Browsing by Author "El-Zeiny, Mohamed B"

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Analysis of commonly prescribed analgesics using in-silico processing of spectroscopic signals: application to surface water and industrial effluents, and comparative study via green and white assessments
(CSIRO, 2023-02) Elbalkiny, Heba T; El-Zeiny, Mohamed B; Saleh, Sarah S
RESEARCH ARTICLEPrevious Contents Vol 19(7) Analysis of commonly prescribed analgesics using in-silico processing of spectroscopic signals: application to surface water and industrial effluents, and comparative study via green and white assessments Heba T. Elbalkiny A , Mohamed B. El-Zeiny B and Sarah S. Saleh https://orcid.org/0000-0002-1608-008X A * + Author Affiliations * Correspondence to: drsarahsalah@gmail.com Handling Editor: Kurunthachalam Kannan Environmental Chemistry 19(7) 446-459 https://doi.org/10.1071/EN22108 Submitted: 13 October 2022 Accepted: 6 December 2022 Published: 10 February 2023 © 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing. Environmental context. Pharmaceuticals find their way to wastewater mainly through hospital and industrial effluents, and in turn affect all living organisms. The routine analysis of different water sources is tedious and of high cost. Our work presents a safe, low-cost method for analysing water samples to ensure proper cleanup of water and its suitability for human and animal use. Rationale. Analgesics are one of the top classes of commonly prescribed drugs, and used over the counter. Therefore, they are most likely to be detected in wastewater samples coming from hospital and industrial effluents. Methodology. This study focused on developing an in-silico UV spectroscopic manipulation of variant signal nature of low cost, using the methods of: advanced amplitude centring (AAC), mean centring of ratio spectra (MCR), successive derivative subtraction (SDS) and continuous wavelet transformation (CWT), for the determination of a ternary mixture of three analgesics: paracetamol (PCM), diclofenac (DCF) and ibuprofen (IBU) in water samples after sample cleanup using dispersive liquid–liquid microextraction (DLLME). Results. The proposed methods were compared to those reported in terms of greenness, simplicity and effectiveness using the greenness assessment tools (Eco-scale & AGREE) and white analytical chemistry (WAC) tool. The AAC method showed the highest scores: an Eco-scale of 71, AGREE of 0.55 and RGB of 84.4 when compared to the reported methods. Discussion. The AAC method was applied effectively for the study of surface water samples and industrial effluents with high accuracy and precision. Thus, real water samples could be routinely analysed with minimal cost to ensure proper cleanup of water and its suitability for human and animal use.
A comparative study of different aspects in manipulating ratio spectra used for the analysis of cefradine in the presence of its alkaline degradation product
(ELSEVIER, 1/15/2019) Salama, Fathy M.M; Attia, Khalid A.M; Said, Ragab A.M; El-Zeiny, Mohamed B; .El-Attara, Abdul-Aziz M.M
Six stability-indicating UV-spectrophotometric methods manipulating ratio spectra were utilized for the analysis of cefradine in presence of its alkaline degradate. These methods are different forms of transformations; ratio difference, mean centering, derivative ratio using numerical differentiation, derivative ratio using Savitsky-Golay filter, continuous wavelet transform and derivative continuous wavelet transform. Water was used as a solvent and the linearity ranges were 6-26 mu g/mL. Determination of accuracy and precision for the suggested procedures were executed. Assessment of specificity was run through analyzing laboratory prepared mixtures containing cefradine and its alkaline degradate. The suggested methods were useful for cefradine estimation in tablets. Statistically, the outputs obtained from the recommended and published methods reveal no significant differences. (C) 2018 Elsevier B.V. All rights reserved.
Full spectrum and selected spectrum based chemometric methods for the simultaneous determination of Cinnarizine and Dimenhydrinate in laboratory prepared mixtures and pharmaceutical dosage form
(PERGAMON-ELSEVIER, 2017) Tawakkol, Shereen M; El-Zeiny, Mohamed B; Hemdan, A
Three chemometric methods namely, concentration residual augmented classical least squares (CRACLS), spectral residual augmented classical least squares (SRACLS) and partial least squares (PLS) were applied for the simultaneous quantitative determination of Cinnarizine and Dimenhydrinate in their binary mixtures. All techniques were applied with and without variable selection using genetic algorithm (GA) resulting in six models (CRACLS, GA-CRACLS, SRACLS, GA-SRACLS, PLS, GA-PLS). These models were applied for the simultaneous determination of the drugs in their laboratory prepared mixtures and pharmaceutical dosage form via handling their UV spectral data. It was found that GA based models are simpler and more robust than those built with the full spectral data. The proposed models were found to be simple, fast and require no preliminary separation steps; so they can be used for the routine analysis of this binary mixture in quality control laboratories. (C) 2016 Elsevier B.V. All rights reserved.
Stability indicating methods for the analysis of cefprozil in the presence of its alkaline induced degradation product
(PERGAMON-ELSEVIER SCIENCE LTD, 4/15/2016) Serag, Ahmed; El-Zeiny, Mohamed B; Nassar, Mohammed W. I; Attia, Khalid A. M
Three simple, specific, accurate and precise spectrophotometric methods were developed for the determination of cefprozil (CZ) in the presence of its alkaline induced degradation product (DCZ). The first method was the bivariate method, while the two other multivariate methods were partial least squares (PLS) and spectral residual augmented classical least squares (SRACLS). The multivariate methods were applied with and without variable selection procedure (genetic algorithm GA). These methods were tested by analyzing laboratory prepared mixtures of the above drug with its alkaline induced degradation product and they were applied to its commercial pharmaceutical products. (C) 2016 Elsevier B.V. All rights reserved.