Kendra J. Lechtenberg

599 total citations
8 papers, 173 citations indexed

About

Kendra J. Lechtenberg is a scholar working on Neurology, Immunology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Kendra J. Lechtenberg has authored 8 papers receiving a total of 173 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Neurology, 4 papers in Immunology and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Kendra J. Lechtenberg's work include Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Immunotherapy and Immune Responses (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). Kendra J. Lechtenberg is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Immunotherapy and Immune Responses (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). Kendra J. Lechtenberg collaborates with scholars based in United States, France and Canada. Kendra J. Lechtenberg's co-authors include Marion S. Buckwalter, Todd C. Peterson, Michelle L. James, Haley C. Cropper, Marc Y. Stevens, Emily M. Johnson, Aisling M. Chaney, Donna M. Bouley, Kim Butts Pauly and Jarrett Rosenberg and has published in prestigious journals such as Glia, Journal of Nuclear Medicine and Journal of Neuroinflammation.

In The Last Decade

Kendra J. Lechtenberg

7 papers receiving 171 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kendra J. Lechtenberg United States 7 79 44 34 29 22 8 173
Haley C. Cropper United States 7 37 0.5× 39 0.9× 21 0.6× 22 0.8× 21 1.0× 12 145
Joe Guadagno United Kingdom 4 121 1.5× 57 1.3× 20 0.6× 28 1.0× 41 1.9× 4 205
Vanessa O. Torres United States 8 146 1.8× 49 1.1× 99 2.9× 10 0.3× 24 1.1× 16 282
Ulrike Köck Austria 6 68 0.9× 42 1.0× 26 0.8× 75 2.6× 32 1.5× 7 254
Nicolas Lonjon France 9 75 0.9× 42 1.0× 33 1.0× 19 0.7× 89 4.0× 15 267
Rajasekaran Mahalingam United States 10 20 0.3× 83 1.9× 21 0.6× 9 0.3× 13 0.6× 18 212
Gayathri Devarajan United Kingdom 5 93 1.2× 125 2.8× 64 1.9× 60 2.1× 12 0.5× 9 301
Franziska Bachhuber Germany 5 31 0.4× 63 1.4× 11 0.3× 36 1.2× 57 2.6× 13 278
Fanny Béguier France 6 59 0.7× 91 2.1× 31 0.9× 31 1.1× 15 0.7× 6 203
Min Ji China 9 35 0.4× 145 3.3× 17 0.5× 36 1.2× 30 1.4× 45 281

Countries citing papers authored by Kendra J. Lechtenberg

Since Specialization
Citations

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

Fields of papers citing papers by Kendra J. Lechtenberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kendra J. Lechtenberg

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

All Works

8 of 8 papers shown
1.
Eng, Lawson, William K. Evans, Katherine K. Nishimura, et al.. (2025). The International Association for the Study of Lung Cancer Staging Project: The Impact of Smoking Status on Lung Cancer Staging in the Ninth Edition of the TNM Classification. Journal of Thoracic Oncology. 20(10). 1441–1458.
3.
Li, Ningrui, Kendra J. Lechtenberg, Jarrett Rosenberg, et al.. (2020). Histologic evaluation of activation of acute inflammatory response in a mouse model following ultrasound-mediated blood-brain barrier using different acoustic pressures and microbubble doses. Nanotheranostics. 4(4). 210–223. 21 indexed citations
4.
Peterson, Todd C., Kendra J. Lechtenberg, Brian Piening, et al.. (2020). Obesity Drives Delayed Infarct Expansion, Inflammation, and Distinct Gene Networks in a Mouse Stroke Model. Translational Stroke Research. 12(2). 331–346. 10 indexed citations
5.
Stevens, Marc Y., Haley C. Cropper, Aisling M. Chaney, et al.. (2020). Development of a CD19 PET tracer for detecting B cells in a mouse model of multiple sclerosis. Journal of Neuroinflammation. 17(1). 275–275. 12 indexed citations
6.
Lechtenberg, Kendra J., et al.. (2019). Augmented β2-adrenergic signaling dampens the neuroinflammatory response following ischemic stroke and increases stroke size. Journal of Neuroinflammation. 16(1). 112–112. 40 indexed citations
7.
Chaney, Aisling M., Haley C. Cropper, Emily M. Johnson, et al.. (2018). 11C-DPA-713 Versus 18F-GE-180: A Preclinical Comparison of Translocator Protein 18 kDa PET Tracers to Visualize Acute and Chronic Neuroinflammation in a Mouse Model of Ischemic Stroke. Journal of Nuclear Medicine. 60(1). 122–128. 41 indexed citations
8.
James, Michelle L., Aileen Hoehne, Aaron T. Mayer, et al.. (2017). Imaging B Cells in a Mouse Model of Multiple Sclerosis Using 64Cu-Rituximab PET. Journal of Nuclear Medicine. 58(11). 1845–1851. 24 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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