Hillarie Plessner Windish

1.6k total citations
15 papers, 1.2k citations indexed

About

Hillarie Plessner Windish is a scholar working on Immunology, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Hillarie Plessner Windish has authored 15 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Immunology, 5 papers in Molecular Biology and 4 papers in Infectious Diseases. Recurrent topics in Hillarie Plessner Windish's work include Immune Response and Inflammation (5 papers), Tuberculosis Research and Epidemiology (4 papers) and Muscle Physiology and Disorders (4 papers). Hillarie Plessner Windish is often cited by papers focused on Immune Response and Inflammation (5 papers), Tuberculosis Research and Epidemiology (4 papers) and Muscle Physiology and Disorders (4 papers). Hillarie Plessner Windish collaborates with scholars based in United States, Switzerland and Canada. Hillarie Plessner Windish's co-authors include Steven G. Reed, Malcolm S. Duthie, Christopher B. Fox, Rhea N. Coler, Susan L. Baldwin, Sylvie Bertholet, Thomas S. Vedvick, Maria Kahn, Samuel Pine and Magdalini Moutaftsi and has published in prestigious journals such as PLoS ONE, The Journal of Infectious Diseases and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Hillarie Plessner Windish

14 papers receiving 1.2k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Hillarie Plessner Windish 782 475 409 363 88 15 1.2k
Marta Sánchez‐Hernández 1.1k 1.4× 373 0.8× 318 0.8× 341 0.9× 103 1.2× 9 1.6k
Estella A. Koppel 834 1.1× 380 0.8× 341 0.8× 243 0.7× 66 0.8× 8 1.2k
Karen Lingnau 1.3k 1.6× 583 1.2× 499 1.2× 480 1.3× 114 1.3× 34 1.9k
David A. Hokey 1.0k 1.3× 665 1.4× 407 1.0× 428 1.2× 42 0.5× 44 1.5k
Teena Mohan 431 0.6× 227 0.5× 361 0.9× 321 0.9× 65 0.7× 26 954
Simona Tavarini 1.2k 1.6× 316 0.7× 507 1.2× 398 1.1× 117 1.3× 38 1.8k
Prabhu S. Arunachalam 585 0.7× 294 0.6× 204 0.5× 365 1.0× 48 0.5× 9 997
Rajko Reljić 952 1.2× 879 1.9× 525 1.3× 480 1.3× 59 0.7× 67 1.8k
Pablo D. Becker 811 1.0× 160 0.3× 387 0.9× 419 1.2× 144 1.6× 51 1.6k
Rolf Billeskov 882 1.1× 897 1.9× 526 1.3× 374 1.0× 25 0.3× 22 1.4k

Countries citing papers authored by Hillarie Plessner Windish

Since Specialization
Citations

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

Fields of papers citing papers by Hillarie Plessner Windish

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hillarie Plessner Windish. 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 Hillarie Plessner Windish. The network helps show where Hillarie Plessner Windish may publish in the future.

