{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T18:00:50Z","timestamp":1777658450379,"version":"3.51.4"},"reference-count":53,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2024,7,28]],"date-time":"2024-07-28T00:00:00Z","timestamp":1722124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000180","name":"US Department of Homeland Security","doi-asserted-by":"publisher","award":["22STESE00001-02-00"],"award-info":[{"award-number":["22STESE00001-02-00"]}],"id":[{"id":"10.13039\/100000180","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000180","name":"US Department of Homeland Security","doi-asserted-by":"publisher","award":["21-CWDARI 00042-01-00"],"award-info":[{"award-number":["21-CWDARI 00042-01-00"]}],"id":[{"id":"10.13039\/100000180","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000180","name":"US Department of Homeland Security","doi-asserted-by":"publisher","award":["2022-77040-37623"],"award-info":[{"award-number":["2022-77040-37623"]}],"id":[{"id":"10.13039\/100000180","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000199","name":"US Department of Agriculture, National Institute of Food and Agriculture","doi-asserted-by":"publisher","award":["22STESE00001-02-00"],"award-info":[{"award-number":["22STESE00001-02-00"]}],"id":[{"id":"10.13039\/100000199","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000199","name":"US Department of Agriculture, National Institute of Food and Agriculture","doi-asserted-by":"publisher","award":["21-CWDARI 00042-01-00"],"award-info":[{"award-number":["21-CWDARI 00042-01-00"]}],"id":[{"id":"10.13039\/100000199","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000199","name":"US Department of Agriculture, National Institute of Food and Agriculture","doi-asserted-by":"publisher","award":["2022-77040-37623"],"award-info":[{"award-number":["2022-77040-37623"]}],"id":[{"id":"10.13039\/100000199","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Molecules"],"abstract":"<jats:p>The development of new methods of identification of active pharmaceutical ingredients (API) is a subject of paramount importance for research centers, the pharmaceutical industry, and law enforcement agencies. Here, a system for identifying and classifying pharmaceutical tablets containing acetaminophen (AAP) by brand has been developed. In total, 15 tablets of 11 brands for a total of 165 samples were analyzed. Mid-infrared vibrational spectroscopy with multivariate analysis was employed. Quantum cascade lasers (QCLs) were used as mid-infrared sources. IR spectra in the spectral range 980\u20131600 cm\u22121 were recorded. Five different classification methods were used. First, a spectral search through correlation indices. Second, machine learning algorithms such as principal component analysis (PCA), support vector classification (SVC), decision tree classifier (DTC), and artificial neural network (ANN) were employed to classify tablets by brands. SNV and first derivative were used as preprocessing to improve the spectral information. Precision, recall, specificity, F1-score, and accuracy were used as criteria to evaluate the best SVC, DEE, and ANN classification models obtained. The IR spectra of the tablets show characteristic vibrational signals of AAP and other APIs present. Spectral classification by spectral search and PCA showed limitations in differentiating between brands, particularly for tablets containing AAP as the only API. Machine learning models, specifically SVC, achieved high accuracy in classifying AAP tablets according to their brand, even for brands containing only AAP.<\/jats:p>","DOI":"10.3390\/molecules29153562","type":"journal-article","created":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T09:50:05Z","timestamp":1722246605000},"page":"3562","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["QCL Infrared Spectroscopy Combined with Machine Learning as a Useful Tool for Classifying Acetaminophen Tablets by Brand"],"prefix":"10.3390","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1230-4119","authenticated-orcid":false,"given":"Jos\u00e9 A.","family":"Mart\u00ednez-Trespalacios","sequence":"first","affiliation":[{"name":"Mechanical Engineering Program, School of Engineering, Universidad Tecnol\u00f3gica de Bol\u00edvar, Parque Industrial y Tecnol\u00f3gico Carlos V\u00e9lez Pombo, Cartagena 