Cuishuang Dong, Bin Li, Cong Liu, Jiajing Cui, Yunhui Li, Lirong Liang*, Yang Song* and Xiaobo Li*,
{"title":"Inhibition of Circadian Rhythm Gene per1 Promotes Macrophage Infiltration in e-Cigarette Aerosol-Induced Pulmonary Fibrosis in Mice","authors":"Cuishuang Dong, Bin Li, Cong Liu, Jiajing Cui, Yunhui Li, Lirong Liang*, Yang Song* and Xiaobo Li*, ","doi":"10.1021/envhealth.5c00031","DOIUrl":"https://doi.org/10.1021/envhealth.5c00031","url":null,"abstract":"<p >Although electronic cigarettes (e-cigarettes) are a substitute for traditional cigarettes, increasing studies indicate that e-cigarettes are unsafe. Here, we first analyzed the constituents of e-cigarette liquid (e-liquid) and e-liquid vaping-produced aerosols (e-aerosols) by gas chromatography quadrupole time-of-flight mass spectrometry (GC/Q-TOF MS) and inductively coupled plasma-MS (ICP-MS), and our result indicated that the components of e-aerosols differed from those of e-liquid. However, there is insufficient evidence on the toxicity of e-aerosols; therefore, an animal study was conducted accordingly. Mice were exposed to e-aerosols for 30, 60, or 90 days within a whole-body exposure chamber equipped with an air quality monitor. Compared with the control, weakened lung function and fiber deposition in murine lungs were observed following e-cigarette exposure. Microcomputed tomography (Micro-CT) images suggested fibrosis-like lesions in the lungs. Mechanistically, the expression of the core circadian rhythm gene, <i>per1</i>, was significantly inhibited by e-aerosols, which is negatively correlated with interleukin-6 (IL6) expression and resulted in continuous IL6<sup>+</sup> macrophage infiltration in the lungs during both daytime and night. Eventually, the knockout of <i>il6</i> expression could completely resist e-aerosol-induced pulmonary fibrosis in mice. Our results raise concerns regarding the role of circadian rhythm in regulating pulmonary fibrosis and the potential damages of e-cigarette consumption.</p>","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 8","pages":"866–877"},"PeriodicalIF":6.3,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/envhealth.5c00031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"New Technologies Call for New Pathways: How Does Machine Learning Pave the Way for Discovering Optimal Green Plastic Additives?","authors":"Zheng Hao, Qianhong Wang and Yongming Luo*, ","doi":"10.1021/envhealth.5c00036","DOIUrl":"https://doi.org/10.1021/envhealth.5c00036","url":null,"abstract":"","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 8","pages":"833–836"},"PeriodicalIF":6.3,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/envhealth.5c00036","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Runming He, Ke Fang, Jiankun Qian, Shuling Duan, Fengjiao Jiang, Yifu Lu, Zhaomin Dong, Lin Xu, Wen Gu* and Song Tang*,
{"title":"A Review of Contamination Status and Health Risk Assessment of Volatile Methylsiloxanes in Environmental Matrices","authors":"Runming He, Ke Fang, Jiankun Qian, Shuling Duan, Fengjiao Jiang, Yifu Lu, Zhaomin Dong, Lin Xu, Wen Gu* and Song Tang*, ","doi":"10.1021/envhealth.4c00245","DOIUrl":"https://doi.org/10.1021/envhealth.4c00245","url":null,"abstract":"<p >Volatile methylsiloxanes (VMS) are a group of synthetic chemical compounds broadly used in industrial applications and consumer products, leading to a sharply increased global emission through diverse pathways. Consequently, human exposure to VMS through inhalation or other routes poses potential health risks. To provide insights for environmental contamination by VMS and its concerning health risks, a systematic literature search was conducted in online databases, including the Web of Science, PubMed, Elsevier ScienceDirect, and the China National Knowledge Infrastructure. This review analyzed contamination levels of VMS in various environmental matrices, including air, dust, water, and soil. It further summarized health risk assessments for different external exposure pathways. The exacerbation of VMS pollution is predominantly linked to the increase in atmospheric concentrations, resulting in health risks primarily driven by inhalation exposure. Vulnerable groups require greater attention as their daily intake levels may potentially approach the reference dose, including occupational populations and children residing in areas near factories. Currently, data on long-term and simultaneous environmental monitoring of VMS remain limited. Furthermore, there is a lack of established exposure guidance values, due to insufficient toxicity data and limited risk quantification methods. Therefore, advancing monitoring technologies and networks for VMS and their transformation products is crucial. Future efforts should prioritize integrating advanced tools, such as mixture toxicity models, to achieve more accurate quantification of health risks under complex exposure scenarios. Overall, this review sheds light on developing and revising regulatory frameworks for governing the production and handling of VMS, as well as guiding the health risk assessment.</p>","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 8","pages":"837–853"},"PeriodicalIF":6.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.acs.org/doi/pdf/10.1021/envhealth.4c00245","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiangyu Jia, Qin Li, Fenfang Deng, Jia He, Jinhua Zhou, Lili Sun, Jun Yuan and Lei Tan*,
