{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T20:02:35Z","timestamp":1775937755227,"version":"3.50.1"},"reference-count":48,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,18]],"date-time":"2023-08-18T00:00:00Z","timestamp":1692316800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"PT national funds (FCT\/MCTES, Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia and Minist\u00e9rio da Ci\u00eancia, Tecnologia e Ensino Superior)","award":["UIDB\/50006\/2020"],"award-info":[{"award-number":["UIDB\/50006\/2020"]}]},{"name":"PT national funds (FCT\/MCTES, Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia and Minist\u00e9rio da Ci\u00eancia, Tecnologia e Ensino Superior)","award":["UIDP\/50006\/2020"],"award-info":[{"award-number":["UIDP\/50006\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>Biologically active compounds present in the diet can interact with biological membranes (such as cell membranes), changing their properties. Their mutual interactions can influence their respective activities. In this study, we analyzed the interactions of oleanolic acid and phenolic compounds such as apigenin, rutin, resveratrol and ferulic acid with phosphatidylcholine membranes. Spectroscopic methods (fluorescence spectroscopy, dynamic light scattering) and machine learning were applied. The results of structural studies were compared with the antioxidant activity of the investigated substances in lipid membranes. In liposomes loaded with oleanolic acid, the pro-oxidant activity of resveratrol arises from changes in membrane structure, leading to an increased exposure of its hydrophilic region to external radicals. A similar mechanism may be involved in the pro-oxidant action of oleanolic acid. By contrast, apigenin, rutin and ferulic acid are present at the membrane surface. Their presence in this region protects the bilayer from radicals generated in the aqueous phase. Lower antioxidant activity observed in the case of ferulic aid is probably related to weaker interactions of this compound with the membrane, compared to the investigated flavonoids. Appropriate machine learning models for predicting oleanolic acid and phenolic compounds have been developed for the future application of intelligent predictive systems to optimizing manufacturing processes involving liposomes. The most effective regression model turned out to be the MLP 1:1-100-50-50-6:1, identifying resveratrol with a determination index of 0.83.<\/jats:p>","DOI":"10.3390\/app13169362","type":"journal-article","created":{"date-parts":[[2023,8,18]],"date-time":"2023-08-18T10:28:48Z","timestamp":1692354528000},"page":"9362","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Interactions of Oleanolic Acid, Apigenin, Rutin, Resveratrol and Ferulic Acid with Phosphatidylcholine Lipid Membranes\u2014A Spectroscopic and Machine Learning Study"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1438-1217","authenticated-orcid":false,"given":"Krzysztof","family":"Dwiecki","sequence":"first","affiliation":[{"name":"Department of Food Biochemistry and Analysis, Pozna\u0144 University of Life Sciences, ul. Mazowiecka 48, 60-623 Poznan, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2535-8370","authenticated-orcid":false,"given":"Krzysztof","family":"Przyby\u0142","sequence":"additional","affiliation":[{"name":"Department of Dairy and Process Engineering, Faculty of Food Science and Nutrition, Pozna\u0144 University of Life Sciences, ul. Wojska Polskiego 31, 60-624 Poznan, Poland"}]},{"given":"Dobrawa","family":"Dezor","sequence":"additional","affiliation":[{"name":"Department of Food Biochemistry and Analysis, Pozna\u0144 University of Life Sciences, ul. Mazowiecka 48, 60-623 Poznan, Poland"}]},{"given":"Ewa","family":"B\u0105kowska","sequence":"additional","affiliation":[{"name":"Department of Food Biochemistry and Analysis, Pozna\u0144 University of Life Sciences, ul. Mazowiecka 48, 60-623 Poznan, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0396-3019","authenticated-orcid":false,"given":"Silvia M.","family":"Rocha","sequence":"additional","affiliation":[{"name":"Department of Chemistry & LAQV-REQUIMTE, University of Aveiro, Campus Universit\u00e1rio de Santiago, 3810-193 Aveiro, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ayeleso, T.B., Matumba, M.G., and Mukwevho, E. (2017). Oleanolic Acid and Its Derivatives: Biological Activities and Therapeutic Potential in Chronic Diseases. Molecules, 22.","DOI":"10.3390\/molecules22111915"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"113586","DOI":"10.1016\/j.biopha.2022.113586","article-title":"Exploring the Underlying Mechanism of Oleanolic Acid Treating Glioma by Transcriptome and Molecular Docking","volume":"154","author":"Huang","year":"2022","journal-title":"Biomed. Pharmacother."