130001, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel E.","family":"Polo-Herrera","sequence":"additional","affiliation":[{"name":"Chemistry Program, Department of Natural and Exact Sciences, San Pablo Campus, University of Cartagena, Cartagena 130015, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tamara Y.","family":"F\u00e9lix-Massa","sequence":"additional","affiliation":[{"name":"Center for Chemical Sensors and Chemical Imaging and Surface Analysis Center, Department of Chemistry, University of Puerto Rico, Mayaguez, PR 00681, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2536-6693","authenticated-orcid":false,"given":"Samuel P.","family":"Hernandez-Rivera","sequence":"additional","affiliation":[{"name":"Center for Chemical Sensors and Chemical Imaging and Surface Analysis Center, Department of Chemistry, University of Puerto Rico, Mayaguez, PR 00681, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2330-8580","authenticated-orcid":false,"given":"Joaqu\u00edn","family":"Hernandez-Fernandez","sequence":"additional","affiliation":[{"name":"Mechanical Engineering Program, School of Engineering, Universidad Tecnol\u00f3gica de Bol\u00edvar, Parque Industrial y Tecnol\u00f3gico Carlos V\u00e9lez Pombo, Cartagena 130001, Colombia"},{"name":"Chemistry Program, Department of Natural and Exact Sciences, San Pablo Campus, University of Cartagena, Cartagena 130015, Colombia"},{"name":"Department of Natural and Exact Science, Universidad de la Costa, Barranquilla 080002, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fredy","family":"Colpas-Castillo","sequence":"additional","affiliation":[{"name":"Chemistry Program, Department of Natural and Exact Sciences, San Pablo Campus, University of Cartagena, Cartagena 130015, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3210-1167","authenticated-orcid":false,"given":"John R.","family":"Castro-Suarez","sequence":"additional","affiliation":[{"name":"\u00c1rea B\u00e1sicas Exactas, Universidad del Sin\u00fa, Seccional Cartagena, Cartagena 130015, Colombia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,28]]},"reference":[{"key":"ref_1","unstructured":"FDA (2024, February 02). Counterfeit Medicine, Available online: http:\/\/www.fda.gov\/Drugs\/ResourcesForYou\/Consumers\/BuyingUsingMedicineSafely\/CounterfeitMedicine\/."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s40290-023-00468-w","article-title":"Tackling Counterfeit Drugs: The Challenges and Possibilities","volume":"37","author":"Pathak","year":"2023","journal-title":"Pharm. Med."},{"key":"ref_3","unstructured":"World Health Organization (2023, March 01). Health and Well-Being. Available online: https:\/\/www.who.int\/data\/gho\/data\/major-themes\/health-and-well-being."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"El-Dahiyat, F., Fahelelbom, K.M.S., Jairoun, A.A., and Al-Hemyari, S.S. (2021). Combatting Substandard and Falsified Medicines: Public Awareness and Identification of Counterfeit Medications. Front. Public Health, 9.","DOI":"10.3389\/fpubh.2021.754279"},{"key":"ref_5","unstructured":"World Health Organization (2017, November 28). 1 in 10 Medical Products in Developing Countries is Substandard or Falsified. Available online: https:\/\/www.who.int\/news\/item\/28-11-2017-1-in-10-medical-products-in-developing-countries-is-substandard-or-falsified."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"111382","DOI":"10.1016\/j.forsciint.2022.111382","article-title":"Trends in counterfeit drugs and pharmaceuticals before and during COVID-19 pandemic","volume":"338","author":"Ziavrou","year":"2022","journal-title":"Forensic Sci. Int."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2754","DOI":"10.1136\/bmj.n2754","article-title":"Fake covid vaccines boost the black market for counterfeit medicines","volume":"375","author":"Srivastava","year":"2021","journal-title":"BMJ"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"102","DOI":"10.22543\/7674.91.P102110","article-title":"Acetaminophen, a therapeutic or an extremely toxic remedy\u2014A review","volume":"9","author":"Caragea","year":"2022","journal-title":"J. Mind Med. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1002\/jps.2600580417","article-title":"Colorimetric Determination of Acetaminophen","volume":"58","author":"Vaughan","year":"1969","journal-title":"J. Pharm. