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Natural Product Research
Formerly Natural Product Letters
Volume 35, 2021 - Issue 24
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Natural products in diabetes research: quantitative literature analysis

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Pages 5813-5827 | Received 03 Jun 2020, Accepted 28 Aug 2020, Published online: 07 Oct 2020
 

Abstract

The current study aimed to identify which natural products and which research directions are related to the major contributors to academic journals for diabetes therapy. Bibliometric data were extracted from the Web of Science online database using the search string TOPIC = (‘‘natural product*’ OR ‘‘natural compound*’ OR ‘‘natural molecule*’ OR ‘phytochemical*’ OR ‘‘secondary metabolite*’) AND TS = (‘diabet*’) and analysed by a bibliometric software, VOSviewer. The search yielded 3694 publications, which were collectively cited 80,791 times, with an H-index of 117 and 21.9 citations per publication on average. The top-contributing countries were India, the USA, China, South Korea and Brazil. Curcumin, flavanone, resveratrol, carotenoid, polyphenols, flavonol, flavone and berberine were the most frequently cited natural products or compound classes. Our results provide a brief overview of the major directions of natural product research in diabetes up to now and hint on promising avenues for future research.

Graphical Abstract

Disclosure statement

No potential conflict of interes must be reported by the authors.

Additional information

Funding

Atanas G. Atanasov acknowledges the support of the Polish KNOW (Leading National Research Centre) Scientific Consortium ‘Healthy Animal – Safe Food’, decision of the Ministry of Science and Higher Education No. 05-1/KNOW2/2015. Dongdong Wang acknowledges the Cultivation project for clinical medicine of the integrated traditional Chinese and western medicine and Cultivation project for education team of internal medicine of the integrated traditional Chinese and western medicine in the first-term subjects with special support in the first-class universities in Guizhou province (Qin Jiao Gao Fa No. 2017-158). Javier Echeverría gratefully acknowledges funding from CONICYT (PAI/ACADEMIA No. 79160109).

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