Analytical Methods最新文献

In this study, a modified "Quick, Easy, Cheap, Effective, Rugged, and Safe" (QuEChERS) sample preparation method, utilizing gas chromatography tandem mass spectrometry (GC-MS/MS), was employed for the simultaneous analysis of 222 pesticides in roasted coffee beans. The range and linearity of calibration curves, as well as the accuracy and intermediate precision, were assessed using spiked samples. Additionally, the Limits of Detection (LOD) and Quantitation (LOQ) were evaluated. The method has been linear in the 0.01-0.1 mg kg^-1 range. For most analytes, the mean recovery and Relative Standard Deviation (% RSD) were within the 70-120% range and under 20%, respectively. The mean recovery for all pesticides was 100.92 ± 10.69% at 0.015 mg kg^-1, 107.61 ± 7.77% at 0.03 mg kg^-1, and 96.63 ± 9.07% at 0.06 mg kg^-1. Method validation demonstrated quantification capabilities for 222 analytes, with LOQs of 0.01 mg kg^-1 for 194 pesticides (87.4%), 0.015 mg kg^-1 for 26 compounds (11.7%), and 0.02 mg kg^-1 for the remaining 2 analytes (0.9%). Upon comparing the results with the requirements of SANTE/11312, it is evident that the method meets the necessary criteria to ensure the quality control of real samples. Out of 16 tested real coffee bean samples, three Arabica coffee bean samples contained residues of Flutriafol below the LOQ.

Hydrazine (N₂H₄) is a highly toxic and versatile chemical raw material that has been widely used in industrial production and agricultural applications, but it has also caused environmental pollution. In this research, a fluorescent probe SDG-2 was designed and synthesized for hydrazine detection through esterification functionalization of pyridinium acylion. Hydrazine induces the hydrolysis of the ester group in SDG-2 to a hydroxyl group, thereby creating an intramolecular hydrogen bond donor that results in fluorescence enhancement, characteristic of sensitive N₂H₄ monitoring. Analytical results demonstrate that SDG-2 achieves an exceptional detection limit of 0.43 μM with a linear response spanning 20-250 μM. The probe exhibits remarkable selectivity and resistance to interference from competing analytes, accompanied by recovery rates ranging from 92.40 to 106.27% in practical sample analysis. This work establishes a robust molecular platform with significant potential for environmental hydrazine assessment, featuring both operational convenience and analytical reliability. The mechanistic insights into IMHB-mediated sensing provide valuable guidelines for developing advanced fluorogenic probes for environmental chemistry applications.

The development of advanced chemiluminescent compounds and hematology methodologies has significant implications for forensic science, particularly for the detection of evidential residues at crime scenes. This study introduces a novel chemiluminescent (CL) method that utilizes a smartphone to produce digital videos of the chemiluminescent reaction between the luminol (5-amino-2,3-dihydrophthalazine-1,4-dione) reagent and blood. This innovative approach significantly reduces reagent consumption by 6 times, requiring less than 1 mL/0.01 g of sample/chemicals, which agrees with green chemistry principles. Blood samples used in this study were sourced from bovine liver and human subjects and were collected by the official forensic police at crime scenes. All samples were subsequently discarded by the criminal police. Frames from a 3-minutes video were processed using ImageJ software and the Color Grab app to generate RGB, HSV, and CMYK pattern recognition, combined with chemometric modeling. This enabled the differentiation of samples based on positive and negative patterns, effectively preventing false results. The pattern recognition models developed were able to distinguish bovine from human blood, even after dilution, which simulated attempts to hide traces at crime scenes through washing. The method demonstrated an accuracy of 90.30% with only four prediction errors and presented 100% sensitivity and specificity for the cotton + ceramics class, with 77.78% sensitivity and 93.10% specificity for both the wood and glass classes. Additionally, it was possible to estimate the age of the samples with a precision of 3.6 days. These results were obtained using a new data fusion strategy that facilitated the modeling of digital videos as a combination of frames to enhance model sensitivity and selectivity without increasing model complexity. These results indicate that the developed method is accurate, sensitive, and rapid. Supported by these results, this method represents a significant advancement in forensic science, offering a practical and efficient solution for crime scene investigations.

