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.

Selective Ion Transport in Two-Dimensional Lamellar Nanochannel Membranes.

Precise and ultrafast ion sieving is highly desirable for many applications in environment-, energy-, and resource-related fields. The development of a permselective lamellar membrane constructed from parallel stacked two-dimensional (2D) nanosheets opened a new avenue for the development of next-generation separation technology because of the unprecedented diversity of the designable interior nanochannels. In this Review, we first discuss the construction of homo- and heterolaminar nanoarchitectures from the starting materials to the emerging preparation strategies. We then explore the property-performance relationships, with a particular emphasis on the effects of physical structural features, chemical properties, and external environment stimuli on ion transport behavior under nanoconfinement. We also present existing and potential applications of 2D membranes in desalination, ion recovery, and energy conversion. Finally, we discuss the challenges and outline research directions in this promising field.

Circular RNAs in atherosclerosis.

Atherosclerosis (AS) is a chronic inflammatory lesion of the arterial vessel wall caused by a variety of complex factors. Furthermore, it is a major cause of cardiovascular disease and a leading cause of death. Circular RNAs (circRNAs) are a new family of endogenous non-coding RNAs with unique covalently closed loops that have sparked interest due to their unique characteristics and potential diagnostic and therapeutic applications in various diseases. A growing number of studies have shown that circRNAs can be used as biomarkers for the diagnosis and treatment of AS. In this article, we review the biogenesis, classification as well as functions of circRNA and summarize the research on circRNA as a diagnostic biomarker for AS. Finally, we describe the regulatory capacity of circRNA in AS pathogenesis through its pathogenesis and demonstrate the potential therapeutic role of circRNA for AS.