最新刊期
卷 45 ， 期 6 ， 2026
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摘要：The deep integration of artificial intelligence into the traditional Chinese medicine （TCM） system of syndrome differentiation and treatment is driving its evolution from an experience-dependent inheritance model towards a modern paradigm powered by both data and knowledge. This review systematically outlines the core pathways of this transformation：achieving objective fusion of information from the four diagnostic methods through multimodal technology； capturing the dynamic evolution of syndromes and their theoretical logic using temporal modeling and knowledge enhancement； and realizing the recommendation，generation，and optimization of prescriptions based on the intelligent computation of“formula-syndrome correspondence”further combined with network pharmacology to analyze compatibility mechanisms and discover new drugs. Although current research still faces limitations in data quality，model interpretability，and clinical validation，artificial intelligence has laid a solid foundation for constructing a computable，verifiable，and human-AI collaborative intelligent TCM diagnosis and treatment system，vigorously promoting the innovation and scientific development of TCM while preserving its core principles.关键词：artificial intelligence;traditional Chinese medicine;syndrome differentiation and treatment;four diagnostic methods;prescription pecommendation742|961|0更新时间：2026-07-15 -
AI-driven Intelligent Characterization and Chemical Space Expansion for Traditional Chinese Medicine AI导读
摘要：The compositional analysis of complex material systems in traditional Chinese medicine（TCM）—including small molecules，proteins，polysaccharides，and higher-order self-assembled structures—has long been constrained by insufficient spectral library coverage and the bottleneck of manual interpretation，thereby limiting the standardization and depth of research into their material basis. Leveraging its strong capability for multi-source data integration and deep representation learning，artificial intelligence（AI） is driving a paradigm shift in TCM constituent analysis from experience-driven approaches to data-driven methodologies. This review systematically surveyed learning paradigms，core architectures，and representative tasks of AI-based TCM constituent analysis，with a particular focus on molecular representation learning methods，spectroscopic data processing strategies，and recent advances in complex multidimensional component identification and chemical space expansion. Finally，key challenges and future directions were discussed，including data standardization，multimodal integration，and model interpretability. From an interdisciplinary perspective，this review aimed to provide methodological support for the modernization and high-quality development of traditional Chinese medicine.关键词：artificial intelligence;traditional Chinese medicine（TCM）;deep learning;representation learning;intelligent characterization538|398|0更新时间：2026-07-15 -
摘要：Traditional Chinese medicine preparations still have potential safety hazards due to complex components，vague pharmacodynamic material basis，insufficient quality controllability and unclear mechanism of action，which affect their popularization and internationalization. In response to the above problems，the field of traditional Chinese medicine has gradually formed a systematic re-development idea with the core concept of“new use of old drugs and renewal of classics”，and promoted the in-depth excavation and re-evaluation of large varieties of traditional Chinese medicine. With the in-depth application of artificial intelligence，process analysis technology，network pharmacology，mass spectrometry technology and quality by design concept in the research of traditional Chinese medicine，the modernization and scientific development of large varieties of traditional Chinese medicine ushered in new opportunities. In this paper，Xuefu Zhuyu preparation，a typical large variety of traditional Chinese medicine for promoting blood circulation and removing blood stasis，was taken as the research object. For the first time，the key technical system involved in its secondary development was systematically sorted out，including five dimensions：quality control，mechanism analysis，clear efficacy，efficacy improvement and international recognition. At the same time，combined with the application examples of artificial intelligence and large language model，the relevant technical paths were optimized and the common experience was refined to explore the future development direction of large varieties of traditional Chinese medicine，so as to provide a reference paradigm for the modernization and upgrading of similar varieties.关键词：large varieties of traditional Chinese medicine;Xuefu Zhuyu preparations;secondary development;process analytical technology;artificial intelligence436|175|0更新时间：2026-07-15 -
摘要：The establishment of a quality control system for traditional Chinese medicine is of great importance for clarifying its pharmacodynamic material basis，ensuring medication safety，and improving the quality level of compound preparations. Conventional quality control approaches for traditional Chinese medicine mainly rely on appearance identification based on morphological features and qualitative or quantitative analysis of exogenous chemical components. These methods have limitations in reflecting the real action process of traditional Chinese medicine in vivo. Evaluation based only on in vitro chemical composition is insufficient to accurately and comprehensively assess the overall quality and therapeutic effects of traditional Chinese medicine.In recent years，with the rapid development of artificial intelligence technologies such as language models，their advantages in knowledge integration and semantic representation have provided important technical support for the precise prediction of in vivo processes of traditional Chinese medicine components. This review systematically summarizes the applications of artificial intelligence in the prediction of in vivo components of traditional Chinese medicine and the screening of quality marker（Q-marker）. The covered methods include rule based models，machine learning，deep learning，and multi omics data integration strategies. In addition，future research on artificial intelligence driven quality control of traditional Chinese medicine is discussed，aiming to provide references for promoting the development of this field toward intelligent and precise directions.关键词：quality control of traditional Chinese medicine;artificial intelligence;predicting in vivo constituents;Q-marker637|173|0更新时间：2026-07-15 -
