Evidence map›Paper›PMID 41372461›Full record

ArticleScientific reports2025

Determination of optimum extraction conditions and evaluation of biological activities of Prunus Armeniaca L. (Apricot) fruit.

Nazan Çömlekçioğlu, Mustafa Sevindik, Ayşenur Gürgen, Emre Sevindik, İmran Uysal, Oguzhan Koçer

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Nazan ÇömlekçioğluDepartment of Biology, Faculty of Science, Kahramanmaras Sutcu Imam University, Kahramanmaras, 46050, Turkey.
Mustafa SevindikDepartment of Biology, Faculty of Engineering and Natural Sciences, Osmaniye Korkut Ata University, Osmaniye, 80000, Türkiye, Turkey. sevindik27@gmail.com.
Ayşenur GürgenDepartment of Industrial Engineering, Faculty of Engineering and Natural Sciences, Osmaniye Korkut Ata University, Osmaniye, 80000, Türkiye, Turkey.
Emre SevindikDepartment of Agricultural Biotechnology, Faculty of Agriculture, Aydın Adnan Menderes University, Aydın, Türkiye, Turkey.
İmran UysalDepartment of Food Processing, Bahçe Vocational School, Osmaniye Korkut Ata University, Osmaniye, 80000, Türkiye, Turkey.
Oguzhan KoçerDepartment of Pharmacy Services, Vocational School of Health Services, Osmaniye Korkut Ata University, Osmaniye, 80500, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, optimization and biological activities of biologically active components obtained from Prunus armeniaca L. (apricot) fruit were investigated. Within the scope of the study, optimum extraction conditions were determined by using different extraction parameters (temperature, time and ethanol/water ratio) and the most suitable extracts were produced in terms of biological activity. Response Surface Method (RSM) and Artificial Neural Networks-GENetic Algorithms (ANN-GA) techniques were applied for extraction optimization. Antioxidant, antiproliferative and anticholinesterase activities of the extracts obtained under optimum conditions were evaluated. In antioxidant activity tests, it was observed that the extracts optimized by ANN-GA method presented higher values ​​in terms of total antioxidant status (TAS) and DPPH free radical scavenging activity. Likewise, it was determined that total phenolic and flavonoid contents of the extracts obtained by ANN-GA method were higher compared to the extracts obtained by RSM method. In antiproliferative activity tests, cytotoxic effects of optimized extracts on A549 lung cancer cell line were investigated and it was seen that they suppressed cell viability in a dose-dependent manner. It was found that extracts optimized by ANN-GA method showed stronger antiproliferative effect than extracts obtained by RSM method at certain concentrations. In anticholinesterase activity analyses, it was determined that extracts optimized by ANN-GA method had higher potential to inhibit acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes than extracts obtained by RSM method. However, when compared to galantamine used as reference inhibitor, it was found that the inhibitory effect of the obtained extracts was lower. As a result of phenolic component analysis, it was seen that extracts optimized by ANN-GA method had higher concentrations of phenolic components such as kaempferol, fumaric acid, gallic acid, caffeic acid and naringenin. However, it was found that some compounds (e.g. resveratrol and salicylic acid) were extracted at higher rates with the RSM method. In conclusion, the ANN-GA method increases the extraction efficiency of biologically active components of P. armeniaca fruit, strengthening their antioxidant, antiproliferative and anticholinesterase activities. These findings indicate that AI-supported extraction methods have the potential to be used in functional food and pharmaceutical applications.

Indexed as

AntioxidantsFruitPlant ExtractsPrunus armeniacaA549 CellsAntineoplastic Agents, PhytogenicCell Line, TumorCell ProliferationCell SurvivalCholinesterase InhibitorsFlavonoidsHumansNeural Networks, ComputerPhenolsAntineoplastic Agents, PhytogenicAntioxidantsCholinesterase InhibitorsFlavonoidsPhenolsPlant ExtractsAnticholinesterase activityAntioxidant activityAntiproliferative effectArtificial neural networksExtraction optimizationPhenolic compoundsPrunus armeniaca

Identifiers

PMID41372461
PMCPMC12749646

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.