Journal of Analytical Chemistry最新文献

The accurate quantification of analytes in samples with overlapping spectra remains a critical challenge in analytical chemistry, particularly for complex pharmaceutical formulations. Developing a method for simultaneous quantification of metronidazole (MTZ) and spiramycin (SPI) that is rapid, accurate, reliable, and cost-effective is imperative. This study aims to apply an ultraviolet-visible (UV-Vis) method integrating wavelength selection algorithms with partial least squares (PLS) regression for the simultaneous quantification of MTZ and SPI in tablets. Concurrently, it clarifies the steps to compute the limit of detection range, specifically the minimum and maximum values, in PLS methods. UV-Vis spectra of MTZ and SPI mixtures in standard concentration sets were scanned from 200–400 nm with a scan interval of 0.5 nm. The backward variable elimination–partial least square (BVE-PLS), and genetic algorithm–partial least square (GA-PLS) methods were employed for optimal wavelength selection. Analyte concentrations were computed via PLS methods using acquired spectral data. Multivariate regression models were evaluated via statistical parameters: the coefficient of determination (R²), root mean square error, and residual analysis. Methods were assessed following Association of Official Analytical Chemists guidelines. The results demonstrate that the BVE-PLS and GA-PLS wavelength selection methods produced superior computational outcomes compared to full spectral data PLS methods. Ultimately, simultaneous quantification methods for MTZ and SPI were successfully developed, validated, and shown to be accurate, straightforward, rapid, cost-effective, and stable.

A fluorescence polarization immunoassay method is developed to detect residual amounts of the nonsteroidal anti-inflammatory drug flunixin, commonly used for prevention and treatment in veterinary medicine and animal husbandry. The assay required only 15 min, including sample preparation, and demonstrated a linear detection range of 20–5000 ng/mL with a limit of detection of 2 ng/mL. The immunoreagents exhibited high selectivity for flunixin, with cross-reactivity coefficients for structurally related compounds remaining below 0.01%. the method for detecting flunixin in milk was validated using a spiking (standard addition) approach and it was confirmed that the sample preparation procedure reliably detected the analyte within the linear range. These findings demonstrate that the method, which employs polyclonal antibodies, enables the rapid, sensitive, and selective detection of flunixin in milk.

Multiple enhancement of metal lines in the emission spectrum of a drop-spark discharge was detected upon the introduction of nonionic surfactants into the sample. The effect arises at a Triton X-100 concentration higher than 1 wt % and is observed up to 35 wt %. The degree of enhancement depends on the concentration of the background electrolyte and attains two orders of magnitude for highly diluted acids (e.g., 10 mM HCl). In the presence of 1.5 wt % Triton X-100, the limits of detection for Cu, Cs, Mg, Li, and Pb decrease by one order of magnitude.

A green microextraction method entitled ‘ultrasound-assisted deep eutectic solvent (DES)-based liquid-liquid microextraction’ was devised for the pre-concentration of cobalt in water samples, with subsequent analysis performed via atomic absorption spectroscopy. Key extraction parameters were optimized, and the method was validated using central composite design for multivariate analysis. The DES was prepared by combining DL-menthol as a hydrogen bond acceptor and dodecanoic acid as a hydrogen bond donor in a 1 : 2 mass ratio. Under optimal conditions, pH of the solution, DES volume (µL), sonication time (min), and mass ratio of DES components were achieved, respectively: 5, 200, 9, and 1 : 2. The method demonstrated excellent linearity in the concentration range of 10–2000 µg/L, with a detection limit of 3.2 µg/L, quantification limits of 10 µg/L, relative standard deviations below 1.8%, and enrichment factors up to 234. The technique was successfully applied to determine cobalt concentrations in real samples.

The atmospheric pressure laser plasma ionization (APLPI) method, in combination with machine learning methods, is tested to solve the problem of vegetable oil classification. Samples of olive, rapeseed, sunflower, and linseed oils are studied. The samples are classified based on the mass-spectrometric profiles of volatile organic compounds emitted by the oils. It is shown that, in conducting hierarchical cluster analysis (HCA) with preliminary feature selection by the ANOVA method and reducing the dimensions of the response matrix using the t-distributed stochastic neighbor embedding (t-SNE), each type of oil forms a distinct cluster. Using an example of analyzing olive and rapeseed oil mixtures, it is demonstrated that a combination of the APLPI method with the multiple linear regression (MLR) method ensures the quantitative determination of the proportion of oils in the studied mixtures. The developed approach allows for the rapid and direct non-destructive analysis of vegetable oils without sample preparation and can be used to identify counterfeit products.

Hyper-crosslinked polystyrene is proposed for the purification of extracts after sample preparation by the QuEChERS method using multicomponent dispersive solid-phase extraction in the determination of residues of 19 pesticides in wheat grains by gas chromatography with tandem mass spectrometry detection. Sample preparation included extraction with water and acetonitrile followed by the purification of the extracts using hyper-crosslinked polystyrene. The method ensures the quantitative isolation of pesticides (recovery range from 66 to 100%). Pesticides are identified by selected transitions in the multiple reaction monitoring mode. The determination is performed using the matrix calibration method, the limits of detection and quantification are 0.03–0.3 and 0.1–1.0 μg/kg, respectively. An analysis of contaminated wheat samples show that the results satisfactorily coincide with the data obtained by the classical QuEChERS method in determining pesticide residues in agricultural products.