{"title":"Serial Cross-Sectional Human Biomonitoring Analysis of Pesticide Exposure Patterns and Their Association with Lipid Metabolism Biomarkers: The Mediating Role of Liver Function","authors":"Xiangyu Jia, Qin Li, Fenfang Deng, Jia He, Jinhua Zhou, Lili Sun, Jun Yuan and Lei Tan*, ","doi":"10.1021/envhealth.5c00030","DOIUrl":"10.1021/envhealth.5c00030","url":null,"abstract":"<p >Continuous low-level exposure to pesticides is inevitable in daily life. Previous studies have demonstrated the adverse effects of pesticide exposure on lipid metabolism. However, population studies have focused primarily on individual pesticides and have short-term fluctuations, and the animal experiments used doses far higher than those exposed by the general population. In this study, urinary concentrations of metabolites of three classes of pesticides, including organophosphate, pyrethroid, and phenoxy carboxylic acid, were determined in 1858 participants of repeated cross-sectional biomonitoring programs from 2018 to 2022. We comprehensively analyzed the association of pesticide metabolites and pesticide exposure patterns with lipid metabolism biomarkers. The indirect effects of liver function markers in these associations were explored by using the structural equation model analysis. Generalized linear models showed that 3,5,6-trichloro-2-pyridinol and para-nitrophenol were positively correlated with high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglyceride. In contrast, 3-phenoxybenzoic acid was negatively correlated with apolipoprotein B. Quantile g-computation and Bayesian Kernel Machine Regression showed a consistent gradual increase in high-density lipoprotein cholesterol and low-density lipoprotein cholesterol levels but a gradual decrease in apolipoprotein B levels with increasing exposure to pesticide mixtures. By analyzing the exposure patterns of different categories of pesticides, we found that the population has a high level of exposure to organophosphate pesticides, which disrupts lipid metabolism more significantly than other pesticides. Liver function exhibited significant mediating effects in the association between pesticide exposure and lipid metabolism biomarkers. The results indicated that pesticide exposure was significantly associated with lipid metabolism, and this association may be modulated by improvements in liver function.</p>","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 7","pages":"818–830"},"PeriodicalIF":6.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12281205/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144699728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mei Liu, Xiaoling Guan, Lingling Meng*, Gaoxin Zhang, Jiyan Liu, Yingming Li*, Mary E. Turyk, An Li, Qinghua Zhang and Guibin Jiang,
{"title":"Short-Chain Polychlorinated Alkanes Exposure and Risk of Thyroid Cancer in a Population-Based Case-Control Study","authors":"Mei Liu, Xiaoling Guan, Lingling Meng*, Gaoxin Zhang, Jiyan Liu, Yingming Li*, Mary E. Turyk, An Li, Qinghua Zhang and Guibin Jiang, ","doi":"10.1021/envhealth.5c00044","DOIUrl":"10.1021/envhealth.5c00044","url":null,"abstract":"<p >Exposure to short-chain polychlorinated alkanes (PCAs-C<sub>10–13</sub>) can disturb thyroid homeostasis, warranting an in-depth analysis of their relationship with thyroid risk and related clinical parameters. This study recruited and obtained serum samples from 478 participants in Shandong, China, including 240 thyroid cancer patients and 238 healthy controls. PCAs-C<sub>10</sub> presented as the predominant homologues in both case and control groups. PCAs-C<sub>10–13</sub> exposure displayed an essential role in thyroid cancer risk, in which a nonlinear dose-risk relationship was observed for PCAs-C<sub>10–13</sub>, with PCAs-C<sub>12</sub> and PCAs-C<sub>13</sub> exhibiting significantly reduced risks (odds ratios < 1) for thyroid cancer. Specific PCAs-C<sub>10–13</sub> homologues were significantly associated with triglycerides, cholesterol, low-density lipoprotein cholesterol, and total lipid in the control group. Weighted quantile sum regression and Bayesian kernel machine regression revealed predominantly negative combined effects of PCAs-C<sub>10–13</sub> exposure on thyroid cancer, thyroid hormone, and serum lipid parameters. Our results showed that exposure to the current environmental level of PCAs-C<sub>10–13</sub> cannot heighten risks of thyroid cancer. Overall, this study first provides epidemiological evidence on the potential implications of PCAs-C<sub>10–13</sub> exposure and thyroid cancer risk.</p>","PeriodicalId":29795,"journal":{"name":"Environment & Health","volume":"3 7","pages":"807–817"},"PeriodicalIF":6.3,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12281199/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144699729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}