Objective To establish a liquid chromatography method for the simultaneous determination of 13 aromatic amine compounds (AAs) in workplace air. Methods A total of 13 AAs in both vapor and aerosol phases were collected in workplace air using a new GDH-6 sampling tube. Samples were desorbed and eluted with methanol, separated using a Symmetry Shield™ RP₁₈ reversed-phase liquid chromatography column, and detected with a diode array detector. Quantification was performed using an external standard method. Results The linear range of the 13 AAs measured by this method was 0.02-373.60 μg/L with the correlation coefficients greater than 0.999 0. The minimum detection concentration was 0.09-14.37 μg/m³, and the minimum quantitative concentration was 0.31-47.90 μg/m³ (both calculated based on sampling 15.0 L of air and 3.0 mL of elution volume). The average desorption and elution efficiency ranged from 97.46% to 101.23%. The within-run relative standard deviation (RSD) was 0.10%-5.99%, and the between-run RSD was 0.17%-2.71%. Samples could be stably stored in sealed conditions at 2-8 ℃ for more than seven days. Conclusion This method is suitable for the simultaneous determination of 13 AAs in workplace air, including both vapor and aerosol phases.

Objective To establish a method for simultaneous determination of four high-molecular-weight thiol derivatives (TDs) in workplace air by gas chromatography. Methods The four kinds of vapor-phase macromolecular TDs (1-pentanethiol, 1-hexanethiol, 1-benzyl mercaptan, and n-octanethiol) in the workplace air were collected using the GDH-1 air sampling tubes, desorbed with anhydrous ethanol, separated on a DB-FFAP capillary column, and determined by flame ionization detector. Results The quantitation range of the four TDs was 0.30-207.37 mg/L, with the correlation coefficients greater than 0.999 00. The minimum detection mass concentrations and minimum quantitation mass concentrations were 0.18-0.32 and 0.60-1.05 mg/m³, respectively (both calculated based on the 1.5 L sample and 3.0 mL desorption solvent). The mean desorption efficiencies ranged from 87.07% to 103.59%. The within-run and between-run relative standard deviations were 1.92%-8.22% and 1.89%-8.45%, respectively. The samples can be stored at room temperature or 4 ℃ for three days and up to 7 days at -18 ℃. Conclusion This method is suitable for the simultaneous determination of four vapor-phase TDs in workplace air.

Acute Gelsemium poisoning is a systemic disease primarily affecting the central nervous system and respiratory symptoms caused by the ingestion of a substantial amount of Gelsemium within a short period. It manifests as sudden onset and rapid progression, primarily caused by accidental ingestion due to misidentification, and posing significant health risks. The compilation of the Technical Plan for Emergency Health Response to Acute Gelsemium Poisoning describes in detail the specialized practice and technical requirements in the process of handling acute Gelsemium poisoning, including accident investigation and management, laboratory testing and identification, in-hospital treatment, and health monitoring. The guidelines clarify key procedures and requirements such as personal protection, investigation elements, etiology determination, medical rescue, and health education. The key to acute Gelsemium poisoning investigation lies in promptly identifying the toxin through exposure history, clinical manifestations, and sample testing. Because there is no specific antidote for Gelsemium poisoning, immediate removal from exposure, rapid elimination of the toxin, and respiratory monitoring are critical on-site rescue measures. Visual identification of food or herbal materials, followed by laboratory testing to determine Gelsemium alkaloids in samples is a rapid effective screening method. These guidelines offer a scientific, objective, and practical framework to support effective emergency responses to acute Gelsemium poisoning incidences.

Objective To analyze differential metabolites (DMs) in the urine of workers with occupational nickel exposure using non-targeted metabolomics, and to screen differential metabolic pathways. Methods A total of 30 nickel exposed workers were selected as the exposure group, and 30 administrative staff from the same factory were selected as the control group using the judgment sampling method. Urine samples of the individuals from the two groups were collected. The ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry and non-targeted metabolomics were used to detect and identify metabolites. The differential metabolic profiles were compared between workers of the two groups, and key differential metabolic pathways and potential biomarkers were screened. The association of DMs and urinary nickel level were evaluated by Spearman correlation coefficients. The sensitivity and specificity of biomarkers were assessed by receiver operating characteristic (ROC) curve analysis. Results A total of 418 metabolites were identified in the urine of worker in the exposure and control groups. The result of principal component analysis and orthogonal partial least squares analysis showed that there were 128 DMs in the urine of workers in the exposure group compared with the control group. These DMs were mainly enriched in glutathione metabolism, carnitine synthesis, and amino acid and nucleotide metabolism pathways, including glycine and serine metabolism. The result of correlation analysis and ROC curve analysis revealed that 4-methylcatechol, 4-vinylphenol sulfate, 2-hydroxyphenylacetone sulfate, 2-dodecylbenzenesulfonic acid, and decylbenzenesulfonic acid could be the potential biomarkers for nickel exposure (all area under the ROC curve >0.800). Conclusion There were significant differences in the urinary metabolic profiles of workers with occupational nickel exposure. The five DMs including 4-methylcatechol, 4-vinylphenol sulfate, 2-hydroxyphenylacetone sulfate, 2-dodecylbenzenesulfonic acid, and decylbenzenesulfonic acid. These DMs could be potential biomarkers of occupational nickel exposure.