摘要：At present，the construction of big data platforms for traditional Chinese medicine （TCM） pharmaceutical processes faces prominent challenges，including insufficient data standardization，inadequate technology integration，and weak security support. A scientific and rational core technical architecture and key links are critical to improving the quality of platform construction. This study took the construction of big data platform for TCM pharmaceutical processes as the research object，explored the core points and practical paths of platform construction，deeply analyzed its core technical architecture and key construction links，and summarized its practical effects in four core application areas of perception monitoring，process control，intelligent decision-making and quality traceability. It clarified the core role of the platform in integrating full-process data resources and releasing the value of data elements，aiming to provide theoretical references and practical experience for promoting the high-quality construction of big data platforms for TCM pharmaceutical processes and accelerating the precision and intelligent development of the pharmaceutical process control for traditional Chinese medicine.关键词：traditional Chinese medicine manufacturing;big data platform;process control;quality traceability294|100|0更新时间：2026-07-15 -
摘要：The safety and clinical efficacy of traditional Chinese medicine（TCM） are closely related to their quality. However，the complex origin of herbs and significant differences in geo-authenticity lead to the uneven quality of TCM，and the traditional quality control methods have been difficult to meet the complexity and variability of quality assessment. Artificial intelligence（AI），with its powerful data processing ability，accurate pattern recognition and intelligent decision-making advantages，combined with modern analysis technology，provides a new technical path for the standardization，speed and intelligence of TCM quality testing. This review focuses on AI-driven intelligent detection technology and application scenarios of TCM，introduces common modern analytical techniques and AI core algorithms，outlines the specific application of AI in the quality control of the whole industry chain of TCM from the aspects of authenticity identification，quality grade assessment and harmful substance screening，and analyzes the problems and challenges faced by AI in the field of quality control. This review provides a reference for the construction of a whole-process intelligent quality control system of traditional Chinese medicine and the high-quality development of traditional Chinese medicine industry.关键词：traditional Chinese medicine;quality control;artificial intelligence;machine learning;deep learning;data processing474|498|0更新时间：2026-07-15 -
摘要：In order to solve the limitation of relying on a single index or experience to judge the concentration end point in the production of traditional Chinese medicine extract，this study took Xuefu Zhuyu extract as the object，and innovatively proposes an intelligent quality control system of“physical fingerprint + machine vision + large language model”multi-modal fusion strategy. Seven core physical indexes such as density and pH value were screened and standardized to construct physical fingerprint. Then，the abnormal samples were eliminated by Mahalanobis distance，and the comprehensive score was calculated by “CRITIC+entropy weight+TOPSIS” method. With 0.6 as the qualified threshold，100 batches of samples were divided into 62 batches of qualified samples and 38 batches of unqualified samples. At the same time，the extract image features were collected and extracted，and six machine learning models were constructed. Among them，the XGBoost model had the best performance，with accuracy，precision，recall，F1 score，and AUC reaching 0.933 3，1.000 0，0.833 3，0.909 1，and 0.963 0，respectively. Based on this，an intelligent assessment platform integrating large language models can be further developed，which can complete the analysis and generate actionable process suggestions within about ten seconds. This system provides an integrated quality control scheme of“objective grading+rapid prediction+intelligent”suggestion for Xuefu Zhuyu extract，and also provides a reusable technical paradigm for multi-dimensional quality evaluation of Chinese medicine extract intermediates，which effectively promotes the transformation of Chinese medicine production to“data-driven”.关键词：Xuefu Zhuyu extract;physical fingerprint;machine vision;large language model;quality control475|345|0更新时间：2026-07-15 -
