Development of AOP relevant to microplastics based on toxicity mechanisms of chemical additives using ToxCast™ and deep learning models combined approach

A review on advancements in atmospheric microplastics research: The pivotal role of machine learning

Microplastics (MPs), recognized as emerging pollutants, pose significant potential impacts on the environment and human health. The investigation into atmospheric MPs is nascent due to the absence of effective characterization methods, leaving their concentration, distribution, sources, and impacts on human health largely undefined with evidence still emerging. This review compiles the latest literature on the sources, distribution, environmental behaviors, and toxicological effects of atmospheric MPs. It delves into the methodologies for source identification, distribution patterns, and the contemporary approaches to assess the toxicological effects of atmospheric MPs. Significantly, this review emphasizes the role of Machine Learning (ML) and Artificial Intelligence (AI) technologies as novel and promising tools in enhancing the precision and depth of research into atmospheric MPs, including but not limited to the spatiotemporal dynamics, source apportionment, and potential health impacts of atmospheric MPs. The integration of these advanced technologies facilitates a more nuanced understanding of MPs' behavior and effects, marking a pivotal advancement in the field. This review aims to deliver an in-depth view of atmospheric MPs, enhancing knowledge and awareness of their environmental and human health impacts. It calls upon scholars to focus on the research of atmospheric MPs based on new technologies of ML and AI, improving the database as well as offering fresh perspectives on this critical issue.

Critical evaluation of hyperspectral imaging technology for detection and quantification of microplastics in soil

In this study, we critically evaluated the performance of an emerging technology, hyperspectral imaging (HSI), for detecting microplastics (MPs) in soil. We examined the technology's robustness against varying environmental conditions in five groups of experiments. Our findings show that near-infrared (NIR) hyperspectral imaging (HSI) effectively detects microplastics (MPs) in soil, though detection efficacy is influenced by factors such as MP concentration, color, and soil moisture. We found a generally linear relationship between the levels of MPs in various soils and their spectral responses in the NIR HSI imaging spectrum. However, effectiveness is reduced for certain MPs, like polyethylene, in kaolinite clay. Furthermore, we showed that soil moisture considerably influenced the detection of MPs, leading to nonlinearities in quantification and adding complexities to spectral analysis. The varied responses of MPs of different sizes and colors to NIR HSI present further challenges in detection and quantification. The research suggests pre-grouping of MPs based on size before analysis and proposes further investigation into the interaction between soil moisture and MP detectability to enhance HSI's application in MP monitoring and quantification. To our knowledge, this study is the first to comprehensively evaluate this technology for detecting and quantifying microplastics.

Inhalation Toxicity Screening of Consumer Products Chemicals using OECD Test Guideline Data-based Machine Learning Models

This study aimed to screen the inhalation toxicity of chemicals found in consumer products such as air fresheners, fragrances, and anti-fogging agents submitted to K-REACH using machine learning models. We manually curated inhalation toxicity data based on OECD test guideline 403 (Acute inhalation), 412 (Sub-acute inhalation), and 413 (Sub-chronic inhalation) for 1709 chemicals from the OECD eChemPortal database. Machine learning models were trained using ten algorithms, along with four molecular fingerprints (MACCS, Morgan, Topo, RDKit) and molecular descriptors, achieving F1 scores ranging from 51 % to 91 % in test dataset. Leveraging the high-performing models, we conducted a virtual screening of chemicals, initially applying them to data-rich chemicals generally used in occupational settings to determine the prediction uncertainty. Results showed high sensitivity (75 %) but low specificity (23 %), suggesting that our models can contribute to conservative screening of chemicals. Subsequently, we applied the models to consumer product chemicals, identifying 79 as of high concern. Most of the prioritized chemicals lacked GHS classifications related to inhalation toxicity, even though they were predicted to be used in many consumer products. This study highlights a potential regulatory blind spot concerning the inhalation risk of consumer product chemicals while also indicating the potential of artificial intelligence (AI) models to aid in prioritizing chemicals at the screening level.