Co-authorship network of co-authors of Hillarie Plessner Windish

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

All Works

15 of 15 papers shown
1.
Johnson, Melissa L., Mark M. Awad, Martin Gutierrez, et al.. (2023). OA05.05 Ifinatamab Deruxtecan (I-DXd; DS-7300) in Patients with Refractory SCLC: A Subgroup Analysis of a Phase 1/2 Study. Journal of Thoracic Oncology. 18(11). S54–S55. 23 indexed citations
2.
Ling, Xiaoxi, Joseph D. Latoche, Cindy J. Choy, et al.. (2019). Preclinical Dosimetry, Imaging, and Targeted Radionuclide Therapy Studies of Lu-177-Labeled Albumin-Binding, PSMA-Targeted CTT1403. Molecular Imaging and Biology. 22(2). 274–284. 25 indexed citations
3.
Gumerson, Jessica, Kimmo Lehtimäki, Jukka Puoliväli, et al.. (2017). Effect of Ibuprofen on Skeletal Muscle of Dysferlin-Null Mice. Journal of Pharmacology and Experimental Therapeutics. 364(3). 409–419. 3 indexed citations
4.
Potter, Rachael A., Danielle A. Griffin, R.W. Johnson, et al.. (2017). Systemic Delivery of Dysferlin Overlap Vectors Provides Long-Term Gene Expression and Functional Improvement for Dysferlinopathy. Human Gene Therapy. 29(7). 749–762. 41 indexed citations
5.
Nonneman, Randal J., Natallia V. Riddick, Sheryl S. Moy, et al.. (2017). Hip region muscular dystrophy and emergence of motor deficits in dysferlin‐deficient Bla/J mice. Physiological Reports. 5(6). 21 indexed citations
6.
Orr, Mark T., Hillarie Plessner Windish, Elyse A. Beebe, et al.. (2015). Interferon γ and Tumor Necrosis Factor Are Not Essential Parameters of CD4+T-Cell Responses for Vaccine Control of Tuberculosis. The Journal of Infectious Diseases. 212(3). 495–504. 25 indexed citations
7.
Albrecht, Douglas E., Laura Rufibach, Bradley A. Williams, et al.. (2013). 6th Dysferlin Conference, 3–6 April 2013, Arlington, Virginia, USA. Neuromuscular Disorders. 24(3). 277–287.
8.
Orr, Mark T., Malcolm S. Duthie, Hillarie Plessner Windish, et al.. (2013). MyD88 and TRIF synergistic interaction is required for TH1‐cell polarization with a synthetic TLR4 agonist adjuvant. European Journal of Immunology. 43(9). 2398–2408. 68 indexed citations
9.
Coler, Rhea N., Sylvie Bertholet, Samuel Pine, et al.. (2012). Therapeutic Immunization against Mycobacterium tuberculosis Is an Effective Adjunct to Antibiotic Treatment. The Journal of Infectious Diseases. 207(8). 1242–1252. 81 indexed citations
10.
Arias, Mauricio A., John S. Tregoning, Magdalini Moutaftsi, et al.. (2012). Glucopyranosyl Lipid Adjuvant (GLA), a Synthetic TLR4 Agonist, Promotes Potent Systemic and Mucosal Responses to Intranasal Immunization with HIVgp140. PLoS ONE. 7(7). e41144–e41144. 80 indexed citations
11.
Windish, Hillarie Plessner, Malcolm S. Duthie, Greg C. Ireton, et al.. (2011). Protection of mice from Mycobacterium tuberculosis by ID87/GLA-SE, a novel tuberculosis subunit vaccine candidate. Vaccine. 29(44). 7842–7848. 33 indexed citations
12.
Coler, Rhea N., Sylvie Bertholet, Magdalini Moutaftsi, et al.. (2011). Development and Characterization of Synthetic Glucopyranosyl Lipid Adjuvant System as a Vaccine Adjuvant. PLoS ONE. 6(1). e16333–e16333. 250 indexed citations
13.
Duthie, Malcolm S., Hillarie Plessner Windish, Christopher B. Fox, & Steven G. Reed. (2010). Use of defined TLR ligands as adjuvants within human vaccines. Immunological Reviews. 239(1). 178–196. 334 indexed citations
14.
Bertholet, Sylvie, Gregory C. Ireton, Diane Ordway, et al.. (2010). A Defined Tuberculosis Vaccine Candidate Boosts BCG and Protects Against Multidrug-Resistant Mycobacterium tuberculosis. Science Translational Medicine. 2(53). 53ra74–53ra74. 247 indexed citations
15.
Windish, Hillarie Plessner, Philana Ling Lin, Joshua T. Mattila, et al.. (2009). Aberrant TGF-β signaling reduces T regulatory cells in ICAM-1-deficient mice, increasing the inflammatory response to Mycobacterium tuberculosis. Journal of Leukocyte Biology. 86(3). 713–725. 14 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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