摘要：Based on high performance liquid chromatography-diode array detector（HPLC-DAD）chromatographic data from 75 batches of compound liquorice tablets，this study proposed and validated a 3D fingerprint constructed by AI-integrated fusion across 38 wavelengths in the 200-348 nm range. Combined with a binary triple fingerprint method to calculate Sm and Pm，this approach enabled quality consistency evaluation. Simultaneously，nine pharmacologically active substances were quantitatively determined using standard curve method and ratio fingerprint method，with comparative analysis conducted. Results demonstrated that compared to the single-wavelength fingerprint at 220 nm，the 3D fingerprint maintained macro-qualitative consistency while significantly enhancing the discrimination power for Pm. Principal component analysis（PCA） and radar charts indicated its superior sensitivity in distinguishing batches and manufacturers. Furthermore，the ratio fingerprint method and standard curve method showed high consistency（r>0.99）in quantifying the nine target components，validating the reliability of the quantitative strategy. The 3D fingerprint integrates detection information from 38 wavelengths，enabling a comprehensive and sensitive characterization of the chemical composition and quality variations in compound liquorice tablets. This significantly enhances the ability to distinguish between batches and manufacturers. Combined with the binary triple fingerprint method，this approach provides a big data-driven consistency monitoring method for herbal medicine quality in traditional Chinese medicine consistency evaluation and standardized control. It offers empirical support and a scalable technical pathway for quality monitoring research based on artificial intelligence and large-scale chromatographic data.关键词：compound liquorice tablets;binary triple fingerprint method;3D fingerprint;quality consistency evaluation;multicomponent content determination;HPLC395|100|0更新时间：2026-07-15 -
摘要：Based on ultra-high performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry（UPLC-Q-TOF-MS/MS），this study developed an automated matching algorithm for the theoretical m/z values of characteristic fragment ions，utilizing NumPy matrix operations and Matplotlib visualization in Python. By integrating self-built databases of molecular formulas and characteristic fragment ions，the platform achieved rapid screening and automated identification of multi-component in Shangke Jiegu Tablet. The MS/MS fragmentation patterns of various compounds were systematically investigated and validated through comparison with the reference standards and literatures. A total of 77 compounds were identified，including 28 triterpenoids，16 saponins，9 amino acids，9 flavonoid glycosides，6 alkaloids，6 fatty acids，2 iridoid glycosides，and 1 pigment. Performance validation demonstrates that this Python algorithm achieves the detection rate of 100%，relative standard deviations（RSDs） less than 3.0%，and false matching rate of 2.5%. This research provides scientific data and technical support for the study of the pharmacodynamic material basis and quality evaluation of this traditional Chinese medicine prescription.关键词：Shangke Jiegu Tablet;UPLC-Q-TOF-MS/MS;Python-based algorithm;automated identification of constituents;mass spectrometry fragmentation mechanism303|89|0更新时间：2026-07-15
Special Topic
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摘要：Abnormal postmortem glycolytic rates are among the primary drivers of meat quality defects，such as pale，soft，exudative（PSE） and dark，firm，dry（DFD） conditions. Phosphoglycerate kinase 1（PGK1） and pyruvate kinase M2（PKM2） catalyze two key substrate-level phosphorylation steps in glycolysis and can therefore partially reflect postmortem energy metabolism status. In this study，Tan sheep muscle was used as the research object. The immunoreactivity levels of PGK1 and PKM2 were determined，and a nondestructive evaluation framework integrating visible-near-infrared hyperspectral imaging（Vis-NIR HSI） with two-dimensional correlation spectroscopy（2D-COS） was developed to enhance sensitive band interpretation and model explainability. Five sensitive wavelengths（476，562，605，715，and 800 nm） were identified by 2D-COS，and their spectral responses were plausibly associated with changes in myoglobin state and differences in water-binding status and/or tissue-structure-related scattering. Furthermore，multiple preprocessing and feature extraction strategies were systematically compared across partial least squares regression（PLSR），random forest（RF），and convolutional neural network（CNN） models. The best performance was achieved by the CNN model coupled with variable combination population analysis-iteratively retaining informative variables（VCPA-IRIV），yielding for PGK1：RP2=0.892 0，RMSEP=38.365 3，RPD=3.093 5；and for PKM2：RP2=0.903 0，RMSEP=18.177 8，RPD=3.265 9 in the prediction set. Pixel-wise pseudo color visualization based on the optimal models intuitively revealed the spatial heterogeneity and dynamic evolution of the two enzyme levels across different storage stages. These results demonstrate that Vis-NIR HSI combined with 2D-COS and deep learning enables nondestructive prediction of PGK1 and PKM2 enzyme levels in mutton，providing technical support for rapid grading and process monitoring of metabolism-related indicators.关键词：visible-near infrared hyperspectral imaging;Tan sheep;phosphoglycerate kinase 1;pyruvate kinase M2;two-dimensional correlation spectroscopy;deep learning;nondestructive detection161|88|0更新时间：2026-07-15 -
摘要：Aiming to address the challenges posed by the structural diversity of synthetic cathinones，the strong library dependence of traditional detection techniques，and their weak capability in identifying unknown compounds，this study proposed an intelligent analysis system based on machine learning integrated with gas chromatography-mass spectrometry（GC-MS） technology. Leveraging spectral features derived from GC-MS analysis of synthetic cathinones，combined with insights from molecular structures and mass spectrometric fragmentation rules，secondary classification features were constructed by systematically summarizing and refining fragment ion patterns. An intelligent analysis and precise identification platform for the characterization of synthetic cathinones was developed to precisely characterize their features utilizing Python and PySide6. Experimental results demonstrated that the developed intelligent analysis system for characterizing synthetic cathinones achieved a model accuracy of 98.41%，precision of 94.03%，recall of 100%，specificity of 97.88%，F1 score of 96.92%，and balanced accuracy of 98.94%. The approach not only boasted high identification accuracy and strong interpretability，but also effectively overcame the limitations of traditional detection techniques and models，thereby offering a novel strategy for the identification of new psychoactive substances.关键词：cathinones;GC-MS;machine learning;characterization;Python130|86|0更新时间：2026-07-15 -
