Chinese Journal of Chromatography (Se Pu)

An analytical method based on dispersive solid-phase extraction (d-SPE) and ultrafast liquid chromatography-tandem mass spectrometry (UFLC-MS/MS) was employed for the determination of 43 mycotoxins in chestnut flour and wheat flour. A total of 128 samples consisting of 48 chestnut samples and 80 wheat flour samples were collected randomly and subjected to analysis. Finally, five specific toxins were selected as markers to identify these two foodstuffs. Acetonitrile-water (84∶16, v/v) was used to extract mycotoxins from chestnut flour and wheat flour. After extraction, the supernatant was transferred to the d-SPE equipment, using which purification was performed with C18 and EMR-Lipid (lipid adsorbent). Chromatographic separation was carried out by gradient elution with eluent A (ESI+: 0.1% formic acid, ESI-: water) and eluent B (ESI+: methanol-acetonitrile (1∶1) containing 0.1% formic acid, ESI-: acetonitrile) on a BEH C18 column (100 mm×2.1 mm, 1.7 μm). Quantitative analysis was performed with the aid of matrix-matched curves. When establishing the method, the experimental matrix for optimization was designed by central-composite design based on the response surface methodology. Quadratic polynomial equations were deduced to describe the relationships between the responses and variables, and assess the interaction effects among the variables to acquire the true optimal conditions with less workload. Using the optimum experimental conditions, the accuracy of the proposed method was determined through three-level spiking tests, while the precision was evaluated in terms of the repeatability (six replications per level). Satisfactory precisions (RSDs≤7.5% in chestnut flour and RSDs≤9.3% in wheat flour) were achieved in all tested assays. The recoveries were also acceptable, and ranged from 72.4% to 109.4% for chestnut flour and from 70.7% to 112.9% for wheat flour. The matrix effects of mycotoxins were 48%-128% in wheat flour and 41%-112% in chestnut flour. The detectability of mycotoxins in the two matrices was assessed by spiking the blank extracts with various low concentrations, and determined as the lowest values that can produce chromatographic peaks at a signal-to-noise ratio (S/N) of 3∶1. The obtained limits of quantification varied from 0.10 μg/kg to 20 μg/kg (bongkrekic acid) in both investigated matrices. Satisfactory linearities were obtained, with correlation coefficients>0.9991 for all the analytes. After validation, the contamination status of the multiple mycotoxins was evaluated for various concentration ranges. Based on the obtained data, both wheat flour and chestnut flour were severely contaminated, with 17 mycotoxins detected in them. Particularly, chaetoglobosin A, ochratoxin B, and penicillic acid were only detected in chestnut flour, while 3-acetyl-deoxynivalenol, deoxynivalenol, and nivalenol were detected in wheat flour. Further, the positive rates and contamination concentrations of chaetoglobosin A, ochratoxin B, and penicillic acid were not significant; hence, they did not qualify as identification markers. On the other hand, the incidence of deoxynivalenol in wheat flour almost reached 100%, which is very significant. Finally, deoxynivalenol and its four derivatives (3-acetyl-deoxynivalenol, 15-acetyl-deoxynivalenol, deepoxy-deoxynivalenol, and nivalenol) were treated as adulteration markers for the two foodstuffs. To improve the reliability of the conclusion, all samples were re-tested using the first method prescribed by the National Food Safety Standard, i. e., GB 5009.111-2016. Ten chestnut flour samples were also randomly selected to prepare moldy samples under suitable environmental conditions for the growth of Fusarium, to verify the production and release of deoxynivalenol and its derivative mycotoxins under the extreme conditions. The distribution data for these mycotoxins were consistent with those obtained by d-SPE, confirming that the adulteration criterion is trustworthy. The established method is simple, rapid, sensitive, and accurate, and can effectively meet the requirements for the simultaneous determination of multiple mycotoxins in chestnut flour and wheat flour. Moreover, the adulteration results, which were obtained for natural contaminants (deoxynivalenol and its four derivatives), are less affected by humans and hence, much more accurate and reliable.

