Development of predictive models for silicone rubber-water partition coefficients of hydrophobic organic contaminants

Development and application of diffusive gradients in thin films for in situ sampling of the organic UV filter 4-methylbenzylidene camphor (4-MBC) in waters

4-Methylbenzylidene camphor (4-MBC), a typical organic UV filter (OUVF) in personal care products, is considered to be a potential endocrine disruptor due to its estrogenic activity and bioaccumulation. Although 4-MBC residues have been extensively identified in aquatic waters, little is known about their occurrence, levels, and potential risk in coastal waters. This study developed a reliable sampling approach, based on diffusive gradients in thin films (DGT) with XAD-2 as the binding agent, for monitoring 4-MBC in coastal waters. The diffusion coefficients of 4-MBC in freshwater and artificial seawater were 3.65 × 10-6 cm2/s and 3.83 × 10-6 cm2/s, respectively. XAD-2 binding gel showed rapid adsorption to 4-MBC. The accumulated masses of 4-MBC in XAD-2 DGT increased linearly with deployed time for 7 days in freshwater and seawater, which agreed well with theoretical predictions. The sampling performance was independent of ionic strength (0.0001-0.5 M), pH (4.0-8.5), and dissolved organic matter (0-20 mg/L). Field deployment in the river estuary and bathing beach showed that DGT-measured 4-MBC concentrations were consistent in comparison with grab sampling. Environmental risk assessment showed that 4-MBC may pose a medium risk to aquatic organisms based on computed risk quotient (RQ) values. Sewage discharge is the main source of 4-MBC risk, while the residue in recreation beaches contributes more significantly in summer. The established DGT sampling is suitable for seasonal monitoring, source identification, and risk assessment of 4-MBC in coastal waters.

Versatile in silico modelling of microplastics adsorption capacity in aqueous environment based on molecular descriptor and machine learning

To comprehensively evaluate the hazards of microplastics and their coexisting organic pollutants, the sorption capacity of microplastics is a major issue that is quantified through the microplastic-aqueous sorption coefficient (K_d). Almost all quantitative structure-property relationship (QSPR) models that describe K_d apply only to narrow, relatively homogeneous groups of reactants. Herein, non-hybrid QSPR-based models were developed to predict PE-water (K_PE-w), PE-seawater (K_PE-sw), PVC-water (K_PVC-w) and PP-seawater (K_PP-sw) sorption coefficients at different temperatures, with eight machine learning algorithms. Moreover, novel hybrid intelligent models for predicting K_d more accurately were innovatively developed by applying GA, PSO and AdaBoost algorithms to optimize MLP and ELM models. The results indicated that all three optimization algorithms could improve the robustness and predictability of the standalone MLP and ELM models. In all models trained with K_PE-w, K_PE-sw, K_PVC-w and K_PP-sw data sets, GBDT-1 and XGBoost-1 models, MLP-GA-2 and MLP-PSO-2 models, MLR-3 and MLR-4 models performed better in terms of goodness of fit (R_adj²: 0.907-0.999), robustness (Q_BOOT²: 0.900-0.937) and predictability (R_ext²: 0.889-0.970), respectively. Analyzing the descriptors revealed that temperature, lipophilicity, ionization potential and molecular size were correlated closely with the adsorption capacity of microplastics to organic pollutants. The proposed QSPR models may assist in initial environmental exposure assessments without imposing heavy costs in the early experimental phase.

Researching the Links between Smartphone Behavior and Adolescent Wellbeing: The Study Protocol for the FUTURE (WP4) Ecological Momentary Assessment Study (Preprint)

Background

Smartphone ownership has increased among teens within the last decade, with up to 89% of adolescents owning a smartphone and engaging daily with the online world through it. Although the results of recent meta-analyses suggest that engaging digital technology plays only a small role in adolescent well-being, parents, professionals, and policymakers remain concerned about the impact that the instant connectivity of smartphones has on adolescent well-being.

Objective

Herein, we introduce the protocol of a research study investigating the associations between adolescent smartphone use and different facets of well-being (social, physical, and psychological), with the aim to apply innovative methods to address the limitations of existing empirical studies.

Methods

This 12-month prospective study of adolescents uses a repeated measurement-burst design with the ecological momentary assessment methodology. Adolescents (N=203; age range 13-17 years) complete baseline assessments through online questionnaires, four 14-day intensive data collection bursts, and an online questionnaire at the end of the study. As part of the 4 measurement bursts, adolescent smartphone behavior is assessed objectively by passive data collection of smartphone data logs and through self-reports in short questionnaires administered via a custom-built Android app.

Results

The protocol describes the study objectives, research tools (including the development of the Android app and specialized software), and process (including pilot studies, the main study, and targets for machine learning approaches). Two of the 203 enrolled participants provided no data during the first data collection burst of the main study. Preliminary analyses of the data from the first data collection burst indicated an acceptable level of compliance (72.25%) with the daily questionnaires. The design of the study will allow for the assessment of both within- and between-person variabilities in smartphone behavior, as well as short-term variation and long-term change in smartphone behavior and how it impacts the indicators of social, physical, and psychological well-being.

Conclusions

The innovative methods applied in this study (objective smartphone logs, ecological momentary assessment, and machine learning) will allow for a more nuanced assessment of the links between smartphone use and well-being, informing strategies to help adolescents navigate the online world more constructively in terms of the development of their physical, social, and psychological well-being.

International Registered Report Identifier (IRRID)

DERR1-10.2196/35984