Artificial intelligence-assisted optimization of extraction enhances the biological activity of Phylloporia ribis
SCIENTIFIC REPORTS, cilt.15, sa. 41206, ss.1-28, 2025 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 15 Sayı: 41206
- Basım Tarihi: 2025
- Dergi Adı: SCIENTIFIC REPORTS
- Derginin Tarandığı İndeksler: Scopus, Science Citation Index Expanded (SCI-EXPANDED), BIOSIS, Chemical Abstracts Core, MEDLINE, Directory of Open Access Journals
- Sayfa Sayıları: ss.1-28
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Ankara Üniversitesi Adresli: Evet
Özet
This research focuses on
enhancing the extraction efficiency of Phylloporia ribis and assessing
its biological functions. Key parameters including extraction temperature,
duration, and ethanol-to-water ratio were optimized through both Response
Surface Methodology (RSM) and an integrated Artificial Neural Network–Genetic
Algorithm (ANN-GA) approach. The extracts obtained via ANN-GA exhibited greater
antioxidant activity and higher concentrations of phenolic constituents such as
gallic acid, quercetin, and vanillic acid. Compared to RSM-optimized samples,
ANN-GA extracts demonstrated superior free radical scavenging, stronger ferric
reducing power, and a more potent dose-dependent inhibition of cell
proliferation. In addition, P. ribis extracts showed enzyme-inhibitory
properties against acetylcholinesterase and butyrylcholinesterase, suggesting
their potential utility in pharmaceutical and biotechnological applications.
The ANN-GA method appears to be a promising tool for maximizing both the yield
of phenolic compounds and the biological efficacy of extracts. Further advanced
biotechnological optimization studies are advised to unlock the full
therapeutic potential of P. ribis.