Jian Zhou

Xiaohong Chen

Micong Jin

Chinese Journal of Chromatography

Adulteration identification of wheat flour in chestnut flour based on differences in mycotoxin contamination by liquid chromatography-tandem mass spectrometry

Ovarian cancer is a serious threat to women's health and safety. So far, people have discovered more than 130 small molecule compounds of natural origin for anti-tumor, of which approximately 50% are of microbial origin. The

Xiao-Lin Ma

Lai-Yan Cai

Yan-Ying Liu

Shang-Ping Xing

Liang Kang

Xia Wei

Dan Zhu

Using metabolomics to explore the effects of epigenetic-modification strategies on the metabolites of &amp;lt;italic&amp;gt;Acanthus ilicifolius&amp;lt;/italic&amp;gt; L. endophytic fungi against ovarian cancer

利用代谢组学探究表观遗传修饰策略对卵巢癌内生真菌<italic>老鼠簕</italic>L.代谢物的影响

Urea is a simple organic compound that is widely used in both the industry and daily life. Compared with conventional methods, the preparation of urea by electrochemical synthesis is more environmentally friendly and sustainable. However, after the reaction, low amounts of urea and high concentrations of inorganic ions, including [Formula: see text] concentration was achieved without interference. Thus, the developed method can be applied for the detection of trace urea and other related ions in urea-containing electrolyte products.

Rui Shen

Yong-Yi Li

Xiao-Jing Gao

Chao-Ou Shi

Determination of electrosynthesized urea products by igh performance liquid chromatography based n porous graphitic carbon column

基于多孔石墨碳柱的高效液相色谱法测定电合成尿素产物

利用超高效液相色谱-四极杆-飞行时间质谱（UPLC-Q-TOF/MS）快速与高分辨的分析优势，通过系统地考察样品制备、仪器分析中影响维生素C响应灵敏度和稳定性的各主要因素，建立了果蔬中维生素C的定量分析方法。果蔬样品在干冰保护下高速匀浆获得均匀的匀浆液，用0.1%（v/v）甲酸溶液提取后，采用Waters Acquity-UPLC T3色谱柱（100 mm×2.1 mm，1.8 μm）分析，柱温为30℃，进样量为5 μL，流动相为0.05%（v/v）甲酸-甲醇溶液（8：2，v/v），流速为0.25 mL/min。提取的定量离子为[M-H] - （ m/z 175.0238），定性离子为[M-C 3 H 4 O 3 ] - （ m/z 87.0077），质量允许误差为5×10 -6 （5 ppm）。结果表明：维生素C在0.02~5.0 mg/L范围内峰面积与质量浓度呈线性，线性相关系数（ R 2 ）为0.9992；检出限及定量限分别为0.008 mg/L（ S/N =3）和0.02 mg/L（ S/N =10）；在不同添加水平下，维生素C的平均回收率为89.3%~113%，相对标准偏差小于5.40%。在优化的条件下，对32批次的国产和新西兰猕猴桃样品进行检测，国产猕猴桃中维生素C的含量范围为498~1625 mg/kg，新西兰进口猕猴桃中维生素C的含量范围为247~449 mg/kg。该方法操作简便，重复性良好，可用于果蔬中维生素C含量的准确测定。

Zhenzhen LIU

Peipei QI

Xinquan WANG

Wenxue CHEN

Liyu WU

Qiang WANG

Determination of vitamin C in fruits and vegetables by ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry

<p id=C2>In “shotgun” proteomics strategy, the proteome is explained by analyzing tryptic digested peptides using liquid chromatography-mass spectrometry. In this strategy, the retention time of peptides in liquid chromatography separation can be predicted based on the peptide sequence. This is a useful feature for peptide identification. Therefore, the prediction of the retention time has attracted much research attention. Traditional methods calculate the physical and chemical properties of the peptides based on their amino acid sequence to obtain the retention time under certain chromatography conditions; however, these methods cannot be directly adopted for other chromatography conditions, nor can they be used across laboratories or instrument platforms. To solve this problem, in recent years, deep learning was introduced to proteomics research for retention time prediction. Deep learning is an advanced machine-learning method that has extraordinary capability to learn complex relationships from large-scale data. By stacking multiple hidden neural networks, deep learning can ingest raw data without manually designed features. Transfer learning is an important method in deep learning. It improves the learning process a new task through the transfer of knowledge from an already-learned related task. Transfer learning allows models trained using large datasets to be utilized across conditions by fine-tuning on smaller datasets, instead of retraining the whole model. Many retention time prediction methods have been developed. In the process of training the model, the sequences of peptides are encoded to represent peptide information. Deep learning considers the relationship between the characteristics of the peptides and their corresponding retention times without the need for manual input of the physical and chemical properties of the peptides. Compared with traditional methods, deep learning methods have higher accuracy and can be easily used under different chromatography conditions by transfer learning. If there are not enough datasets to train a new model, a trained model from other datasets can be used as a replacement after calibration with small datasets obtained from these chromatography conditions. While the retention times of modified peptides can also be predicted, the predictions are inadequate for complex modifications such as glycosylation, and this is one of the main problems to be solved. The predicted retention times were used to control the quality of peptide identification. With high accuracy, the predicted retention times can be considered as actual retention times. Therefore, the difference between predicted and observed retention times can serve as an effective and unbiased quantitative metric for evaluating the quality of peptide-spectrum matches (PSMs) reported using different peptide identification methods. Combined with fragment ion intensity prediction, retention time prediction is used to generate spectral libraries for data-independent acquisition (DIA)-based mass spectrometry analysis. Generally, DIA methods identify peptides using specific spectrum libraries obtained from data-dependent acquisition (DDA) experiments. As a result, only peptides detected in the DDA experiments can be present in the libraries and detected in DIA. Furthermore, it takes a lot of time and effort to build libraries from DDA experiments, and typically, they cannot be adopted across different laboratories or instrument platforms. In contrast, the pseudo spectral libraries generated by retention times and fragment ion intensity prediction can overcome these shortcomings. The pseudo spectral libraries generate theoretical spectra of all possible peptides without the need for DDA experiments. This paper reviews the research progress of deep learning methods in the prediction of retention time and in related applications in order to provide references for retention time prediction and protein identification. At the same time, the development direction and application trend of retention time prediction methods based on deep learning are discussed.

Zhuokun DU

Wei SHAO

Weijie QIN

Research progress and application of retention time prediction method based on deep learning

基于深度学习的保留时间预测方法研究进展与应用

Metal organic frameworks (MOFs) are crystalline compounds composed of metal ions (or metal clusters) and organic ligands. Chiral MOFs have been successfully utilized as novel materials for the separation of chiral enantiomers by chromatography, demonstrating excellent chiral separation performance. In this study, a chiral MOF-modified silica monolithic capillary column was used for pressurized capillary electrochromatography. First, a chiral MOF (Co-glycyl-L-glutamic acid, Co-L-GG) was synthesized. This MOF was then used to prepare a chiral capillary monolithic column via a one-step in situ polymerization method. The optimal conditions for preparing the chiral capillary monolithic column were determined as follows: Co-L-GG amount, 5 mg; polyethylene glycol amount, 0.96 mg; tetramethoxysilane dosage, 3.6 mL; trimethoxymethylsilane dosage, 0.4 mL. Next, the effects of the separation conditions on the separation of chiral drugs were investigated. Under the conditions of an applied voltage of -20 kV and a mobile phase consisting of acetonitrile and 20 mmol/L disodium hydrogen phosphate (80∶20, v/v), six chiral drugs were separated within 3 min, with baseline separation achieved for amlodipine, fluvastatin, and tryptophan. Moreover, the prepared chiral capillary monolithic column exhibited good reproducibility and stability. Finally, molecular docking studies were conducted using AutoDock to explore the chiral recognition mechanism, and the results were analyzed using Discovery Studio. The results indicated that larger differences in binding free energy between Co-L-GG and the enantiomers of the chiral drugs were correlated with higher enantioselectivity factors. However, this correlation did not necessarily lead to an increase in resolution. Co-L-GG, which is enriched with primary amines, secondary amines, and carbonyl groups, demonstrated enantiomeric recognition capability. In conclusion, this study demonstrates that chiral MOFs can be effectively used as chiral functional monomers to prepare chiral monolithic capillary columns, highlighting their significant potential for the separation and analysis of chiral compounds. The comprehensive exploration of the synthesis, characterization, and applications of these MOFs will help provide valuable insights into the development of advanced separation technologies.