Biotoxins, which include bacterial, fungal, marine, plant, and animal toxins, are widespread in living and occupational environments, posing potential threats to human health. Rapid detection of biotoxins in blood is crucial for preventing health hazards and enabling timely disease diagnosis and treatment. Biosensors and immunoassay technologies have critical advantages in the rapid detection of biotoxins in blood. Common biosensors, such as surface plasmon resonance biosensors and fluorescent biosensors, enhance sensitivity and reduce detection limits through signal amplification. Common immunoassay methods, such as colloidal gold immunochromatography, fluorescence immunochromatography, and chemiluminescence immunoassay, improve detection efficacy and sensitivity through specific antibody-antigen binding and nanotechnology. However, current rapid detection technologies of bitoxins in blood face challenges such as matrix interference and insufficient specificity, and they fall short in high-throughput detection of multiple toxins simultaneously. Future developments should focus on improving sample pretreatment, innovating signal amplification methods, enhancing specificity on recognition of elements, and designing portable detection devices and high-throughput platforms for simultaneous toxin analysis. These advancements aim to improve the sensitivity and reliability of detection methods, providing more accurate and convenient solutions for biotoxin detection in blood.

Metabolomics, including targeted metabolomics and non-targeted metabolomics, is a method to study endogenous small molecule metabolites in organisms. The process of metabolomics analysis generally includes sample collection and pre-treatment, sample detection, data preprocessing, metabolite identification, data statistical analysis, and others. At present, metabolomics technology has been applied to study toxicological mechanism of occupational hazards, early detection and diagnosis of occupational diseases, screening biomarkers of occupational exposure, and others. The application of metabolomics technology to explore the relationship between workers' metabolites and exposure to occupational hazardous, assess the potential impact of occupational exposure on workers' health, and search for ideal biomarkers or therapeutic targets is conducive to early warning and monitoring of occupational health hazards, and assistance in the early diagnosis and prognosis of occupational diseases.In the future, further research is needed in the field of occupational health using metabolomics to establish more complete and standardized workflows and experimental methods, combine big data technology to explore potential biomarkers, utilize metabolic information to provide precise occupational health services, and use artificial intelligence models for data mining and disease diagnosis in metabolomics.

Objective To analyze the problems and differences in workplace on-site sampling and testing skills in external quality assessment in laboratory among occupational health technical service institutions. Methods A total of 108 occupational health technical service institutions nationwide, participated in the external quality assessment in laboratory of the on-site individual sampling operation skills for silica dust (hereinafter refer to as "silica dust sampling assessment") and on-site detection operation skills for carbon monoxide (hereinafter refer to as " carbon monoxide sampling assessment") in 2023, were selected as the research subjects. The result of the assessment was analyzed. Results The qualification rate of the institutions for the silica dust sampling assessment was 98.1%. The unqualified rate of institutions in the Pearl River Delta region was lower than that in non-Pearl River Delta regions (0.0% vs 11.1%, P<0.017). The excellence rate was higher in public institutions than that in private enterprises (73.5% vs 40.0%, P<0.017). The unqualified rate of institutions with permit was lower than that of institutions without permit (0.0% vs 13.3%, P<0.05). The qualification rate of the institutions for the carbon monoxide sampling assessment was 79.4%. The proportion of the institutes, whose results of carbon monoxide standard gas (gas bag) deviation was >±20.0% was higher in private enterprises than that in public institutions (32.8% vs 7.1%, P<0.017). In terms of the normativity of on-site individual sampling for silica dust, the rates of conducting air tightness checks before sampling, correct disassembly and installation and correct placement direction of dust sampling heads, and correct flow for calibration based on the provided dust sampling heads were low, at 53.7%, 33.3%, and 14.8%, respectively. In terms of the normativity of on-site detection of carbon monoxide, the accuracy rate of converting results by on-site detection individuals was low, at only 57.8%. ConclusionIt is necessary to further strengthen the training of theoretical knowledge and practical skills of individuals in occupational health technical service institutions in Guangdong Province, especially to enhance the capacity of occupational health technical services in non-Pearl River Delta regions of the province.

