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    Chinese Journal of Chromatography
    2026, Vol. 44, No. 4
    Online: 08 April 2026

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    Articles
    Preparation of a novel polyhydroxy silica stationary phase and application in the separation of alginate oligosaccharides
    JIAO Ruiwen, ZHANG Dandan, HU Xingyuan, ZHU Wanting, LI Xiang, CAI Yidi, REN Dandan, WANG Qiukuan, WU Long, ZHOU Hui
    2026, 44 (4):  373-382.  DOI: 10.3724/SP.J.1123.2025.03006
    Abstract ( 150 )   HTML ( 15 )   PDF (1461KB) ( 52 )  

    Hyperbranched polyglycerols (HPG) represent an emerging class of dendritic polyethers characterized by a highly branched, three-dimensional architecture and a multitude of terminal hydroxyl groups. This distinctive structural configuration confers exceptional hydrophilicity, biocompatibility, and a high density of modifiable surface functionalities, thus establishing HPG as highly promising materials for the development of advanced chromatographic stationary phases. Their application is particularly relevant for the separation of polar and hydrophilic analytes, which has long posed a significant challenge in conventional reversed-phase liquid chromatography. The integration of such hyperbranched polymers with robust inorganic substrates, such as silica gel, has recently gained traction as a sophisticated materials strategy. This approach synergistically combines the superior mechanical strength and pressure resistance of the inorganic matrix with the rich surface chemistry and tunable hydrophilicity of the polymer, thereby addressing critical limitations of traditional stationary phases in hydrophilic interaction liquid chromatography (HILIC) applications.In the present study, a novel HILIC stationary phase, designated HPG-Sil 3, was synthesized through the in-situ ring-opening polymerization of glycidol monomers from the surface of aminopropyl-functionalized silica microparticles. The synthesis commenced with a meticulous silanization step to graft (3-aminopropyl)triethoxysilane (APTES) onto the silica surface, thereby introducing a uniform layer of primary amine groups. These amine functionalities served as initiation sites for the subsequent grafting-from polymerization, ensuring the formation of a covalently anchored, robust HPG layer. This covalent immobilization strategy is critical for mitigating stationary phase degradation and polymer leaching under prolonged chromatographic use, thereby guaranteeing long-term operational stability. The successful fabrication of the HPG-Sil 3 material and its physicochemical properties were thoroughly characterized using a suite of analytical techniques. Elemental analysis indicated a substantial increase in carbon and hydrogen content post-modification, providing quantitative evidence of organic polymer grafting. Fourier-transform infrared (FTIR) spectroscopy further corroborated this result, revealing signature absorption bands associated with the stretching vibrations of O-H and C-O-C ether linkages, which are characteristic of the HPG polyether structure. Thermogravimetric analysis (TGA) demonstrated the material’s excellent thermal resilience, with the onset of HPG decomposition occurring above 200 ℃, a temperature window far exceeding the operational range of typical HILIC analyses. Textural properties, evaluated via nitrogen physisorption, showed a predictable decrease in specific surface area and pore volume relative to the unmodified silica substrate. This reduction is attributed to the partial filling of the mesoporous silica network by the grafted HPG chains. Importantly, the material retained a sufficiently open porous structure to facilitate efficient mass transfer of analytes during chromatographic runs. To systematically investigate the chromatographic behavior and retention mechanism of the HPG-Sil 3 phase, a set of model polar compounds, including thymine, uracil, hypoxanthine, and adenosine, was selected. The influence of critical mobile phase parameters on the analyte retention factor (k) was examined, including the acetonitrile (ACN) content, the concentration of ammonium acetate buffer, and the buffer pH. The observed retention trends were unequivocally indicative of a dominant HILIC mechanism. A pronounced increase in retention with increasing ACN content was observed for all analytes, consistent with the enhanced partitioning of solutes into a water-rich layer immobilized on the hydrophilic stationary phase surface. Conversely, an increase in buffer concentration led to a decrease in retention, a phenomenon explained by the competitive adsorption of buffer ions with the analytes for polar interaction sites on the HPG layer. Furthermore, the retention of ionizable analytes, namely hypoxanthine and adenosine, was demonstrably influenced by the buffer pH, as pH variations alter their ionization state and thus their overall hydrophilicity and interaction strength with the stationary phase. Under the optimized chromatographic conditions, all four model analytes were baseline separated within a 10-min runtime, exhibiting excellent peak symmetry and high repeatability. The practical utility of the HPG-Sil 3 stationary phase was further demonstrated through the efficient separation of alginate oligosaccharide homologs with degrees of polymerization (DP) ranging from 2 to 7. The elution order followed increasing DP, which aligns perfectly with the HILIC retention principle, as larger oligosaccharides possess more hydroxyl groups and exhibit stronger hydrophilic interactions. The stationary phase also demonstrated remarkable operational stability, with no observable changes in retention times or chromatographic efficiency over 10 consecutive injections, underscoring its robustness for routine analytical applications. In conclusion, the HPG-Sil 3 stationary phase synthesized in this work exhibits outstanding hydrophilic separation performance, a well-understood HILIC retention mechanism, and excellent long-term stability. These attributes position it as a highly competitive and promising material for the analysis of a wide array of polar compounds, including nucleosides, carbohydrates, and polar pharmaceuticals, across diverse fields such as metabolomics, biopharmaceutical analysis, and food chemistry. Future research will focus on the precise control of polymer parameters, including molecular weight, branching density, and post-functionalization, to fine-tune the properties of the HPG layer for tailored selectivity towards specific applications. Furthermore, a systematic evaluation of its performance using complex biological and environmental matrices will be conducted to assess its practical applicability.

