Objective To develop a solvent desorption-gas chromatography method for quantifying malononitrile in workplace air. Methods Malononitrile in workplace air was collected using a silica gel tube and desorbed with methanol. Separation was performed using DB-FFAP capillary column, and detection was performed by hydrogen flame ionization detector. Results The linear ranges of malononitrile were 4.00-600.00 mg/L, with the correlation coefficient of 0.999 92. The detection limit was 0.54 mg/L. The minimum detection concentration was 0.36 mg/m³ (based on a collected air volume of 1.5 L). The average desorption efficiency was 95.0%-101.0%. The within-run and between-run relative standard deviations were 0.9%-5.3% and 1.0%-6.8%, respectively. The sampling efficiency was 100.0%. The samples were stable at 4 ℃ for at least 14 days. Conclusion The solvent desorption-gas chromatography method established in this study for the determination of malononitrile in workplace air is simple to use, with high accuracy and good precision, and is suitable for the determination of malononitrile in workplace air.

Perfluorobutyric acid (PFBA) is a representative short-chain compound of per- and polyfluoroalkyl substances (PFAS), which is widely used in fluorochemical manufacturing, food packaging, and outdoor textile processing industries. PFBA primarily enters into the human body via oral intake, inhalation, and dermal exposure and can be efficiently metabolized. PFBA exhibits cytotoxicity by disrupting cell proliferation, inducing oxidative stress, and disturbing lipid metabolism, thereby impairing cellular homeostasis. In addition, PFBA can induce abnormal activation of peroxisome proliferator-activated receptor α-dependent and/or independent pathways, leading to lipid metabolism disorders and subsequent liver injury. Animal studies have demonstrated that PFBA exposure alters renal biochemical parameters and induces epidermal inflammation, abnormal keratinization, and even necrosis, suggesting potential nephrotoxicity and dermal toxicity. PFBA is capable of crossing the placental barrier, and PFBA levels in umbilical cord blood have been negatively correlated with insulin and insulin-like growth factor 1. Moreover, plasma PFBA levels in patients infected with coronavirus disease 2019 have been associated with infection severity, indicating potential reproductive, developmental, and immunotoxic effects. At present, systematic occupational and environmental exposure monitoring data for PFBA remain limited, the toxic mechanisms in certain target organs have not been fully elucidated, and the molecular regulatory networks underlying reproductive and immune toxicity remain unclear. Future research should focus on improving PFBA monitoring strategies, strengthening studies on PFBA occupational exposure detection methods, toxic effects and mechanisms, and refining occupational risk assessment systems, to provide a scientific basis for establishing occupational exposure limits, optimizing risk management strategies, and safeguarding public health.

Dust and chemical substances are widely present occupational hazards in workplaces. Long-term exposure to dust and chemical substances can pose serious threats to workers′ health. Owing to their advantages in real-time detection, rapid response, and high accuracy, online monitoring technologies enable continuous measurement and analysis of the concentration and composition of dust and chemical substances in workplaces. These technologies provide timely and effective data support for the prevention and control of occupational diseases and have become an important protective tool in the field of occupational hazard. Current online monitoring technologies for workplace dust mainly include the tapered element oscillating microbalance method, light scattering method, β-ray method, triboelectric charging, video exposure monitoring, and ultrasonic methods. Online monitoring devices for workplace chemical substances are still in the early stages of development. However, this equipment has been partially applied in environmental monitoring, covering methods such as spectral analysis, electrochemical sensors, cataluminescence sensors, and intelligent sensing systems. In the future, the development of online dust monitoring technology should focus on overcoming technical bottlenecks to improve detection accuracy and exploring the synergistic effects of different technologies to compensate for the limitations of single methods. Meanwhile, online monitoring technologies for chemical substances should aim to develop integrated detection systems that combine high precision, real-time performance, low cost, and stability.

