Analytical Methods最新文献

In order to develop a highly efficient H₂S gas sensor at low working temperature, in this work, a kind of novel Ce-doped ZnCo₂O₄ hollow microspheres (Ce/ZnCo₂O₄ HMSs) were successfully synthesized using a template-free one-pot method, showing a sensitive response toward H₂S. The microstructure and morphology of the material were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The gas-sensing performance of the composite was investigated, showing that the ZnCo₂O₄ doped with 6 mol% Ce had the highest response to 20 ppm H₂S at a low operating temperature of 160 °C with a response value of 67.42, which was about 2 times higher than that of original ZnCo₂O₄. The prepared Ce/ZnCo₂O₄ HMS sensor in response to H₂S exhibited a linear range of 0.1-200 ppm with a low detection limit of 0.1 ppm under the conditions of ambient humidity of 45% and ambient temperature of 20 °C. Meanwhile, it also possessed good selectivity, repeatability and reproducibility. The response value of the sensor decreased by 5.32% after 7 months of continuous monitoring of H₂S in an atmospheric environment of a pig farm, indicating that the sensor had a long-term stability and continuous service life with important application prospects.

High-frequency pulse lasers, applied in the form of rapid scanning, act upon the surface of aircraft skin paint layers, thereby removing the paint layers, exhibiting characteristics of efficiency and eco-friendliness. Real-time monitoring of the paint removal effect and prevention of substrate damage necessitates the continuous monitoring of paint removal thickness. Combining Laser-Induced Breakdown Spectroscopy (LIBS) online monitoring technology enables laser-controlled paint removal under multiple effects coupling, meeting the requirements of airworthiness maintenance. This paper, based on a high-frequency nanosecond infrared pulse laser paint removal LIBS monitoring platform, conducts research on laser paint removal thickness LIBS online monitoring of aluminum alloy plates coated with dual-layer paint. Spectra corresponding to the removal thickness of each group are collected and, respectively, paint removal thickness monitoring models based on LIBS spectra are established using the standard curve method and Principal Component Analysis-Support Vector Regression (PCA-SVR) algorithm. When monitoring paint removal thickness using the standard curve method, the intensity of five Ti element characteristic spectral lines selected is correlated with the paint removal thickness, and segmented curve fitting according to the paint layer structure satisfies the segmented curve fitting of topcoat and topcoat + primer. Among them, the average coefficient of the curve fitting of the Ti II 589.088 nm characteristic spectral line is 0.89, and the root mean square error (RMSE) is 12.28 μm. Its performance is superior in the five standard curves; thus, its fitting equation is used as the criterion for paint removal thickness monitoring. To further improve monitoring accuracy, research on paint removal thickness monitoring models based on PCA-SVR is conducted. Compared to the traditional univariate standard curve method, the PCA-SVR model does not require segmented monitoring. After parameter optimization, the average fitting coefficient reaches 0.97, and the RMSE is 2.92 μm. The results indicate that the PCA-SVR-based paint removal thickness monitoring model has higher accuracy, thereby forming the basis for paint removal thickness monitoring. Through comparative research on paint removal thickness monitoring models, two types of paint removal thickness monitoring criteria are obtained, providing model solutions for high-precision monitoring and automation of aircraft skin laser paint removal thickness.

This work deals with the rapid and simple determination of the probable carcinogen ethyl carbamate (EC), which is naturally present in fermented food products. An undemanding, robust, and rapid pre-column derivatization utilizing a 9-xanthydrol reagent has been developed. The resulting derivative was subsequently analysed by reversed-phase high-performance liquid chromatography coupled with fluorescence detection. As a result of the thorough optimisation of the chromatographic conditions, the run was completed in just 5 minutes, considerably speeding up the usual time of EC separation (30-60 min). Thanks to the fast separation, satisfactory yields (around 90%), negligible matrix effects, no interfering peaks, very low detection limit, and simple sample pre-treatment (for the very first time, the derivatization was performed in the presence of light and without any extraction step), the proposed method represents a significant improvement of the EC determination protocol used so far. After method validation, a total of fifty food samples were subjected to analysis without any additional sample pre-treatment despite their diverse matrix. Due to its robustness, simplicity, and low time, cost, and manual demands, this method is suitable for rapid screening of EC in both final food products and during their production.

Influenza A virus (IAV), a common respiratory infectious pathogen, poses a significant risk to personal health and public health safety due to rapid mutation and wide host range. To better prevent and treat IAV, comprehensive measures are needed for early and rapid screening and detection of IAV. Although traditional laboratory-based techniques are accurate, they are often time-consuming and not always feasible in emergency or resource-limited areas. In contrast, emerging point-of-care strategies provide faster results but may compromise sensitivity and specificity. Here, this review critically evaluates various detection methods for IAV from established laboratory-based procedures to innovative rapid diagnosis. By analyzing the recent research progress, we aim to address significant gaps in understanding the effectiveness, practicality, and applicability of these methods in different scenarios, which could provide information for healthcare strategies, guide public health response measures, and ultimately strengthen patient care in the face of the ongoing threat of IAV. Through a detailed comparison of diagnostic models, this review can provide a reliable reference for rapid, accurate and efficient detection of IAV, and to contribute to the diagnosis, treatment, prevention, and control of IAV.