    Magnetic fluorinated covalent triazine frameworks for efficient extraction of perfluorinated compounds
    ZHANG Wenmin, LIU Guancheng, FANG Min, GUO Junling, ZHANG Lan
    2026, 44 (4):  383-392.  DOI: 10.3724/SP.J.1123.2025.07004
    Abstract ( 136 )   HTML ( 6 )   PDF (1491KB) ( 40 )  

    Perfluorinated compounds (PFCs) are a new type of persistent organic pollutants. When consumers consume soft drinks contaminated with PFCs, it can cause severe systemic diseases. Increasing concern regarding the presence of PFCs in soft drinks has resulted in the need for reliable analytical methods for the monitoring of PFCs. However, the content of PFCs in soft drinks is extremely low and the matrix is complex, making it difficult to directly determine their content using high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). Therefore, the necessary sample pretreatment is required before instrumental analysis. Magnetic solid-phase extraction (MSPE) is a simple, rapid, and efficient solid-liquid separation technique, and its extraction efficiency depends on the characteristics of the magnetic adsorbent. Covalent triazine frameworks (CTFs) are porous organic polymers connected by triazine bonds. They have the characteristics of large specific surface area, rich pore structure, adjustable functionality, good chemical stability and thermal stability, making them widely used in sample pretreatment. In this study, a magnetic fluorinated covalent triazine framework material (Fe2O3/CTF-F) was prepared by a one-pot method and characterized in detail. The X-ray photoelectron spectra (XPS), Fourier-transform infrared (FT-IR) spectrum, and X-ray diffraction (XRD) pattern demonstrated the successful synthesis of Fe2O3/CTF-F with a high fluorine content (17.50%), which was formed through tetrafluoroterephthalonitrile polymerization and hydrated ferric chloride decomposition. The highly fluorinated material can provide a specific and strong affinity for PFCs through fluorous-fluorous (F-F) interactions. The experimental results of nitrogen adsorption-desorption and magnetic properties showed that the Fe2O3/CTF-F has a high specific surface area (1 452.3 m2/g) and porosity (0.82 cm3/g), as well as a strong magnetic responsivity (7.1 emu/g). It indicates that the Fe2O3/CTF-F possesses a large number of accessible adsorption sites and a rapid magnetic separation capability, providing a guarantee for efficient extraction of PFCs. Subsequently, the Fe2O3/CTF-F was used as an adsorbent for MSPE technology for the efficient extraction of seven PFCs. Because of its many accessible adsorption sites and strong fluorine-fluorine interactions, the Fe2O3/CTF-F showed excellent extraction ability for PFCs. Finally, by combining the MSPE method with HPLC-MS/MS technology, a new analytical method was established for the analysis of PFCs in soft drinks. To achieve the best performance, single-factor experiments were conducted to optimize the dosage of the adsorbent, the extraction time, the elution solvent and elution time in the MSPE process. Under the optimal conditions, the established analytical method has the advantages of wide linear ranges (0.008–250.0 pg/mL), high linear correlations (R≥0.999 2), low LODs (0.002–0.005 pg/mL), and good repeatability (RSDs≤8.2%, n=5). The established analytical method was then used to analyze five kinds of soft drink samples, and ultra-trace amounts of PFCs were detected in all samples, with contents ranging from 3.5 to 54.6 pg/mL. Among them, the highest content of perfluorooctanoic acid (PFOA) measured was 54.6 pg/mL, and its content did not exceed the limit stipulated in the national standard GB 5749-2022 (80 pg/mL). Besides, the established analytical method was also compared comprehensively with other reported methods. The established method only requires a small amount of adsorbent (5.0 mg), and can achieve a low detection limit (0.002 pg/mL) after a short pretreatment time (20 min). The comparison results indicate that the established method has the advantages of being rapid, sensitive, and accurate, and can be used for the monitoring of PFCs in soft drinks. Meanwhile, the preparation method of the Fe2O3/CTF-F in this study is very simple and convenient, which is conducive to the transformation and application of this method. In conclusion, the Fe2O3/CTF-F is a highly potential adsorbent for the efficient extraction of PFCs, and the established analytical method is also suitable for the high-sensitivity detection of PFCs in soft drinks.

    Determination of 65 synthetic cannabinoids in whole blood by QuEChERS-ultra performance liquid chromatography- mass spectrometry
    XI Zhang, YE Yi, LI Songpan, KANG Jing, LIU Weiqun, ZHANG Jing, LI Daoxia
    2026, 44 (4):  393-402.  DOI: 10.3724/SP.J.1123.2025.04037
    Abstract ( 112 )   HTML ( 15 )   PDF (1088KB) ( 57 )  
    Supporting Information