Rui-Ke Song

Gan Liao

Jia-Li Lin

Jia-Lian Wu

Lu Huang

Preparation of chiral metal organic framework modified silica monolithic capillary column and its application in enantioseparations of chiral drugs

手性金属有机框架改性硅胶整体毛细管柱的制备及其在手性药物拆分中的应用

Antimicrobials inhibit the growth and reproduction of microorganisms thereby alleviating skin and other problems caused by microorganisms. Antimicrobials are classified into different categories, including antibacterials, antifungals, and antivirals, among others, and include azoles, sulfonamides, tetracyclines, quinolones, and many other classes of synthetic and natural compound. The inappropriate or excessive use of antimicrobials can damage skin and other human organs and increase antimicrobial resistance. Relevant regulations and standards clearly state that antimicrobials are prohibited for use as ingredients in disinfection products. However, since antimicrobials enhance the disinfection or antibacterial effect of a product, with a significant short-term effect, antimicrobials are occasionally illegally added to disinfectant products, including those intended for human use. Therefore, establishing testing methods that provide technical support for enforcing regulations is an urgent objective. Herein, a method was established for the analysis of 42 antimicrobials in disinfection products, that is applicable to common types of disinfection-product matrix, including creams, gels, and aqueous solutions, using high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) combined with dispersive solid phase extraction. The 42 antimicrobials comprise antibacterials, antifungals, and antivirals, and include seven sulfonamides, ten quinolones, three lincosamides, five tetracyclines, three macrolides, eight azoles, three purine nucleoside analogs, one furan, one nonpolyene antifungal, and one steroid. Briefly, 0.2 g of a sample was first dispersed in 2 mL of water and then extracted with 10 mL of 0.5% formic acid in acetonitrile, with 3 g of anhydrous Na

Jia-Qi Tong

Gu-Huan Zhu

Hang-Zhen Lan

Hong-Lan Shi

Xiao-Yan Zhu

Yao Sun

Determination of 42 antimicrobials in disinfection products by dispersive solid phase extraction-high performance liquid chromatography-tandem mass spectrometry

消毒产品中42种抗微生物剂的分散固相萃取-高效液相色谱-串联质谱测定

Tetracycline (TC) is one of the most important therapeutic drugs that is widely used in hospitals. However, its harmful effects on human health and various ecosystems cannot be ignored. Owing to its poor metabolic activity and low biodegradability, TC commonly discharges as the parent compound and accumulates readily in sludges and soils by precipitation from wastewater, which can induce the evolution of antibiotic-resistant bacteria; therefore, it has been listed as one of the new pollutants with potential ecotoxicological risk. The control measures and environmental management of TC pollutants in environmental water samples require precise determination of TC pollutant concentrations. Carbon dots (CDs) are an emerging type of fluorescent material with numerous advantages such as easy preparation, low cost, low toxicity, and good biocompatibility. Consequently, they have attracted widespread attention in the field of TC detection. Herein, we synthesized TE-CDs with good blue-fluorescence performance via flow-assisted melt polymerization using tricarboxylic acid and ethylenediamine as raw precursors. The morphology and structure of the prepared TE-CDs were characterized. The transmission electron microscopy (TEM) results showed that the prepared TE-CDs were well dispersed, with an average diameter of (2.43±0.48) nm. The X-ray diffraction (XRD) results showed that the TE-CDs had an amorphous carbon structure. Infrared spectroscopy and X-ray photoelectron spectroscopy (XPS) characterizations showed that the surface of the TE-CDs was rich in hydrophilic groups, such as amino, hydroxyl, and carboxyl groups, which indicated that TE-CDs had good water solubility and were advantageous for detecting TC in medical wastewater. Subsequently, the optical properties of the TE-CDs were investigated. The fluorescence emission spectra of the TE-CDs were recorded at various excitation wavelengths. The emission spectra of the TE-CDs exhibited excitation wavelength dependence and when the excitation wavelength changes from 300 nm to 400 nm, their fluorescence intensity decreased to varying degrees. The TE-CDs exhibited optimal fluorescence intensity at an excitation wavelength of 368 nm, while the emission wavelength was 448 nm. TC could effectively quench the blue fluorescence of the CDs, and by utilizing this property, the detection of TC concentration could be achieved. After the addition of TC, the fluorescence of the system immediately reached an extreme value, and no significant change was observed within 10 min. An incubation time of 20 s was selected to obtain precise results. Additionally, the TE-CDs exhibited stable fluorescence intensity over a wide pH range. The fluorescence stability of the TE-CDs was investigated, and no significant change in fluorescence intensity was observed after standing for 10 d, indicating that the prepared TE-CDs had excellent fluorescence stability. The fluorescence intensity of the TE-CDs decreased to varying degrees within the range of 2-200 mg/L TC until complete quenching occurred. TC mass concentration in the range of 4-20 mg/L showed a good linear relationship (

