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.

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.

In recent years, fibroblast activation protein inhibitor (FAPI) PET imaging, which targets the tumor microenvironment, has shown significant potential in evaluating solid tumors. Particularly, studies have demonstrated the value of 68Ga-FAPI PET in evaluation of gastric and colorectal cancer. This article reviews previous studies and provides an overview of how 68Ga-FAPI PET can be used in the diagnosis, staging, recurrence monitoring, clinical management, efficacy evaluation, and prognostic prediction of gastric and colorectal cancer, in order to provide a basis for the further utilization of this novel imaging agent, 68Ga-FAPI, in gastric and colorectal cancer.

Objective:To explore the clinical features and molecular characteristics of myeloproliferative neoplasms (MPNs) patients with NFE2 gene mutations.Methods:Gene targeted sequencing was used to detect NFE2 gene mutation in 723 patients diagnosed with MPNs who were admitted to Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College between April 2021 and June 2023. The association between NFE2 gene mutations and clinical features and molecular characteristics of MPNs patients were retrospectively analyzed.Results:Among 723 patients with MPNs, NFE2 gene mutations were found in 41 cases (5.7%) . NFE2 gene mutations were predominantly frameshift mutations (44.4%) , followed by nonsense mutations (33.3%) . The median number of mutations in patients with NFE2 gene mutations (4 [2,5]) was higher compared to the group without NFE2 gene mutations (2, [1,3]) ( P<0.001) . NFE2 gene mutations frequently co-occurred with mutations in MPL, ATM, PPM1D, and TET1. NFE2 gene mutations were mostly sub-clonal events, with 80.5% occurring after MPNs driver mutations (JAK2, CALR, or MPL) . NFE2 mutations were correlated with older age [median age: 60 (54, 67) years vs 54 (41, 63) years, P=0.001]. Patients with NFE2 gene mutations had a higher incidence of pre-diagnosis thrombosis (39.0% vs 22.0%, P=0.012) and pre-diagnosis arterial thrombosis (36.6% vs 20.4%, P=0.014) . Using a logistic regression analysis model adjusting for age and comorbidities (including chronic infections, malignancies, and autoimmune diseases) , NFE2 gene mutation was identified as an independent determinant of elevated tumor necrosis factor-alpha (TNF-α) ( OR=2.747, 95% CI: 1.143-6.605, P=0.024) , interferon-gamma (IFN-γ) ( OR=2.689, 95% CI: 1.191-6.076, P=0.017) , IL-10 ( OR=3.219, 95% CI: 1.343-7.717, P=0.009) , IL-12P70 ( OR=3.397, 95% CI:1.003-11.508, P=0.049) , IL-17 ( OR=2.284, 95% CI: 1.017-5.127, P=0.045) . In polycythaemia vera (PV) patients with the NFE2 gene mutation, the proportion of those classified as high-risk is notably higher in both the IWG-PV and mutation-enhanced international prognostic systems for PV (MIPSS-PV) (66.7% vs 25.3% for IWG-PV, P=0.033; 22.2% vs 2.0% for MIPSS-PV, P=0.013) . Similarly, for essential thrombocythaemia (ET) patients, the proportion in the high-risk group of the mutation-enhanced international prognostic systems for ET (MIPSS-ET) is significantly higher (15.4% vs 6.1%, P=0.021) . No statistically significant differences were observed in overall survival or cumulative incidence of thrombosis between NFE2-mutated (38 cases) and non-mutated MPNs patients (671 cases, P>0.05) . Conclusion:NFE2 gene mutations in MPNs were predominantly frameshift mutations. NFE2 gene mutations were correlated with older age, elevated levels of several inflammatory factors (including TNF-α、IFN-γ、IL-10、IL-12P70、IL-17) , and they mostly occurred in late-stage of MPNs.