Cytotoxic drug 5-fluorouracil (5-FU) is a fluorine derivative of uracil; it is one of the most significant medications used to treat cancers of the stomach, breast, colon, pancreas, and cervical regions. Here, a reliable, rapid, highly sensitive and selective method is proposed for determining 5-FU in real samples. In this study, a molecularly imprinted polymer (MIP) based electrochemical sensor is designed for the sensitive and selective determination of 5-FU. The MIP was developed by the electropolymerization of a pyrrole thin film around template molecules (5-FU) on a glassy carbon electrode (GCE). The sensor was characterized after each stage of fabrication using cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). The MIP sensor exhibited a wide linear range for determining 5-FU from 2-42 μM. The developed sensor achieved a limit of detection (LOD) and limit of quantification (LOQ) of 0.605 μM and 1.834 μM, respectively. The applicability of the proposed sensor was examined for 5-FU determination in real samples. The MIP sensor exhibited excellent selectivity, repeatability, stability, and commercialization potential for 5-FU detection. Furthermore, the proposed method offers significant advantages over existing electrochemical techniques for 5-FU detection. This method provides single-step preparation alongside simple template molecule removal by cyclic voltammetry scans and does not need any extracting solvents.

Rapid prototyping and 3D-printed devices have become important enabling technologies for measurement science. Work presented here aims to add to the 3D-printed toolset by demonstrating the economical production and application of printed centrifuge and electrode holders for micro and nanoelectrodes. These holders provide freedom of configuration and design and can also circumvent availability issues which may exist for commercial electrode holders. Here we demonstrate 3D-printed centrifuge holders which aid in filling small pipettes with fluid and 3D-printed electrode holders used both in electroanalytical probe characterization and in scanning ion conductance microscopy.

Metabolic molecules are highly correlated with various physiological indicators and diseases, so it is particularly important to monitor the levels of multiple metabolites in the body. Due to the similar electrochemical properties of uric acid (UA), dopamine (DA), and ascorbic acid (AA), multi-component detection of these substances is challenging. When establishing relationships between electrochemical characteristics and concentrations of the respective components, there will be issues such as overlapping peaks and other difficulties. In order to accurately identify the components and determine their concentration in the detection solution, we designed a multi-component detection experiment for AA, UA, and DA. After obtaining the detection results, we applied curve smoothing and feature extraction to construct classification and regression machine learning models. The ANN model achieved the highest accuracy of 94.06% among the five classification models evaluated. Regression models were built using RF and XGBoost, with the best performing XGBoost model achieving an average R-squared prediction of 96.2%. With high component discrimination and prediction accuracy, these models ensure user-friendliness and support qualitative and quantitative analysis of multi-component solutions.

Erdafitinib (ERDF), despite its known adverse effects, remains a key chemotherapeutic agent for metastatic urothelial carcinoma, requiring reliable monitoring in biological matrices to ensure safe and effective treatment. In this study, we developed a cost-effective, energy-efficient method for synthesizing highly fluorescent nitrogen-doped carbon dots (NCDs) using simple precursors. The resulting NCDs displayed excellent photostability and a high fluorescence quantum yield of 41.87%. ERDF induced a concentration-dependent quenching of the NCDs' fluorescence at 520 nm, attributed to the inner filter effect, with a low detection limit of 0.013 μM (S/N = 3). The NCDs demonstrated high selectivity toward ERDF with minimal interference from coexisting substances. Recovery rates in spiked human serum and urine ranged from 97.8% to 104.4%, validating the method's practical applicability. The relative standard deviations (RSDs) remained below 3.72%, confirming the precision and reproducibility of the NCD-based sensing platform.