    Synthetic cannabinoids (SCs) have become the most diverse and widely abused class of new psychoactive substances in the world. Blood and urine are classic sample matrices for in vivo toxin analysis, but some SCs have high lipophilicity, and the concentration of parent drugs in urine is extremely low, making them difficult to detect. Metabolites need to be investigated, and SCs with similar structures can produce the same metabolites. Therefore, establishing urine detection methods and interpreting results are relatively complex. In contrast, the detection of synthetic cannabinoid parent drugs in blood is more straightforward, and detecting parent drugs in blood can serve as direct evidence in legal cases. In order to detect the abuse of SCs, a QuEChERS-ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed to simultaneously determine 65 SCs in blood. The sample preparation and detection conditions were optimized. Quantification was achieved using an internal standard and matrix-matched calibration curves, enabling rapid screening and quantitative analysis of the 65 SCs in blood. Following protein precipitation with acetonitrile, the blood extract was further extracted and purified using QuEChERS reagents. Chromatographic separation of all 65 SCs was performed on a Waters Acquity UPLC HSS T3 column (100 mm×2.1 mm, 1.8 μm) maintained at 40 ℃. Detection employed dynamic multiple reaction monitoring (dMRM) mode with a mobile phase consisting of 0.1% (volume fraciotn) formic acid aqueous solution and acetonitrile, delivered at a flow rate of 0.25 mL/min. The injection volume was 2 μL. The 65 SCs exhibited good linear relationships in the mass concentration range of 0.05-200 ng/mL with correlation coefficents (r) exceeding 0.992. The limits of detection (LODs) were between 0.01 and 0.2 ng/mL, and the limits of quantitation (LOQs) were between 0.05 and 0.5 ng/mL, respectively, which meet the requirements for analyzing SCs in blood sample. The intra-day and inter-day precisions (n=6) were determined to be 1.0%–9.9% by spiking blank blood samples with the 65 SCs at mass concentrations of 1, 5, and 50 ng/mL. The recoveries of the 65 SCs were between 62.2% and 116.9%, and the matrix effects were between 70.2% and 117.7%. All analytes demonstrated good stability and acceptable dilution integrity in blood samples. Using the established method, 10 blood samples from suspected drug use cases were successfully screened for SCs. The target compounds were detected in all 10 samples, specifically including ADB-BUTINACA, MDMB-4en-PINACA, MDMB-FUBICA, and 5F-MDMB-PICA with mass concentrations ranging from 1.9 to 23.1 ng/mL. The detection rates of ADB-BUTINACA and MDMB-4en-PINACA were 90% and 50%, respectively, suggesting their relatively high prevalence in China’s illegal drug market. In addition, two or more SCs were detected simultaneously in six blood samples. Compared with other existing literature methods, this study combines QuEChERS with precipitation protein method for blood sample pretreatment, greatly improving the detection efficiency and suitable for rapid screening of whole blood samples in batches. The results demonstrate that the established method offers accuracy, rapidity, sensitivity, and effective chromatographic separation. It can serve as a reliable tool for forensic laboratories to perform rapid screening and quantitative analysis of SCs in blood, providing robust technical support for combating drug-related crime and supporting social stability.

    Determination of ergot alkaloids toxins in forage grass by ultra performance liquid chromatography-tandem mass spectrometry coupled with solid-phase supported liquid-liquid extraction
    REN Caixia, WANG Xiaomin, SHENG Wanli, HAN Yizhi, ZHANG Chunyan, ZHENG Shuzhan
    2026, 44 (4):  403-412.  DOI: 10.3724/SP.J.1123.2025.02014
    Abstract ( 176 )   HTML ( 4 )   PDF (1732KB) ( 73 )  

    Toxic alkaloids, especially ergot alkaloid toxins, present in forage grass and pose serious health hazards to humans and livestock. Hence, a method for simultaneously detecting these dangerous plant toxins is needed. This study established a rapid method for detecting ten ergot alkaloid toxins using solid-phase supported liquid-liquid extraction technology combined with ultra performance liquid chromatography-tandem mass spectrometry. Forage samples were extracted with 8.0 mL of acetonitrile containing 1% formic acid. The extraction mixture was vortexed and then centrifuged at 8 000 r/min for 5 min, after which 1.0 mL of the supernatant was mixed with 3.0 mL of water and vortexed for 0.5 min. The entire mixture was transferred to a solid-phase supported liquid-liquid extraction column and allowed to stand for 10 min. The column was eluted with 6.0 mL of ethyl acetate and the collected eluate was evaporated under nitrogen at temperatures below 40 ℃. The residue was dissolved in 1 mL of acetonitrile-water (1∶3, volume ratio, containing 0.5% formic acid), and separated using an Acquity UPLC BEH C18 column (100 mm×2.1 mm, 1.7 μm). A solution of 0.5% formic acid in water containing 0.25 mmol/L ammonium acetate was used as mobile phase A, while 0.5% formic acid in acetonitrile was used as mobile phase B. The following gradient elution program was used: 0-1.0 min, 90%B; 1.0-5.0 min, 90%B-75%B; 5.0-10 min, 75%B-50%B; 10-12 min, 50%B-10%B; 12-14 min, 10%B; 14-16 min, 10%B-90%B. Ten ergot alkaloid toxins (including three pairs of isomers: ergocornine, ergocristine, ergocristinine, ergocryptine, and ergocryptinine) were effectively separated following gradient elution. Positive electrospray-ionization mode and multiple reaction monitoring (MRM) scanning was used for detection, with an external standard curve used for quantification purposes. The ten ergot alkaloid toxins exhibited good linear relationships within their respective linear ranges (r2>0.995). Alfalfa, Leymus chinensis, oats, and silage corn exhibited LODs of 0.1–2.3 μg/kg for the ten ergot alkaloid toxins, with LOQs of 0.4–7.3 μg/kg. The developed method exhibited overall recovery rates of between 66.3% and 116.7%, with relative standard deviations of less than 9.9%. The matrix effect mainly manifested itself in the form of matrix suppression, with silage corn exhibiting a significantly stronger matrix effect than the other three types of forage. Silage corn exhibited a strong matrix effect in more than 50% of samples, while alfalfa, oats, and Leymus chinensis showed relatively low matrix effects, with more than 63% being weak. The developed method is simple to operate, provides accurate results, and exhibits minimal interference; hence, it is suitable for simultaneously screening and confirming ergot alkaloid toxins in forage, thereby providing technical support for monitoring forage quality, while also expanding the applicability of solid-phase supported liquid-liquid extraction technology in the toxin-detection field.