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 To explore the mechanism of the gut-lung axis in paraquat-induced lung injury in mice, with a focus on analyzing the changes in intestinal gene expression and their potential roles. Methods Specific pathogen-free C57BL/6 wild-type mice were randomly divided into control, low-dose, and high-dose groups, with 10 mice in each group. Mice in the three groups received a single intragastric administration of paraquat solution at doses of 0, 25, or 50 mg/kg body weight. The mice were euthanized on day 21. Lung histopathological changes were assessed, and the differentially expressed genes (DEGs) in the intestinal tissues of mice in these two groups were analyzed through transcriptomics. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore potential mechanisms of the gut-lung axis in paraquat-induced lung injury and fibrosis. Results Paraquat exposure induced dose-dependent pulmonary injury and fibrosis in the mice. The Ashcroft score of lung tissue was higher in the mice of low-dose group than that in the control group (P<0.05). Both the lung organ coefficient and Ashcroft score of lung tissues in the mice of high-dose group were higher than those in the control group and the low-dose group (all P<0.05). The result of transcriptomic analysis showed 146 DEGs, including 91 upregulated and 55 downregulated genes, in intestinal tissues of mice in the low-dose group, and 57 DEGs, including 47 upregulated and 10 downregulated genes in the high-dose group, compared with the control group. Notably, 19 DEGs were commonly altered in both low- and high-dose groups. The result of GO enrichment analysis showed that the DEGs were primarily involved in biological processes including "immune response", "oxidative stress" and "cell differentiation". The result of KEGG enrichment analyses showed that DEGs were primarily involved in key processes including "oxidative stress response path way", "immune response path way" and "digestion and absorption path way". Conclusion Paraquat exposure alters intestinal gene expression, particularly in genes in biological processes related to immune responses and oxidative stress. These changes may mediate inflammatory signaling via the gut-lung axis and contribute to the development of paraquat-induced pulmonary fibrosis.

In recent years, fibroblast activation protein inhibitor (FAPI) PET imaging, which targets the tumor microenvironment, has shown significant potential in evaluating solid tumors. Particularly, studies have demonstrated the value of 68Ga-FAPI PET in evaluation of gastric and colorectal cancer. This article reviews previous studies and provides an overview of how 68Ga-FAPI PET can be used in the diagnosis, staging, recurrence monitoring, clinical management, efficacy evaluation, and prognostic prediction of gastric and colorectal cancer, in order to provide a basis for the further utilization of this novel imaging agent, 68Ga-FAPI, in gastric and colorectal cancer.

Objective:To explore the clinical features and molecular characteristics of myeloproliferative neoplasms (MPNs) patients with NFE2 gene mutations.Methods:Gene targeted sequencing was used to detect NFE2 gene mutation in 723 patients diagnosed with MPNs who were admitted to Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College between April 2021 and June 2023. The association between NFE2 gene mutations and clinical features and molecular characteristics of MPNs patients were retrospectively analyzed.Results:Among 723 patients with MPNs, NFE2 gene mutations were found in 41 cases (5.7%) . NFE2 gene mutations were predominantly frameshift mutations (44.4%) , followed by nonsense mutations (33.3%) . The median number of mutations in patients with NFE2 gene mutations (4 [2,5]) was higher compared to the group without NFE2 gene mutations (2, [1,3]) ( P<0.001) . NFE2 gene mutations frequently co-occurred with mutations in MPL, ATM, PPM1D, and TET1. NFE2 gene mutations were mostly sub-clonal events, with 80.5% occurring after MPNs driver mutations (JAK2, CALR, or MPL) . NFE2 mutations were correlated with older age [median age: 60 (54, 67) years vs 54 (41, 63) years, P=0.001]. Patients with NFE2 gene mutations had a higher incidence of pre-diagnosis thrombosis (39.0% vs 22.0%, P=0.012) and pre-diagnosis arterial thrombosis (36.6% vs 20.4%, P=0.014) . Using a logistic regression analysis model adjusting for age and comorbidities (including chronic infections, malignancies, and autoimmune diseases) , NFE2 gene mutation was identified as an independent determinant of elevated tumor necrosis factor-alpha (TNF-α) ( OR=2.747, 95% CI: 1.143-6.605, P=0.024) , interferon-gamma (IFN-γ) ( OR=2.689, 95% CI: 1.191-6.076, P=0.017) , IL-10 ( OR=3.219, 95% CI: 1.343-7.717, P=0.009) , IL-12P70 ( OR=3.397, 95% CI:1.003-11.508, P=0.049) , IL-17 ( OR=2.284, 95% CI: 1.017-5.127, P=0.045) . In polycythaemia vera (PV) patients with the NFE2 gene mutation, the proportion of those classified as high-risk is notably higher in both the IWG-PV and mutation-enhanced international prognostic systems for PV (MIPSS-PV) (66.7% vs 25.3% for IWG-PV, P=0.033; 22.2% vs 2.0% for MIPSS-PV, P=0.013) . Similarly, for essential thrombocythaemia (ET) patients, the proportion in the high-risk group of the mutation-enhanced international prognostic systems for ET (MIPSS-ET) is significantly higher (15.4% vs 6.1%, P=0.021) . No statistically significant differences were observed in overall survival or cumulative incidence of thrombosis between NFE2-mutated (38 cases) and non-mutated MPNs patients (671 cases, P>0.05) . Conclusion:NFE2 gene mutations in MPNs were predominantly frameshift mutations. NFE2 gene mutations were correlated with older age, elevated levels of several inflammatory factors (including TNF-α、IFN-γ、IL-10、IL-12P70、IL-17) , and they mostly occurred in late-stage of MPNs.

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.