Analytical Methods最新文献

In the field of global health, the quality of Traditional Chinese Medicine (TCM) holds pivotal significance. Ensuring the clinical efficacy and medication safety of TCM not only enhances international trust in TCM, injecting strong impetus into the process of TCM globalization, but also promotes the dissemination of traditional medical culture, strengthens cultural exchanges between China and foreign countries, enriches the global medical system, and realizes complementary advantages with modern medicine. In recent years, the application of fingerprinting combined with chemometrics in TCM quality evaluation has attracted increasing attention from both academic and industrial circles. Among them, fingerprinting technology can intuitively display the overall characteristics and internal correlations of chemical components in TCM, while chemometrics, by means of multivariate statistical analysis, pattern recognition and other methods, performs dimensionality reduction on fingerprint data, constructs new models, and thus deeply excavates the potential effective information hidden in the data. The synergistic application of these two technologies in TCM quality evaluation shows significant advantages: in terms of TCM origin tracing, it can accurately analyze the differences in TCM components under different producing areas and growth environments, realizing precise traceability of medicinal materials; in the work of authenticity identification, it can effectively identify counterfeits by comparing characteristic fingerprints and data differences, ensuring the authenticity of medicinal materials; in the content determination link, combined with chemometric algorithms, it can realize simultaneous quantitative analysis of multiple components, improving detection efficiency and accuracy; for compound TCM, this technology combination can comprehensively consider the interactions among various components to conduct comprehensive quality evaluation. This article systematically reviews the research progress of the integration of this technology in the field of TCM quality evaluation in recent years, elaborates on the research overview in various key links and the specific methods of compound medicine quality evaluation, and looks forward to its future development trends and application prospects. It aims to provide strong support for constructing a standardized, standardized and comprehensive theoretical research system of TCM, and help realize the goals of precision, clarity, predictability and controllability of TCM quality.

Rosa rugosa Thunb. can be skillfully blended with high-quality, mellow Baijiu to produce Rose Lujiu (RL), which emits a delightful aroma. In this study, e-nose, e-tongue, GC-MS, and GC-IMS were employed to analyze the aromatic compounds. Relative odor activity value (ROAV) analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to comprehensively assess volatile compounds and predict key aroma compounds. A total of 111 volatile compounds were identified using GC-MS analysis. Additionally, GC-IMS analysis identified a total of 70 aroma compounds, among which 13 key contributors to the aroma were determined based on odor activity thresholds. These results indicate that ethyl acetate, ethyl butanoate, propyl hexanoate, and 3-methyl-1-butanol emerged as pivotal odorants enabling discrimination among different RL samples. These findings would provide valuable data for the application of commercial samples in the flavor modulation of RL.

The growing concern about chemical contaminants in food has increased the need for a rapid, selective, and cost-efficient sensing technology. Molecularly imprinted polymers (MIPs) have emerged as potential artificial sensing elements owing to their high sensitivity, stability, selectivity, and reproducibility. Recent advances further highlight the growing role of computational tools, including molecular docking, molecular dynamics (MD), quantum chemical calculations (QC), and molecular mechanics (MM), in rational MIP design. These methods guide the rational selection of monomers, solvents, and cross-linkers by predicting their effects on template interactions, solvent polarity, and cavity stability, thereby minimizing trial and error in MIP design. This review presents a comprehensive overview of recent progress in MIP-based sensors for the detection of chemical contaminants in food, emphasizing experimental and computational perspectives. In addition, this review covers chromatography-integrated MIP systems, where imprinted polymers are used as selective recognition elements within separation-based methods for food contaminant analysis. The reviewed platforms enable not only sensitive detection but also reliable quantification of food contaminants across diverse matrices. Special focus is given to case studies that demonstrate the applications of MIPs in food analysis and the role of in silico strategies in optimizing sensor performance. By bridging experimental innovation with a computational design, this review aims to provide researchers with an integrated framework for developing next-generation sensing platforms that are selective, sensitive, and practical for real-world food safety monitoring.