摘要：Near-infrared（NIR） spectroscopy is susceptible to interference from outliers in quantitative analysis. Since NIR spectra are formed by the superposition of absorption peaks from hydrogen-containing groups，traditional methods analyze the entire spectrum as a whole，relying solely on global features. This makes it difficult to detect subtle outlier features within specific peaks，and the use of fixed thresholds lacks adaptability. To address this，this paper proposed an outlier detection strategy based on Gaussian mixture decomposition. Specifically，a Gaussian mixture model was established within key absorption peak regions to resolve overlapping spectral peaks using multiple Gaussian components. A normal range was then constructed for the amplitude of each component based on the interquartile range criterion，and samples exceeding this range were identified as outliers. The proposed method was applied to the prediction of total sugar concentration in the raw-material mixture of citric acid fermentation. The results showed that the method could effectively identify both artificially introduced and naturally occurring spectral outliers. Compared with the original spectra，the PLS model built after removing the outliers achieves a 34.69% reduction in RMSE and a 26.28% increase in the coefficient of determination. By analyzing the compositional structure of absorption peaks，this method enables adaptive detection of local outlier features，providing a structured and highly interpretable approach for enhancing NIR spectral data quality.关键词：near-infrared spectroscopy;outlier detection;Gaussian mixture model;overlapping peak resolution;citric acid fermentation168|49|0更新时间：2026-07-15 -
摘要：A solid-phase extraction coupled with high-performance liquid chromatography-tandem mass spectrometry（SPE/HPLC-MS/MS） method was developed for the simultaneous determination of multiple PFAS in dairy products. Milk，yogurt，and cheese samples were freeze-dried prior to extraction. Three successive vortex-assisted extractions were performed using organic solvents，30 min each. For milk and yogurt，methanol was used in the first extraction，followed by acidified methanol in the subsequent two extractions； for cheese and whey protein powder，acetonitrile was used in the first extraction，followed by acidified acetonitrile in the subsequent two extractions，followed by purification using a WAX cartridge. Compared with non-acidified solvents，acidified methanol and acetonitrile significantly reduced matrix effects and improved method accuracy and precision. The target analytes were detected under multiple reaction monitoring mode and quantified using isotope-labeled internal standards. Under optimized conditions，satisfactory linearity was achieved over the concentration range of 0.05-10 ng/mL，with correlation coefficients（r2） exceeding 0.99. The limits of detection（LODs） ranged from 0.001 8 to 0.068 ng/g，and limits of quantitation（LOQs） ranged from 0.005 9 to 0.23 ng/g. The recoveries of analytes were between 31.0% and 154% and the relative standard deviation were 0.10%-20%. Application of the method to commercial dairy products revealed the presence of PFAS in different dairy categories，with total PFAS concentrations ranging from below the detection limit to 1.34 ng/g. PFNA was the dominant PFAS in milk and yogurt，whereas short-chain PFAS were more frequently detected in cheese and whey protein powder. Overall，the developed method exhibited good sensitivity and stability，providing a reliable analytical approach for PFAS monitoring in dairy products and dietary exposure assessment.关键词：per- and polyfluoroalkyl substances;dairy products;solid-phase extraction;HPLC-MS/MS168|69|0更新时间：2026-07-15 -
摘要：Benefiting from their fluorescence-free background and ultrahigh imaging signal-to-noise ratio， near-infrared persistent luminescent（NIR-PL） nanoparticles have gradually emerged as promising probes for in vivo bioimaging. Despite the rapid development of this field，efficient strategies to fabricate NIR-PL nanoparticles（NIR-PLNPs） with both small sizes and superior optical performance are still lacking. In view of these bottlenecks，this work develops a novel strategy for the preparation of small-sized，high-performance NIR-PLNPs. A two-phase hydrothermal method is employed to synthesize oleic acid-capped precursor ZnGa2O4∶Cr3+ NIR-PLNPs，which are subsequently coated with SiO2 using a reverse microemulsion approach and optimized through high-temperature post-treatment. The resulting monodisperse core-shell structured ZnGa2O4∶Cr3+@SiO2 NIR-PLNPs exhibit a uniform particle size of approximately 40 nm. X-ray powder diffraction（XRD），transmission electron microscopy （TEM），dynamic light scattering（DLS），and fluorescence spectroscopy are used to characterize the nanoparticles. Increasing the dosage of tetraethyl orthosilicate（TEOS） is found to regulate and enhance the thickness of the SiO2 coating. Under 265 nm excitation，the optimally prepared ZnGa2O4∶Cr3+@SiO2 NIR-PLNPs exhibit excellent NIR-PL，generating 600-800 nm NIR emission with an afterglow duration exceeding 1 h. Hemolysis and cytotoxicity assays confirm the biosafety of the material. In vivo imaging experiments in mice further verify its potential for optical probe applications： clear NIR-PL imaging signals with a signal-to-noise ratio of 7.64 are captured 5 min after subcutaneously injecting the pre-charged aqueous solution of the material. Furthermore，1 h after tail vein injection，imaging signals are detected throughout the mouse body without significant accumulation in the reticuloendothelial system，proving that the small size and monodisperse characteristics endow the material with outstanding in vivo long-circulation capabilities. The synthesis method is controllable and universal，providing a new technical path for the preparation of small-sized，monodisperse，high-performance luminescent nanomaterials，and is expected to promote the application of NIR-PL nanoprobes in biological imaging.关键词：near-infrared persistent luminescence;Cr3+;bioimaging;nanoprobes30|14|0更新时间：2026-07-15 -
