Ikram Mezghani

879 total citations · 2 hit papers
10 papers, 616 citations indexed

About

Ikram Mezghani is a scholar working on Rehabilitation, Endocrinology, Diabetes and Metabolism and Molecular Biology. According to data from OpenAlex, Ikram Mezghani has authored 10 papers receiving a total of 616 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Rehabilitation, 6 papers in Endocrinology, Diabetes and Metabolism and 2 papers in Molecular Biology. Recurrent topics in Ikram Mezghani's work include Wound Healing and Treatments (9 papers), Diabetic Foot Ulcer Assessment and Management (6 papers) and Mesenchymal stem cell research (2 papers). Ikram Mezghani is often cited by papers focused on Wound Healing and Treatments (9 papers), Diabetic Foot Ulcer Assessment and Management (6 papers) and Mesenchymal stem cell research (2 papers). Ikram Mezghani collaborates with scholars based in United States, United Kingdom and China. Ikram Mezghani's co-authors include Aristidis Veves, Georgios Theocharidis, Antonios Kafanas, Ioannis S. Vlachos, Brandon J. Sumpio, Zhuqing Li, Peng Wang, Teresa Sandoval-Schaefer, Valerie Horsley and Henry C. Hsia and has published in prestigious journals such as Nature Communications, Scientific Reports and Journal of Clinical Microbiology.

In The Last Decade

Ikram Mezghani

10 papers receiving 609 citations

Hit Papers

Single cell transcriptomic landscape of diabetic foot ulcers 2022 2026 2023 2024 2022 2022 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ikram Mezghani United States 6 350 163 131 128 113 10 616
Maryam Sharifiaghdam Iran 10 295 0.8× 88 0.5× 175 1.3× 181 1.4× 143 1.3× 11 621
Reza Faridi‐Majidi Iran 9 289 0.8× 87 0.5× 164 1.3× 208 1.6× 142 1.3× 15 626
Zoe West Australia 5 432 1.2× 87 0.5× 150 1.1× 163 1.3× 75 0.7× 7 809
Mali Dai China 13 349 1.0× 69 0.4× 287 2.2× 142 1.1× 207 1.8× 34 1.0k
Stephan Hager Germany 5 622 1.8× 79 0.5× 240 1.8× 145 1.1× 116 1.0× 6 988
Kamila Raziyeva Kazakhstan 8 443 1.3× 92 0.6× 347 2.6× 223 1.7× 191 1.7× 9 1.1k
Xinjing Lv China 6 424 1.2× 103 0.6× 309 2.4× 117 0.9× 278 2.5× 8 793
Guandong Dai China 8 226 0.6× 53 0.3× 131 1.0× 98 0.8× 195 1.7× 10 535
Elaine J. Lin United States 4 269 0.8× 47 0.3× 119 0.9× 96 0.8× 50 0.4× 5 470
Xiaorong Zhang China 19 380 1.1× 48 0.3× 164 1.3× 214 1.7× 140 1.2× 54 995

Countries citing papers authored by Ikram Mezghani

Since Specialization
Citations

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

Fields of papers citing papers by Ikram Mezghani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ikram Mezghani. 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 Ikram Mezghani. The network helps show where Ikram Mezghani may publish in the future.

Co-authorship network of co-authors of Ikram Mezghani

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

All Works

10 of 10 papers shown
1.
Sumpio, Brandon J., Kyongmin Yeo, Georgios Theocharidis, et al.. (2025). Integrated machine learning analysis of proteomic and transcriptomic data identifies healing associated targets in diabetic wound repair. Scientific Reports. 15(1). 34355–34355. 1 indexed citations
2.
Sumpio, Brandon J., Anne Dallas, Adam G. Berger, et al.. (2024). Use of Therapeutic RNAs to Accelerate Wound Healing in Diabetic Rabbit Wounds. Advances in Wound Care. 13(9). 435–445. 5 indexed citations
3.
Theocharidis, Georgios, Brandon J. Sumpio, Ikram Mezghani, et al.. (2024). Use of Serum Protein Measurements as Biomarkers that Can Predict the Outcome of Diabetic Foot Ulceration. Advances in Wound Care. 13(9). 426–434. 3 indexed citations
4.
Sumpio, Brandon J., et al.. (2023). Experimental treatments in clinical trials for diabetic foot ulcers: wound healers in the pipeline. Expert Opinion on Investigational Drugs. 32(2). 95–99. 8 indexed citations
5.
Mezghani, Ikram, Georgios Theocharidis, Brandon J. Sumpio, et al.. (2023). Contrast-Free High Frame Rate Ultrasound Imaging for Assessment of Vascular Remodeling During Wound Healing. IRBM. 45(1). 100818–100818. 1 indexed citations
6.
Theocharidis, Georgios, Beena Thomas, Debasree Sarkar, et al.. (2022). Single cell transcriptomic landscape of diabetic foot ulcers. Nature Communications. 13(1). 181–181. 251 indexed citations breakdown →
7.
Theocharidis, Georgios, Hyunwoo Yuk, Heejung Roh, et al.. (2022). A strain-programmed patch for the healing of diabetic wounds. Nature Biomedical Engineering. 6(10). 1118–1133. 246 indexed citations breakdown →
8.
Sumpio, Brandon J., et al.. (2022). Future Directions in Research in Transcriptomics in the Healing of Diabetic Foot Ulcers. Advances in Therapy. 40(1). 67–75. 4 indexed citations
9.
Dong, Jie, Lihong Chen, Ying Zhang, et al.. (2020). Mast Cells in Diabetes and Diabetic Wound Healing. Advances in Therapy. 37(11). 4519–4537. 74 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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