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Verstraeten, S., Catteau, L., Boukricha, L., Quetin-Leclercq, J., and Mingeot-Leclercq, M.-P. (2021). Effect of Ursolic and Oleanolic Acids on Lipid Membranes: Studies on MRSA and Models of Membranes. Antibiotics, 10.","DOI":"10.3390\/antibiotics10111381"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Castellano, J.M., Ramos-Romero, S., and Perona, J.S. (2022). Oleanolic Acid: Extraction, Characterization and Biological Activity. Nutrients, 14.","DOI":"10.3390\/nu14030623"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"769","DOI":"10.1007\/s11745-997-0098-9","article-title":"Oleanolic Acid and Ursolic Acid Stabilize Liposomal Membranes","volume":"32","author":"Han","year":"1997","journal-title":"Lipids"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Naparlo, K., Bartosz, G., Stefaniuk, I., Cieniek, B., Soszynski, M., and Sadowska-Bartosz, I. (2020). Interaction of Catechins with Human Erythrocytes. Molecules, 25.","DOI":"10.3390\/molecules25061456"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1038\/sj.bjp.0705460","article-title":"Interactions of Androgens, Green Tea Catechins and the Antiandrogen Flutamide with the External Glucose-Binding Site of the Human Erythrocyte Glucose Transporter GLUT1","volume":"140","author":"Naftalin","year":"2003","journal-title":"Br. J. Pharmacol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Karonen, M. (2022). Insights into Polyphenol\u2013Lipid Interactions: Chemical Methods, Molecular Aspects and Their Effects on Membrane Structures. Plants, 11.","DOI":"10.3390\/plants11141809"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2670","DOI":"10.1016\/j.bbamem.2014.07.001","article-title":"Structure-Dependent Interactions of Polyphenols with a Biomimetic Membrane System","volume":"1838","author":"Phan","year":"2014","journal-title":"Biochim. Biophys. Acta Biomembr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"114689","DOI":"10.1016\/j.molliq.2020.114689","article-title":"The Biophysical Interaction of Ferulic Acid with Liposomes as Biological Membrane Model: The Effect of the Lipid Bilayer Composition","volume":"324","author":"Andrade","year":"2021","journal-title":"J. Mol. Liq."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"112093","DOI":"10.1016\/j.lwt.2021.112093","article-title":"Phytosomal Nanocarriers for Encapsulation and Delivery of Resveratrol-Preparation, Characterization, and Application in Mayonnaise","volume":"151","author":"Rabbani","year":"2021","journal-title":"LWT"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"888245","DOI":"10.3389\/fnut.2022.888245","article-title":"Application of Machine Vision System in Food Detection","volume":"9","author":"Xiao","year":"2022","journal-title":"Front. Nutr."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Przyby\u0142, K., Wawrzyniak, J., Koszela, K., Adamski, F., and Gawrysiak-Witulska, M. (2020). Application of Deep and Machine Learning Using Image Analysis to Detect Fungal Contamination of Rapeseed. Sensors, 20.","DOI":"10.3390\/s20247305"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Przyby\u0142, K., Koszela, K., Adamski, F., Samborska, K., Walkowiak, K., and Polarczyk, M. (2021). Deep and Machine Learning Using SEM, FTIR, and Texture Analysis to Detect Polysaccharide in Raspberry Powders. Sensors, 21.","DOI":"10.3390\/s21175823"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"110014","DOI":"10.1016\/j.measurement.2021.110014","article-title":"Artificial Neural Networks in the Evaluation of the Influence of the Type and Content of Carrier on Selected Quality Parameters of Spray Dried Raspberry Powders","volume":"186","author":"Samborska","year":"2021","journal-title":"Measurement"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Przyby\u0142, K., Duda, A., Koszela, K., Stangierski, J., Polarczyk, M., and Gierz, \u0141. (2020). Classification of Dried Strawberry by the Analysis of the Acoustic Sound with Artificial Neural Networks. Sensors, 20.","DOI":"10.3390\/s20020499"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1581","DOI":"10.1016\/j.cell.2018.05.015","article-title":"Next-Generation Machine Learning for Biological Networks","volume":"173","author":"Camacho","year":"2018","journal-title":"Cell"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4538","DOI":"10.1016\/j.csbj.2021.08.011","article-title":"A Review on Machine Learning Approaches and Trends in Drug Discovery","volume":"19","author":"Novoa","year":"2021","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1947","DOI":"10.1007\/s10462-021-10058-4","article-title":"Machine Learning in Drug Discovery: A Review","volume":"55","author":"Dara","year":"2022","journal-title":"Artif. Intell. Rev."