Analytical Methods最新文献

Use of FTIR spectroscopy together with isotopic exchange offers a powerful approach towards understanding cation dependence of water uptake in alkali perchlorate salts at room temperature. ATR-FTIR data reveal distinct vibrational features of H₂O, HDO, and D₂O isotopologues entrapped in LiClO₄ and NaClO₄ matrices, as opposed to the case of KClO₄, where no discernible IR-spectral evidence is provided for the presence of water. Moreover, precipitates of the co-dissolved aqueous mixtures of LiClO₄ + NaClO₄ and LiClO₄ + KClO₄ always end up having water trapped within the LiClO₄ matrix, evidenced and validated by the isotopically substituted IR spectral features, even though the presence of the other salts (i.e. NaClO₄ in the former mixture and KClO₄ in the latter one) is verified by the use of both X-ray diffraction and X-ray photoelectron spectroscopic data. A ternary mixture has also been investigated, which supports the surprisingly strong cation dependence of the water uptake of these alkali perchlorate salts. Our results indicate that the order of water uptake is LiClO₄ > NaClO₄ >> KClO₄ crystals, which can qualitatively be correlated with charge density of their corresponding cations.

A rapid in situ analytical method combining ultrasonic nebulization extraction with atmospheric pressure photoionization mass spectrometry was developed for direct detection of endogenous compounds in complex tobacco matrices. The ultrasonic nebulization enabled efficient extraction and aerosolization of samples, while dopant-assisted photoionization significantly enhanced ionization efficiency (e.g., the nicotine signal increased by ∼100-fold). A total of 35 endogenous constituents, including alkaloids, organic acids, phenols, and amino acids, were characterized. Under optimized conditions, the relative standard deviations of nicotine and salicylic acid signals were 4.8% and 5.6% (n = 11) in positive and negative ion modes, respectively, indicating good precision. The standard addition method effectively minimized matrix effects and allowed accurate quantification of eight representative compounds such as nicotine, quinic acid, and proline, all showing excellent linearity (R² > 0.99) with contents ranging from 0.03 to 20.4 µg mg^-1. The method requires no tedious pretreatment or chromatographic separation, offering in situ, rapid, and sensitive analysis with minimal sample consumption, and providing an efficient new strategy for qualitative and quantitative profiling of chemical constituents in tobacco and other economic crops.

Breast cancer is one of the most serious threats to women's health. The simultaneous detection of tumor markers is crucial for improving the survival rate of patients. Herein, a potential-resolved electrochemiluminescent (ECL) aptasensor has been developed for the simultaneous detection of MUC1 and HER2 proteins on the surface of breast cancer cell-derived exosomes. Exosomes were specifically captured via CD63 aptamers immobilized on an indium tin oxide (ITO) electrode. Ru(bpy)₃²⁺@SiO₂ nanoparticles (Ru@SiO₂) and luminol@Au nanoparticles (lum@Au) labeled with the corresponding aptamers of the MUC1 and HER2 proteins, respectively, were employed as ECL nanoprobes to specifically recognize these two proteins expressed on exosomes, and were anchored on two independent regions of an ITO electrode patterned by polydimethylsiloxane (PDMS). This physical isolation eliminated ECL resonance energy transfer (ECL-RET) between the nanoprobes. The ECL behaviors of the two nanoprobes at different potentials were recorded under cyclic voltammetry scanning, achieving the simultaneous detection of both proteins. Under the optimized conditions, the ECL aptasensor exhibited favorable linear response relationships for MUC1 and HER2 on four types of exosomes, thus enabling the quantitative analysis and the reliable discrimination of these distinct exosomal subtypes. Endowed with excellent specificity, stability and reproducibility, this aptasensor was further applied to the detection of serum samples, demonstrating potential for clinical application.

Accurate nitrite detection in beverages and pickled foods is crucial for food safety but remains challenging due to matrix complexity, particularly interference from salinity. To address this, a highly sensitive electrochemical sensor was constructed by modifying a screen-printed electrode with an electrodeposited platinum–palladium nanoparticles/gold layer (Pt–Pd NPs/Au/SPE). The electrocatalytic effect of the bimetallic nanoparticles conferred a 1.60-fold sensitivity enhancement, enabling the sensor to achieve a wide linear range (1–7500 µM), a low detection limit of 0.11 µM, and high sensitivity (226.03 µA mM⁻¹ cm⁻²). Crucially, quantification errors caused by salinity were corrected through a novel strategy that couples the developed Pt–Pd NPs/Au/SPE sensor with a commercial salinity meter. The NaCl concentration measured with the salinity meter served as the key input to a multilayer perceptron (MLP) neural network, which specifically compensated for the matrix effect. This intelligent compensation reduced the mean absolute error of nitrite quantification from 45.99% to 4.14%. The method was successfully applied to commercial beverages and pickled food, such as cola, milk, and pickled ginger, onion, garlic, and mustard, achieving recoveries of 92.77–106.56%. This work provides a reliable tool for food analysis and demonstrates a practical AI-assisted approach to overcome matrix interference in electrochemical sensing.