Objective Focusing on gynecological surgery,we constructed a prediction model for surgical duration by extracting features from unstructured surgical planning texts and integrating multimodal data via artificial intelligence technology.Methods The clinical data of 34 614 patients who underwent gynecologic surgeries at West China Second University Hospital,Sichuan University between January 2022 and October 2024 were collected.An embedding-transformer model was constructed to convert surgical planning texts into a one-dimensional numerical feature,referred to as the step feature.The predictive value of the step feature was assessed by comparing the performance improvements of linear regression,random forest,eXtreme Gradient Boosting(XGBoost),support vector regression,K-nearest neighbor regression,and artificial neural network algorithms in two scenarios—with and without the step feature as an input.The out-of-sample prediction accuracy of the models was assessed using mean absolute error(MAE),root mean squared error(RMSE),and R-squared(R2).Furthermore,the model interpretability was examined using SHapley Additive exPlanations(SHAP)values.Results SHAP results showed that the step feature had the highest predictive contribution.Temporal factors in surgical scheduling also influenced gynecological surgery duration.The XGBoost model demonstrated optimal performance on the test set,significantly improving prediction accuracy with a 40.43%increase in R2,while reducing MAE and RMSE by 21.27%and 20.13%,respectively,compared to the baseline model without the step feature.Conclusion The embedding-transformer model developed in this study effectively extracts features from surgical planning texts and enhances the predictive performance of machine learning models.The XGBoost prediction model can assist hospital administrators in implementing more refined management of gynecological surgeries and improving the utilization efficiency of surgical resources.

Objective To explore the nephrotoxic effects of exposure to perfluorobutanoic acid (PFBA) and its mechanism in mice, with a particular focus on analyzing the changes in kidney metabolism and their potential implications. Methods The specific pathogen free C57BL/6 mice were randomly divided into control group, low-dose group, and high-dose group, with 10 mice in each group. Mice in the three groups received intragastric administration of PFBA solution at doses of 0, 35 and 350 mg/kg body weight, once per day for seven consecutive days. The histopathological changes of kidneys of mice in these three groups were evaluated. Metabolomic profiling of mouse kidneys was performed using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Differentially accumulated metabolites (DAMs) were identified based on the Human Metabolome Database, and related metabolic pathways were analyzed through MetaboAnalyst 6.0 and Kyoto Encyclopedia of Genes and Genomes (KEGG). Results Histopathological analysis of kidneys showed that the renal pelvis mucosa of mice in the low-dose group presented focal mild inflammatory changes without marked structural damage, whereas mice in the high-dose group showed severe inflammation and partial destruction of renal structure. The kidney coefficient of mice in both low-dose group and the high-dose group decreased (both P<0.05), and the Paller scores of renal tissues increased (both P<0.05) compared with that in the control group. The Paller score of mouse renal tissue in the high-dose group was higher than that in the low-dose group (P<0.05). Metabolomic profiling identified 46 DAMs (26 upregulated, 20 downregulated) in the low-dose group and 104 DAMs (54 upregulated, 50 downregulated) in the high-dose group, with 26 shared DAMs between the two dose groups. KEGG pathway analysis revealed that DAMs were mainly involved in metabolic pathways such as glycerophospholipid metabolism, glycerolipid metabolism, sphingolipid and steroid hormone synthesis. Conclusion Acute exposure to PFBA can cause kidney injury in mice. Lipid metabolism pathways such as glycerophospholipid and sphingolipid metabolism is involved in the development of acute renal toxicity of PFBA.

Objective To establish an ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectrometry method for the determination of N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine quinone (6PPDQ) in human plasma and urine. Methods Plasma and urine samples (0.3 mL each) were mixed with 0.9 mL acetonitrile and dichloromethane, vortexed, and subjected to ultrasonic treatment to facilitate extraction. After centrifugation, the extract was collected, evaporated to dry powder under nitrogen, and reconstituted. Separation was performed on a C18 column, and detection was carried out using ultra-high-performance liquid chromatography-triple quadrupole tandem mass spectrometry with external standard quantification. Results 6PPDQ showed good linearity in the range of 0.01-25.00 μg/L in both human plasma and urine, with correlation coefficients of 0.999 5 and 0.999 7, respectively. The detection limits for plasma and urine were 8 and 6 ng/L, and the lower limits of quantification were 27 and 19 ng/L, respectively. The average recovery rates were 97.00%-100.00% for plasma and 90.00%-96.50% for urine. The within-run relative standard deviations (RSDs) were 4.35%-10.00% for plasma and 2.34%-11.11% for urine, while the between-run RSDs were 6.80%-8.46% and 2.60%-10.00%, respectively. Samples can be stored for seven days at 4 ℃ or -20 ℃. respectively. Samples can be stored for seven days at 4 ℃ or -20 ℃. Matrix effects ranged from 87.12%-99.27% for plasma and 91.00%-97.56% for urine. Conclusion The proposed method is simple, highly sensitive, and reproducible, and is suitable for the determination of 6PPDQ in human plasma and urine samples.