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1186\/s13063-021-05489-x","article-title":"The Role of Machine Learning in Clinical Research: Transforming the Future of Evidence Generation","volume":"22","author":"Weissler","year":"2021","journal-title":"Trials"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Ocampo, I., L\u00f3pez, R.R., Camacho-Le\u00f3n, S., Nerguizian, V., and Stiharu, I. (2021). Comparative Evaluation of Artificial Neural Networks and Data Analysis in Predicting Liposome Size in a Periodic Disturbance Micromixer. Micromachines, 12.","DOI":"10.3390\/mi12101164"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3275","DOI":"10.1007\/s11164-013-1431-6","article-title":"Prediction of Silver Nanoparticles\u2019 Diameter in Montmorillonite\/Chitosan Bionanocomposites by Using Artificial Neural Networks","volume":"41","author":"Shabanzadeh","year":"2015","journal-title":"Res. Chem. Intermed."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1016\/j.bbamem.2017.11.012","article-title":"Antioxidant Activity of Hydroxytyrosyl Esters Studied in Liposome Models","volume":"1860","author":"Balducci","year":"2018","journal-title":"Biochim. Biophys. Acta Biomembr."},{"key":"ref_24","unstructured":"Kingma, D.P., and Ba, J.L. (2014). Adam: A Method for Stochastic Optimization. 3rd International Conference on Learning Representations, ICLR 2015\u2014Conference Track Proceedings. arXiv."},{"key":"ref_25","unstructured":"Patterson, J., and Gibson, A. (2017). Deep Learning A Practitioner\u2019s Approach, O\u2019Reilly Media, Inc."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1955","DOI":"10.1007\/s11746-014-2541-z","article-title":"Association Colloids Formed by Multiple Surface Active Minor Components and Their Effect on Lipid Oxidation in Bulk Oil","volume":"91","author":"Kittipongpittaya","year":"2014","journal-title":"JAOCS J. Am. Oil Chem. Soc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1111\/j.1574-6968.2001.tb10897.x","article-title":"A Fluorescence Quenching Test for the Detection of Flavonoid Transformation","volume":"204","author":"Schoefer","year":"2006","journal-title":"FEMS Microbiol. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2823","DOI":"10.1091\/mbc.e11-07-0645","article-title":"A Simple Guide to Biochemical Approaches for Analyzing Protein-Lipid Interactions","volume":"23","author":"Zhao","year":"2012","journal-title":"Mol. Biol. Cell"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"131533","DOI":"10.1016\/j.foodchem.2021.131533","article-title":"Heat-Induced Changes in Lupin Seed \u03b3-Conglutin Structure Promote Its Interaction with Model Phospholipid Membranes","volume":"374","author":"Czubinski","year":"2022","journal-title":"Food Chem."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1002\/biof.5520160301","article-title":"Membrane-Rigidifying Effects of Anti-Cancer Dietary Factors","volume":"16","author":"Tsuchiya","year":"2002","journal-title":"BioFactors"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1080\/096876899294616","article-title":"Interactions of the Monomeric and Dimeric Flavones Apigenin and Amentoflavone with the Plasma Membrane of L929 Cells; A Fluorescence Study","volume":"16","author":"Lobstein","year":"1999","journal-title":"Mol. Membr. Biol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"113558","DOI":"10.1016\/j.lwt.2022.113558","article-title":"Effect of Sterols on Liposomes: Membrane Characteristics and Physicochemical Changes during Storage","volume":"164","author":"Song","year":"2022","journal-title":"LWT"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.jcis.2016.12.025","article-title":"Enhanced Chemotherapeutic Efficacy of Apigenin Liposomes in Colorectal Cancer Based on Flavone-Membrane Interactions","volume":"491","author":"Banerjee","year":"2017","journal-title":"J. Colloid Interface Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.jcis.2015.04.030","article-title":"Probing the Potential of Apigenin Liposomes in Enhancing Bacterial Membrane Perturbation and Integrity Loss","volume":"453","author":"Banerjee","year":"2015","journal-title":"J. Colloid Interface Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1016\/j.bbamem.2012.10.013","article-title":"FTIR, 1H NMR and EPR Spectroscopy Studies on the Interaction of Flavone Apigenin with Dipalmitoylphosphatidylcholine Liposomes","volume":"1828","author":"Misiak","year":"2013","journal-title":"Biochim. Biophys. Acta Biomembr."