Susan M. Lessner

2.3k total citations
58 papers, 1.8k citations indexed

About

Susan M. Lessner is a scholar working on Surgery, Biomedical Engineering and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Susan M. Lessner has authored 58 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Surgery, 25 papers in Biomedical Engineering and 23 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Susan M. Lessner's work include Elasticity and Material Modeling (20 papers), Coronary Interventions and Diagnostics (16 papers) and Cerebrovascular and Carotid Artery Diseases (11 papers). Susan M. Lessner is often cited by papers focused on Elasticity and Material Modeling (20 papers), Coronary Interventions and Diagnostics (16 papers) and Cerebrovascular and Carotid Artery Diseases (11 papers). Susan M. Lessner collaborates with scholars based in United States, China and France. Susan M. Lessner's co-authors include Zorina S. Galis, Michael A. Sutton, Chad Johnson, Hak‐Joon Sung, X. Ke, Edmund K. Waller, Richard Magid, M. Elizabeth Fini, Jaikirshan Khatri and Ha Won Kim and has published in prestigious journals such as Journal of Biological Chemistry, Circulation and PLoS ONE.

In The Last Decade

Susan M. Lessner

55 papers receiving 1.8k citations

Peers

Susan M. Lessner

SURGE

PRM

IMMUN

Zhigang Wang China

Marcelo E. Andía Chile

Changyong Li China

Tong Tong China

Yuan Chang China

Xi Lin China

Kenichi Hakamada Japan

Bo Chen China

S. David Gertz Israel

Kaoru Tanaka Japan

Zhigang Wang China

Susan M. Lessner

840 ×1.7

324 ×0.7

SURGE

837 ×2.2

PRM

181 ×0.5

155 ×0.6

IMMUN

Citations per year, relative to Susan M. Lessner Susan M. Lessner (= 1×) peers Zhigang Wang

Countries citing papers authored by Susan M. Lessner

Since Specialization

Citations

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

Fields of papers citing papers by Susan M. Lessner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Susan M. Lessner

This figure shows the co-authorship network connecting the top 25 collaborators of Susan M. Lessner. A scholar is included among the top collaborators of Susan M. Lessner 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 Susan M. Lessner. Susan M. Lessner 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

Çetįn, Metin, Özge Saatci, Abdol-Hossein Rezaeian, et al.. (2024). A highly potent bi-thiazole inhibitor of LOX rewires collagen architecture and enhances chemoresponse in triple-negative breast cancer. Cell chemical biology. 31(11). 1926–1941.e11. 10 indexed citations

Clair, Daniel G., et al.. (2023). Automated Measurement of Vascular Calcification in Femoral Endarterectomy Patients Using Deep Learning. Diagnostics. 13(21). 3363–3363. 7 indexed citations

Smith, Andrew, et al.. (2023). TransONet: Automatic Segmentation of Vasculature in Computed Tomographic Angiograms Using Deep Learning. 1312–1317.

Lessner, Susan M., et al.. (2023). Full-field strain mapping of healthy and pathological mouse aortas using stereo digital image correlation. Journal of the mechanical behavior of biomedical materials. 141. 105745–105745. 3 indexed citations

Saaoud, Fatma, Junfeng Wang, Stephen Iwanowycz, et al.. (2020). Bone marrow deficiency of mRNA decaying protein Tristetraprolin increases inflammation and mitochondrial ROS but reduces hepatic lipoprotein production in LDLR knockout mice. Redox Biology. 37. 101609–101609. 16 indexed citations

Li, Yong, Wei Sun, Fatma Saaoud, et al.. (2020). MiR155 modulates vascular calcification by regulating Akt‐FOXO3a signalling and apoptosis in vascular smooth muscle cells. Journal of Cellular and Molecular Medicine. 25(1). 535–548. 21 indexed citations

Wang, Xiaoying, et al.. (2020). Targeted Gold Nanoparticles as an Indicator of Mechanical Damage in an Elastase Model of Aortic Aneurysm. Annals of Biomedical Engineering. 48(8). 2268–2278. 13 indexed citations

Mohamed, Mohamed A., et al.. (2018). Comparative mechanics of diverse mammalian carotid arteries. PLoS ONE. 13(8). e0202123–e0202123. 26 indexed citations

Leng, Xiaochang, Boran Zhou, Xiaomin Deng, et al.. (2018). Determination of Viscoelastic Properties of human Carotid Atherosclerotic Plaque by Inverse Boundary Value Analysis. IOP Conference Series Materials Science and Engineering. 381. 12171–12171. 5 indexed citations

10.

He, Hui, Fang Guo, Yong Li, et al.. (2016). Adiporedoxin suppresses endothelial activation via inhibiting MAPK and NF-κB signaling. Scientific Reports. 6(1). 38975–38975. 17 indexed citations

11.

Sinha, Aditi, Nasim Nosoudi, Lei Yang, et al.. (2014). Nanoparticle targeting to diseased vasculature for imaging and therapy. Nanomedicine Nanotechnology Biology and Medicine. 10(5). e1003–e1012. 46 indexed citations

12.

Badel, Pierre, Stéphane Avril, Michael A. Sutton, & Susan M. Lessner. (2014). Numerical simulation of arterial dissection during balloon angioplasty of atherosclerotic coronary arteries. Journal of Biomechanics. 47(4). 878–889. 30 indexed citations

13.

Avril, Stéphane, et al.. (2013). Biomechanics of Porcine Renal Arteries and Role of Axial Stretch. Journal of Biomechanical Engineering. 135(8). 81007–81007. 22 indexed citations

14.

Wang, Ying, J. A. Johnson, Francis G. Spinale, Michael A. Sutton, & Susan M. Lessner. (2013). Quantitative Measurement of Dissection Resistance in Intimal and Medial Layers of Human Coronary Arteries. Experimental Mechanics. 54(4). 677–683. 21 indexed citations

15.

Liang, Qiaoli, et al.. (2013). Sparstolonin B Inhibits Pro-Angiogenic Functions and Blocks Cell Cycle Progression in Endothelial Cells. PLoS ONE. 8(8). e70500–e70500. 27 indexed citations

16.

Braxton, Vaughn G., et al.. (2010). Speckle Patterning of Soft Tissues for Strain Field Measurement Using Digital Image Correlation: Preliminary Quality Assessment of Patterns. Microscopy and Microanalysis. 17(1). 81–90. 18 indexed citations

17.

Fann, Stephen A., et al.. (2009). Focused In Vivo Genetic Analysis of Implanted Engineered Myofascial Constructs. Journal of Investigative Surgery. 22(1). 35–45. 7 indexed citations

18.

Itoh, Shinichi, Ha Won Kim, Osamu Nakagawa, et al.. (2008). Novel Role of Antioxidant-1 (Atox1) as a Copper-dependent Transcription Factor Involved in Cell Proliferation. Journal of Biological Chemistry. 283(14). 9157–9167. 254 indexed citations

19.

Sutton, Michael A., et al.. (2007). Strain field measurements on mouse carotid arteries using microscopic three‐dimensional digital image correlation. Journal of Biomedical Materials Research Part A. 84A(1). 178–190. 115 indexed citations

20.

Lessner, Susan M., et al.. (2002). Atherosclerotic Lesions Grow Through Recruitment and Proliferation of Circulating Monocytes in a Murine Model. American Journal Of Pathology. 160(6). 2145–2155. 136 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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