Objective To improve the national standardized method for determining biphenyl in workplace air, which was based on activated carbon tube sampling, carbon disulfide desorption, and gas chromatography, by developing a method using GDX-502 tubes for sampling, toluene for desorption, and gas chromatography. Methods Workplace air samples were collected using GDX-502 sampling tubes and desorbed with toluene, followed by determination with gas chromatography. Results The improved method demonstrated good linearity for biphenyl concentrations ranging from 0.33 to 330.00 mg/L, with a correlation coefficient of 0.999 9. The detection limit and lower limit of quantification were 0.06 and 0.21 mg/L, and the minimum detection concentration and minimum quantification concentration were 0.04 and 0.14 mg/m³ (based on 1.5 L air sample volume), respectively. The average desorption efficiency ranged from 96.6% to 101.1%. The within-run and between-run relative standard deviations were 0.6%-1.4% and 1.4%-3.3%, respectively, with 100.0% sampling efficiency. Samples remained stable for at least 14 days at room temperature. Conclusion The improved method for biphenyl detection demonstrates rapid and accurate performance, with the advantages of low detection limits and high sampling and desorption efficiency.

Objective To summarize the key precautions in the determination of nitrogen oxides (nitric oxide and nitrogen dioxide) in the workplace air and to explore potential optimization items in the national standard analytical method. Methods According to GBZ/T 160.29-2004 Methods for Determination of Inorganic Nitrogen Compounds in the Air Workplace, comparative experiments were conducted to evaluate and optimize critical technical parameters of the standardized method, including the oxidation efficiency of oxidation tubes and the preparation and storage of absorption solutions. The application details of the standard method were refined. Results The concentrations of nitrogen oxides (nitric oxide and nitrogen dioxide) were expressed as nitrogen dioxide equivalents. During calibration, the flow calibrator should be connected to the upstream of the air sampler, and the sampling system should undergo an air tightness check. Each batch of oxidation tubes should be validated before use. Before sampling, both end caps should be removed and the tube should be equilibrated for one hour in a clean environment with 30.00%-70.00% relative humidity. The prepared absorption stock solution in this method can be stored at 4 ℃ for up to 96 days. Commercial porous plate absorption tubes must be batch-validated before use. The sampling flow rate during sampling should be consistent with that specified in the standard method. After sampling, collected samples should be sealed in 10.00 mL amber glass bottles with screw caps and stored at 4 ℃ for up to 120 hours. Conclusion This study summarizes precautions for the sampling, detection, and calculation of nitrogen oxides (nitric oxide and nitrogen dioxide)in workplace air to strengthen quality control. Experimental optimizations of oxidation tube conditioning, absorption stock solution preparation and preservation, and sample storage conditions and durations may provide references for diversifying and simplifying the detection process, which facilitate the practical application in actual work.

Objective To investigate an automated pretreatment technology for detecting levels of free silica in workplace dust. Methods An fully automated pretreatment workstation for detecting free silica levels in workplace dust was developed by integrating graphite-controlled digestion temperature, online-controlled dilution of digestion solutions, and filtration endpoint recognition based on monitoring technology, combined with multi-channel synchronous measurements. Results The fully automatic pretreatment workstation was used to digest and filter 14 standard samples of free silica produced by three institutions, and then detected by pyrophosphate method. The result range of high-, medium-, and low-level free silica standard samples detection was 66.5%-84.8%, 40.0%-44.5%, and 2.1%-24.8%, respectively. The mean relative standard deviations were 3.9%, 1.4% and 1.5%. Conclusion The fully automated pretreatment workstation produced results that met relevant requirements. It can effectively replace the manual digestion and filtration steps of the pyrophosphate method to measure free silica levels in workplace dust and enable rapid detection of free silica in dust samples.

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.