    Determination of eight ultraviolet absorbers in surface water and wastewater by ultra performance liquid chromatography-triple quadrupole mass spectrometry
    SUN Huijing, ZHANG Beibei, HUANG Mengqiao, WANG Hui, HU Guanjiu, CHEN Huimin
    2026, 44 (4):  413-421.  DOI: 10.3724/SP.J.1123.2025.08001
    Abstract ( 123 )   HTML ( 7 )   PDF (1756KB) ( 34 )  

    Ultraviolet (UV) absorbers are a group of chemicals widely used in various industrial and consumer products, such as plastics, coatings, and personal care products, to protect against UV radiation. Among them, benzotriazole derivatives (e.g. UV-326, UV-327, UV-328, UV-329, and UV-P) are the most frequently employed. Owing to their widespread use and potential persistence in the environment, these compounds have been detected in various environmental matrices, including surface water, wastewater, sediment, and biota. Certain UV stabilizers have been reported to exhibit endocrine-disrupting properties and pose potential ecological risks. Therefore, developing sensitive and reliable analytical methods for monitoring these compounds in environmental samples is essential. To address the need for reliable detection methods, this study developed a robust method based on liquid-liquid extraction (LLE) coupled with ultra performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-MS/MS) for the simultaneous determination of eight UV absorbers in surface water and wastewater. Critical optimization of the pretreatment process focused on solvent selection and purification parameters. The finalized protocol involved extracting 100 mL water samples twice with dichloromethane. After nitrogen-assisted solvent evaporation, the residue was reconstituted in methanol and mixed with the internal standard solution. UPLC-MS/MS parameters were optimized to achieve optimal instrumental performance. The separation of the eight UVs was performed using a BEH C18 column (100 mm × 2.1 mm, 1.7 μm) with a gradient elution system consisting of 0.2% (mass fraction) formic acid aqueous solution and acetonitrile at a flow rate of 0.4 mL/min. The injection volume was 2 μL. Detection was performed in positive ion mode using multiple reaction monitoring (MRM), with an electrospray ionization voltage set at 5 500 V. Quantification was achieved via internal standard calibration to ensure precision and accuracy. The method demonstrated excellent linearity for all target compounds across their respective concentration ranges, with a correlation coefficient (r)>0.995. The method detection limits (MDLs) ranged from 1.3 ng/L to 2.8 ng/L, indicating high sensitivity. Recovery tests conducted at low, medium, and high spiking levels (20, 200, and 800 ng/L) yielded recoveries of 80.3%-117.8%, with relative standard deviations (RSDs) of 1.4%–10.5%, confirming the method’s robustness across different sample matrices. Application of the method to 10 textile dyeing wastewater samples revealed the presence of four UV absorbers: UV-329, UV-326, UV-328, and UV-350. Notably, UV-329 showed the highest detection frequency and accounted for 85% of the total detected mass concentrations, ranging from 5.2 to 2 109 ng/L. Its prevalence suggests its widespread use in industrial processes and potential persistence in aquatic environments. In conclusion, the developed method is highly sensitive, accurate, and reliable for detecting UV absorbers in environmental water samples. Its successful application to surface water and wastewater analysis provides a valuable tool for monitoring these emerging contaminants, thereby supporting the assessment of their environmental and health risks. This study highlights the importance of continued monitoring and regulation of UV absorbers to mitigate their potential adverse effects on ecosystems and human health.

    Deep eutectic solvent and improved needle filter-based liquid-membrane microextraction combined with high performance liquid chromatography for the determination of sulfonamide and fluoroquinolone residues in milk
    XU Ruiming, WU Youyi, GU Zhihao, WEI Wei, LU Xingyu, XIA Zihan
    2026, 44 (4):  422-431.  DOI: 10.3724/SP.J.1123.2025.03012
    Abstract ( 162 )   HTML ( 3 )   PDF (1766KB) ( 52 )  