摘要：2-FXE is a new psychoactive substances（NPS） of phencyclidine-type，which has dissociative and psychoactive properties. The cases of its abuse has been reported in recent years. However，no human metabolism data about 2-FXE have been reported. The metabolism knowledge of 2-FXE is essential to help identify them in authentic forensic case samples. An understanding of 2-FXE metabolism is needed to identify formed metabolites that may serve as biomarkers in forensic toxicology screening and for understanding the pharmacokinetics of the drugs. Urine is a good sample for metabolite identification in forensic toxicology analysis because it can extend the detection window. The present study aimed to identify the metabolites of 2-FXE in urine，via ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry（UPLC-QTOF MS）. The authentic urine from drug abuser was diluted with acetonitrile，followed by centrifugation and filtration through a 0.22 μm membrane. The metabolites were analyzed and structurally elucidated by UPLC-QTOF MS，and the accurate masses of precursor ions and fragment ions，mass error（ppm），and chemical formula were obtained for each metabolite. The metabolism of 2-FXE in urine observed were hydroxylation，carbonyl reduction，dehydrogenation，dealkylation，oxidation as well as combined reactions and glucuronide conjugation. A total of 23 phase Ⅰ metabolites and 12 phase Ⅱ metabolites were identified，and the potential metabolic pathways were proposed. Among these metabolites，M32，a metabolite generated through carbonyl reduction and glucuronide conjugation，was identified as a suitable target for the detection of 2-FXE abuse. In this study，the metabolic pathways and metabolites of 2-FXE in authentic urine were systematically investigated，and providing a theoretical basis and technical support for the identification of 2-FXE abuse cases. To the authors' knowledge，this is the first report of the identification of the metabolites of 2-FXE in authentic human urine sample.关键词：new psychoactive substances（NPS）;2-FXE;urine;ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry（UPLC-QTOF MS）;metabolite165|154|0更新时间：2026-07-15 -
摘要：To meet the demand for rapid and non-destructive brand identification of plastic toothbrush handle evidence in practical police casework，a dual-spectral identification method based on differential Raman spectroscopy and X-ray fluorescence spectroscopy（XRF） was developed，and a stepwise hierarchical gating network（SHG-Net） was proposed. Differential Raman and XRF data were collected from 111 toothbrush handles covering nine brands. Stable elemental variables were selected from the XRF data and then standardized，while the differential Raman spectra were preprocessed and subjected to dimensionality reduction. Meanwhile，data augmentation based on normal-distribution sampling was adopted to alleviate the small-sample problem. SHG-Net uses separate feature-extraction branches for differential Raman and XRF data，and integrates a gating mechanism to achieve adaptive weighted fusion of features before outputting the predicted brand category. Five-fold cross-validation results showed that SHG-Net achieved an accuracy of 0.96 and a balanced accuracy of 0.94，outperforming single-modality recognition and simple concatenation-based fusion methods. Compared with traditional machine-learning models and deep-learning baseline models，SHG-Net showed better performance across multiple evaluation metrics，with smaller overall fluctuations. The complementary dual-spectral information and gated fusion mechanism can effectively improve brand identification performance under small-sample conditions，providing technical support for the rapid classification of plastic evidence recovered from crime scenes.关键词：differential Raman spectroscopy;X-ray fluorescence spectroscopy;gated fusion;toothbrush handle evidence;rapid classification48|40|0更新时间：2026-07-15 -
摘要：A gas chromatography-mass spectrometry（GC-MS） method was developed for the simultaneous determination of 81 fragrance components in cosmetics. Samples were extracted with ethyl acetate by ultrasonically assisted procedure. The chromatographic separation was performed on a DB-WAX capillary column（30 m×0.32 mm×0.50 μm）. Data acquisition was carried out in selected ion monitoring（SIM） mode，and quantification was achieved using an internal standard method. The 81 fragrance components had a good linear relationship（r2>0.99） in the range of 0.5-10 mg/L，the limits of detection（LODs） ranged from 1.0 mg/kg to 3.0 mg/kg and the limits of quantification（LOQs） ranged from 3.3 mg/kg to 10 mg/kg. The average recoveries were in the range of 80.2%-123% at the spiked levels of 10，40，100 mg/kg，and the relative standard deviations（RSDs） was in the range of 0.80%-7.5%（n=6）．The method was proved to be simple，practical，and accurate，making it suitable for the determination of 81 fragrance components in cosmetics.关键词：cosmetics;fragrance components;gas chromatography-mass spectrometry;determination171|65|0更新时间：2026-07-15 -