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Ar\u0131kan, C.C., Kulaba\u015f, N., and K\u00fc\u00e7\u00fckg\u00fczel, \u0130. (2023). Synthesis and standardization of an impurity of acetaminophen, development and validation of liquid chromatographic method. J. Pharm. Biomed. Anal., 223.","DOI":"10.1016\/j.jpba.2022.115123"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1007\/s11094-023-02844-x","article-title":"Optimization of Analytical Method for Simultaneous Determination of Acetaminophen, Caffeine, and Aspirin in Tablet Dosage Form","volume":"56","author":"Ismail","year":"2023","journal-title":"Pharm. Chem. J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/S0009-9120(83)90028-0","article-title":"Colorimetric determination of acetaminophen","volume":"16","author":"Gupta","year":"1983","journal-title":"Clin. Biochem."},{"key":"ref_13","first-page":"53","article-title":"Spectrophotometric Determination of Paracetamol in Some Manufactured Tablets in Iraqi markets","volume":"42","author":"Saeed","year":"2017","journal-title":"Int. J. Pharm. Sci. Rev. Res."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Magerusan, L., Pogacean, F., and Pruneanu, S. (2022). Enhanced Acetaminophen Electrochemical Sensing Based on Nitrogen-Doped Graphene. Int. J. Mol. Sci., 23.","DOI":"10.3390\/ijms232314866"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"110549","DOI":"10.1016\/j.diamond.2023.110549","article-title":"A novel electrochemical sensor based on MoO3 nanobelt-graphene oxide composite for the simultaneous determination of paracetamol and 4-aminophenol","volume":"140","author":"Vazan","year":"2023","journal-title":"Diam. Relat. Mater."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1016\/j.addr.2005.01.022","article-title":"Pharmaceutical applications of Mid-IR and Raman spectroscopy","volume":"57","author":"Wartewig","year":"2005","journal-title":"Adv. Drug Deliv. Rev."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1016\/j.jpba.2007.03.023","article-title":"A review of near infrared spectroscopy and chemometrics in pharmaceutical technologies","volume":"44","author":"Roggo","year":"2007","journal-title":"J. Pharm. Biomed. Anal."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Scappaticci, C., Spera, S., Biancolillo, A., and Marini, F. (2022). Detection and Quantification of Alprazolam Added to Long Drinks by Near Infrared Spectroscopy and Chemometrics. Molecules, 27.","DOI":"10.3390\/molecules27196420"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"8323","DOI":"10.1039\/D0RA08030F","article-title":"Pharmaceutical application of multivariate modelling techniques: A review on the manufacturing of tablets","volume":"11","author":"Shi","year":"2021","journal-title":"RSC Advances"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"510","DOI":"10.1016\/j.jpba.2010.06.003","article-title":"Acetaminophen determination in low-dose pharmaceutical syrup by NIR spectroscopy","volume":"53","author":"Mantanus","year":"2010","journal-title":"J. Pharm. Biomed. Anal."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1039\/b108240j","article-title":"Quantitative determination of acetylsalicylic acid and acetaminophen in tablets by FT-Raman spectroscopy","volume":"127","author":"Szostak","year":"2001","journal-title":"Analyst"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1007\/s10947-010-0097-9","article-title":"Qualitative Discrimination Between Paracetamol Tablets Made by Near Infrared Spectroscopy and Chemometrics With Regard to Polymorphism","volume":"51","author":"Khanmohammadi","year":"2010","journal-title":"J. Struct. Chem."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.saa.2015.01.036","article-title":"A rapid Fourier-transform infrared (FTIR) spectroscopic method for direct quantification of paracetamol content in solid pharmaceutical formulations","volume":"141","author":"Mallah","year":"2015","journal-title":"Spectrochim. Acta Part A Mol. Biomol. Spectrosc."},{"key":"ref_24","first-page":"e01537","article-title":"Comparative evaluation of acetaminophen form (I) in commercialized paracetamol brands","volume":"19","author":"Oloyede","year":"2023","journal-title":"Sci. Afr."