    Antibiotic residues in dairy products pose serious threats to food safety and affect human health. To accurately determine the level of sulfonamide and fluoroquinolone residues in milk, a deep eutectic solvent and improved needle filter-based liquid membrane microextraction (DES&INF-LMME) method combined with high performance liquid chromatography (HPLC) was developed for their determination in this study. Octanoic acid (hydrogen bond donor) and thymol (hydrogen bond acceptor) were selected to synthesize hydrophobic deep eutectic solvent, which acted as supporting liquid membrane (SLM) and extractant in the LMME process. Further investigations were conducted to examine the effects of various factors on extraction efficiency, including type and volume of DES, molar ratio of thymol to octanoic acid, type of extraction membrane, sample volume, salt type and addition amount, pH value, stirring speed and extraction time. The optimal extraction conditions were determined as follows: DES∶thymol-octanoic acid=2∶1 (n/n), 100 μL; filter membrane, polytetrafluoroethylene (PTFE); sample volume and pH, 30 mL (addition of 3 g ammonium sulfate) and pH=7; stirring speed, 400 r/min; extraction time, 35 min. Under the optimized conditions, the proposed DES&INF-LMME-HPLC exhibited good linearity in the range of 2.86-1 000 μg/L (r2>0.997 2), with limits of detection (LODs) (S/N=3) and limits of quantification (LOQs) (S/N=10) ranging from 0.86-10.0 μg/L and 2.86-33.3 μg/L, respectively. The obtained enrichment factors (EFs) ranged from 32 to 84 with recoveries of 99.4%-109.2%. The intra-day and inter-day precisions at three spiked levels (low: 30 μg/L; medium: 50 μg/L; high: 100 μg/L), expressed as relative standard deviations (RSDs), were no more than 4.9% and 5.3%, respectively (n=6). This method has been successfully applied to the determination of four antibiotics in commercially available milk products. The spiked recoveries for the four antibiotics at high, medium and low levels ranged from 88.9% to 113.4%. The proposed method is accurate, simple, sensitive and eco-friendly, and could be a good reference to the development of new analytical method for antibiotic residues in dairy products.

    Assessment on data processing methods for nontarget identification of per- and polyfluoroalkyl substances using liquid chromatography-high-resolution mass spectrometry
    ZHANG Boxuan, HE Qinwen, HAN Baocang, MA Cundi, LUO Zhujun, MENG Xiangzhou
    2026, 44 (4):  432-443.  DOI: 10.3724/SP.J.1123.2025.07011
    Abstract ( 202 )   HTML ( 9 )   PDF (1989KB) ( 45 )  

    The widespread use, persistence, bioaccumulation, and toxicity of per- and polyfluoroalkyl substances (PFAS) have raised global concern. The number of PFAS types continues to grow, driven by changing industrial demands and regulatory environments. Non-target analysis using high-resolution mass spectrometry (HRMS) is an effective methodology for identifying novel and unknown PFAS in environmental matrices. The efficacy of non-target analysis is critically influenced by the data acquisition mode, peak picking algorithm, and deconvolution strategy. Using ultra-high performance liquid chromatography coupled with an Orbitrap mass spectrometer (UHPLC-Orbitrap MS), this study aims to systematically evaluate data processing methods for non-targeted PFAS identification under data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes. A clean sludge sample was spiked with 34 PFAS standards at three levels to assess method performance, alongside the analysis of three electroplating sludge samples. To compare the identification performance between DDA and DIA modes, a multi-step evaluation process was employed. Firstly, we assessed the peak picking capabilities of two widely used data processing software packages, MS-DIAL and MZmine. The key parameters for peak picking process are MS1 mass tolerance of 0.002 5 Da, MS2 mass tolerance of 0.01 Da, minimum peak height of 1 000, and retention time alignment tolerance of 0.1 min. Secondly, a comparison was made regarding DIA data deconvolution, specifically between MS2Dec algorithm and IonDecon algorithm. Finally, FluoroMatch was utilized to compare the true positive rate (TPR) and positive predictive value (PPV) of PFAS identification in both DDA and DIA datasets. In the spiked samples, the [M-H]- precursor ions for 33 PFAS standards and the [M-CO2-H]- ion for HFPO-DA were successfully detected and manually verified across all three levels. For peak picking, MS-DIAL demonstrated superior performance, achieving a 100% detection rate in all spiked samples, outperforming MZmine. When comparing deconvolution performance for DIA data, MS2Dec algorithm and the IonDecon algorithm showed similar efficacy, although MS2Dec algorithm exhibited slightly better results for low-concentration samples. In DDA mode, the true positive rate for PFAS identification increased from 80% to 100% with rising analyte concentration, accompanied by a minimal decrease in positive predictive value. Conversely, in DIA mode, the true positive rate remained at 100% across all concentrations, but positive predictive value decreased as concentration increased, primarily due to interferences from in-source fragmentation and adduct ions. The degree of in-source fragmentation of perfluorocarboxylic acids (PFCAs) decreases with increasing carbon chain length. However, the proportion of adduct ions remains nearly constant across different PFAS, leading to false positive identification of hydrogen-substituted PFAS. Based on the evaluation results, the data processing methods for DDA and DIA modes were optimized. These methods were then applied to three electroplating sludge samples, leading to the identification of 36 PFAS species belonging to 10 classes, including eight perfluorocarboxylic acids (PFCAs), eight perfluorosulfonic acids (PFSAs), one hydrogen-substituted perfluorosulfonic acid (H-PFSA), five unsaturated perfluorosulfonic acids (UPFSAs), one carbonyl perfluorosulfonic acid (KPFSA), one chlorine-substituted perfluorosulfonic acid (Cl-PFSA), one n∶2 fluorotelomer sulfonic acid (n∶2 FTSA), five chlorinated polyfluoroethersulfonic acids (Cl-PFESAs), two hydrogen-substituted polyfluoroethersulfonic acids (H-PFESAs), and four polyfluoroethersulfonic acids (PFESAs). Their presence was largely attributed to the use of chrome mist suppressants in the electroplating process. Combining DDA and DIA data for FluoroMatch input captured more information on unknown PFAS, possibly because the inclusion of multiple samples improves peak extraction. Based on the performance of PFAS identification in spiked and real samples, we developed a processing method that couples DDA and DIA data. This method can generate a composite list of identified PFAS while keeping data files independent, increasing the true positive rate and efficiency of identification. This study systematically evaluated nontargeted PFAS data processing methods, clarifying the optimal combination of tools for key steps (acquisition mode, peak picking, and deconvolution), and validating its application potential in complex environmental matrices.