Leveraging integrative toxicogenomic approach towards development of stressor-centric adverse outcome pathway networks for plastic additives

Plastics are widespread pollutants found in atmospheric, terrestrial and aquatic ecosystems due to their extensive usage and environmental persistence. Plastic additives, that are intentionally added to achieve specific functionality in plastics, leach into the environment upon plastic degradation and pose considerable risk to ecological and human health. Limited knowledge concerning the presence of plastic additives throughout plastic life cycle has hindered their effective regulation, thereby posing risks to product safety. In this study, we leveraged the adverse outcome pathway (AOP) framework to understand the mechanisms underlying plastic additives-induced toxicities. We first identified an exhaustive list of 6470 plastic additives from chemicals documented in plastics. Next, we leveraged heterogenous toxicogenomics and biological endpoints data from five exposome-relevant resources, and identified associations between 1287 plastic additives and 322 complete and high quality AOPs within AOP-Wiki. Based on these plastic additive-AOP associations, we constructed a stressor-centric AOP network, wherein the stressors are categorized into ten priority use sectors and AOPs are linked to 27 disease categories. We visualized the plastic additives-AOP network for each of the 1287 plastic additives and made them available in a dedicated website: https://cb.imsc.res.in/saopadditives/ . Finally, we showed the utility of the constructed plastic additives-AOP network by identifying highly relevant AOPs associated with benzo[a]pyrene (B[a]P), bisphenol A (BPA), and bis(2-ethylhexyl) phthalate (DEHP) and thereafter, explored the associated toxicity pathways in humans and aquatic species. Overall, the constructed plastic additives-AOP network will assist regulatory risk assessment of plastic additives, thereby contributing towards a toxic-free circular economy for plastics.

Hepatic toxicity prediction of bisphenol analogs by machine learning strategy

Toxicological studies have demonstrated the hepatic toxicity of several bisphenol analogs (BPs), a prevalent type of endocrine disruptor. The development of Adverse Outcome Pathway (AOP) has substantially contributed to the rapid risk assessment for human health. However, the lack of in vitro and in vivo data for the emerging BPs has limited the hazard assessment of these synthetic chemicals. Here, we aimed to develop a new strategy to rapidly predict BPs' hepatotoxicity using network analysis coupled with machine learning models. Considering the structural and functional similarities shared by BPs with Bisphenol A (BPA), we first integrated hepatic disease related genes from multiple databases into BPA-Gene-Phenotype-hepatic toxicity network and subjected it to the computational AOP (cAOP). Through cAOP network and conventional machine learning approaches, we scored the hepatotoxicity of 20 emerging BPs and provided new insights into how BPs' structure features contributed to biologic functions with limited experimental data. Additionally, we assessed the interactions between emerging BPs and ESR1 using molecular docking and proposed an AOP framework wherein ESR1 was a molecular initiating event. Overall, our study provides a computational approach to predict the hepatotoxicity of emerging BPs.

The potential of micro- and nanoplastics to exacerbate the health impacts and global burden of non-communicable diseases

Non-communicable diseases (NCD) constitute one of the highest burdens of disease globally and are associated with inflammatory responses in target organs. There is increasing evidence of significant human exposure to micro- and nanoplastics (MnPs). This review of environmental MnP exposure and health impacts indicates that MnP particles, directly and indirectly through their leachates, may exacerbate inflammation. Meanwhile, persistent inflammation associated with NCDs in gastrointestinal and respiratory systems potentially increases MnP uptake, thus influencing MnP access to distal organs. Consequently, a future increase in MnP exposure potentially augments the risk and severity of NCDs. There is a critical need for an integrated one-health approach to human health and environmental research for assessing the drivers of human MnP exposure and their bidirectional links with NCDs. Assessing these risks requires interdisciplinary efforts to identify and link drivers of environmental MnP exposure and organismal uptake to studies of impacted disease mechanisms and health outcomes.