It has been well-elaborated that KIN17 protein is closely related to the expression, development and prognosis of liver cancer; however, till date, there has been no study about detecting the KIN17 protein in serum, which is important to developing clinical applications. The objective of this work is to detect serum KIN17 protein by the ELISA method and to explore the diagnostic significance of the KIN17 protein in liver cancer. First, we verified the ELISA method for serum KIN17 measurement according to five aspects: accuracy, precision, specificity, stability and detection limit. Results illustrate that the recovery rate of the ELISA method can be controlled between 90% and 110%, the variation coefficient of intra-assay can be controlled within 16%, and the variation coefficient of inter-assay can be controlled within 10%. There is no non-specific reaction with common tumor markers, and the detection limit can reach 0.125 ng mL^-1. The results show that the KIN17 protein can be detected by ELISA, and there is a significant rise in KIN17 concentration in a liver cancer group compared with a healthy group, whose average concentrations are 1.730 ng mL^-1 and 0.3897 ng mL^-1, respectively. On this basis, we hypothesize that the serum KIN17 protein can serve as a potential biomarker of liver cancer and be measurable with the verified ELISA system after specific ultrafiltration and centrifugation, which is of great significance for the diagnosis and treatment of liver cancer.

In this work, two types of optical sensors were prepared for the quantification of potassium: the bulk optode (BO) and nano-optode (NO). The BO was prepared using three main components: the ionophore valinomycin, the ion exchanger tetrakis(4-chlorophenyl) potassium borate (K-TCPB), and the chromoionophore ETH 5294 (CHI). The optimal composition was found to be in a ratio of [1 : 1 : 1]. The NO was prepared by miniaturizing the BO through sonication in surfactant Pluronic F-127. The working range for the linear calibration model of BO was from 10^-6 to 1.0 M K⁺ with a LOD_BO = 0.31 μM, meanwhile for NO was from 10^-4 to 1.0 M K⁺ with a LOD_NO = 30.3 μM. Both optodes were tested for selectivity towards K⁺ in the presence of alkaline and alkaline earth ions, with a selectivity coefficient > 1.0. Furthermore, precision and stability studies of BO and NO were performed for three levels of K⁺ concentrations, 10^-6, 10^-3, 1.0 M for BO and 10^-4, 10^-2, 1.0 M for NO, showing a good homogeneity of the NO in the whole concentration range. However, an excessive variability was obtained for BO at 1.0 M K⁺. Therefore, the NO represents a potential tool for quantification of K⁺.

Fumonisin B1 (FB1) is a mycotoxin, a water-soluble metabolite produced by Fusarium cepacia, which mainly contaminates grain and its products and is acutely toxic and potentially carcinogenic to certain domestic animals. In this work, plasma nanocomposites of Fe₃O₄@Cu@Cu₂O with magnetic and optoelectronic properties were synthesized as a sensing platform. On one hand, the surface plasmon resonance (SPR) of metallic Cu accelerates the electron transfer rate. On the other hand, plasma-induced resonance energy transfer of metals and semiconductors can improve the utilization efficiency of light energy. A split photoelectrochemical (PEC) sensor based on Fe₃O₄@Cu@Cu₂O was proposed for the detection of FB1. The sensor has a wide linear range of 1.0-10 000 pg mL^-1 and a low detection limit of 0.28 pg mL^-1 (LOD, S/N = 3), which can realize the specific detection of FB1 in real samples.

The objective of the current study was to develop a simple method to measure fatty acid soaps, making use of FT-IR, representative for the soap formation observed in clinical trials. Calcium soaps have a unique coordination which leads to a typical double-splitting of the antisymmetric and symmetric carboxylate peaks. Absorbance values of these carboxylate peaks were used together with the absorbance of the hydrocarbon -CH₂ antisymmetric and symmetric peaks to calculate the calcium soap absorbance. Based on the linear correlation between the calcium soap absorbance and the calcium soap concentration measured with GC-FID, a model was set-up and subsequently successfully validated to quantify calcium soap concentrations in faecal samples from clinical trials with this FT-IR method. With in vivo as well as in vitro digestion an inverse correlation between the long chain saturated fatty acid part of milk fat containing fat blends used for the infant formulas, and the formation of fatty acid soaps after digestion and defaecation could be observed. There is a clear link between the amount of long chain saturated fatty acids at the sn-1/3 position and their release as free fatty acid after lipolysis with the appearance of fatty acid soaps. These insights enable future development of fat blends for infant nutrition to optimize fatty acid soap formation and thereby gut discomfort in infants. These insights can be used to predict the soap formation capacity of a newly designed fat blend and thereby the improvement of infant nutrition products.

Worldwide, plant pathogens have been a considerably important cause of economic loss in agriculture especially in the decades of agricultural intensification. The increasing losses in agriculture due to biotic plant diseases have drawn attention towards the development of plant disease analyzing methods. In this context, biosensors have emerged as significantly important tools which help farmers in on-field diagnosis of plant diseases. Compared to traditional methods, biosensors have outstanding features such as being highly sensitive and selective, cost-effective, portable, fast and user-friendly operation, and so on. There are three common types of biosensors including electrochemical, fluorescent, and colorimetric biosensors. In this review, some common biotic plant diseases caused by fungi, bacteria, and viruses are first summarized. Then, current advances in developing biosensors are discussed.