},{"key":"ref_36","first-page":"100059","article-title":"Flavonoid-Liposomes Formulations: Physico-Chemical Characteristics, Biological Activities and Therapeutic Applications","volume":"5","author":"Halevas","year":"2022","journal-title":"Eur. J. Med. Chem. Rep."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.ifset.2013.03.006","article-title":"Resveratrol Loaded Liposomes Produced by Different Techniques","volume":"19","author":"Zvonar","year":"2013","journal-title":"Innov. Food Sci. Emerg. Technol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"46","DOI":"10.3164\/jcbn.22-37","article-title":"Protective Effects of Liposomes Encapsulating Ferulic Acid against CCl4-Induced Oxidative Liver Damage in Vivo Rat Model","volume":"72","author":"Ara","year":"2023","journal-title":"J. Clin. Biochem. Nutr."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"218","DOI":"10.1016\/j.colsurfa.2017.01.019","article-title":"A Comparison of Physicochemical and Functional Properties of Icaritin-Loaded Liposomes Based on Different Surfactants","volume":"518","author":"Tai","year":"2017","journal-title":"Colloids Surf. A Physicochem. Eng. Asp."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"714","DOI":"10.1002\/mnfr.200600018","article-title":"Lipid Peroxidation Inhibition Capacity Assay for Antioxidants Based on Liposomal Membranes","volume":"50","author":"Zhang","year":"2006","journal-title":"Mol. Nutr. Food Res."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1080\/10715760000300661","article-title":"Resveratrol Inhibition of Lipid Peroxidation","volume":"33","author":"Tadolini","year":"2000","journal-title":"Free Radic. Res."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Li, Z., Chen, X., Liu, G., Li, J., Zhang, J., Cao, Y., and Miao, J. (2021). Antioxidant Activity and Mechanism of Resveratrol and Polydatin Isolated from Mulberry (Morus alba L.). Molecules, 26.","DOI":"10.3390\/molecules26247574"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"S1409","DOI":"10.1016\/j.arabjc.2013.04.016","article-title":"Analytical Techniques in Pharmaceutical Analysis: A Review","volume":"10","author":"Siddiqui","year":"2017","journal-title":"Arab. J. Chem."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"485","DOI":"10.2340\/00015555-0311","article-title":"Changes in European Legislation Make It Timely to Introduce a Transparent Market Surveillance System for Cosmetics","volume":"87","author":"Ungerth","year":"2007","journal-title":"Acta Derm. Venereol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"20130587","DOI":"10.1098\/rstb.2013.0587","article-title":"Pharmaceuticals in the Environment: Scientific Evidence of Risks and Its Regulation","volume":"369","author":"Adler","year":"2014","journal-title":"Philos. Trans. R. Soc. B Biol. Sci."},{"key":"ref_46","first-page":"316","article-title":"Recent Applications of Analytical Techniques for Quantitative Pharmaceutical Analysis: A Review","volume":"7","author":"Bonfilio","year":"2010","journal-title":"WSEAS Trans. Biol. Biomed."},{"key":"ref_47","unstructured":"Chen, L. (2020). Stock Price Prediction Using Adaptive Time Series Forecasting and Machine Learning Algorithms, University of California."},{"key":"ref_48","unstructured":"Bashir, D., Monta\u00f1ez, G.D., Sehra, S., Segura, P.S., and Lauw, J. (2020). Lecture Notes in Computer Science, Proceedings of the Australasian Joint Conference on Artificial Intelligence, Canberra, ACT, Australia, 29\u201330 November 2020, Springer."}],"container-title":["Applied Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-3417\/13\/16\/9362\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:36:20Z","timestamp":1760128580000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-3417\/13\/16\/9362"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,18]]},"references-count":48,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2023,8]]}},"alternative-id":["app13169362"],"URL":"https:\/\/doi.org\/10.3390\/app13169362","relation":{},"ISSN":["2076-3417"],"issn-type":[{"value":"2076-3417","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,18]]}}}