Inflammation-mediated metabolic regulation in adipose tissue

Chronic inflammation of adipose tissue is a prominent characteristic of many metabolic diseases. Lipid metabolism in adipose tissue is consistently dysregulated during inflammation, which is characterized by substantial infiltration by proinflammatory cells and high cytokine concentrations. Adipose tissue inflammation is caused by a variety of endogenous factors, such as mitochondrial dysfunction, reactive oxygen species (ROS) production, endoplasmic reticulum (ER) stress, cellular senescence, ceramides biosynthesis and mediators of lipopolysaccharides (LPS) signaling. Additionally, the gut microbiota also plays a crucial role in regulating adipose tissue inflammation. Essentially, adipose tissue inflammation arises from an imbalance in adipocyte metabolism and the regulation of immune cells. Specific inflammatory signals, including nuclear factor-κB (NF-κB) signaling, inflammasome signaling and inflammation-mediated autophagy, have been shown to be involved in the metabolic regulation. The pathogenesis of metabolic diseases characterized by chronic inflammation (obesity, insulin resistance, atherosclerosis and nonalcoholic fatty liver disease [NAFLD]) and recent research regarding potential therapeutic targets for these conditions are also discussed in this review.

Science-based evidence on pathways and effects of human exposure to micro- and nanoplastics

Human exposure to plastic particles has raised great concern among all relevant stakeholders involved in the protection of human health due to the contamination of the food chain, surface waters, and even drinking water as well as due to their persistence and bioaccumulation. Now more than ever, it is critical that we understand the biological fate of plastics and their interaction with different biological systems. Because of the ubiquity of plastic materials in the environment and their toxic potential, it is imperative to gain reliable, regulatory-relevant, science-based data on the effects of plastic micro- and nanoparticles (PMNPs) on human health in order to implement reliable risk assessment and management strategies in the circular economy of plastics. This review presents current knowledge of human-relevant PMNP exposure doses, pathways, and toxic effects. It addresses difficulties in properly assessing plastic exposure and current knowledge gaps and proposes steps that can be taken to underpin health risk perception, assessment, and mitigation through rigorous science-based evidence. Based on the existing scientific data on PMNP adverse health effects, this review brings recommendations on the development of PMNP-specific adverse outcome pathways (AOPs) following the AOP Users' Handbook of the Organisation for Economic Cooperation and Development (OECD).

Polystyrene micro- and nanoplastics induce gastric toxicity through ROS mediated oxidative stress and P62/Keap1/Nrf2 pathway

Microplastics (MPs) exist widely in the environment and can enter the human body indirectly through the food chain or directly through inhalation or ingestion. The primary organ that MPs contaminated food or water enters the human body through the digestive tract is the stomach. However, at present, the effects of MPs on the stomach and the related mechanism remain unclear. In this study, our results indicated that 50 nm and 250 nm polystyrene MPs (PS-MPs) at environmental related dose significantly decreased stomach organ coefficient, inhibited gastric juice secretion and mucus secretion, disrupted gastric barrier function and suppressed antioxidant ability in mice. In vitro experiments showed that PS-MPs inhibited cell viability, increased ROS generation, and induced apoptosis through mitochondria-dependent pathway. Simultaneously, PS-MPs also decreased mitochondrial membrane potential, ATP level, disrupted mitochondrial kinetic homeostasis, and activated P62 / Nrf2 / Keap1 pathway. Furthermore, blocking ROS (NAC) partially alleviated ROS and apoptosis caused by PS-MPs. Based on above findings, the potential adverse outcome pathway (AOP) of PS-MPs-caused gastric toxicity was proposed which provides a new insight into the risk assessment of MP related gastric damage. Our study unveils the gastric injury induced by PS MPs is dependent on ROS - mediated P62 / Nrf2 / Keap1 signaling pathway, and provides scientific basis for further exploration the mechanism of gastric toxicity of PS MPs.

