Ethyl acrylate (EA) exposure and thyroid carcinogenicity in rats and mice with relevance to human health

Risk of papillary thyroid carcinoma and nodular goiter associated with exposure to semi-volatile organic compounds: A multi-pollutant assessment based on machine learning algorithms

BACKGROUND

Exposure to semi-volatile organic compounds (SVOCs) may link to thyroid nodule risk, but studies of mixed-SVOCs exposure effects are lacking. Traditional analytical methods are inadequate for dealing with mixed exposures, while machine learning (ML) seems to be a good way to fill the gaps in the field of environmental epidemiology research.

OBJECTIVES

Different ML algorithms were used to explore the relationship between mixed-SVOCs exposure and thyroid nodule.

METHODS

A 1:1:1 age- and gender-matched case-control study was conducted in which 96 serum SVOCs were measured in 50 papillary thyroid carcinoma (PTC), 50 nodular goiters (NG), and 50 controls. Different ML techniques such as Random Forest, AdaBoost were selected based on their predictive power, and variables were selected based on their weights in the models. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to assess the mixed effects of the SVOCs exposure on thyroid nodule.

RESULTS

Forty-three of 96 SVOCs with detection rate >80 % were included in the analysis. ML algorithms showed a consistent selection of SVOCs associated with thyroid nodule. Fluazifop-butyl and fenpropathrin are positively associated with PTC and NG in single compound models (all P < 0.05). WQS model shows that exposure to mixed-SVOCs was associated with an increased risk of PTC and NG, with the mixture dominated by fenpropathrin, followed by fluazifop-butyl and propham. In the BKMR model, mixtures showed a significant positive association with thyroid nodule risk at high exposure levels, and fluazifop-butyl showed positive effects associated with PTC and NG.

CONCLUSION

This study confirms the feasibility of ML methods for variable selection in high-dimensional complex data and showed that mixed exposure to SVOCs was associated with increased risk of PTC and NG. The observed association was primarily driven by fluazifop-butyl and fenpropathrin. The findings warranted further investigation.

Cancer weight of evidence for three lower acrylates: Conclusions and recommendations from an expert panel

An international panel of experts was engaged to assess the cancer weight of evidence (WOE) for three lower acrylates: methyl acrylate, ethyl acrylate, and 2-ethylhexyl acrylate. The review was structured as a three-round, modified Delphi format, a systematic process for collecting independent and deliberative input from panel members, and it included procedural elements to reduce bias and groupthink. Based upon the available science, the panel concluded: (1) The MOA for point of contact tumors observed in rodent cancer bioassays that is best supported by available data involves increased cell replication by cytotoxicity and regenerative proliferation; (2) The WOE supports a cancer classification of "Not likely to be carcinogenic to humans" a conclusion that is more in line with an IARC classification of Group 3 rather than Group 2 B; (3) Quantitative cancer potency values based on rodent tumor data are not required for these chemicals; and (4) Human health risk assessment for these chemicals should instead rely on non-cancer, precursor endpoints observed at the point of contact (e.g., hyperplasia). The degree of consensus (consensus scores of 0.84-0.91 out of a maximum score of 1) and degree of confidence (7.7-8.7 out of a maximum score of 10) in the WOE conclusions is considered high.

1Non-thermal plasma coupled with a wet scrubber for removing odorous VOC

Odorous volatile organic compounds (VOCs) deteriorate the quality of life and affect human health. In this study, a process was developed to remove an odorous VOC using a combined non-thermal plasma (NTP) and wet scrubber (WS) system. The low removal efficiency of WSs and the large amount of ozone generated by NTP were resolved. Compared to the decomposition effects when using a WS and NTP separately, the NTP + WS system improved the removal efficiency of ethyl acrylate (EA) and significantly reduced ozone emissions. The maximum EA removal efficiency was 99.9%. Additionally, an EA removal efficiency of over 53.4% and a 100% ozone removal efficiency were achieved even at discharge voltages lower than 4.5 kV. Ozone catalysis was confirmed to occur in the NTP + WS system. Furthermore, we verified the removal of by-products such as residual ozone and formaldehyde, which is a representative organic intermediate of EA. This study demonstrates that the NTP + WS system is a green technology for removing odorous VOCs.

Application of Carbon Fiber Cement-Based Composites in Improving Construction Durability

In order to improve the durability of building construction, this study proposes a construction method based on carbon fiber and cement-based composites. Analyze the mechanical properties of carbon fiber cement-based composites, combined with experiments to further analyze its advantages in building construction, to achieve the purpose of building durability construction. The experimental results show that the elastic modulus of CFRC samples with a 0.6% carbon fiber volume percentage is the largest. When the content of carbon fiber increases within a certain range, the elastic modulus of CFRC samples will also increase. Conclusion. The application of carbon fiber cement-based composites in building construction can effectively improve the durability of buildings and further improve the quality of buildings.