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A. S. Alqahtani

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Open access Aug 2026

Development and validation of a green spectrofluorimetric method using a rhodamine 6G probe and FCCCD-optimized dispersive liquid–liquid microextraction for tenuazonic acid surveillance in dried figs

Tenuazonic acid (TeA) is a major Alternaria mycotoxin frequently contaminating dried figs, yet its routine surveillance remains constrained by reliance on costly chromatographic instrumentation. To address this analytical gap, a novel “turn-off” spectrofluorimetric method was developed for TeA determination in dried fig samples using rhodamine 6G as a cationic xanthene fluorescent probe. Given the complexity of the sugar-rich matrix, dispersive liquid–liquid microextraction was first optimized through a face-centered central composite design coupled with Derringer's desirability function. Optimal conditions comprised 350 µL of 1-octanol as extractant, 700 µL of acetonitrile as disperser, pH 3.3, and 5% (w/v) ammonium sulfate, yielding an experimental recovery of 95.23% ± 1.48%. Subsequently, spectral characterization demonstrated strong native fluorescence of rhodamine 6G at 555 nm (λex 526 nm), progressively quenched in the presence of TeA. Multi-temperature Stern–Volmer analysis, Job's continuous variation method, and thermodynamic evaluation confirmed a static quenching mechanism involving 1 : 1 ground-state complex formation. Comprehensive validation demonstrated linearity across 20–4000 µg kg−1 (R2 = 0.9981), with an LOQ of 19.2 µg kg−1. Mean recoveries ranged from 94.9% to 99.7%, intra- and inter-day precision remained below 11%, expanded measurement uncertainty was within ±22.4%, and matrix effects were negligible (−3.4%). Application to 60 Egyptian dried fig samples revealed widespread contamination (90% incidence; mean 726 ± 483 µg kg−1), with 26.7% exceeding the 1000 µg kg−1 indicative level. Green chemistry evaluation using AGSA-Prep (65%), WECA (81%), and EPPI (84.2) confirmed the method's sustainability, establishing it as a practical alternative to LC-MS/MS for routine TeA surveillance in resource-limited laboratories.

Fotoon F. Redwan, Ahmed Serag, A. Abdelazim et al. · 0 citations
Open access Aug 2026

A sensitive and green spectrofluorimetric method for determination of guanfacine hydrochloride based on NBD-Cl derivatization

A sensitive and environmentally friendly spectrofluorimetric method was developed for the determination of guanfacine in pharmaceutical formulations. The method is based on derivatization of guanfacine with 4-chloro-7-nitrobenzofurazan in alkaline medium to yield a highly fluorescent product measured at 535 nm after excitation at 466 nm. Experimental conditions affecting the reaction were systematically optimized to achieve maximum fluorescence intensity. The method exhibited excellent linearity over the concentration range of 50–500 ng/mL with a correlation coefficient of 0.9994. The limits of detection and quantitation were found to be 13.80 and 41.82 ng/mL, respectively, indicating high sensitivity. The method was validated in accordance with ICH guidelines and demonstrated satisfactory accuracy, precision, robustness, and selectivity. It was successfully applied to the analysis of guanfacine in commercial tablet formulations without interference from excipients. Greenness assessment using Analytical Eco-scale and AGREE tools confirmed the environmentally benign nature of the method, achieving a high Eco-scale score of 89 and an AGREE score of 0.68. Compared with a reported method, the proposed approach offers improved sensitivity and superior environmental benignity, making it suitable for routine quality control analysis.

Aamal A. Al-Mutairi, Saleh I. Alaqel, Farooq M. Almutairi et al. · 0 citations
Open access Aug 2026

Drugs solubility parameter prediction using modified Cubic Plus Chain equation of state.

The proposed CPC-TST model demonstrated good accuracy in predicting solubility parameter, particularly for strongly associating systems, while maintaining low computational complexity, and highlights the potential of the CPC-TST model as a robust and efficient alternative for modeling solubility behavior in pharmaceutical systems.

A. S. Alqahtani, Saeed Shirazian · 0 citations

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