Christopher M. Walthers

747 total citations
17 papers, 481 citations indexed

About

Christopher M. Walthers is a scholar working on Biomaterials, Surgery and Biomedical Engineering. According to data from OpenAlex, Christopher M. Walthers has authored 17 papers receiving a total of 481 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Biomaterials, 6 papers in Surgery and 5 papers in Biomedical Engineering. Recurrent topics in Christopher M. Walthers's work include Electrospun Nanofibers in Biomedical Applications (6 papers), Tissue Engineering and Regenerative Medicine (4 papers) and Bone Tissue Engineering Materials (3 papers). Christopher M. Walthers is often cited by papers focused on Electrospun Nanofibers in Biomedical Applications (6 papers), Tissue Engineering and Regenerative Medicine (4 papers) and Bone Tissue Engineering Materials (3 papers). Christopher M. Walthers collaborates with scholars based in United States. Christopher M. Walthers's co-authors include Stephanie K. Seidlits, Benjamin M. Wu, Alireza Sohrabi, Jesse Liang, James Dunn, Alireza K. Nazemi, Nan Lei, Weikun Xiao, Arshia Ehsanipour and Soojung Hur and has published in prestigious journals such as Journal of Clinical Oncology, Blood and PLoS ONE.

In The Last Decade

Christopher M. Walthers

17 papers receiving 479 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher M. Walthers United States 12 236 152 144 84 82 17 481
Wai Hon Chooi Singapore 13 164 0.7× 135 0.9× 132 0.9× 177 2.1× 81 1.0× 24 510
Nikolaos Mitrousis Canada 8 247 1.0× 181 1.2× 122 0.8× 204 2.4× 180 2.2× 10 644
Jiajia Shi China 8 133 0.6× 155 1.0× 161 1.1× 100 1.2× 100 1.2× 23 517
Arshia Ehsanipour United States 10 190 0.8× 89 0.6× 61 0.4× 115 1.4× 119 1.5× 11 469
R. Chase Cornelison United States 8 152 0.6× 133 0.9× 94 0.7× 45 0.5× 98 1.2× 15 328
Karen Dubbin United States 12 388 1.6× 90 0.6× 79 0.5× 128 1.5× 88 1.1× 16 618
Priya N. Anandakumaran United States 7 182 0.8× 115 0.8× 129 0.9× 156 1.9× 169 2.1× 9 567
Ariel A. Szklanny Israel 9 288 1.2× 147 1.0× 153 1.1× 72 0.9× 62 0.8× 12 418
Uri Merdler Israel 7 277 1.2× 140 0.9× 150 1.0× 80 1.0× 71 0.9× 8 390
Erez Shor Israel 8 211 0.9× 158 1.0× 195 1.4× 111 1.3× 51 0.6× 13 397

Countries citing papers authored by Christopher M. Walthers

Since Specialization
Citations

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

Fields of papers citing papers by Christopher M. Walthers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher M. Walthers

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher M. Walthers. A scholar is included among the top collaborators of Christopher M. Walthers 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 Christopher M. Walthers. Christopher M. Walthers 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.
Larson, Sarah M., Christopher M. Walthers, Jacob Naparstek, et al.. (2022). CD19/CD20 bispecific chimeric antigen receptor (CAR) in naïve/memory T cells for the treatment of relapsed or refractory non-Hodgkin lymphoma.. Journal of Clinical Oncology. 40(16_suppl). 2543–2543. 6 indexed citations
2.
Walthers, Christopher M., Jacob Naparstek, Caitlin Harris, et al.. (2021). Abstract CT007: CD19/CD20 bispecific chimeric antigen receptor (CAR) in naive/memory T-cells for the treatment of relapsed or refractory B-cell lymphomas. Cancer Research. 81(13_Supplement). CT007–CT007. 2 indexed citations
3.
Walthers, Christopher M., Jacob Naparstek, Monica Mead, et al.. (2020). Phase I Dose-Escalation Trial of CD19/CD20 Bispecific Chimeric Antigen Receptor (CAR) T-Cells for the Treatment of Relapsed or Refractory B-Cell Lymphomas and Chronic Lymphocytic Leukemia. Blood. 136(Supplement 1). 19–20. 4 indexed citations
4.
Ehsanipour, Arshia, et al.. (2019). Injectable, Hyaluronic Acid-Based Scaffolds with Macroporous Architecture for Gene Delivery. Cellular and Molecular Bioengineering. 12(5). 399–413. 26 indexed citations
5.
Seidlits, Stephanie K., Jesse Liang, Alireza Sohrabi, et al.. (2019). Peptide‐modified, hyaluronic acid‐based hydrogels as a 3D culture platform for neural stem/progenitor cell engineering. Journal of Biomedical Materials Research Part A. 107(4). 704–718. 64 indexed citations
6.
Wang, Qianqian, Ke Wang, R. Sergio Solórzano-Vargas, et al.. (2018). Bioengineered intestinal muscularis complexes with long-term spontaneous and periodic contractions. PLoS ONE. 13(5). e0195315–e0195315. 14 indexed citations
7.
Xiao, Weikun, Rongyu Zhang, Alireza Sohrabi, et al.. (2017). Brain-Mimetic 3D Culture Platforms Allow Investigation of Cooperative Effects of Extracellular Matrix Features on Therapeutic Resistance in Glioblastoma. Cancer Research. 78(5). 1358–1370. 69 indexed citations
8.
Margul, Daniel J., Jonghyuck Park, Ryan M. Boehler, et al.. (2016). Reducing neuroinflammation by delivery of IL‐10 encoding lentivirus from multiple‐channel bridges. Bioengineering & Translational Medicine. 1(2). 136–148. 31 indexed citations
9.
Walthers, Christopher M., et al.. (2016). Collagen and heparan sulfate coatings differentially alter cell proliferation and attachmentin vitroandin vivo. PubMed. 4(3). 159–169. 1 indexed citations
10.
Walthers, Christopher M. & Stephanie K. Seidlits. (2015). Gene Delivery Strategies to Promote Spinal Cord Repair. Biomarker Insights. 10s1(Suppl 1). 11–29. 28 indexed citations
11.
Walthers, Christopher M., et al.. (2014). The effect of scaffold macroporosity on angiogenesis and cell survival in tissue-engineered smooth muscle. Biomaterials. 35(19). 5129–5137. 73 indexed citations
12.
Walthers, Christopher M., Min Lee, Benjamin M. Wu, & James Dunn. (2014). Smooth Muscle Strips for Intestinal Tissue Engineering. PLoS ONE. 9(12). e114850–e114850. 13 indexed citations
13.
Lee, Matthew, Adam S. DeConde, Min Lee, et al.. (2014). Biomimetic scaffolds facilitate healing of critical-sized segmental mandibular defects. American Journal of Otolaryngology. 36(1). 1–6. 26 indexed citations
14.
Wagner, Justin P., et al.. (2014). Function of mechanically lengthened jejunum after restoration into continuity. Journal of Pediatric Surgery. 49(6). 971–975. 16 indexed citations
15.
Lei, Nan, et al.. (2013). Macroporosity enhances vascularization of electrospun scaffolds. Journal of Surgical Research. 183(1). 18–26. 63 indexed citations
16.
Hur, Soojung, et al.. (2012). Label-Free Enrichment of Adrenal Cortical Progenitor Cells Using Inertial Microfluidics. PLoS ONE. 7(10). e46550–e46550. 44 indexed citations
17.
Ngai, Mae M., et al.. (2012). Injectable macroporous microparticles for soft tissue augmentation. 2428–2431. 1 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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