Simultaneous determination of cefotaxime and nimesulide using poly(L-cysteine) and graphene composite modified glassy carbon electrode

New approaches in antibiotics detection: The use of square wave voltammetry

Antibiotics belongs to a class of pharmaceutical compounds widely used due to their effectiveness against bacterial infections. However, if consumed or inappropriately disposed of in the environment can results in environmental and public health problems, because they are considered emerging contaminants and their residues represent damage, whether in the long or short term, to different terrestrial ecosystems, in addition to bringing potential risks to agricultural sectors, such as livestock and fish farming. For this, the development of analytical methods for low-concentration detection and identification of antibiotics in natural waters, wastewaters, soil, foods, and biological fluids is necessary. This review shows the applicability of square wave voltammetry for the analytical determination of antibiotics from different chemical classes and covers a variety of samples and working electrodes that are used as voltammetric sensors. The review involved the analysis of scientific publications from the Science Direct® and Scopus® databases, with scientific manuscripts covering the period between January 2012 and May 2023. Various manuscripts were discussed indicating the applicability of square wave voltammetry in antibiotics detection in urine, blood, natural waters, milk, among other complex samples.

Green Chemometric Determination of Cefotaxime Sodium in the Presence of Its Degradation Impurities Using Different Multivariate Data Processing Tools; GAPI and AGREE Greenness Evaluation

Four eco-friendly, cost-effective, and fast stability-indicating UV-VIS spectrophotometric methods were validated for cefotaxime sodium (CFX) determination either in the presence of its acidic or alkaline degradation products. The applied methods used multivariate chemometry, namely, classical least square (CLS), principal component regression (PCR), partial least square (PLS), and genetic algorithm-partial least square (GA-PLS), to resolve the analytes' spectral overlap. The spectral zone for the studied mixtures was within the range from 220 to 320 nm at a 1 nm interval. The selected region showed severe overlap in the UV spectra of cefotaxime sodium and its acidic or alkaline degradation products. Seventeen mixtures were used for the models' construction, and eight were used as an external validation set. For the PLS and GA-PLS models, a number of latent factors were determined as a pre-step before the models' construction and found to be three for the (CFX/acidic degradants) mixture and two for the (CFX/alkaline degradants) mixture. For GA-PLS, spectral points were minimized to around 45% of the PLS models. The root mean square errors of prediction were found to be (0.19, 0.29, 0.47, and 0.20) for the (CFX/acidic degradants) mixture and (0.21, 0.21, 0.21, and 0.22) for the (CFX/alkaline degradants) mixture for CLS, PCR, PLS, and GA-PLS, respectively, indicating the excellent accuracy and precision of the developed models. The linear concentration range was studied within 12-20 μg mL^-1 for CFX in both mixtures. The validity of the developed models was also judged using other different calculated tools such as root mean square error of cross validation, percentage recoveries, standard deviations, and correlation coefficients, which indicated excellent results. The developed methods were also applied to the determination of cefotaxime sodium in marketed vials, with satisfactory results. The results were statistically compared to the reported method, revealing no significant differences. Furthermore, the greenness profiles of the proposed methods were assessed using the GAPI and AGREE metrics.

Recent developments on graphene and its derivatives based electrochemical sensors for determinations of food contaminants

The sensing of food contaminants is essential to prevent their adverse health effects on the consumers. Electrochemical sensors are promising in the determination of electroactive analytes including food pollutants, biomolecules etc. Graphene nanomaterials offer many benefits as electrode material in a sensing device. To further improve the analytical performance, doped graphene or derivatives of graphene such as reduced graphene oxide and their nanocomposites were explored as electrode materials. Herein, the advancements in graphene and its derivatives-based electrochemical sensors for analysis of food pollutants were summarized. Determinations of both organic (food colourants, pesticides, drugs, etc.) and inorganic pollutants (metal cations and anions) were considered. The influencing factors including nature of electrode materials and food pollutants, pH, electroactive surface area etc., on the sensing performances of modified electrodes were highlighted. The results of pollutant detection in food samples by the graphene-based electrode have also been outlined. Lastly, conclusions and current challenges in effective real sample detection were presented.