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Mouhamed AA, Nadim AH, Mostafa NM, Eltanany BM. Application of smart chemometric models for spectra resolution and determination of challenging multi-action quaternary mixture: statistical comparison with greenness assessment. BMC Chem 2024; 18:44. [PMID: 38431694 PMCID: PMC10909257 DOI: 10.1186/s13065-024-01148-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 02/20/2024] [Indexed: 03/05/2024] Open
Abstract
A multivariate spectrophotometric method is a potential approach that enables discrimination of spectra of components in complex matrices (e.g., pharmaceutical formulation) serving as a substitution method for chromatography. Four green smart multivariate spectrophotometric models were proposed and validated, including principal component regression (PCR), partial least-squares (PLS), multivariate curve resolution-alternating least squares (MCR-ALS), and artificial neural networks (ANN). The developed chemometric models were compared to resolve highly overlapping spectra of Paracetamol (PARA), Chlorpheniramine maleate (CPM), Caffeine (CAF), and Ascorbic acid (ASC). The four multivariate calibration models were assessed via recoveries percent, and root mean square error of prediction. Hence, the proposed models were efficiently applied with no need for any preliminary separation step. The models were utilized to analyze the studied components in their combined pharmaceutical formulation (Grippostad® C capsules). Analytical GREEnness Metric Approach (AGREE) and eco-scale tools were applied to assess the greenness of the established models and found to be 0.77 and 85, respectively. Moreover, the proposed models have been compared to official ones showing no considerable variations in accuracy and precision. Therefore, these models can be highly advantageous for conducting standard pharmaceutical analysis of the substances researched within product testing laboratories.
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Affiliation(s)
- Aya A Mouhamed
- Department of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, Cairo University, Cairo, 11562, Egypt
| | - Ahmed H Nadim
- Department of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, Cairo University, Cairo, 11562, Egypt.
| | - Nadia M Mostafa
- Department of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, Cairo University, Cairo, 11562, Egypt
| | - Basma M Eltanany
- Department of Pharmaceutical Analytical Chemistry, Faculty of Pharmacy, Cairo University, Cairo, 11562, Egypt
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De Géa Neves M, Noda I, Siesler HW. Investigation of bread staling by handheld NIR spectroscopy in tandem with 2D-COS and MCR-ALS analysis. Microchem J 2023. [DOI: 10.1016/j.microc.2023.108578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
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Mazivila SJ, Santos JL. A review on multivariate curve resolution applied to spectroscopic and chromatographic data acquired during the real-time monitoring of evolving multi-component processes: From process analytical chemistry (PAC) to process analytical technology (PAT). Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Darío Pierini G, Andrés Bortolato S, Noel Robledo S, Raquel Alcaraz M, Fernández H, Casimiro Goicoechea H, Alicia Zon M. Second-order electrochemical data generation to quantify carvacrol in oregano essential oils. Food Chem 2022; 368:130840. [PMID: 34450499 DOI: 10.1016/j.foodchem.2021.130840] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/17/2021] [Accepted: 08/09/2021] [Indexed: 12/28/2022]
Abstract
A novel analytical method using voltammetric second-order modeling based on multivariate curve resolution-alternating least-square (MCR-ALS) is presented for the first time for the quantitation of carvacrol (CAR) in oregano essential oils (OEO). The second-order cyclic voltammetry data were generated on the basis that CAR shows a diffusional system. Thus, the scan rate (v) was used as a second instrumental mode and cyclic voltammograms at different v were acquired for a single sample, generating the second-order data. CAR determination was performed in presence of thymol, included as a potential interferent. Results demonstrated that MCR-ALS successfully exploited the second-order advantage and the recoveries were not statistically different than 100%. The limits of detection and quantitation were estimated using the MCR-ALS which were 6.27 × 10-5°mol°L-1°and 1.90 × 10-4°mol L-1, respectively. Finally, the developed methodology was implemented to quantify of CAR in OEO samples.
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Affiliation(s)
- Gastón Darío Pierini
- Departamento de Química, Grupo GEANA, Instituto para el Desarrollo Agroindustrial y de la Salud (IDAS), Facultad de Ciencias Exactas, Físico-Químicas y Naturales, Universidad Nacional de Río Cuarto, Agencia Postal N° 3, 5800 Río Cuarto, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, CABA C1425FQB, Argentina.
| | - Santiago Andrés Bortolato
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, CABA C1425FQB, Argentina; Instituto de Química Rosario (IQUIR, CONICET-UNR), Suipacha 570 (S2002LRL), Rosario, Argentina.
| | - Sebastian Noel Robledo
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, CABA C1425FQB, Argentina; Departamento de Tecnología Química, Grupo GEANA, Instituto para el Desarrollo Agroindustrial y de la Salud (IDAS), Facultad de Ingeniería, Universidad Nacional de Río Cuarto, Agencia Postal N°3 (5800), Río Cuarto, Argentina.