摘要：In this study，a validated residue analysis method was established for the simultaneous determination of mefentrifluconazole and its four primary metabolites（1，2，4-triazole，triazoleacetic acid，ttriazolealanine，and triazolepropionic acid） in fresh leaves and stems of Dendrobium officinale. Method optimization involved systematic comparison of extraction solvents，purification sorbent combinations，and chromatographic responses of reconstitution solvents. The optimized procedure was successfully applied to field samples，verifying its practical applicability. Specifically，samples were extracted with 2% formic acid-acetonitrile solution，followed by salting-out phase separation，purified using a mixed sorbent（C18，GCB，and MgSO₄），filtered，concentrated to near dryness，and reconstituted in acetonitrile-5 mmol/L ammonium acetate solution （1∶1，volume ratio） for instrumental analysis. Separation was achieved on a HSS T3 column，and quantification was performed via ultra performance liquid chromatography-tandem mass spectrometry（UPLC-MS/MS） using the matrix-matched external standard method. For matrix-matched standards，the linear correlation coefficients（r²） of mefentrifluconazole at 0.005-2.0 mg/L and its metabolites at 0.05-5.0 mg/L all exceeded 0.991 0. At three spiked levels（low，medium，high），average recoveries ranged from 73.1% to 107%，with relative standard deviations（RSDs） of 1.7%-11%，and the limits of quantification（LOQs） were 0.01 mg/kg except for the four metabolites in fresh stems（0.10 mg/kg）. After greenhouse application of 400 g/L mefentrifluconazole·pyraclostrobin suspension concentrate on Dendrobium officinale，the dissipation of mefentrifluconazole in fresh leaves and stems followed first-order kinetics，with regression equations of C=69.641 7e-0.093t（r2=0.983 2，half-life=7.45 days） and C=30.864 63e-0.052t（r2=0.905 3，half-life=13.33 days），respectively. These results confirm that the developed method is accurate，sensitive，and reliable for routine residue analysis，and can be effectively utilized for the real sample determination of mefentrifluconazole and its metabolites in Dendrobium officinale.关键词：Dendrobium officinale;pesticide residue;mefentrifluconazole;metabolites;ultra performance liquid chromatography-tandem mass spectrometry124|66|0更新时间：2026-07-15 -
摘要：A headspace-solid-phase microextraction/gas chromatography-mass spectrometry（HS-SPME/GC-MS） method was developed for the analysis of trace odorants in common substrates collected from gas explosion sites. The background interference effects within complex matrices were systematically investigated. The method exhibited excellent linearity（r²>0.99） for tetrahydrothiophene（THT），dimethyl sulfide（DMS），and ethyl mercaptan（EM），with limits of detection ranged of 0.05-37.59 ng/g.The spiked recoveries ranged from 87.3% to 115%. The intra-day and inter-day relative standard deviations（RSDs，n=3） were 4.4%-8.3% and 4.4%-8.9%，respectively. An interference system was constructed using gradient spiking at mass ratios of 1-200，and a first-order exponential decay model（r²≥0.93） was established to describe the relationship between signal response and interferent concentration，revealing the signal suppression pattern under matrix interference. Results indicated that competitive adsorption at the fiber coating sites was the dominant mechanism for signal suppression，showing a distinct selectivity order：naphthalene>toluene>n-pentadecane. By comparing different target components，THT exhibits significantly superior anti-matrix masking capability compared with DMS and EM. Regarding matrix effects，cotton fibers demonstrated the highest resistance to interference，while soil exhibited the most pronounced suppression. Full-scale simulated explosion experiments further confirmed that soil and sponge，owing to the physical encapsulation within their microporous structures，could retain detectable THT for up to two hours post-explosion. This study quantifies the interference resistance thresholds of common matrices for the first time，providing a scientific foundation and strategic sampling recommendations for gas explosion investigations and forensic evidence identification.关键词：gas odorants;matrix effect;HS-SPME/GC-MS;simulated explosion experiment128|69|0更新时间：2026-07-15 -
摘要：In the emergency response work for public safety incidents involving ricin，it is imperative to perform tracing and source classifications of castor beans. This research established a gas chromatography-mass spectrometric method for fatty acid determination and a sandwich enzyme-linked immunosorbent assay for ricin measurement. Afterwards it quantified six major fatty acids and ricin in 100 batches of castor bean samples collected from 23 domestic origins in China. Guided by plant psychological energy and metabolic mechanisms，it introduced three energy feature parameters，i.e.，unsaturation index，oleic/linoleic acid ratio，ricin/fatty acid ratio，and integrated with three machine learning algorithms to enhance the classification of origins. Model evaluation indicated that L1-regularized support vector machine model achieved area under the receiver operating characteristic curve（ROC-AUC） values of 73.63% with introduced energy feature parameters and 71.95% using the minimal feature cluster. The corresponding test accuracy were 70.37% and 68.52%，respectively. Both external validation accuracies reached 75.00%，demonstrating robust generalization performance. This research confirms the feasibility and application potential of high-abundance metabolites in the traceability of castor beans，and the energy-based feature integrated machine learning provides a reliable route for biological feature-based data mining.关键词：castor beans;ricin;fatty acids;provenance discrimination;machine learning;energy feature parameters124|86|0更新时间：2026-07-15 -