    Development of a machine learning-based ionization efficiency prediction model for per- and polyfluoroalkyl substances and its application in semi-quantitative analysis
    SUN Shenzheng, LI Yaoyao, GAO Yan, LI Kangcong, CHEN Zhi, LI Xiuqin, ZHANG Qinghe
    2026, 44 (4):  444-452.  DOI: 10.3724/SP.J.1123.2025.02012
    Abstract ( 178 )   HTML ( 7 )   PDF (1070KB) ( 42 )  

    Per- and polyfluoroalkyl substances (PFASs) represent a category of emerging contaminants of global concern in fields such as environmental science and food safety, due to their persistence, bioaccumulative properties and potential toxicity. Although screening methods for PFASs using high resolution mass spectrometry (HRMS) have been developed rapidly, the diversity of PFASs and the absence of standards pose significant challenges for quantitative analysis. In this study, 50 PFASs were analyzed by HPLC-HRMS. The ionization efficiency (IE) was calculated as the slope of the calibration curve. A quantitative structure-activity relationship (QSAR) model was developed employing machine learning to predict the ionization efficiencies of PFASs using PaDEL molecular descriptors. The model enables semi-quantitative estimation of PFASs concentrations in the absence of reference standards by incorporating predicted IE values. Eighteen critical descriptors were selected from a total of 1 444 PaDEL descriptors through the application of recursive feature elimination (RFE). These selected descriptors encompassed topological descriptors, geometrical descriptors, autocorrelation descriptors, electrostatic and polarity descriptors. These individual descriptors including VE1_Dzv, GATS6i, JGI10, GATS1p and MATS4m were of great importance. Three algorithms including elastic net linear regression, random forest (RF), and XGBoost were evaluated for model performance. In the elastic net linear regression model, the root mean square error (RMSE) for the training dataset was 0.049 0, and the coefficient of determination (R²) was 0.993 0; for the test dataset, the RMSE was 0.163 0, with an R² of 0.756 1. In the RF model, the RMSE for the training dataset was 0.163 1, and the R² was 0.921 9; for the test dataset, the RMSE was 0.131 6, with an R² of 0.840 9. In the XGBoost model, the RMSE for the training dataset was 0.052 1, and the R² was 0.992 0; for the test dataset, the RMSE was 0.118 4, with an R² of 0.871 3. Nonlinear algorithms of random forest and XGBoost demonstrated superior predictive performance compared to the elastic net linear regression, with XGBoost exhibiting best performance. Random forest, a bagging-based approach, trains individual decision trees independently and aggregates predictions through averaging. In contrast, XGBoost employs gradient boosting methodology, iteratively optimizing the model by sequentially training new trees in order to address residuals from previous iterations. The independent training mechanism of random forest inherently lacks the iterative optimization framework that is characteristic of gradient boosting. Specifically, XGBoost systematically enhances predictive accuracy by generating new trees that target residual errors from preceding models, thereby progressively refining predictive performance. This fundamental difference in optimization strategy enables XGBoost to more effectively correct prediction errors compared to the ability of random forest. Based on the results of a comprehensive evaluation of the three models, the XGBoost algorithm was ultimately selected for its demonstrated performance advantages. The prediction errors of ionization efficiency (IE) for the 50 PFASs were within 1.67-fold, with a median value of 1.04-fold and RMSE of 1.06. The established XGBoost model was further applied for the semi-quantitative concentration prediction of 50 PFASs across concentration gradients, where the prediction errors ranged from 0.12 to 4.90-fold, with a median value of 0.96-fold and RMSE of 0.94. The accuracy of the prediction improved as the concentrations increased. Furthermore, the model was applied to predict concentrations of PFASs in fish tissue. After sample extraction and cleanup using solid-phase extraction, the samples were analyzed using HPLC-HRMS. The concentrations of PFASs were semi-quantified using the predicted IEs, yielding prediction errors ranging from 0.79-fold to 1.81-fold. These findings highlight the robustness of the IE prediction model for PFASs. Notably, the performance of the developed model was better than or comparable to the performance of previous studies. In conclusion, this study introduces a machine learning-based QSAR model for the prediction of ionization efficiency. This approach illustrates the ability to estimate the concentrations of PFASs in the absence of standards, thereby presenting considerable potential for the risk assessment of compounds lacking standards in suspect and non-targeted screening.