Various additive release from microplastics and their toxicity in aquatic environments

Additives may be present in amounts higher than 50% within plastic objects. Additives in plastics can be gradually released from microplastics (MPs) into the aquatic environment during their aging and fragmentation because most of them do not chemically react with the polymers. Some are known to be hazardous substances, which can cause toxicity effects on organisms and pose ecological risks. In this paper, the application of functional additives in MPs and their leaching in the environment are first summarized followed by their release mechanisms including photooxidation, chemical oxidation, biochemical degradation, and physical abrasion. Important factors affecting the additive release from MPs are also reviewed. Generally, smaller particle size, light irradiation, high temperature, dissolved organic matter (DOM) existence and alkaline conditions can promote the release of chemicals from MPs. In addition, the release of additives is also influenced by the polymer's structure, electrolyte types, as well as salinity. These additives may transfer into the organisms after ingestion and disrupt various biological processes, leading to developmental malformations and toxicity in offspring. Nonetheless, challenges on the toxicity of chemicals in MPs remain hindering the risk assessment on human health from MPs in the environment. Future research is suggested to strengthen research on the leaching experiment in the actual environment, develop more techniques and analysis methods to identify leaching products, and evaluate the toxicity effects of additives from MPs based on more model organisms. The work gives a comprehensive overview of current process for MP additive release in natural waters, summarizes their toxicity effects on organisms, and provides recommendations for future research.

Airborne microplastics: A narrative review of potential effects on the human respiratory system

There has been growing evidence showing the widespread of airborne microplastics (AMPs) in many regions of the world, raising concerns about their impact on human health. This review aimed to consolidate recent literature on AMPs regarding their physical and chemical characteristics, deposition in the human respiratory tract, translocation, occurrence from human studies, and toxic effects determined in vitro and in vivo. The physical characteristics influence interactions with cell membranes, cellular internalization, accumulation, and cytotoxicity resulting from cell membrane damage and oxidative stress. In addition, prolonged exposure to AMP-associated toxic chemicals might lead to significant health effects. Most toxicological assessments of AMPs in vitro and in vivo have demonstrated that oxidative stress and inflammation are major mechanisms of action for their toxic effects. Elevated reactive oxygen species production could lead to mitochondrial dysfunction, inflammatory responses, and subsequent apoptosis in experimental models. To date, there has been some evidence suggesting exposure in humans. However, the data are still insufficient, and adverse human health effects need to be investigated. Future research on the existence, exposure, and health effects of AMPs is required for developing preventive and mitigation measures to protect human health.

Machine Learning-Based Hazard-Driven Prioritization of Features in Nontarget Screening of Environmental High-Resolution Mass Spectrometry Data

Nontarget high-resolution mass spectrometry screening (NTS HRMS/MS) can detect thousands of organic substances in environmental samples. However, new strategies are needed to focus time-intensive identification efforts on features with the highest potential to cause adverse effects instead of the most abundant ones. To address this challenge, we developed MLinvitroTox, a machine learning framework that uses molecular fingerprints derived from fragmentation spectra (MS2) for a rapid classification of thousands of unidentified HRMS/MS features as toxic/nontoxic based on nearly 400 target-specific and over 100 cytotoxic endpoints from ToxCast/Tox21. Model development results demonstrated that using customized molecular fingerprints and models, over a quarter of toxic endpoints and the majority of the associated mechanistic targets could be accurately predicted with sensitivities exceeding 0.95. Notably, SIRIUS molecular fingerprints and xboost (Extreme Gradient Boosting) models with SMOTE (Synthetic Minority Oversampling Technique) for handling data imbalance were a universally successful and robust modeling configuration. Validation of MLinvitroTox on MassBank spectra showed that toxicity could be predicted from molecular fingerprints derived from MS2 with an average balanced accuracy of 0.75. By applying MLinvitroTox to environmental HRMS/MS data, we confirmed the experimental results obtained with target analysis and narrowed the analytical focus from tens of thousands of detected signals to 783 features linked to potential toxicity, including 109 spectral matches and 30 compounds with confirmed toxic activity.