A binary mixture of isoniazid and mesalazine was analyzed by the application of the H-point standard addition method. The method is based on the difference in absorbance at the wavelength pair (∆λ) of 540 and 605 nm for the charge-transfer complexes formed between the above drugs as n-donors and o-chloranil as a π-acceptor in a basic medium. The results showed that isoniazid and mesalazine can be determined in their mixture, considering isoniazid as the analyte and mesalazine as the interferent at a weight ratio of 6.0 : 20.0 and 8.5 : 10.0, with recoveries from 94.3 to 105% and a relative standard deviation of less than 4.3%. Under optimum conditions, the suggested method was successfully applied to the simultaneous determination of isoniazid and mesalazine in synthetic and pharmaceutical formulations.

Processes of the chromatographic separation and the formation of negative ion (NI) mass spectra are studied by gas chromatography–mass spectrometry (GC–MS) in the resonance electron capture mode, implemented with the minimal technical modification of the domestic serial GC–MS Chromatec-Crystal complex, and a comparison with the basic positive ion (PI) mode upon electron ionization is made. It is found that the chromatographic retention time for isomers increases in direct proportion to the dipole moment of their molecules, illustrating the importance of intermolecular dipole interactions between the polar molecules of the analyte and the stationary phase. It is shown that the chromatograms by the total current of the NI recorded with the fast continuous scanning by the energy of ionizing electrons in the low-energy range 0–10 eV reflect well the component composition of the analyzed sample, and the integral mass spectra of the NI are characteristic of and selective for isomers, and are complementary in information content to the standard PI mass spectra. This is due to the predominance of nitro–nitrite rearrangements and the simple cleavage of the C–NO₂ bond during negative ion formation over H-shift reactions, dominating in the formation of PI from TNT isomers.

An ion-selective electrode is proposed for the rapid determination of ceftriaxone (Ceftr) in biological samples. The ion-pair of octadecylamine (ODA) with ceftriaxone is a ionophore of the ceftriaxone-selective electrode (Ceftr-ISE) membrane. To elucidate the membrane’s operation mechanism, we investigated equilibria in the membrane–solution system as functions of medium acidity and ionophore concentration. At pH values ranging from 6 to 9, the ion pair (ODA)(_{2}^{ + })·Ceftr^2– remains stable, and the membrane responds selectively to ceftriaxone. The optimal membrane composition for the Ceftr-ISE was determined as follows (wt %): (ODA)(_{2}^{ + })·Ceftr^2– 0.80, polyvinyl chloride 33.06, ODA 1.7 (100 mM), dioctyl sebacate 66.14. The internal electrolyte consisted of Ceftr (0.01 M) and KCl (0.01 M). The electrochemical performance of the Ceftr-ISE membrane was characterized by a linear response range from 1 × 10^–5 to 0.1 M, electrode slope of 24.9 mV per decade, and limit of detection of 8.3 × 10^–6 M. Potentiometric selectivity coefficients of the Ceftr-ISE were determined using the separate solution method. The electrode enabled the determination of Ceftr in blood and saliva samples from COVID-19 patients. The accuracy of Ceftr quantification was validated using the standard addition method.

Multivariate calibrations are used in spectrophotometric analysis to determine multiple analytes in multicomponent solutions. These calibrations relate generalized signals measured at multiple wavelengths with concentrations of the analytes. The aim of this study was to assess the applicability of inverted multivariate calibrations (IMCs) for the separate determination of similar analytes under conditions of nonadditive absorbance. The test samples were model aqueous solutions simultaneously containing Cu(II), Co(II), Ni(II), Zn(II), and Pb(II) along with an excess of the photometric reagent 4-(2-pyridylazo)resorcinol. In these solutions, statistically significant deviations from additive absorbance were observed, likely due to a shift in the complexation equilibrium. The input data for constructing the IMC were the spectra of model mixtures from the training set. The number of analytical wavelengths (m) and the number of mixtures in the training set (n) were varied during the experiment. The metal concentrations in the mixtures of the test set were calculated individually by multiple linear regression, using different spectral regions and different IMCs. The best results were obtained with m = 16 and n = 30. The determination errors for Co, Ni, and Zn in single mixtures did not exceed 25 rel % (in modulo), while the generalized errors (RMSEP) were 10–15 rel %. The determination errors for copper and lead were significantly higher. The experiment demonstrated that IMCs allow to determine the separate components of mixtures with similar but nonadditive spectra. However, the amount of the input data required must be significantly larger than in assessing the total amount of the same analytes, the accuracy of the results will be lower, and the correct determination of all analytes cannot be guaranteed.