Zi-Wei Liu

Lan-Xiu Ni

Jie Chi

Ying-Xi Qin

Zhen-Jia Shi

Yu Wang

Huang-Zhao Wei

Liang Feng

Cheng-Lin Sun

Preparation of fluorescent carbon dots by flow-assisted melt polymerization for tetracycline detection in medical wastewater

利用流动辅助熔融聚合法制备荧光碳点用于医疗废水中四环素检测

The ability to accurately analyze perfluoroalkyl substance (PFAS) levels in beef is imperative in order to effectively assess food-safety risks and ensure consumer safety because PFASs are harmful and prevalent in beef. In this study, we developed a rapid and accurate method for the simultaneously determination of the 17 PFASs in beef using dispersive solid-phase extraction (d-SPE) and ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), and optimized the mobile phase system, extraction solvent, and d-SPE materials. Samples were finally extracted using 0.1% (v/v) formic acid in acetonitrile, cleaned using d-SPE with PSA, C

Qiao-Li Qiu

Sheng-Dong Pan

Li Wang

Lan-Yun Fang

Xiao-Hong Chen

Mi-Cong Jin

Simultaneous determination of 17 perfluoroalkyl substances in beef by EMR-Lipid dispersive solid-phase extraction and ultra performance liquid chromatography-tandem mass spectrometry

同时测定牛肉中17种全氟烷基物质的超高效液相色谱-串联质谱法结合EMR-脂质分散固相萃取技术

Against the backdrop of the Ministry of Education's promotion of new agricultural science construction and interdisciplinary integration, a comprehensive chemistry experiment to enhance the practical skills of students in preparing biomass functional materials and detecting pesticide residues was designed. Natural loofah was utilized as a precursor in synthesizing nitrogen-doped magnetic porous carbon materials, which were then applied in a magnetic solid-phase extraction (MSPE) technique. Subsequently, high performance liquid chromatography (HPLC) was employed to analyze and detect the phenylurea herbicide monuron in tea. The experimental process included material synthesis, characterization, optimization of the MSPE conditions, adsorption performance studies, and HPLC, reflecting its scientific, systematic nature and providing a comprehensive learning platform for students. It not only deepens student understanding of the relationship between material characterization and application, but also improves their experimental design and problem-solving capacities. Moreover, by integrating cutting-edge science, ideological and political education, and experimental training, it not only stimulates student interest in scientific research and cultivates innovative thinking and practical skills, but also strengthens their feelings of social responsibility and historical mission. This approach realizes the comprehensive educational goals of experimental training and lays the foundation for nurturing high-quality talent with a global perspective and sense of social responsibility.

Zhuang Liu

Ying Su

Dong-Wei Yang

Li-Mei Li

Xu Xu

Comprehensive undergraduate experiment: determination of phenylurea herbicide in tea by magnetic solid-phase extraction-high performance liquid chromatography

综合本科实验：磁性固相萃取-高效液相色谱法测定茶叶中的苯脲类除草剂

Abbreviation	CJCSP
Journal Impact	1.39
Quartiles(Global)	CHEMISTRY, ANALYTICAL(Q4)

ISSN	1000-8713, 1872-2059
h-index	23

Publication Information	Publisher: Zhongguo Kexueyuan - Chinese Academy of Sciences，Publishing cycle: ，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1997，Proportion of original research papers: 96.80%，Self Citation Rate:41.70%， Gold OA Rate: 46.35%

Chinese Journal of Chromatography (Se Pu)

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