosis of Juvenile Idiopathic Arthritis. Frontiers in Immunology. 9. 3168–3168. 57 indexed citations
9.
Owen, David L., Shawn A. Mahmud, Kieng B. Vang, et al.. (2018). Identification of Cellular Sources of IL-2 Needed for Regulatory T Cell Development and Homeostasis. The Journal of Immunology. 200(12). 3926–3933. 65 indexed citations
10.
Mahmud, Shawn A., Luke S. Manlove, Heather Schmitz, et al.. (2014). Costimulation via the tumor-necrosis factor receptor superfamily couples TCR signal strength to the thymic differentiation of regulatory T cells. Nature Immunology. 15(5). 473–481. 215 indexed citations
11.
Mahmud, Shawn A., Luke S. Manlove, & Michael A. Farrar. (2013). Interleukin-2 and STAT5 in regulatory T cell development and function. PubMed. 2(1). e23154–e23154. 114 indexed citations
12.
Vang, Kieng B., Jianying Yang, Shawn A. Mahmud, et al.. (2008). IL-2, -7, and -15, but Not Thymic Stromal Lymphopoeitin, Redundantly Govern CD4+Foxp3+ Regulatory T Cell Development. The Journal of Immunology. 181(5). 3285–3290. 206 indexed citations
13.
Wang, Jianguo, Shawn A. Mahmud, Peter B. Bitterman, Yuqing Huo, & Arne Slungaard. (2007). Histone Deacetylase Inhibitors Suppress TF-κB-dependent Agonist-driven Tissue Factor Expression in Endothelial Cells and Monocytes. Journal of Biological Chemistry. 282(39). 28408–28418. 56 indexed citations
15.
Kowalska, M. Anna, Shawn A. Mahmud, Michele P. Lambert, Mortimer Poncz, & Arne Slungaard. (2007). Endogenous platelet factor 4 stimulates activated protein C generation in vivo and improves survival after thrombin or lipopolysaccharide challenge. Blood. 110(6). 1903–1905. 33 indexed citations
16.
Wang, Jianguo, Shawn A. Mahmud, Julia Nguyen, & Arne Slungaard. (2006). Thiocyanate-Dependent Induction of Endothelial Cell Adhesion Molecule Expression by Phagocyte Peroxidases: A Novel HOSCN-Specific Oxidant Mechanism to Amplify Inflammation. The Journal of Immunology. 177(12). 8714–8722. 54 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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