Naim Akhtar Khan

6.6k total citations · 1 hit paper
171 papers, 5.1k citations indexed

About

Naim Akhtar Khan is a scholar working on Nutrition and Dietetics, Molecular Biology and Sensory Systems. According to data from OpenAlex, Naim Akhtar Khan has authored 171 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Nutrition and Dietetics, 57 papers in Molecular Biology and 36 papers in Sensory Systems. Recurrent topics in Naim Akhtar Khan's work include Biochemical Analysis and Sensing Techniques (51 papers), Olfactory and Sensory Function Studies (28 papers) and Fatty Acid Research and Health (25 papers). Naim Akhtar Khan is often cited by papers focused on Biochemical Analysis and Sensing Techniques (51 papers), Olfactory and Sensory Function Studies (28 papers) and Fatty Acid Research and Health (25 papers). Naim Akhtar Khan collaborates with scholars based in France, Algeria and Benin. Naim Akhtar Khan's co-authors include Aziz Hichami, Philippe Besnard, Akadiri Yessoufou, Amira Sayed Khan, Kabirou Moutaïrou, Anne Denys, Patricia Passilly‐Degrace, Abdelhafid Nani, Zouhaïr Tabka and Oussama Grissa and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Physiological Reviews.

In The Last Decade

Naim Akhtar Khan

168 papers receiving 5.0k citations

Hit Papers

Antioxidant and Anti-Inflammatory Potential of Polyphenol... 2021 2026 2022 2024 2021 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Naim Akhtar Khan France 40 1.9k 1.3k 873 745 648 171 5.1k
Aziz Hichami France 36 1.1k 0.6× 1.2k 0.9× 401 0.5× 496 0.7× 544 0.8× 111 4.0k
Jennifer L. Pluznick United States 31 984 0.5× 2.6k 1.9× 760 0.9× 1.5k 2.1× 63 0.1× 79 4.2k
Anthony I. Mallet United Kingdom 31 478 0.2× 567 0.4× 185 0.2× 273 0.4× 470 0.7× 80 3.2k
Rina Yu South Korea 47 883 0.5× 2.4k 1.8× 513 0.6× 2.2k 3.0× 38 0.1× 138 6.9k
Shannon Reagan‐Shaw United States 21 576 0.3× 2.8k 2.1× 84 0.1× 934 1.3× 94 0.1× 21 7.0k
François Blachier France 39 864 0.4× 2.6k 2.0× 76 0.1× 1.3k 1.7× 74 0.1× 137 5.3k
Tatsuo Watanabe Japan 47 1.2k 0.6× 1.1k 0.8× 1.9k 2.2× 1.0k 1.3× 16 0.0× 190 6.6k
Süleyman Aydın Türkiye 38 879 0.5× 1.4k 1.1× 35 0.0× 2.4k 3.2× 436 0.7× 260 5.8k
Daniela Impellizzeri Italy 53 449 0.2× 2.1k 1.6× 86 0.1× 1.1k 1.5× 102 0.2× 215 7.4k
Sebastiano Banni Italy 44 2.8k 1.4× 1.7k 1.3× 148 0.2× 1.0k 1.4× 29 0.0× 120 6.3k

Countries citing papers authored by Naim Akhtar Khan

Since Specialization
Citations

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

Fields of papers citing papers by Naim Akhtar Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Naim Akhtar Khan. 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 Naim Akhtar Khan. The network helps show where Naim Akhtar Khan may publish in the future.