| | - Mirta Raquel Alcaraz
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, CABA C1425FQB, Argentina; Laboratorio de Desarrollo Analítico y Quimiometría (LADAQ), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral-CONICET, Ciudad Universitaria, Santa Fe S3000ZAA, Argentina.
| | - Héctor Fernández
- Departamento de Química, Grupo GEANA, Instituto para el Desarrollo Agroindustrial y de la Salud (IDAS), Facultad de Ciencias Exactas, Físico-Químicas y Naturales, Universidad Nacional de Río Cuarto, Agencia Postal N° 3, 5800 Río Cuarto, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, CABA C1425FQB, Argentina.
| | - Héctor Casimiro Goicoechea
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, CABA C1425FQB, Argentina; Laboratorio de Desarrollo Analítico y Quimiometría (LADAQ), Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral-CONICET, Ciudad Universitaria, Santa Fe S3000ZAA, Argentina.
| | - María Alicia Zon
- Departamento de Química, Grupo GEANA, Instituto para el Desarrollo Agroindustrial y de la Salud (IDAS), Facultad de Ciencias Exactas, Físico-Químicas y Naturales, Universidad Nacional de Río Cuarto, Agencia Postal N° 3, 5800 Río Cuarto, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290, CABA C1425FQB, Argentina.
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Zhang M, Lv J. Source apportionment of potentially toxic elements in soils of the Yellow River Delta Nature Reserve, China: The application of three receptor models and geostatistical independent simulation. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 289:117834. [PMID: 34315037 DOI: 10.1016/j.envpol.2021.117834] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 06/11/2021] [Accepted: 07/21/2021] [Indexed: 06/13/2023]
Abstract
The Yellow River Delta (YRD) wetland, the most important estuary wetland in eastern China, has an important ecosystem service function. Rapid and intensive development has inevitably led to the accumulation of potentially toxic elements (PTEs) in soils. Therefore, identifying quantitative sources and spatial distributions of PTEs is essential for soil environmental protection in the YRD. A total of 240 topsoil samples (0-20 cm) were collected in the Yellow River Delta Nature Reserve (YRDNR) and analyzed the PTE contents. To avoid the biases of the single receptor model, positive matrix factorization, factor analysis with nonnegative constraints, and maximum likelihood principal component analysis-multivariate curve resolution-alternating least squares were used for source apportionment of soil PTEs. To promote the efficiency of multivariate geostatistical simulation, a minimum/maximum autocorrelation factor-sequential Gaussian simulation was built to map the spatial patterns of PTEs. Three factors were derived by the three receptor models, and their contributions to the source explanation were similar. As, Cr, Cu, Mn, Ni, and Zn originated from natural sources, with contributions of 85.6%-96.4 %. A total of 61.5 % of Hg was associated with atmospheric deposition of coal combustion and wastewater from upstream. Agricultural activities and oil exploitation contributed 33.5 % and 15.9 % of the Cd and Pb concentrations. Spatial distributions of soil PTEs were controlled by sedimentary grain size. A total of 47.2 % of the total study area was identified as hazardous area for Cd, 10.3 % for As, and 5.4 % for Hg. This work is expected to provide references for soil pollution assessment and management of YRDNR.
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Affiliation(s)
- Mengna Zhang
- College of Geography and Environment, Shandong Normal University, Ji'nan, 250014, China
| | - Jianshu Lv
- College of Geography and Environment, Shandong Normal University, Ji'nan, 250014, China.
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Berto S, Alladio E. Application of Chemometrics Tools to the Study of the Fe(III)-Tannic Acid Interaction. Front Chem 2020; 8:614171. [PMID: 33363116 PMCID: PMC7759621 DOI: 10.3389/fchem.2020.614171] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 11/16/2020] [Indexed: 12/02/2022] Open
Abstract
Chemometric techniques were applied to the study of the interaction of iron(III) and tannic acid (TA). Modeling the interaction of Fe(III)–TA is a challenge, as can be the modeling of the metal complexation upon natural macromolecules without a well-defined molecular structure. The chemical formula for commercial TA is often given as C76H52O46, but in fact, it is a mixture of polygalloyl glucoses or polygalloyl quinic acid esters with the number of galloyl moieties per molecule ranging from 2 up to 12. Therefore, the data treatment cannot be based on just the stoichiometric approach. In this work, the redox behavior and the coordination capability of the TA toward Fe(III) were studied by UV-vis spectrophotometry and fluorescence spectroscopy. Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and Parallel Factor Analysis (PARAFAC) were used for the data treatment, respectively. The pH range in which there is the redox stability of the system Fe(III)–TA was evaluated. The binding capability of TA toward Fe(III), the spectral features of coordination compounds, and the concentration profiles of the species in solution as a function of pH were defined. Moreover, the stability of the interaction between TA and Fe(III) was interpreted through the chemical models usually employed to depict the interaction of metal cations with humic substances and quantified using the concentration profiles estimated by MCR-ALS.
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Affiliation(s)
- Silvia Berto
- Department of Chemistry, University of Turin, Turin, Italy
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