The lateral flow immunochromatography assay (LFIA) offers a rapid and on-site method for food safety. However, the current LFIA shows a limitation due to the random binding between the label and antibodies resulting in target recognition sites on the antibody being occupied yielding false-negative outcomes. To address these issues, this study utilized genetic engineering technology to integrate the super folded green fluorescent protein (SGFP) gene into the sequence of a specific nanobody for fenpropathrin, a Nb-SGFP fluorescent probe, realizing site-directed modification to avoid the block of recognition sites. Meanwhile, it also minimizes potential antibody performance issues during the process that may affect antibody affinity. Based on this, a fluorescent strip detection method was established, providing a new strategy for efficient and convenient detection of fenpropathrin. The detection limit of the method was 1.2 ng mL⁻¹, which adequately met the sensitivity requirements for fenpropathrin detection. To validate its accuracy, the fluorescent test strip method was compared with GC-MS/MS analysis. The strong correlation between the two methods confirms that our approach enables rapid detection of fenpropathrin residues in fruits and vegetables.

A newly identified selective interaction between As(III) and luminol enhances the formation of excited 3-aminophthalate, thereby amplifying the ECL signals. The luminol/As(III) ECL response was observed across all studied electrodes; however, Au/BDD was selected for its highest sensitivity, driven by the strong electrocatalytic activity of the immobilized gold nanoparticles.

We present a simple, reagent-free method to quantify cyanuric acid (CYA) in tap water by analyzing the drying patterns of CYA solution droplets. The analytical signature is a set of white dendritic columns that grow radially from the droplet perimeter toward the center, a pattern not observed for other common dissolved organic compounds in tap water. Patterns were recorded with a basic optical camera under dark-field illumination, and their morphology varied systematically with CYA concentration. The deposits consist mainly of CYA together with ions naturally present in tap water. Using a deep learning model with data augmentation and statistical analysis, we proposed an algorithm for accurate quantitation over 0–120 ppm. The method performs best under neutral to slightly acidic conditions and is compatible with free-chlorine at the levels used for water sanitation. To our knowledge, this is the first demonstration of quantitation of an analyte in a complex mixture based on image analysis of droplet drying pattern. The approach is low cost and requires only imaging and data analysis, although it does require waiting for droplet drying (ca. 2 h under ambient conditions). The practical constraints include repeatable sampling volume (ca. 50 µL) and keeping illumination conditions as in the calibration set.

The escalating global reliance on synthetic pesticides to secure agricultural productivity has intensified concerns over their adverse impacts on human health and ecosystems. With pesticide exposure linked to severe pathologies—including neurotoxicity, endocrine disruption, and carcinogenesis—there is an urgent need for rapid, sensitive, and field-deployable monitoring tools. Conventional analytical methods such as gas or liquid chromatography coupled with mass spectrometry offer high accuracy but are impractical for on-site, real-time screening due to their cost, complexity, and infrastructure demands. In response, optical (bio)sensor arrays have emerged as powerful alternatives that mimic biological sensory systems by generating multidimensional response patterns (analyte-specific fingerprints) from ensembles of cross-reactive sensing elements. This review provides a comprehensive and mechanism-driven analysis of the key sensing element classes used in these arrays for pesticide detection, including label-free plasmonic nanoparticles, chemosensors, host–guest systems, enzymes, antibodies, and aptamers. This review critically evaluates the operational principles, recent advances, practical limitations, and real-world applicability of each platform. By unifying diverse sensing paradigms under a common conceptual framework, this review distills key design principles from reported optical sensor arrays and provides actionable guidance for designing practical platforms to detect and discriminate pesticide residues—balancing robustness, simplicity, and scalability for real-world environmental and food safety applications.

We present a novel one-step methodology for direct mass spectrometric characterization of sulfated non-saccharide glycosaminoglycan mimetics in their sodiated form using the high reactivity of trifluorodiazoethane to form hydrophobic and chemically stable esters that facilitates separation and detection in a liquid chromatography–mass spectrometry system. The methodology preserves all sulfates present in the parent molecule, thereby allowing for accurate mass characterization of the per-sulfated molecule.

Laser cleaning is a precise, ‘touch-free’ technique that uses focused laser radiation to remove contaminants from surfaces. It has become increasingly popular in a cultural heritage context due to its ability to target contaminants with minimal damage to underlying materials, particularly where traditional mechanical or chemical cleaning may pose risks to delicate surfaces. However, every cleaning intervention requires a degree of assessment and monitoring, and lasers are no different. This Technical Brief will provide an overview of the physical phenomena behind laser cleaning, give examples of successful cultural heritage applications and list the main pros and cons of the technique.