Since the implementation of the State administration for market supervision and administration's Measures for the Administration of the Qualification of Inspection and Testing Institutions (Order No. 163) amendment and Measures for the Supervision and Administration of Inspection and Testing Institutions (Order No. 39) in 2021, regulatory authorities at all levels have significantly intensified their efforts in conducting random inspections and targeted rectification campaigns. Cases of inspection and testing agencies being stripped of their qualifications, suspended, fined, or publicly reprimanded have frequently appeared in the media, attracting significant attention from the industry. As inspection and testing agencies, it is imperative to enhance their quality compliance management capabilities, thoroughly study and understand various regulatory policies and cases, and strengthen internal quality compliance management to mitigate the risk of administrative penalties, thereby boosting the confidence of all sectors of society in the industry. This article first introduces the necessity and urgency of introducing a quality risk management mechanism in laboratories. It then describes various sources of risk. Finally, it elaborates on the planning, implementation, performance evaluation, and improvement of the quality compliance risk management mechanism in laboratories, aiming to help readers initially grasp and understand the basic approach to implementing quality compliance risk management in laboratories.

University laboratories play a crucial role in technological innovation, talent cultivation, achievement transformation, and enhancing comprehensive national strength, but at the same time, they have also become prone to safety accidents. The lack of safety awareness, safety willingness, safety knowledge and skills among student groups is a common problem among current university students. In addition, the safety characteristics of medical university laboratories involve more chemical and medical aspects. Therefore, analyzing the current status of laboratory safety education in medical universities, based on the concept of "three pronged education" in the context of "new medicine" construction, this paper explores how to build an integrated safety education system and diverse implementation paths for schools, colleges, and laboratories from the perspectives of all staff, the whole process, and all aspects.

ABSTRACT: With the rapid advancement of industrialization and urbanization, a series of new pollutants, such as drug residues, personal care products, and industrial chemicals, have gradually emerged. These pollutants pose a serious threat to the ecological environment and human health due to their low concentration, high toxicity, easy bioaccumulation, and environmental persistence. New pollutants, as a type of environmental pollutant that has recently been identified or begun to receive widespread attention, are characterized by their low content but significant toxicity. Among them, the problems of new pollutants such as microplastics, antibiotics, and environmental endocrine disruptors are particularly prominent. How to efficiently identify and monitor these pollutants has become a core concern for researchers in the field of environmental science. This article will deeply analyze the characteristics, hazards, and monitoring difficulties of new pollutants, and summarize the latest research trends in the field of environmental monitoring, especially the detection technologies for pollutants such as microplastics, antibiotics, and environmental endocrine disruptors. By comparing the advantages and disadvantages of various monitoring methods, guidance is provided for environmental workers in selecting appropriate monitoring methods, in order to achieve rapid and accurate identification and monitoring of new pollutants.

Objective To explore the comprehensive quality evaluation of Panax notoginseng based on high performance liquid chromatography (HPLC) multi-component quantification combined with grey relational analysis. Methods HPLC was used to simultaneously determine the contents of notoginsenoside R1, ginsenoside Rg1, Re, Rb1, and Rd in Panax notoginseng samples from different origins and different commercial specifications. A comprehensive quality evaluation model was established by combining the grey relational method. Results The established method simultaneously determined the contents of notoginsenoside R1, ginsenoside Rg1, Re, Rb1, and Rd, with good methodological investigation results. The grey relational method could distinguish between samples from authentic origins, qualified samples, and unqualified samples. Conclusion The fusion model of HPLC multi-component quantification and grey relational analysis was constructed to accurately evaluate the quality of Panax notoginseng, providing a scientific evaluation basis.

Engineering rubber products are widely used in construction, transportation, industry, and other fields, and their quality is directly related to the safety and longevity of projects. Therefore, establishing scientific testing standards and quality control techniques is crucial. This paper first introduces the basic characteristics of engineering rubber products and their main application areas, followed by a discussion on the standardized testing process, including physical property testing, chemical composition analysis, and performance evaluation. In terms of quality control techniques, the paper details the control methods during production, the selection and testing of raw materials, and the key stages of finished product inspection. Finally, with reference to current technological advances, the paper looks ahead to the future development trends of testing and quality control technologies for engineering rubber products, particularly focusing on intelligent testing and the use of environmentally friendly materials. This study is of great significance for improving the performance of engineering rubber products, extending their service life, and ensuring project safety, while also providing theoretical and technical support for the formulation of testing standards and quality control specifications in relevant industries.