摘要：This study employed microwave digestion-inductively coupled plasma mass spectrometry（ICP-MS） to determine the residual levels of Pb，Cd，As，Hg，Cu，V，Cr，Mn，Co，Ni，Mo，Ru，Pd，Ba，Pt，Tl，Ir，and Rh in different parts of Scutellaria baicalensis. Chemometric methods，including cluster heatmap，correlation heatmap，and orthogonal partial least squares-discriminant analysis（OPLS-DA），were applied for data analysis. Health risk assessment was conducted using the single pollution index（Pi），Nemerow integrated pollution index（PN），estimated daily intake（EDI），target hazard quotient（THQ），and carcinogenic risk（CR）.The results indicated that the copper（Cu） content was relatively high in the roots of Scutellaria baicalensis，thallium（Tl），chromium（Cr），and cadmium（Cd） were highest in the stems of Scutellaria baicalensis，while those of manganese（Mn），barium（Ba），lead（Pb），molybdenum（Mo），and arsenic（As） were highest in the leaves. Principal component analysis identified As，Pb，Ba，Mn，and Co as characteristic elements distinguishing the different parts. Both cluster heatmap and OPLS-DA clearly separated the roots，stems，and leaves，with Cr，Mo，Pb，Ba，Mn，As，Co，Hg，and V serving as differential characteristic elements for part discrimination.The elemental correlation heatmap revealed 9 pairs of extremely significant positive correlations（p<0.01） and 1 pair of extremely significant negative correlation（p<0.01） in the roots；15 pairs of extremely significant positive correlations（p<0.01） in the stems；and 19 pairs of extremely significant positive correlations（p<0.01） in the leaves.Safety evaluation and health risk assessment results indicated that mercury（Hg） exceeded the limit and caused pollution in four batches of stem samples. Potential non-carcinogenic risks were associated with different parts of S. baicalensis，while the carcinogenic risk coefficients fell within the acceptable safety range. Furthermore，the risk in roots was lower than that in stems and leaves，with stems showing notable mercury enrichment，which warrants further attention.关键词：Scutellaria baicalensis;heavy metals and harmful elements;inductively coupled plasma mass spectrometry;chemometrics;health risk assessment90|32|0更新时间：2026-07-15 -
摘要：This study aims to monitor the flavor evolution of infant formula throughout the production process，thereby providing a scientific basis for optimizing flavor quality and enhancing infant acceptance. Representative samples were collected across the entire infant formula production line，encompassing milk base，sterilized milk，wet-mixed milk，dried powder，and final formula powder. Volatile compounds were qualitatively and quantitatively analyzed using headspace solid-phase microextraction/gas chromatography-mass spectrometry（HS-SPME/GC-MS），and flavor changes were characterized by relative odor activity value（ROAV）. A total of 45 volatile odor substances were identified，belonging to eight classes：aldehydes，ketones，acids，alcohols，lactones，furans，sulfides，and terpenes. Among these，aldehydes（18 species） were the most abundant and served as the core contributors to the flavor profile. The key volatile odorants were identified as hexanal，nonanal，octanal，and 2-nonenal. Aldehydes exhibit pleasant grassy and fruity aromas at low concentrations. Notably，the wet-mixing process induced significant alterations in the profile of volatile compounds，while the drying process also impacted their contents. Compared with the milk base，the final formula powder showed distinct differences in the composition and content of key volatile substances. The increase in the total content of aldehydes may be attributed to heat treatment and is also related to the addition of nutrients. Therefore，manufacturers are advised to implement additional measures to ensure flavor stability during production，reduce off-flavors，and further improve infant acceptance.This study provides theoretical references for flavor regulation in the production process of infant formula.关键词：infant formula;flavor;heating process;gas chromatography-mass spectrometry （GC-MS）;headspace solid-phase microextraction（HS-SPME）95|41|0更新时间：2026-07-15
Scientific Papers
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摘要：A portable mass spectrometry method was established for the analysis of cyclopropanecarboxylic acid，1，1′-［（2-pyridinylmethylene）di-4，1-phenylene］ ester and chlorosipentramine in four matrices：beverages，pressed candies，preserved fruits，and jellies. Samples were extracted with methanol via ultrasonication，and an appropriate amount of the extract was placed into a dedicated reagent kit for instrumental detection. The two compounds showed good linearity within the concentration range of 50-2 500 ng/mL，with correlation coefficients（r2） all above 0.99. The limits of detection（LODs） was 0.5 mg/kg and the limits of quantification（LOQs） was 2.5 mg/kg for both. The average spiked recoveries of the two compounds at three levels（1×，2×，and 10× LOQ） ranged from 80.2% to 111%，with relative standard deviations（RSDs） between 10% and 18%. The method was applied to actual samples，and two batches of positive samples were detected. The results from the positive samples were verified and compared with those obtained by liquid chromatography-tandem mass spectrometry （LC-MS/MS）. The relative deviation was 10.6% and 17.2% respectively for chlorosipentramine and cyclopropanecarboxylic acid，1，1′-［（2-pyridinylmethylene）di-4，1-phenylene］ ester. With relative deviations below 20%，the results from the two methods were considered essentially consistent. Although portable mass spectrometry is inferior to conventional LC-MS/MS in terms of sensitivity，precision，and linear correlation，it offers the advantages of simple operation and suitability for on-site rapid screening. It is applicable for preliminary screening and on-site supervision of illegal additives，providing timely and effective technical support for food safety regulation.关键词：portable mass spectrometry;food;new weight-loss drugs144|124|0更新时间：2026-07-15 -
