Evidence map›Paper›PMID 39468527›Full record

ArticleBMC biotechnology2024

Biological activities of Hypericum spectabile extract optimized using artificial neural network combined with genetic algorithm application.

Ayşenur Gürgen, Mustafa Sevindik, Tetiana Krupodorova, Imran Uysal, Orhan Unal

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Article in BMC biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

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12citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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  5. Betulinic Acid-EnrichedAntioxidants (Basel, Switzerland) · 2025
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ayşenur GürgenDepartment of Industrial Engineering, Faculty of Engineering and Natural Sciences, Osmaniye Korkut Ata University, Osmaniye, 80000, Turkey.
Mustafa SevindikDepartment of Biology, Faculty of Engineering and Natural Sciences, Osmaniye Korkut Ata University, Osmaniye, 8000, Turkey.
Tetiana KrupodorovaDepartment of Plant Food Products and Biofortification, Institute of Food Biotechnology and Genomics, National Academy of Sciences of Ukraine, Kyiv, 04123, Ukraine. krupodorova@gmail.com.
Imran UysalDepartment of Food Processing, Bahçe Vocational School, Osmaniye Korkut Ata University, Osmaniye, 80000, Turkey.
Orhan UnalDepartment of Biology, Faculty of Science, Akdeniz University, Antalya, 07058, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optimizing extraction conditions can help maximize the efficiency and yield of the extraction process while minimizing negative impacts on the environment and human health. For the purpose of the current study, an artificial neural network (ANN) combined with a genetic algorithm (GA) was utilized for that the extraction conditions of Hypericum spectabile were optimized. In this particular investigation, the main objective was to get the highest possible levels of total antioxidant status (TAS) for the extracts that were obtained. In addition to this, conditions of the extract that exhibited the maximum activity have been determined and the biological activity of the extract that was obtained under these conditions was analyzed. TAS values were obtained from extracts obtained using extraction temperatures of 30-60 °C, extraction times of 4-10 h, and extract concentrations of 0.25-2 mg/mL. The best model selected from the established ANN models had a mean absolute percentage error (MAPE) value of 0.643%, a mean squared error (MSE) value of 0.004, and a correlation coefficient (R) value of 0.996, respectively. The genetic algorithm proposed optimal extraction conditions of an extraction temperature of 59.391 °C, an extraction time of 8.841 h, and an extraction concentration of 1.951 mg/mL. It was concluded that the integration of ANN-GA can successfully be used to optimize extraction parameters of Hypericum spectabile. The total antioxidant value of the extract obtained under optimum conditions was determined as 9.306 ± 0.080 mmol/L, total oxidant value as 13.065 ± 0.112 µmol/L, oxidative stress index as 0.140 ± 0.001. Total phenolic content (TPC) was 109.34 ± 1.29 mg/g, total flavonoid content (TFC) was measured as 148.34 ± 1.48 mg/g. Anti-AChE value was determined as 30.68 ± 0.77 µg/mL, anti-BChE value was determined as 41.30 ± 0.48 µg/mL. It was also observed that the extract exhibited strong antiproliferative activities depending on the increase in concentration. As a result of LC-MS/MS analysis of the extract produced under optimum conditions in terms of phenolic content. The presence of fumaric, gallic, protocatechuic, 4-hydroxybenzoic, caffeic, 2-hydoxycinamic acids, quercetin and kaempferol was detected. As a result, it was determined that the H. spectabile extract produced under optimum conditions had significant effects in terms of biological activity.

Indexed as

AlgorithmsAntioxidantsHypericumNeural Networks, ComputerPlant ExtractsHumansAntioxidantsPlant ExtractsExtraction conditionsGenetic algorithmHypericum spectabileOptimization

Identifiers

PMID39468527
PMCPMC11520853

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