Mycotoxins are a class of exogenous metabolites that are major contributors to foodborne diseases and pose a potential threat to human health. However, little attention has been paid to trace mycotoxin co-exposure situations in vivo. To address this, we devised a novel analytical strategy, both highly sensitive and comprehensive, for quantifying 67 mycotoxins in human plasma samples. This method employs isotope dilution mass spectrometry (IDMS) for approximately 40% of the analytes and utilizes internal standard quantification for the rest. The mycotoxins were classified into three categories according to their physicochemical properties, facilitating the optimization of extraction and detection parameters to improve analytical performance. The lowest limits of detection and quantitation were 0.001–0.5 μg/L and 0.002–1 μg/L, respectively, the intra-day precision ranged from 1.8% to 11.9% RSD, and the intra-day trueness ranged from 82.7–116.6% for all mycotoxins except Ecl, DH-LYS, PCA, and EnA (66.4–129.8%), showing good analytical performance of the method for biomonitoring. A total of 40 mycotoxins (including 24 emerging mycotoxins) were detected in 184 plasma samples (89 from infertile males and 95 from healthy males) using the proposed method, emphasizing the widespread exposure of humans to both traditional and emerging mycotoxins. The most frequently detected mycotoxins were ochratoxin A, ochratoxin B, enniatin B, and citrinin. The incidence of exposure to multiple mycotoxins was significantly higher in infertile males than in healthy subjects, particularly levels of ochratoxin A, ochratoxin B, and citrinin, which were significantly increased. It is necessary to carry out more extensive biological monitoring to provide data support for further study of the relationship between mycotoxins and male infertility.

建立了在线固相萃取/净化-高效液相色谱-串联质谱(online SPE-HPLC-MS/MS)同时测定番茄、大米和圆白菜中8种氨基甲酸酯类农药的分析方法。将番茄5.0 g(不加水)、圆白菜和大米各2.0 g(各加3 mL水),以1000 r/min旋涡1 min,加入2 g氯化钠和10 mL 0.5%(v/v)甲酸乙腈溶液,旋涡均匀后离心,上清液氮吹后用10%(v/v)乙腈水溶液复溶,复溶液使用CAPCELL PAK C₁₈净化柱(50 mm×2.0 mm, 15 μm)进行在线净化,当流动相0.1%(v/v)甲酸水溶液和乙腈的体积比分别为90:10和35:65时,可实现氨基甲酸酯农药的吸附和洗脱。以ACQUITY UPLC CSH C₁₈色谱柱(100 mm×2.1 mm, 1.7 μm)为分析柱,实现8种氨基甲酸酯类农药的分离,以0.1%(v/v)甲酸水溶液和乙腈为流动相进行梯度洗脱,在12.0 min内即可完成分析。在优化条件下,8种氨基甲酸酯类农药在各自线性范围内线性良好,相关系数均大于0.995, LOD和LOQ分别为0.01~0.3 ng/mL和0.05~1.0 ng/mL;在3个加标水平下,8种氨基甲酸酯类农药的加标回收率为73.76%~112.32%,相对标准偏差为1.28%~13.14%(n=6)。通过在线净化的方式,大大提高了前处理效率,只需12 min即可完成净化上样,不需氮吹复溶等步骤,提高了处理效率。该法回收率高,重复性好,具有准确、快速、灵敏、环保等优点,可用于植物性食品中8种氨基甲酸酯类农药的检测。

Mixtures analysis can provide more information than individual components. It is important to detect the different compounds in the real complex samples. However, mixtures are often disturbed by impurities and noise to influence the accuracy. Purification and denoising will cost a lot of algorithm time. In this paper, we propose a model based on convolutional neural network (CNN) which can analyze the chemical peak information in the tandem mass spectrometry (MS/MS) data. Compared with traditional analyzing methods, CNN can reduce steps in data preprocessing. This model can extract features of different compounds and classify multi-label mass spectral data. When dealing with MS data of mixtures based on the Human Metabolome Database (HMDB), the accuracy can reach at 98%. In 600 MS test data, 451 MS data were fully detected (true positive), 142 MS data were partially found (false positive), and 7 MS data were falsely predicted (true negative). In comparison, the number of true positive test data for support vector machine (SVM) with principal component analysis (PCA), deep neural network (DNN), long short-term memory (LSTM), and XGBoost respectively are 282, 293, 270, and 402; the number of false positive test data for four models are 318, 284, 198, and 168; the number of true negative test data for four models are 0, 23, 7, 132, and 30. Compared with the model proposed in other literature, the accuracy and model performance of CNN improved considerably by separating the different compounds independent MS/MS data through three-channel architecture input. By inputting MS data from different instruments, adding more offset MS data will make CNN models have stronger universality in the future.

Naturally occurring substances and their derivatives function as vital resources for pesticides that can be used in fields, such as insecticide production and fungicide development. As a botanical entity displaying multifaceted biological functions, wormwood has received thorough scrutiny across multiple sectors. The insect repellency potency combined with antibacterial and antifungal activities of wormwood position it as a potential candidate for prospective development into eco-friendly chemical pesticides. In this research, Wormwood essential oil was procured via ethanol water under ultrasonic scenarios and subsequently diluted with PEG 400 to formulate green chemical pesticides. The defensive efficacy of this green pesticide on plants was validated through 2 weeks of clustered plant growth experiments. Active constituents that exerted their effects were scrutinized by GC-MS. Furthermore, this green pesticide also displays efficacious effects on the prevention and management of aphids, exhibiting a dose-dependent relationship. 4-terpenol, eucalyptol, carvacrol, and L-borneol were identified by GC-MS as the predominant active constituents in this green chemical pesticide. Wormwood can be leveraged to develop green chemical pesticides, which can protect plants without contaminating the environment.

The aim of individuals consuming health supplements is to attain a robust state through nutritional regulation. However, some unscrupulous manufacturers, motivated by profit, fraudulently incorporate drugs or unauthorized components with therapeutic effects into the product for instant product performance enhancement. The long-term use of these products may inadvertently inflict harm on human health and fail to promote nutritive healthcare. The illegal inclusion of these substances is prevalent in kidney-tonifying and sexuality-enhancing products. Developing effective analytical methods to identify these products and screen for illegal added ingredients can effectively prevent such products from reaching and remaining on the market. A target screening method for the detection and quantification of 90 phosphodiesterase type 5 inhibitors (PDE-5is) in 5 kinds of health products was developed and validated. The type of dietary supplements varied from tablets, capsules, and protein powder to wine and beverages. Sample preparation was completed with a one-step liquid phase extraction. The screening process of 90 PDE-5is was done efficiently within 25 min by ultra-high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) using the dynamic multiple reaction monitoring (dMRM) technique. The LODs of 90 PDE-5is were detected at levels ranging from 25 to 85 ng/g or ng/mL. This novel targeting methodology was effective and can be applied to routine market supervision. Among 286 batches of samples, 8 batches were found to be positive. Three kinds of PDE-5is were first detected in healthy products. The screening method demonstrated herein will be a promising and powerful tool for rapid screening of PDE-5is.