ObjectiveTo understand the monitoring result of occupational hazard in the workplace of key industries in Guangdong Province from 2020 to 2023. Methods The data of occupational hazards in the workplace of 20 key industries in Guangdong Province from 2020 to 2023 were collected from the “Workplace Occupational Hazard Monitoring System” of the Chinese Disease Prevention and Control System subsystem. The monitoring result of occupational hazard factors, occupational health training, occupational health examination, occupational protection, detection of occupational hazardous agents such as dust, chemical substances and noise were analyzed. Results A total of 13 058 enterprises from key industries were recruited as the monitoring subjects in Guangdong Province. There were 290 large-, 1 342 medium-, 7 635 small-, and 3 791 micro-enterprises, with small and micro-enterprises accounting for 58.5% and 29.0% of the total, respectively. A total of 7 542 enterprises exceeded the national standard in the detection of occupational hazards, with a rate of 57.8%. A total of 1 942 517 workers from 13 058 enterprises were recruited, with 835 567 workers were exposed to occupational hazards, with a rate of 43.0%. The rate of occupational health training for enterprise leaders, occupational health management personnel, and workers was 71.9%, 73.8%, and 86.5%, respectively. The abnormal rate of occupational health examinations for workers exposed to noise, dust, and chemical agents was 2.0%, 0.6%, and 1.0%, respectively. The distribution rate of dust masks, anti-poisoning masks or face masks, and noise prevention earplugs or earmuffs was 83.3%, 71.3%, and 77.8%, respectively. The rate of installation of dust prevention facilities, anti-poisoning facilities, and noise prevention facilities was 85.6%, 81.2%, and 50.1%, respectively. The rate of exceeded the national standard of dust, noise in the worksites/types and workplaces showed a decreasing trend year by year (all P<0.01), while the rate of exceeded the national standard of chemical agents in worksites/types and workplaces showed an increasing trend year by year in various occupational hazards (all P<0.01). Conclusion Occupational hazards in the workplace of key industries in Guangdong Province are relatively common. The proportion of workers exposed to occupational hazards is relatively high. It is necessary to further improve the use of noise prevention facilities and protective equipment, strengthen occupational health training for enterprises throughout the province and regularly monitor occupational hazards to reduce the risk of occupational diseases.

ObjectiveTo establish a method for the determination of 1,1,1,2-tetrachloroethane (TeCA) and 1,1,2,2-TeCA in human urine using liquid-liquid extraction-gas chromatography. Methods The 5.0 mL urine sample was mixed with 2.0 g anhydrous sodium sulfate and 5.0 mL ethyl acetate, then vortexed mixing. The 1.0 mL extraction was separated by 100% dimethylpolysiloxane capillary gas chromatography column, detected by flame ionization detector, and quantified by an external standard method. Results The linear ranges of 1,1,1,2-TeCA and 1,1,2,2-TeCA were 0.250-50.750 mg/L, with both correlation coefficients of >0.999 9. The detection limit of 1,1,1,2-TeCA in urine was 0.020 mg/L, and the lower limit of quantification was 0.060 mg/L. The average recovery was 88.02%-101.32%, and the within-run and between-run relative standard deviations (RSDs) were 0.11%-0.47% and 0.39%-1.09%, respectively. The detection limit of 1,1,2,2-TeCA in urine was 0.050 mg/L, and the lower limit of quantification was 0.150 mg/L. The average recovery was 93.42%-101.32%, and the within-run and between-run RSDs were 0.28%-1.04% and 0.50%-1.03%, respectively. Both the 1,1,1,2-TeCA and 1,1,2,2-TeCA cannot be stored at room temperature. The 1,1,2,2-TeCA can be stored at 4 ℃ for at least three days. At -20 ℃, the 1,1,1,2-TeCA can only be stored for one day, while 1,1,2,2-TeCA can be stored for at least five days. Conclusion This method has high sensitivity, good specificity, simple sample pretreatment, and more intuitive and reliable results. It can be used to determine the level of 1,1,1,2-TeCA and 1,1,2,2-TeCA in urine of occupational population.

Objective To establish an infrared spectrophotometric method for determination of mineral oil mist in workplace air. Methods The mineral oil mist in workplace air was sampled with glass fiber filter membrane and eluted with carbon tetrachloride. Petroleum-like standard solution of carbon tetrachloride was used as the calibration standard, and quantitative analysis was performed using infrared spectrophotometric oil analyzer. Results The sampling efficiency of the glass fiber filter membrane ranged from 94.8% to 99.2%, and the extraction efficiency ranged from 95.6% to 104.2%. The linear range of mineral oil mist was 1.00-120.00 mg/L, with a correlation coefficient of 0.999 4. The detection limit was 0.52 mg/L, and the quantification limit was 1.74 mg/L. The average recovery rate ranged from 98.8% to 104.1%. The within- and between- run relative standard deviations were 2.2%-6.4% and 2.3%-5.2%, respectively. The samples were stable at room temperature for seven days. This method could be used for air sampling of mineral oil mist in workplaces where mineral oil is used. Conclusion The method is sensitive, accurate, and efficient, which is suitable for determining the concentration of mineral oil mist in workplace air.