摘要：This study aimed to establish a label-free nanopore single-molecule detection method for the topological recognition of G-quadruplexes（G4s）. First，using the parallel vascular endothelial growth factor（VEGF） promoter G4 sequence as the test target，we compared the detection performance of three nanopores：Mycobacterium smegmatis porin A（MspA），aerolysin（AeL），and α-hemolysin（HL），and selected α-hemolysin as the optimal nanopore for subsequent experiments. Subsequently，parallel-type c-Myc proto-oncogene 27 bp sequence（c-Myc27bp），antiparallel-type thrombin-binding aptamer（TBA），and hybrid-type human telomeric DNA G4 sequence（H24A） were chosen as representative G4 models. Their topological conformations were verified by circular dichroism （CD） spectroscopy，and discriminative detection was achieved at the single-molecule level using the α-hemolysin nanopore. To address the issues of long dwell time and low translocation efficiency of c-Myc27bp，we constructed c-Myc77bp by introducing 25 adenine （A） residues at both ends of the original sequence，which optimized its translocation behavior. The results showed that the α-hemolysin nanopore could effectively distinguish single-stranded DNA（ssAf17） from G4 molecules with three distinct topological types. Notably，the optimized c-Myc77bp exhibited characteristic two-step signals during translocation，which significantly enhanced both signal discriminability and translocation efficiency. These findings confirm that the α-hemolysin-based nanopore single-molecule sensing system can be applied to the label-free recognition of G4 topological structures. This work provides a novel technical strategy for the analysis of higher-order nucleic acid structures，and offers methodological support for investigating the mechanisms of G4-related diseases and developing targeted therapeutics.关键词：nanopore technology;G-quadruplex;single-molecule sensing;topological discrimination;α-hemolysin127|119|0更新时间：2026-07-15 -
摘要：The rapid detection of hepatotoxic senecionine（SEN） is crucial for food safety and public health. In this study，a novel，label-free fluorescent aptasensor was developed based on a previously selected SEN-specific DNA aptamer. The core design principle relied on the strong fluorescence signal generated by the specific binding between thioflavin T（ThT） and the aptamer. In the presence of the target，SEN competitively displaced ThT from the ThT-aptamer complex，resulting in a significant fluorescence decrease（“signal-off”mode）. The demonstrated sensor exhibited excellent screening capability for SEN，with a detection limit as low as 40 nmol/L，and samples could be directly observed under blue light irradiation. The sensor demonstrated high specificity. In actual honey samples，the method still maintained a good linear response（0-10 μmol/L，r²=0.98），with a detection limit of 414 nmol/L. Spiked recoveries ranged from 99.2% to103%，and the relative standard deviations were below 3.0%，confirming its accuracy and reliability in complex matrices. This study presents a new method for SEN detection with high sensitivity，strong specificity，and simple operation，offering a promising technological platform for the on-site rapid screening of pyrrolizidine alkaloid biotoxins in food and herbal medicines.关键词：senecionine;thioflavin T;fluorescent probe;aptamer139|89|0更新时间：2026-07-15
Experimental Techniques and Methods
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摘要：To achieve high spatiotemporal resolution characterization of ultrafast material dynamics，a self-designed picosecond time-resolved ultrafast fluorescence spectroscopy system was constructed based on a confocal micro-Raman spectrometer. The system integrated a femtosecond laser excitation source，a confocal Raman spectroscopy module，and a time-correlated single-photon counting detection module. Through optical coupling and synchronized signal acquisition，it enabled submicron spatially resolved Raman spectroscopy and imaging，photoluminescence spectroscopy and imaging，and picosecond time-resolved fluorescence lifetime measurements. Experimental results demonstrated that the system could obtain carrier recombination dynamics on the picosecond scale. It also supported multimodal scanning imaging combining Raman and fluorescence measurements. This established a three‑dimensional“space-time-spectrum”characterization platform. The system provides key theoretical support and an experimental paradigm for the innovative design and performance optimization of various advanced optoelectronic materials and devices.关键词：time-resolved fluorescence;Raman spectroscopy;confocal microscopy;spectrometer design176|196|0更新时间：2026-07-15
Instrument development and application
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摘要：Traditional Chinese medicinal materials are prone to generating mycotoxins and endogenous toxic substances during production and storage，which seriously threaten medication safety. Although traditional instrumental detection features high accuracy，it suffers from high cost，complicated sample pretreatment，and difficulty in on-site rapid screening. This paper reviews the research progress of immunoassays in detection of mycotoxins and endogenous toxic substances in traditional Chinese medicinal materials，clarifies the sources，classification and matrix interference mechanisms of toxins，and focuses on the principles，application characteristics and research status of enzyme-linked immunosorbent assay，chemiluminescence immunoassay，immunochromatography and immunochip，as well as compares the performance differences of these methods. Immunoassays are rapid，simple，highly sensitive and high-throughput，which can effectively compensate for the shortcomings of traditional instrumental methods and serve as the core technology for rapid toxin detection in traditional Chinese medicines. However，problems including matrix interference，difficulties in antibody preparation and imperfect standards for portable technologies restrict their large-scale application. In the future，research should focus on the development of novel recognition elements，multi-target detection，nano-signal amplification and intelligent portable systems to support the whole-process quality and safety control of traditional Chinese medicines.关键词：immunoassay;traditional Chinese medicine （TCM）;mycotoxins;endogenous toxic substances;immunochromatography;chemiluminescence;immunochip79|27|0更新时间：2026-07-15
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