    Determination of atmospheric intermediate volatility organic compounds with thermal desorption-flow modulator comprehensive two-dimensional gas chromatography- time-of-flight mass spectrometry
    WANG Rui, LI Yingjie, WANG Jiahua, MA Changwen, JIANG Jiakui
    2026, 44 (4):  453-466.  DOI: 10.3724/SP.J.1123.2025.07009
    Abstract ( 145 )   HTML ( 5 )   PDF (2169KB) ( 28 )  

    Atmospheric intermediate volatile organic compounds (IVOCs) are complex mixtures. Due to the limited separation and identification capabilities of one-dimensional gas chromatography (1D-GC), a large portion of atmospheric IVOCs—which often elute as unresolved or complex peaks—are categorized as an unspeciated complex mixture (UCM). This constrains the accurate apportionment of atmospheric IVOCs. To address this problem, an alternative analytical method has been developed utilizing thermal desorption-flow modulation comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (TD-FM GC×GC-TOF MS) to measure atmospheric IVOCs. Analytical optimization focused on fill and flush time within a 3-second modulation period, with optimal values determined as 2 870 ms and 130 ms, respectively, to maximize separation efficiency and signal response. Compounds were separated on a ZB-5HT column (20 m×0.18 mm×0.18 μm) as the first dimension, with a BP-50 column (5 m×0.25 mm×0.20 μm) serving as the second dimension. Helium was employed as the carrier gas with column pressures maintained at 254.4 kPa (first dimension) and 202.1 kPa (second dimension). The following temperature program was used: 50 ℃ for 10 min, then increased to 300 ℃ at 10 ℃/min, with the final temperature held for 20 min. The MS was operated in electron impact (EI, 70 eV) ionization mode. Both the ion source and transfer line temperatures were set at 300 ℃. MS signals were recorded in full scan mode with a scan range of m/z 40 to m/z 800. During thermal desorption, the desorption temperature was set at 320 ℃, and the cold trap temperature was maintained at -10 ℃ to capture desorbed targets. The secondary desorption flow rate was set at 16 mL/min. Under these optimized conditions, the method demonstrated acceptable linearity, with correlation coefficients ranging from 0.922 3 to 0.998 4, for 69 selected targets spanning 1 to 20 ng/tube, with method detection limits (spiked at 1 ng/tube) between 0.010 7 and 0.410 1 ng/m3, with recoveries ranging from 80.4% to 136.0%. Relative standard deviation values among replicate samples (n=7) spiked at 1 ng/tube, 3 ng/tube, and 10 ng/tube levels were around 4.5%-33.9%, 3.2%-19.9% and 3.5%-18.6%, respectively. Application of the method to atmospheric IVOC samples collected from an urban site of Shanghai, revealed total IVOCs mass concentrations of 8.6-61.1 μg/m3. Of these, mass concentrations of 853 individual species identified by the present method comprised 96.2% of total IVOCs. Consequently,the newly developed method improved the identification rate for UCM. Importantly, the newly speciated aromatics, chlorinated IVOCs, and oxygenated IVOCs exhibited different emission sources distinct from those routinely monitored compounds. Therefore, this study established a reliable method for determining atmospheric IVOCs, offering strong data support for precise source apportionment of complex IVOCs in the atmosphere. Additionally, this method can be used to monitor IVOCs across various environmental metrics, thereby providing essential data to support the management and control of these compounds.

    Technical Notes
    Determination of 38 antibiotic residues in honey by magnetic dispersive solid-phase extraction-liquid chromatography-tandem mass spectrometry
    SUN Jing, ZHANG Yu, LIU Fengmao, ZHAO Wen, JIN Yue, ZHANG Lin, XUE Xiaofeng, CHEN Rui, ZHOU Huatian
    2026, 44 (4):  467-478.  DOI: 10.3724/SP.J.1123.2025.07017
    Abstract ( 87 )   HTML ( 8 )   PDF (1406KB) ( 40 )  
    Supporting Information

    Accurate antibiotic residue detection in honey is crucial for food safety and veterinary drug regulation in apiculture. Honey is a particularly challenging matrix. The high sugar content, strong viscosity, and pronounced matrix effects of the sample make it difficult to extract and detect target analytes effectively. Moreover, multiple antibiotics are used in beekeeping, while existing residue standards often provide incomplete coverage. These limitations highlight the urgent need for a robust and environmentally friendly multi-residue analytical method. In this study, a green and sensitive method was developed for the simultaneous determination of 38 antibiotic residues, including chloramphenicol, quinolones, and sulfonamides, in honey. Sample preparation was based on magnetic dispersive solid-phase extraction (MDSPE) using a mixed-mode hydrophilic-lipophilic balance (mHLB) magnetic sorbent. This sorbent combines hydrophilic and hydrophobic interactions, enabling efficient extraction of chemically diverse antibiotics. Method optimization was performed systematically. A Plackett-Burman design was used to screen seven factors influencing extraction. The sorbent dosage, sample volume, and extraction time were identified as the most significant. These variables were further optimized by response surface methodology, which minimized the number of experimental runs while clarifying interactions among factors. The final protocol required only 10 mg of sorbent, 5 mL of sample extract, and 1 mL of methanol for elution. This miniaturized approach represents an environmentally sustainable method. Chromatographic separation was achieved on a Poroshell 120 SB-C18 column (100 mm×2.1 mm,2.7 μm) using a gradient of acidified methanol and water. Detection was carried out by high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) with electrospray ionization operated in both positive and negative modes, and multiple reaction monitoring ensured high sensitivity and selectivity. The method was fully validated. Excellent linearity was obtained for all analytes in the range of 0.02-200 μg/L, with correlation coefficients above 0.99. Limits of detection ranged from 0.01 to 0.12 μg/kg, while limits of quantification ranged from 0.02 to 0.39 μg/kg. Recoveries at three spiked levels ranged from 70.5% to 109.3%, with relative standard deviations (RSDs) below 10.8%. Matrix effects ranged from 0.82 to 1.19, indicating effective suppression of interference and reliable quantification in complex honey samples. The method was successfully applied to 42 commercial honey batches from different geographical regions. Several antibiotics were detected, including chloramphenicol, as well as other compounds without established maximum residue limits. These findings indicate potential misuse of antibiotics in beekeeping and reveal important gaps in current regulatory frameworks, underscoring the need for continuous monitoring and timely updates to residue standards. In addition to high sensitivity and wide applicability, the method demonstrated strong environmental advantages. Green performance was assessed using the AGREEprep tool, which evaluates twelve principles of sustainable sample preparation. The method achieved a high score of 0.73, reflecting minimal solvent consumption, low sorbent use, low energy demand, and negligible hazardous waste. These features align with the principles of green analytical chemistry and significantly reduce the environmental impact of residue analysis. In conclusion, this work establishes an MDSPE-HPLC-MS/MS for multi-class antibiotic residue detection in honey. The method combines simplicity, sensitivity, robustness, and environmental compatibility. It provides reliable technical support for risk assessment and regulatory improvement of antibiotic residues in honey, and it offers a valuable reference for the development of green analytical methods for trace contaminants in other complex food and environmental matrices.

