Alumina–based electrodes offer promising possibilities for sensitive electrochemical sensors, but their development is hindered by poor intrinsic electrical conductivity. To overcome this limitation, new carbon-alumina composites were synthesized via a sol-gel method using two distinct calcination approaches: conventional and flash-calcination. The structural and textural properties of pure alumina samples were affected by the calcination approach. The introduction of carbon reduced the crystallite size and increased the specific micropore surface area and total pore volume of the samples. Electrochemical characterization by cyclic voltammetry and electrochemical impedance spectroscopy revealed that the optimal sample was obtained by conventional calcination for 30 min. This approach produced optimal structural integration, with a well-connected network and superior charge-transfer kinetics. The optimized carbon-alumina composite demonstrated excellent performance for the simultaneous electrochemical detection of methyl parathion and aclonifen by utilizing intermediate reduction products. The resulting sensor achieved wide linear ranges (0.5 to 20 µM) alongside low detection limits of 0.08 µM for methyl parathion and 0.14 µM for aclonifen, establishing these composites as effective materials for sensing applications.
Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) offers organic solvent-free powder analysis with high solid-state sensitivity. This positions the technique at the intersection of green analytical chemistry, solid form control, and ICH Q14-aligned, science- and risk-based method development. Despite these advantages, it remains marginal in regulated quality control. This review assesses the DRIFTS literature from Kubelka–Munk theory to current uses in pharmaceutical assays, solid-form quantification, drug-excipient interactions and medicines quality control, and asks why these favourable ergonomics have not been translated into regulatory acceptance. Seven of the nine univariate DRIFTS assays identified operate within a window of about 0.1–3.5% w/w analyte in KBr; two exceed it, with one reaching 30% w/w. Contrary to the common characterisation of the field as univariate, eighteen multivariate DRIFTS assay methods were identified together with a further nine multivariate solid-form methods, published continuously since 1988; what has remained univariate is the single-analyte tablet assay built on peak-area integration. This range is best read as an empirically observed working window for the systems reviewed rather than as a universal limit. Robustness evidence is dominated by single-laboratory, single-instrument, single-lot studies; where multi-lot performance was tested for polymorphic impurities, calibration models transferred poorly and standard outlier diagnostics disagreed. Reports are systematically silent on particle size distribution, packing protocol, diluent water content and ambient humidity. DRIFTS is well-suited to bounded roles: identity confirmation, solid-form screening, compatibility studies and in-house assay of formulations with a known, stable matrix. To advance the field, future efforts must prioritise rigorous evidentiary discipline over the development of new instrumentation.
Colistin is an antibiotic of critical importance in human medicine, while its use in animal production may result in the occurrence of residues in food products and contribute to the spread of antimicrobial resistance. Therefore, rapid and sensitive methods for monitoring colistin residues in meat are required. In this study, competitive lateral flow immunoassays (LFIAs) based on direct and indirect antibody labeling were developed and comparatively evaluated for the detection of colistin. In the direct format, gold nanoparticles (GNPs) were conjugated with specific anti-colistin antibodies, whereas the indirect format employed free specific antibodies and GNPs conjugated with anti-species antibodies. The direct LFIA provided visual and instrumental detection limits of 1.85 and 0.13 ng/mL, respectively. The indirect format demonstrated improved sensitivity, achieving visual and instrumental detection limits of 0.6 and 0.07 ng/mL, respectively. The developed assays were further evaluated using spiked chicken meat extracts. With four-fold dilution of the extracts in PBST, colistin recoveries ranged from 91 to 105% for the direct LFIA and from 90 to 117% for the indirect LFIA. The developed assay provides a rapid and sensitive approach for monitoring colistin residues in chicken meat and demonstrates the potential of indirect labeling as a strategy for improving the sensitivity of competitive lateral flow assays.
Antibiotics are among the most widely used classes of pharmaceuticals in modern medicine. Due to their frequent use, antibiotic residues have been detected in the environment, particularly in aquatic environments. In this study, HPLC method, with sample pretreatment was optimized and validated in order to analyze the presence of two commonly used antibiotics—cephalexin and tetracycline in water samples. Samples were collected from different sources, including wastewater, tap water, the Danube River and groundwater, in order to evaluate how the matrix affects the overall analysis. The main objective of this research was to develop an effective and reliable method for the detection of these antibiotic residues in water. A secondary aim was to establish the most effective sample preparation method. Samples were prepared using the dispersive solid-phase extraction (dSPE) technique with modified diatomaceous earth as the sorbent. The dSPE procedure was applied primarily for sample clean-up and reduction in matrix effects prior to HPLC-DAD analysis. The sorbents were characterized prior to use to investigate the influence of modification on their sorption properties.
Honey is recognized as a valuable tool for environmental biomonitoring, while its contaminant content is relevant to food safety, requiring analytical methods for the simultaneous determination of multiple contaminants. In this study, an ultrasound–vortex-assisted dispersive liquid–liquid microextraction (UVA-DLLME) procedure coupled with gas chromatography–ion trap mass spectrometry (GC–IT/MS) was developed for the simultaneous determination of pesticides, polycyclic aromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) in honey. The extraction solvent composition was optimized using different n-heptane/toluene mixtures, and the selected conditions were validated in terms of linearity, recovery, sensitivity, and precision. The optimized method provided recoveries between 70.2 and 112%, coefficients of determination (R2) from 0.9389 to 0.9998, limits of detection ranging from 0.40 to 21 ng g−1, and intraday and interday relative standard deviations below 15%. The environmental performance of the sample preparation procedure was evaluated using the AGREEprep metric, giving an overall score of 0.52. Application of the method to 21 artisanal honey samples showed a generally low occurrence of the investigated contaminants, with PAHs being the most frequently detected compounds, whereas pesticides and PCBs were mostly below the limits of detection or quantification. The proposed method represents a solvent-efficient analytical procedure suitable for the multiclass determination of organic contaminants in honey.
