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Comparative study on the extraction efficiency, characterization, and bioactivities of Bletilla striata polysaccharides using response surface methodology (RSM) and genetic algorithm-artificial neural network (GA-ANN).
- Source :
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International journal of biological macromolecules [Int J Biol Macromol] 2023 Jan 31; Vol. 226, pp. 982-995. Date of Electronic Publication: 2022 Dec 07. - Publication Year :
- 2023
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Abstract
- This research established the optimal conditions for alkali-assisted extraction (AAE) of bioactive polysaccharides from Bletilla striata integrated with response surface methodology (RSM) and the genetic algorithm-artificial neural networks (GA-ANN). In comparison with RSM, the ANN model showed a relatively higher determination coefficient in the global output values (RSM: ANN = 0.9270: 0.9742) performing more satisfactorily in the validation. Under the optimum conditions (52 °C; 167 min, and 0.01 mol/L NaOH), the extraction yields, IC <subscript>50</subscript> of ABTS, and FRAP value were 29.53 ± 0.97 %, 3.41 mg/mL, and 39.11 μmol Fe <superscript>2+</superscript> /g, respectively. The results indicated that BSPs-A was mainly composed of glucose and mannose with small amounts of arabinose, galactose, and galacturonic acid, while possessed a molecular weight of about 305.94 kDa (Mw). The structural characterization of BSPs-A was initially characterized by FT-IR, SEM, and Congo red tests, which indicated that BSPs-A possessed a triple helix conformation of typical Bletilla striata polysaccharides. In addition, BSPs-A exhibited excellent antioxidant activity, which was further confirmed by a series of in vitro antioxidant activity assays including DPPH, ABTS, FRAP, and ORAC. After incubation in the BSA-glucose system for 15 days, BSPs-A showed inhibition of the advanced glycation end products (AGEs) formation for the first time.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2022 Elsevier B.V. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1879-0003
- Volume :
- 226
- Database :
- MEDLINE
- Journal :
- International journal of biological macromolecules
- Publication Type :
- Academic Journal
- Accession number :
- 36495990
- Full Text :
- https://doi.org/10.1016/j.ijbiomac.2022.12.017