In this study, a molecularly imprinted polymer (MIP) filter, modified with natural polyphenols extracted from green tea, was employed for the extraction of levothyroxine, followed by analysis via high-performance liquid chromatography with ultraviolet-visible detection (HPLC-UV). The filter's characteristics were comprehensively assessed using Fourier-transform infrared spectroscopy (FT-IR) to identify functional groups, scanning electron microscopy (SEM) to examine surface morphology, energy-dispersive spectroscopy (EDS) for elemental analysis, and X-ray diffraction (XRD) to elucidate crystalline structure. Following the passage of sample solutions through the filter, which was integrated with a solvent delivery system, and optimization of extraction parameters by response surface methodology (RSM), a linear range of 1 to 1000 μg L^-1 was achieved for levothyroxine, with a coefficient of determination of 0.9999. The limit of detection and limit of quantification were 0.36 μg L^-1 and 1.19 μg L^-1, respectively. The method has an enrichment factor ranging from 245.0 to 250.5. Furthermore, the effect of the matrix on the extraction was insignificant. Applying this method to biological samples of blood serum and urine yielded recoveries exceeding 98.3%, with RSD below 6.1%.

Besifloxacin (BFN), a fluoroquinolone antibiotic, exhibits weak native fluorescence intensity. A sensitive and rapid spectrofluorimetric approach was developed to enhance the intrinsic fluorescence of BFN through complexation with zinc(II) as an electron acceptor in phosphate buffer (pH 6.0). The resulting BFN-Zn²⁺ complex demonstrated high fluorescence intensity, enabling highly sensitive detection of BFN. Among various tested metal ions, Zn²⁺ was effective in enhancing the native fluorescence of BFN due to its favorable ionic radius, flexible coordination number, and strong affinity for oxygen and nitrogen donor atoms present in BFN. Under optimum conditions, a significant increase in the intensity of BFN fluorescence was observed at 440 nm following excitation at 274 nm. The quantification and detection limits were calculated to be 6.08 and 2.0 ng mL^-1, respectively, and the relationship between emission intensity and BFN concentration was linear from 10 to 150 ng mL^-1. Notably, the binding ratio between BFN and Zn²⁺ ions was found to be 2 : 1, respectively, and this ratio was confirmed by the Job's plot method. The method was validated according to ICH guidelines. The proposed method was successfully applied to quantify the cited drug in its pure state, ophthalmic preparations, and spiked aqueous humor with recovery values ranging from 96.29% to 98.21% in aqueous humor samples.

Nitrofurantoin (NFT) is a broad-spectrum antibiotic used for the treatment of humans, poultry and livestock. Improper use and discharge of NFT can cause serious harm to human health and the environment. Electrochemical analysis has been widely employed in antibiotic detection because of its advantages of simple operation, high sensitivity and rapid response. However, few studies have reported the detection of NFT using this method owing to the limited availability of electrode materials. Layered double hydroxides (LDHs) have attracted widespread attention because of their unique structure and chemical properties as well as the advantages of homogeneous dispersion of laminate elements and adjustable chemical composition. However, their application in NFT detection has rarely been reported due to the inherent defects of weak conductivity and poor stability. To better use LDHs and overcome their shortcomings, a series of superlattice FeCu₃-LDH/MoS₂ materials were successfully designed using stripping and self-assembly strategies. FeCu₃-LDH/MoS₂ modified carbon paper (CP) was used as an integrated sensor for NFT detection. Benefiting from the structural advantages of the superlattice material and dual-synergistic catalysis between the LDH and MoS₂, FeCu₃-LDH/MoS₂/CP (1 : 1) exhibited highly sensitive NFT detection, with a low detection limit. FeCu₃-LDH/MoS₂/CP (1 : 1) could also be successfully applied for NFT determination in real samples, such as human serum, lake water and commercialized drugs, with satisfactory recovery. This work not only provides an effective electrochemical detection method for NFT determination, but also broadens the application of LDHs in the electrochemical field and lays a foundation for the controllable preparation of electrochemical sensors based on superlattice materials.