Efficient and straightforward spectrophotometric analysis of 5-hydroxymethylfurfural (HMF) using citrate@Fe3O4 nanoparticles as an adsorbent.

In this study, we developed a spectrophotometry method for the analysis of 5-hydroxymethylfurfuraldehyde (HMF) in pharmaceutical formulations using citrate@Fe3O4 adsorbent. As bare magnetite (Fe3O4) has certain limitations, such as aggregation and oxidation, surface modifications are commonly used to improve its properties. We successfully coated Fe3O4 with sodium citrate to create a magnetic adsorbent for isolating HMF from samples. We confirmed the successful surface coating of Fe3O4 with citrate using Fourier Transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), Zeta potential, and scanning electron microscopy (SEM). The high adsorption capacity of citrate@Fe3O4 is due to the abundance of carboxyl and hydroxyl groups on the surface of the adsorbent, making it ideal for HMF extraction. The HMF concentration was then quantified using spectrophotometry. Citrate@Fe3O4 exhibited a high surface area and strong interaction with HMF. We analyzed the individual influential factors affecting the magnetic solid phase extraction (MSPE) setup. Validation parameters were also provided to confirm the reliability of the method. Under optimal parameters, the method exhibited excellent linearity in the range of 0.05-30.00 µg/ml with the lower limit of quantification (LLOQ) of 0.05 µg/ml. Relative standard deviations (RSD) values for precision were better than 10% and the method's trueness were better than 10%. Recoveries were found to be in the range of 85% to 106%, indicating excellent accuracy and reliability. We used this method to identify and measure HMF in six different dextrose pharmaceutical dosage forms as intravenous injectable solutions and three honey samples.

An efficient swarm intelligence approach to feature selection based on invasive weed optimization: Application to multivariate calibration and classification using spectroscopic data.

Variable selection plays a key role in classification and multivariate calibration. Variable selection methods are aimed at choosing a set of variables, from a large pool of available predictors, relevant to the analyte concentrations estimation, or to achieve better classification results. Many variable selection techniques have now been introduced among which, those which are based on the methodologies of swarm intelligence optimization have been more respected during a few last decades since they are mainly inspired by nature. In this work, a simple and new variable selection algorithm is proposed according to the invasive weed optimization (IWO) concept. IWO is considered a bio-inspired metaheuristic mimicking the weeds ecological behavior in colonizing as well as finding an appropriate place for growth and reproduction; it has been shown to be very adaptive and powerful to environmental changes. In this paper, the first application of IWO, as a very simple and powerful method, to variable selection is reported using different experimental datasets including FTIR and NIR data, so as to undertake classification and multivariate calibration tasks. Accordingly, invasive weed optimization - linear discrimination analysis (IWO-LDA) and invasive weed optimization- partial least squares (IWO-PLS) are introduced for multivariate classification and calibration, respectively.

Salting-out homogeneous liquid-liquid extraction in narrow-bore tube: extraction and preconcentration of phthalate esters from water.

In this study a simple and rapid sample preparation technique, homogeneous liquid-liquid extraction based on phase separation in the presence of a salt performed in a narrow-bore tube, followed by GC-flame ionization detection has been developed. In this work, sodium chloride and ACN were used as the salting-out agent and water-soluble extraction solvent, respectively. The homogeneous solution of water and ACN was broken by addition of the salt. Small volume of ACN was collected on top of the tube and the extracted analytes in the collected phase were determined. It has been successfully used for the analysis of five phthalate esters as model compounds in aqueous sample. Experimental parameters affecting the extraction efficiency such as kind and volume of the water-soluble organic solvent, length and diameter of the tube, and pH of the sample solution were investigated. Under the optimal conditions, the LODs were between 0.02 and 0.7 µg/L and enrichment factors were in the range of 172-309. In addition, good linearity (between 1 and 5000 µg/L) and high precision on the base of RSD (<8%, C = 600 µg/L, n = 6) were achieved.