    Rapid determination of lubabegron residues in animal-derived foods by ultra performance liquid chromatography- tandem mass spectrometry
    YANG Cheng, ZHU Weixia, LIU Yafeng, ZHANG Hongwei, WEI Wei, HU Kai
    2026, 44 (4):  479-485.  DOI: 10.3724/SP.J.1123.2025.02006
    Abstract ( 170 )   HTML ( 7 )   PDF (894KB) ( 44 )  

    Lubaberone (LUB) is the first U S Food and Drug Administration (FDA) approved feed additives for reducing gaseous emissions from animals or their wastes, and the intake of animal-derived foods is an important source of human exposure to LUB. However, the lack of applicable analytical methods makes it difficult for regulatory authorities to monitor LUB in animal-derived foods. There is an urgent need to establish efficient and accurate methods for the analysis of LUB in animal-derived foods. In this study, a method was developed for the determination of LUB from six types of typical animal-derived foods (beef, bovine liver, bovine fat, mutton, sheep liver and sheep fat) by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The effects of extraction solvent types, extraction methods, extraction time and purification cartridges on the recovery of LUB were investigated, and the optimal conditions for sample pretreatment were confirmed. The homogenized samples were extracted using 0.5% formic acid acetonitrile via ultrasonication for 10 min, and then filtered by high-speed centrifugation, and the extracted solution was cleaned using SPE with a PRiME HLB cartridge. The LUB was separated on a Shim-pack GIST C18-AQ chromatographic column (100 mm×2.1 mm, 2.7 μm) with 0.1% formic acid aqueous solution-0.1% formic acid acetonitrile as mobile phases at a flow rate of 0.3 mL/min, and detected in positive ion switching mode (ESI+) with multiple reaction monitoring (MRM) scanning, and quantitatively analyzed using the external standard method. Under the optimized experimental conditions, LUB in different animal-derived food matrices showed good linearity within their respective linear concentration ranges with the correlation coefficients (r) greater than 0.99. The limits of detection (LODs) and the limits of quantification (LOQs) were 0.4‒1.0 μg/kg and 1.0‒2.0 μg/kg, respectively. The recoveries of LUB spiked at low, medium and high levels ranged from 81.5% to 116.5% with relative standard deviations (RSDs) of 2.0%‒8.2%. The method is simple, rapid and highly sensitive, which can enable the analysis of LUB residues in animal-derived foods, and provides analytical technology support for the daily detection of LUB residues in imported and exported animal-derived foods.

    Teaching Research
    Binary encryption comprehensive experiment based on agarose gel electrophoresis
    DUAN Jinwei, MA Lei, ZHAO Qian, WU Qianqian, XIN Boyu, YANG Jiahua, LI Yao, WANG Qizhao
    2026, 44 (4):  486-495.  DOI: 10.3724/SP.J.1123.2025.10029
    Abstract ( 143 )   HTML ( 11 )   PDF (2509KB) ( 46 )  

    This experiment is based on a 4-bit deoxyribonucleic acid (DNA) nanoswitch, in which specific DNA single strands trigger a “linear-to-circular” conformational transition. By leveraging the migration differences between the two conformations in gel electrophoresis, digital binary encoding is achieved. Different combinations of conformational switches can represent distinct information. Inspired by the “protection-deprotection” strategy in organic chemistry, an ribonucleic acid (RNA) protection strand is introduced to prevent the formation of the circular structure, thereby establishing an information encryption system. The system utilizes ribonuclease A (RNase A) for specific enzymatic cleavage to remove the protection, restoring information readout and establishing an RNA-regulated encryption system. By integrating DNA nanotechnology, binary encoding, and chemical protection strategies, agarose gel electrophoresis is applied throughout the entire experimental process, enabling full visualization from molecular construction to information read-write. This approach not only helps students master gel electrophoresis techniques and deepen their understanding of electrophoretic separation mechanisms and structure-activity relationships at the molecular level, but also exposes them to cutting‑edge fields such as molecular information encoding and DNA nanotechnology, effectively stimulating innovative thinking and interdisciplinary problem-solving skills.