[High-throughput screening of 54 alternative plasticizers in sesame oil using gas chromatography-quadrupole time-of-flight mass spectrometry].

Restrictions on the use of phthalates have led to the wide use of alternative plasticizers (APs) such as organophosphate, adipate, citrate, and sebacate. However, because plasticizers combine with polymers in plastic products via unstable noncovalent bonds, they can easily migrate out of these products, causing environmental pollution. In particular, their migration out of food packaging, containers, and other food-contact materials and into food has raised great concerns. Toxicological studies have shown that APs contain potentially toxic substances that can affect endocrine functions and cause neurotoxicity, genotoxicity, and other adverse effects. Thus, their potential risks to food should not be underestimated. Sesame oil is a necessity in daily cooking. The results of risk monitoring in recent years have indicated that sesame oil often contains phthalates in excess of the standard limits. However, the potential risks of APs in sesame oil have not yet been reported. Some common detection methods for APs include gas chromatography-mass spectrometry, gas chromatography-triple quadrupole mass spectrometry, and liquid chromatography-triple quadrupole mass spectrometry. Unfortunately, these methods use low-resolution mass spectrometry and are limited by the resolution, scan rate, and analysis mode. Gas chromatography-quadrupole time-of-flight mass spectrometry (GC-Q-TOF/MS) has the advantages of high resolution, sensitivity, and analysis speed. In full-scan mode, GC-Q-TOF/MS can accurately collect the full-spectrum mass number of target compounds with low content levels in complex substrates, thereby realizing efficient screening and quantitative analysis. It shows outstanding advantages in the trace analysis of pesticide residues and pollutants. Furthermore, it features strong qualitative and high screening abilities. Establishment of a personal compound database and library (PCDL) addresses limitations in the number of compounds that can be measured and enables the rapid identification of targets without the use of standard products. In addition, increasing the number of targets for synchronous screening enables the retrospective analysis of new targets. In this study, a method based on GC-Q-TOF/MS was developed for the determination of 54 APs in sesame oil. The samples were extracted with acetonitrile and purified using a PSA/silica solid-phase extraction column. The mass-spectral information of the samples was then collected by GC-Q-TOF/MS in full-scan mode, and the 54 APs were searched using an established high-resolution mass-spectrum database to simultaneously achieve the broad-spectrum screening, qualitative identification, and quantitative analysis of multiple targets. The effects of different extraction solvents and purification methods on sample extraction and purification were compared. The accuracy of the screening results was improved by optimizing the GC-separation conditions, quality-extraction window, retention-time deviation, and other screening parameters. The screening detection limits (SDLs) of the 54 APs ranged from 0.01 to 0.02 mg/kg; specifically, the SDL of 41 compounds was 0.01 mg/kg and that of 13 compounds were 0.02 mg/kg. The limits of quantification were in the range of 0.02-0.04 mg/kg. A total of 80 sesame-oil samples were rapidly screened using this method under optimal conditions. Five APs were identified from the 80 sesame-oil samples and quantitatively analyzed using the matrix-matched external-standard method. The results of this quantitative methodology showed that the five APs had good linear relationships in the range of 0.01-0.2 mg/L, with all correlation coefficients greater than 0.99. The accuracy and precision of the method were verified using a standard recovery test with blank sesame-oil samples. Under the three standard levels of 0.04, 0.08, and 0.2 mg/kg, the recoveries of the five APs ranged from 71.3% to 97.8%, and the relative standard deviations (RSDs) ranged from 0.4% to 6.1%(n=6). The developed method is fast, accurate, sensitive, and has high throughput. Thus, it can realize the efficient screening, qualitative identification, and quantitative analysis of the 54 APs in sesame oil and provides a potential solution for the monitoring of other contaminants in food.

[High-throughput screening of multi-pesticide residues in animal-derived foods by QuEChERS-online gel permeation chromatography-gas chromatography-tandem mass spectrometry].