Cysteine (Cys) is an essential sulfur-containing amino acid in the human body and is involved in many important physiological processes. The reliable detection of Cys is of great significance for the precise diagnosis of diseases. Fluorescent probes are powerful tools for the detection of Cys. In the study, we designed and synthesized a series of Cys-recognizable fluorescent probes by employing different recognition groups and conjugated units. Our results demonstrated that the probe based on acrylate and acrolein emits almost no fluorescence in organic solvents, whereas it achieved a near-infrared fluorescence emission (652 nm) due to the excited-state intramolecular proton transfer (ESIPT) effect in the presence of Cys. Importantly, the probe exhibited high selectivity and fast response time (in 10 min). In particular, the limit of detection (LOD) is as low as 3.42 × 10⁻⁴ µM. This probe has been successfully applied for the detection and imaging of Cys in biological cells.

Rapid and accurate detection of allergenic components, such as peanuts and soybeans, in food products is crucial for ensuring the dietary safety of individuals with allergies. In this study, a rapid dual detection method for peanut and soybean allergens was established based on ladder-shape melting temperature isothermal amplification (LMTIA) combined with proofreading enzyme-mediated probe cleavage (Proofman). Specific primers and Proofman probes targeting the peanut Ara h 2.01 gene and the soybean lectin gene sequences were designed. This method facilitates simultaneous detection of peanut and soybean allergens in foods within 30 minutes. The detection sensitivity of the method for genomic DNA (gDNA) of peanuts and soybeans reached 5 pg µL⁻¹, and the minimum detectable limit for allergenic peanut (or soybean) components in non-allergenic matrices was 1%. The designed Proofman-LMTIA method has excellent specificity, and the detection results for the 9 categories of commercial food samples were completely consistent with the allergen labels on the products. Furthermore, this study verified the detection sensitivity of the method by comparing it with the standard singleplex LAMP method, and further confirmed its practical application feasibility through the detection of actual samples. The dual Proofman-LMTIA method established in this study enables rapid and accurate identification of peanut and soybean allergens in food products, which will facilitate market supervision of food allergens.

Background: the emerging UHPLC-Q-orbitrap-MS/MS method is not efficient for the deep analysis of charred Chinese herbal medicines (CHMs) due to the lack of a comprehensive database. This study tried to develop a new strategy, i.e., database-affinity ultra-high-performance liquid chromatography-quadrupole-orbitrap-tandem mass spectrometry (UHPLC-Q-orbitrap-MS/MS), to deeply analyze a charred CHM, i.e., charred Semen Arecae (CSA). Methods: database-affinity UHPLC-Q-orbitrap-MS/MS was used to qualitatively and quantitatively analyze the lyophilized aqueous extract of CSA. The relative chemical contents and antioxidant activities of compounds were further evaluated via a PTIO˙ radical scavenging assay. Antioxidant contributions were calculated as “relative antioxidant level × chemical content.” Based on chemical and antioxidant analyses, supplemental Q-markers were proposed and thereafter investigated for their traceability using quantum chemistry. Furthermore, they were validated for applicability using multiple products and analytical technologies (LC-MS and HPLC-UV). Results: thirty-five compounds were putatively identified by database-affinity UHPLC-Q-orbitrap-MS/MS. In particular, 16 “overlooked” compounds were discovered in CSA. Three procyanidin isomers (B1, B2, and B3) were differentiated from each other, and the Maillard reaction intermediate 5-hydroxymethylfurfural (5-HMF) was found to be enriched in CSA. (+)-Catechin and (−)-epicatechin exhibited the highest antioxidant contributions. (+)-Catechin, (−)-epicatechin, and 5-HMF were thus proposed as supplemental Q-markers for CSA. They were evidenced to show good traceability, pharmacology relevance, TCM relevance, testability, and specificity. They were also demonstrated to be applicable for various CSA products from different batches (25 batches in total), locations, extraction methods, and even analytical technologies. Conclusion: sixteen “overlooked” compounds were found in CSA for the first time by database-affinity UHPLC-Q-orbitrap-MS/MS. Three supplemental Q-markers were integrated with arecoline to develop a new pharmacopeia Q-marker system. The system can overcome the limitations of the old and risky Q-marker (arecoline). This successful attempt indicates that a comprehensive database can enable UHPLC-Q-orbitrap-MS/MS for the in-depth analysis of Chinese herbal medicines and quality-control update of charred CHMs.