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Mokari, A., Guo, S., and Bocklitz, T. (2023). Exploring the Steps of Infrared (IR) Spectral Analysis: Pre-Processing, (Classical) Data Modelling, and Deep Learning. Molecules, 28.","DOI":"10.3390\/molecules28196886"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1080\/05704928.2020.1859525","article-title":"Applications of machine learning in spectroscopy","volume":"56","author":"Ramirez","year":"2020","journal-title":"Appl. Spectrosc. Rev."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"105691","DOI":"10.1016\/j.microc.2020.105691","article-title":"Brand classification of detergent powder using near-infrared spectroscopy and extreme learning machines","volume":"160","author":"Tan","year":"2021","journal-title":"Microchem. J."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1016\/j.saa.2013.11.057","article-title":"Classification of washing powder brands using near-infrared spectroscopy combined with chemometric calibrations","volume":"120","author":"Zhang","year":"2014","journal-title":"Spectrochim. Acta Part A Mol. Biomol. Spectrosc."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Carri\u00f3n-Roca, W., Col\u00f3n-Mercado, A.M., Castro-Suarez, J.R., Caballero-Agosto, E.R., Col\u00f3n-Gonz\u00e1lez, F.M., Centeno-Ortiz, J.A., R\u00edos-Vel\u00e1zquez, C., and Hern\u00e1ndez-Rivera, S.P. (2024). Chemical sensing of common microorganisms found in biopharmaceutical industries using MIR laser spectroscopy and multivariate analysis. J. Biophotonics, 17.","DOI":"10.1002\/jbio.202300391"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"5222","DOI":"10.1364\/OE.447269","article-title":"Advances in mid-infrared spectroscopy enabled by supercontinuum laser sources","volume":"30","author":"Zorin","year":"2022","journal-title":"Opt. Express"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1002\/cphc.201801073","article-title":"Beer\u2019s Law\u2014Why Absorbance Depends (Almost) Linearly on Concentration","volume":"20","author":"Popp","year":"2019","journal-title":"ChemPhysChem"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1126\/science.264.5158.553","article-title":"Quantum Cascade Laser","volume":"264","author":"Faist","year":"1994","journal-title":"Science"},{"key":"ref_33","first-page":"1157","article-title":"Analytical Method Development Using Quantum Laser Cascade Spectroscopy with Diffuse and Attenuated Total Reflectance for Determining Low Concentrations of Active Pharmaceutical Ingredients","volume":"10","year":"2023","journal-title":"Austin J. Anal. Pharm. Chem."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"822","DOI":"10.1080\/05704928.2015.1075208","article-title":"Sensitivity Advantage of QCL Tunable-Laser Mid-Infrared Spectroscopy Over FTIR Spectroscopy","volume":"50","author":"Childs","year":"2015","journal-title":"Appl. Spectrosc. Rev."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1016\/S0378-5173(02)00420-9","article-title":"Spectroscopic characterisation of the monoclinic and orthorhombic forms of paracetamol","volume":"247","author":"Moynihan","year":"2002","journal-title":"Int. J. Pharm."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1016\/j.saa.2017.04.076","article-title":"Conformational and vibrational reassessment of solid paracetamol","volume":"183","author":"Amado","year":"2017","journal-title":"Spectrochim. Acta Part A Mol. Biomol. Spectrosc."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2675","DOI":"10.1021\/acs.jchemed.0c01231","article-title":"Introducing ATR-FTIR Spectroscopy through Analysis of Acetaminophen Drugs: Practical Lessons for Interdisciplinary and Progressive Learning for Undergraduate Students","volume":"98","author":"Zapata","year":"2021","journal-title":"J. Chem. Educ."},{"key":"ref_38","first-page":"527","article-title":"Desarrollo y validaci\u00f3n del an\u00e1lisis cuantitativo de Ibuprofeno en comprimidos por espectroscop\u00eda infrarroja","volume":"23","author":"Matkovic","year":"2004","journal-title":"Acta Farm. Bonaer."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1511","DOI":"10.1177\/0003702816662609","article-title":"Applications of Quantum Cascade Laser Spectroscopy in the Analysis of Pharmaceutical Formulations","volume":"70","year":"2016","journal-title":"Appl. Spectrosc."},{"key":"ref_40","first-page":"257765","article-title":"Determination of Caffeine, the Active Ingredient in Different Coffee Drinks and its Characterization by FTIR\/ATR and TGA\/DTA","volume":"2","author":"Abdalla","year":"2015","journal-title":"Int. J. Eng. Appl. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"533","DOI":"10.2478\/s11532-006-0018-0","article-title":"Solid-state IR-LD spectroscopy of codeine and N-norcodeine derivatives","volume":"4","author":"Bakalska","year":"2006","journal-title":"Open Chem."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.saa.2013.11.040","article-title":"Comprehensive quantum chemical and spectroscopic (FTIR, FT-Raman, 1H, 13C NMR) investigations of O-desmethyltramadol hydrochloride an active metabolite in tramadol\u2014An analgesic drug","volume":"122","author":"Arjunan","year":"2014","journal-title":"Spectrochim. Acta Part A Mol. Biomol. Spectrosc."},{"key":"ref_43","first-page":"48","article-title":"Optimization, Development and evaluation of Microemulsion for the release of combination of Guaifenesin and Phenylephrine","volume":"3","author":"Deepak","year":"2013","journal-title":"J. Appl. Pharm. Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.aca.2012.10.058","article-title":"New discrimination method combining hit quality index based spectral matching and voting","volume":"758","author":"Lee","year":"2013","journal-title":"Anal. Chim. Acta"},{"key":"ref_45","unstructured":"(2009). Standard Guide for Use of Spectral Searching by Curve Matching Algorithms with Data Recorded Using Mid-Infrared Spectroscopy (Standard No. ASTM E2310-04)."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"000370282098784","DOI":"10.1177\/0003702820987847","article-title":"Exploration of Principal Component Analysis: Deriving Principal Component Analysis Visually Using Spectra","volume":"75","author":"Beattie","year":"2021","journal-title":"Appl. Spectrosc."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1712","DOI":"10.21123\/bsj.2023.9010","article-title":"A Comparative Analysis of Machine Learning Algorithms for Classification of Diabetes Utilizing Confusion Matrix Analysis","volume":"21","author":"Mijwil","year":"2023","journal-title":"Baghdad Sci. J."},{"key":"ref_48","first-page":"17","article-title":"Predicting the Presence of Heart Diseases using Comparative Data Mining and Machine Learning Algorithms","volume":"176","author":"Sarku","year":"2020","journal-title":"Int. J. Comput. Appl."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"109461","DOI":"10.1016\/j.microc.2023.109461","article-title":"A rapid method to predict type and adulteration of coconut milk by near-infrared spectroscopy combined with machine learning and chemometric tools","volume":"195","author":"Sitorus","year":"2023","journal-title":"Microchem. J."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"137077","DOI":"10.1016\/j.foodchem.2023.137077","article-title":"Classification of oils and margarines by FTIR spectroscopy in tandem with machine learning","volume":"431","author":"Tachie","year":"2024","journal-title":"Food Chem."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1145\/2786984.2786995","article-title":"Scikit-learn","volume":"19","author":"Pedregosa","year":"2015","journal-title":"GetMobile Mob. Comput. Commun."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Trespalacios, J.A.M., Suarez, J.R.C., and Fern\u00e1ndez, J.H. (2023). Application of Fourier Transform Spectroscopy and Machine Learning to Determine Green Ethylene Content in Samples of Ethylene-Propylene Impact Copolymers. J. Southwest Jiaotong Univ., 58.","DOI":"10.35741\/issn.0258-2724.58.6.15"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"133883","DOI":"10.1016\/j.jclepro.2022.133883","article-title":"A machine learning based classification models for plastic recycling using different wavelength range spectrums","volume":"374","author":"Carrera","year":"2022","journal-title":"J. Clean. Prod."}],"container-title":["Molecules"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1420-3049\/29\/15\/3562\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:25:33Z","timestamp":1760109933000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1420-3049\/29\/15\/3562"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,28]]},"references-count":53,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2024,8]]}},"alternative-id":["molecules29153562"],"URL":"https:\/\/doi.org\/10.3390\/molecules29153562","relation":{},"ISSN":["1420-3049"],"issn-type":[{"value":"1420-3049","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,28]]}}}