Improvements in living standards have led to an increase in the consumption of animal-derived foods. Pesticides may be used illegally during animal breeding as well as meat production and processing for pest control and preservation. Pesticides applied to crops may also be enriched in animal tissues through the food chain, thereby increasing the risk of pesticide residue accumulation in muscles and visceral tissues and endangering human health. China has stipulated maximum residue limits for pesticide residues in livestock and poultry meat and their viscera. Many other major developed countries and organizations, including the European Union, Codex Alimentarius Commission, and Japan, have also set maximum residue limits for these residues (0.005-10, 0.004-10, and 0.001-10 mg/kg, respectively). Research on pretreatment technologies for pesticide residue detection in plant-derived foods is widely available, but insufficient attention has been paid to animal-derived foods. Thus, high-throughput detection technologies for pesticide residues in animal-derived foods are limited. The impurities that can interfere with the detection process for plant-derived foods mainly include organic acids, polar pigments, and other small molecular compounds; by contrast, the matrix of animal-derived foods is much more complex. Macromolecular proteins, fats, small molecular amino acids, organic acids, and phospholipids can interfere with the detection of pesticide residues in animal-derived foods. Thus, selecting the appropriate pretreatment and purification technology is of great importance. In this study, the QuEChERS technique was combined with online gel permeation chromatography-gas chromatography-tandem mass spectrometry (GPC-GC-MS/MS) to determine 196 pesticide residues in animal-derived foods. The samples were extracted with acetonitrile, purified using the QuEChERS technique coupled with online GPC, detected by GC-MS/MS, determined in multiple reaction monitoring mode (MRM), and quantified using the external standard method. The effects of the extraction solvent and purification agent type on the extraction efficiency and matrix removal of the method were optimized. The purification effect of online GPC on the sample solution was investigated. The optimal distillate receiving time was obtained by studying the recoveries of the target substances and matrix effects over different distillate receiving periods to achieve the effective introduction of target substances and efficient matrix removal. Further, the advantages of the QuEChERS technique combined with online GPC were evaluated. The matrix effects of 196 pesticides were assessed; ten pesticide residues showed moderate matrix effects, while four pesticide residues showed strong matrix effects. A matrix-matched standard solution was used for quantification. The 196 pesticides showed good linearity in the range of 0.005-0.2 mg/L, with correlation coefficients greater than 0.996. The limits of detection and quantification were 0.002 and 0.005 mg/kg, respectively. The recoveries of 196 pesticides at spiked levels of 0.01, 0.05, and 0.20 mg/kg were 65.3%-126.2%, with relative standard deviations (RSDs) of 0.7%-5.7%. The proposed method is rapid, accurate, and sensitive; thus, it is suitable for the high-throughput screening and detection of multiple pesticide residues in animal-derived foods.

Robots at the Beijing 2022 Winter Olympics.

The 2022 Winter Olympics has shown that robots can serve, protect, and help people excel in many aspects of their lives.

Learning Mobile Manipulation through Deep Reinforcement Learning.

Mobile manipulation has a broad range of applications in robotics. However, it is usually more challenging than fixed-base manipulation due to the complex coordination of a mobile base and a manipulator. Although recent works have demonstrated that deep reinforcement learning is a powerful technique for fixed-base manipulation tasks, most of them are not applicable to mobile manipulation. This paper investigates how to leverage deep reinforcement learning to tackle whole-body mobile manipulation tasks in unstructured environments using only on-board sensors. A novel mobile manipulation system which integrates the state-of-the-art deep reinforcement learning algorithms with visual perception is proposed. It has an efficient framework decoupling visual perception from the deep reinforcement learning control, which enables its generalization from simulation training to real-world testing. Extensive simulation and experiment results show that the proposed mobile manipulation system is able to grasp different types of objects autonomously in various simulation and real-world scenarios, verifying the effectiveness of the proposed mobile manipulation system.

[Determination of propionic acid and its salts in food by gas chromatography].

A method for the determination of propionic acid and its salts in food by gas chromatography (GC) was developed. Degrease extraction and direct extraction were established for food containing oil and non-oil, respectively. In this study, the effects of different pH values on the solubility and recovery of propionic acid were investigated. The effects of purification conditions, pH values, extraction agent types, and extraction times were studied. After hydrochloric acid solution was added, the pH levels of sample solutions were all found to be less than 2. The sample solutions were degreased with 5 mL n-hexane and extracted twice with 5 mL ethyl acetate. The analytes were detected by GC. The analytes were separated on an HP-INNOWAX chromatographic column and detected by fame ionization detector (FID). The recoveries of degrease extraction were 87.5%-97.6% and relative standard deviation were 3.09%-6.86% (n=6). The recoveries of direct extraction were 90.1%-102.1% and the relative standard deviations were 3.32%-6.33% (n=6). The two methods showed good linearities in the range of 2-1000 mg/L (correlation coefficient is 0.9998). The limit of detection was 0.003 g/kg and the limit of quantification was 0.01 g/kg. The proposed method is accurate, fast, simple, easy, sensitive, and is suitable for the rapid determination of propionic acid and its salts in different food. The proposed method provides a new way for the determination of propionic acid in food.

[Differences of three pretreatment methods for the detection of docosahexaenoic acid, eicosatetraenoic acid, linoleic acid and α-linolenic acid in infant formula milk powder].

The differences of three pretreatment methods (acetyl chloro carbinol esterification, acid hydrolysis esterification and alkali hydrolysis esterification) for the detection of four polyunsaturated fatty acids (docosahexaenoic acid, arachidonic acid, linoleic acid and α -linolenic acid) in infant formula milk powder were discussed. Acetyl chloro carbinol esterification and acid hydrolysis esterification were found to be significantly better than alkali hydrolysis esterification. The sample digestion and fat methyl esterification were carried out simultaneously in the acetyl chloro carbinol esterification method, where the two processes seemed to enhance each other. This allowed the complete release and methyl esterification of the fats. The accuracy of the methods was determined by investigating the reaction processes and recovery rates. Acid and alkali hydrolysis esterification methods were employed to hydrolyze the samples using a hydrochloric acid solution and an ammonia solution, respectively. Then, the fats were extracted for subsequent methyl esterification. These two methods were compared in terms of the digestion efficiency, extraction efficiency, and methylation efficiency. The results showed that the digestion efficiency is the main factor determining the differences between the acid and alkali hydrolysis methods. The accuracies of acetyl chloro carbinol esterification and acid hydrolysis esterification methods were further verified in the detection of samples, providing a basis for the determination of fatty acids in other foods.