The sensitivity of laser-induced fluorescence (LIF) to slight biochemical changes has made it an effective tool for non-invasive biomedical diagnostics. Since milk is a biological fluid that is both optically and biochemically complex, we employed it as a model sample to evaluate how effectively LIF senses thermally induced molecular changes. Full-fat and skimmed milk samples were systematically examined under 405 nm excitation both before and after controlled heating. The collected fluorescence spectra were then subjected to chemometric analysis using Principal Component Analysis (PCA) for unsupervised classification and Partial Least Squares Regression (PLSR), Support Vector Classifier (SVC), and Random Forest (RF) for predictive modeling. The statistical significance of the observed spectral changes was validated using paired t-tests. Following thermal processing, the emission band at around 533 nm, which corresponds to riboflavin, was significantly reduced, based on fluorescence spectra. The statistical significance of this decrease was validated by paired t-tests (p <0.0001). The discriminative power of LIF was further confirmed by chemometric evaluation: PCA successfully classified samples based on both fat content and thermal treatment, with the first two principal components predicting almost 85% of the total variance. The robustness of the approach was verified by the high calibration and cross-validated prediction accuracy (R² >0.95) achieved by PLSR. Excellent classification performance was achieved by the SVM classifier with RBF kernels, correctly classifying 100% of data sets. Good model generalization without overfitting is indicated by the close agreement between the test set and cross-validation accuracies. Furthermore, the robustness and generalizability of the model were confirmed by the low out-of-bag error rate in RF implementations. These results show the potential of LIF as a sensitive, non-destructive method for assessing thermal and metabolic changes in biomedical contexts and validate milk as a practical surrogate system for comparing fluorescence-based methods.

Our research team developed AB-38b, a biphenyl diester derivative containing α,β-unsaturated carbonyl groups, inspired by investigations into the pharmacological prevention and pathophysiology of diabetic kidney disease (DKD). We have completed the synthesis and pharmacodynamic evaluation of AB-38b in preclinical DKD studies. For pharmacokinetic analysis, we established a high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for quantifying AB-38b in rat plasma, as well as in liver and kidney tissues. Sample preparation involved protein precipitation using methanol, with tolvaptan employed as the internal standard (IS). Chromatographic separation was achieved on a Shim-pack VP-ODS C18 column (2.0 × 150 mm, 5 µm), with mobile phase A (5 mM ammonium acetate) and mobile phase B (methanol) under gradient elution at a flow rate of 0.2 mL min⁻¹. AB-38b and the IS were detected and quantified using positive electrospray ionization in multiple reaction monitoring (MRM) mode at transitions of m/z 705.30 → 618.20 for AB-38b and m/z 449.30 → 252.20 for the IS. The method demonstrated excellent linearity, stability, accuracy, precision, recovery, and a non-significant matrix effect within the validated range. A one-compartment model with rapid absorption and distribution, quicker elimination, and clear tissue distribution was demonstrated by the mean blood concentration–time curve of AB-38b in rat plasma. The liver tissue contained high levels of AB-38b, with no evidence of tissue accumulation observed. These findings offer a reference for further research into the pharmacological mechanisms and potential therapeutic applications of AB-38b in metabolically related diseases, especially DKD.

Quantification of trace microRNAs is crucial for early disease diagnosis but remains technically challenging. Herein, we developed an ultrasensitive fluorescence platform for microRNA-21 (miR-21) detection by integrating Bst DNA polymerase – assisted target recycling with CRISPR/Cas12a-mediated signal amplification. In this design, the target miRNA triggers toehold-mediated opening of a hairpin probe, followed by Bst-driven primer extension that enables efficient target recycling and the generation of abundant DNA duplex activators. Subsequently, these activators induce strong trans-cleavage activity of Cas12a, producing markedly enhanced fluorescence responses. Benefiting from the dual amplification of enzymatic recycling and Cas12a activation, the proposed assay exhibits high sensitivity toward miR-21 with a detection limit down to 9.25 × 10⁻¹² M. Furthermore, the platform exhibited excellent sequence selectivity and was successfully applied to monitor miR-21 in both cell lysates and clinical serum samples. Considering its convenient operation, strong analytical performance, and simple readout mode, this method holds great potential for trace biomarker analysis in clinical diagnostics.

Correction for ‘HunStat2 – a simple and low-cost potentiostat with electrochemical impedance spectroscopy capability’ by Istvan Vamos et al., Anal. Methods, 2025, 17, 9494–9499, https://doi.org/10.1039/D5AY01179E.