Objective Establish a detection methodology that can quickly, easily, and in large quantities analyze and detect the blood concentration of valproic acid, and can be applied to evaluate the bioequivalence of Sodium Valproate Sustained-Release Tablets in healthy volunteers. Methods Organize subjects to take the test and reference formulations of 0.5 g sodium valproate sustained-release tablets, collect blood samples, and prepare plasma samples. Determine the concentration of valproic acid in plasma using the established ultra performance lc-mass spectrometry/mass spectrometry (UPLC-MS/MS). Results Under fasting and postprandial conditions, both formulations were bioequivalence in terms of absorption rate and degree. Conclusion This experiment established an accurate and rapid UPLC-MS/MS method for detecting the content of valproic acid in human plasma samples. Two formulations have bioequivalence.

Gas chromatography technology is an important analytical method in the detection of pesticide residues in food. It provides reliable technical support for food safety by separating and detecting pesticide components in samples. However, the technology faces challenges during its application, such as complex sample pretreatment, insufficient detection sensitivity and selectivity, and poor accuracy and reproducibility of results. To address these issues, this paper describes the application and optimization strategies of gas chromatography technology in the inspection of pesticide residues in food. These include optimizing sample pretreatment methods to improve detection efficiency, technological improvements to enhance detection sensitivity and selectivity, and quality control measures to ensure the accuracy and reproducibility of test results. Through these optimization strategies, the application effect of gas chromatography technology in the detection of pesticide residues in food can be significantly improved, providing stronger technical support for ensuring food safety.

Laboratory quality management is the key to ensuring the accuracy and reliability of testing data, but the traditional manual management mode is inefficient and difficult to meet the increasing certification requirements. This article proposes an intelligent laboratory quality management system that integrates artificial intelligence technologies such as knowledge graphs, data mining, and machine learning, achieving full process intelligent management and risk warning of laboratory resources, processes, and results. The innovation points of the system include: ontology based quality knowledge graph construction, multi-objective reinforcement learning for resource allocation and process optimization, and quality trend prediction for spatiotemporal sequences. The application in X laboratory has shown that the system can significantly improve the standardization, effectiveness, and efficiency of quality management, providing the possibility for the establishment of an intelligent certification system.

Objective To realize the intelligentization and visualization of laboratory management and effectively improve the efficiency and quality of inspection work by taking the digital scheme of building drug inspection laboratory in Taizhou Pharmaceutical Inspection Institute as an example. Methods Through the mode of “internet+technology service", the whole process of "one-stop" service was realized in scientific experiment, technology research and development, safety evaluation, industry cultivation and other aspects at drug testing institution. Results Since the operation of the digital laboratory of Taizhou Institute of Drug Control for 2 years, more than 6,700 drug testing reports had been completed, 21 sets of high-end instruments and equipments with a value of 25 million yuan had been shared freely through the "drug inspection pass" service platform, providing efficient services for more than 200 enterprises and institutions, completing 2960 batches of entrusted testing business, reducing the laboratory operation cost by 20%, solving 280 technical problems for pharmaceutical enterprises, directly reducing the cost of more than 400000 yuan for pharmaceutical enterprises, shortening the service cycle to 10~15 working days after entrusted by the enterprise through the platform, and improving the efficiency by 30%. Conclusion The foundation of digital laboratory enables the testing institution to achieve comprehensive, efficient and accurate management and coordination, improve the efficiency and quality, improve the scientific and normative nature of testing work, provide high-efficiency and high-quality services for the development of pharmaceutical enterprises, and provide solid technical support for the digital, precise and intelligent governance of drug supervision work.

Objective To verify the accuracy of rapid detection results for sulfur dioxide. Methods Distillation iodine titration method was used to detect 598 batches of food samples in the rapid detection project, and the accuracy of the rapid detection results was analyzed. Results The overall accuracy of the sulfur dioxide rapid detection project was 93%, with a positive accuracy of 94% and a negative accuracy of 96%. The accuracy is less affected by the factors of rapid detection personnel, ranging from 92% to 94%; The fluctuation range of food variety factors is 75% to 100%; The fluctuation range of fast inspection product factors is 83% to 100%. The quick test results have a moderate degree of consistency with the laboratory results, with a Kappa value of 0.465. The higher the sulfur dioxide content in the sample, the more obvious the quick test results are, and the higher the accuracy of the quick test results.Continuously strengthening the management of rapid inspection products, selecting suitable food varieties, and sampling representative samples can further improve the accuracy of results. Conclusion The data from this validation proves that the fast detection method has high accuracy and can meet the requirements of on-site risk screening, effectively preventing food safety risks.