Co-authorship network of co-authors of Naim Akhtar Khan

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

All Works

20 of 20 papers shown
1.
Dergaa, Ismail, Halil İ̇brahim Ceylan, Wissem Dhahbi, et al.. (2025). Sweet and Fat Taste Perception: Impact on Dietary Intake in Diabetic Pregnant Women—A Cross-Sectional Observational Study. Nutrients. 17(15). 2515–2515. 1 indexed citations
2.
Koceir, Elhadj-Ahmed, et al.. (2025). Cardiometabolic Markers in Algerian Obese Subjects with and Without Type 2 Diabetes: Adipocytokine Imbalance as a Risk Factor. Journal of Clinical Medicine. 14(5). 1770–1770. 1 indexed citations
3.
Khan, Amira Sayed, Thomas Gautier, Semen Yesylevskyy, et al.. (2024). A novel fatty acid analogue triggers CD36–GPR120 interaction and exerts anti-inflammatory action in endotoxemia. Cellular and Molecular Life Sciences. 81(1). 176–176. 3 indexed citations
4.
Hichami, Aziz, et al.. (2023). In Vitro Functional Characterization of Type-I Taste Bud Cells as Monocytes/Macrophages-like Which Secrete Proinflammatory Cytokines. International Journal of Molecular Sciences. 24(12). 10325–10325. 3 indexed citations
5.
Hichami, Aziz, et al.. (2020). Spirulina reduces diet-induced obesity through downregulation of lipogenic genes expression in Psammomys obesus. Archives of Physiology and Biochemistry. 128(4). 1001–1009. 6 indexed citations
6.
Nani, Abdelhafid, Meriem Belarbi, Naim Akhtar Khan, & Aziz Hichami. (2020). Nutritional properties and plausible benefits of Pearl millet (Pennisetum glaucum) on bone metabolism and osteoimmunology : a mini-review. SHILAP Revista de lepidopterología. 4(8). 336–342. 1 indexed citations
7.
Nani, Abdelhafid, Meriem Belarbi, Naim Akhtar Khan, & Aziz Hichami. (2020). Nutritional properties and plausible benefits of Pearl millet (Pennisetum glaucum) on bone metabolism and osteoimmunology : a mini-review. 4(8). 336–342. 2 indexed citations
8.
Hichami, Aziz, et al.. (2020). CD36 and GPR120 Methylation Associates with Orosensory Detection Thresholds for Fat and Bitter in Algerian Young Obese Children. Journal of Clinical Medicine. 9(6). 1956–1956. 8 indexed citations
9.
Murtaza, Babar, Aziz Hichami, Amira Sayed Khan, et al.. (2019). Novel GPR120 agonist TUG891 modulates fat taste perception and preference and activates tongue-brain-gut axis in mice. Journal of Lipid Research. 61(2). 133–142. 22 indexed citations
11.
13.
Abdoul‐Azize, Souleymane, et al.. (2013). Ca2+ signaling in taste bud cells and spontaneous preference for fat: Unresolved roles of CD36 and GPR120. Biochimie. 96. 8–13. 51 indexed citations
14.
Hichami, Aziz, et al.. (2008). Linoleic Acid Induces Calcium Signaling, Src Kinase Phosphorylation, and Neurotransmitter Release in Mouse CD36-positive Gustatory Cells. Journal of Biological Chemistry. 283(19). 12949–12959. 155 indexed citations
16.
Khan, Naim Akhtar, Akadiri Yessoufou, Min Ji Kim, & Aziz Hichami. (2006). N-3 fatty acids modulate Th1 and Th2 dichotomy in diabetic pregnancy and macrosomia. Journal of Autoimmunity. 26(4). 268–277. 42 indexed citations
17.
Betoulle, Stéphane, Danielle Troutaud, Naim Akhtar Khan, & P. Deschaux. (1995). [Antibody response, cortisolemia and prolactinemia in rainbow trouts].. PubMed. 318(6). 677–81. 2 indexed citations
18.
Lucas, Josette, et al.. (1993). The effects of structural analogs of putrescine on proliferation, morphology and karyotype of glioblastoma cells in culture. Biology of the Cell. 77(2). 195–199. 6 indexed citations
19.
Khan, Naim Akhtar, et al.. (1990). Polyamine Binding Sites in the Rat Brain Hippocampus Plasma Membranes: MK 801 Does Not Influence the Binding Process. PubMed. 9(3). 163–169. 1 indexed citations
20.
Khan, Naim Akhtar, et al.. (1989). Characterization of Na+-dependent and system a-independent polyamine transport in normal human erythrocytes. Cell Differentiation and Development. 27. 44–44. 5 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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