Machine learning: Next promising trend for microplastics study

Microplastics (MPs), as an emerging pollutant, pose a significant threat to humans and ecosystems. However, traditional MPs characterization methods are limited by sample requirements and characterization time. Machine Learning (ML) has emerged as a vital technology for analyzing MPs pollution due to its accuracy, broad application, and powerful feature extraction. Nevertheless, environmental scientists require threshold knowledge before using ML, restricting the ML application in MPs research. Furthermore, imbalanced development of ML in MPs research is a pressing concern. In order to achieve a wide ML application in MPs research, in this review, we comprehensively discussed the size and sources of MPs datasets in relevant literature to help environmental scientists deepen their understanding of the construction of MPs datasets. Commonly used ML algorithms are analyzed from the perspective of interpretability and the need for computer facilities. Additionally, methods for improving and evaluating ML model performance, such as dataset pre-processing, model optimization, and model assessment metrics, are discussed. According to datasets and characterization techniques, MPs identification using ML was divided into three categories in this work: spectral identification, image identification, and spectral imaging identification. Finally, other applications of ML in MPs studies, including toxicity analysis, pollutants adsorption, and microbial colonization, are comprehensively discussed, which reveals the great application potential of ML. Based on the discussion above, this review suggests an algorithm selection strategy to assist researchers in selecting the most suitable ML algorithm in different situations, improving efficiency and decreasing the costs of trial and error. We believe that this work sheds light on the application of ML in MPs study.

Predicting chemicals' toxicity pathway of female reproductive disorders using AOP7 and deep neural networks

Experimental evidence shows that certain chemicals, particularly endocrine disrupting chemicals, may negatively affect the female reproductive system, thereby lowering women's fertility. However, humans are constantly exposed to a number of different chemicals with limited or no experimental data regarding their effect and the mechanism of action in the female reproductive system. To predict chemical hazards to the female reproductive system, we used a previously defined adverse outcome pathway (AOP) that links activation of the peroxisome proliferator-activated receptor γ to the reproductive toxicity in adult females (AOP7) and the Convolutional Deep Neural Network models that produce meaningful predictions when trained on a significant amount of data. The models trained using CompTox assays with intended molecular and biological targets corresponding to AOP7 achieved high performance (over 90% validation accuracy). The integration of AOP7 and Deep Neural Network identified chemicals that could negatively affect female reproduction through the mechanism described in AOP7. We provide a solution to quickly analyze the data and produce machine learning models to identify potentially active chemicals in the female reproductive system. Although we focused on the female reproductive system, this approach could be valid for a number of other chemicals and AOPs if the right data exist.

A critical review of microplastics toxicity and potential adverse outcome pathway in human gastrointestinal tract following oral exposure

Microplastics (MPs) are typically produced via environmental degradation of larger plastics, where they enter the human food chain. MPs are complex materials containing chemical and physical characteristics that can potentially affect their hazard and exposure. These physical properties can be altered by environmental exposure potentially altering any risk assessment conducted on the primary material. We conducted a literature review using an Adverse Outcome Pathway (AOP)-based approach from Molecular Initiating Event (MIE) to cell effect event to identify multiple knowledge gaps that affect MPs hazard assessment. There is some convergence of key biological events but could relate to most lying along well-established biological effector pathways such as apoptosis which can respond to many MIEs. In contrast, MIEs of chemicals will be via protein interaction. As MPs may occur in the lumen of the alimentary canal for example to the mucus, therefore, not requiring translocation of MPs across the epithelial membrane. At the other end of the AOP, currently it is not possible to identify a single adverse outcome at the organ level. This work did establish a clear need to understand both external and internal exposure (resulting from translocation) and develop hazard data at both levels to inform on risk assessments.

Chronic poly(l-lactide) (PLA)- microplastic ingestion affects social behavior of juvenile European perch (Perca fluviatilis)

Juvenile perch were exposed to 2 % (w/w) poly(l-lactide) (PLA) microplastic particles (90-150 μm) in food pellets, or 2 % (w/w) kaolin particles, and a non-particle control food over 6 months. Chronic ingestion of PLA microplastics significantly affected the social behavior of juvenile perch, evident as a significantly increased reaction to the vision of conspecifics. PLA ingestion did not alter life cycle parameters, or gene expression levels. In addition to reactions to conspecifics, fish that ingested microplastic particles showed tendencies to decrease locomotion, internal schooling distance, and active predator responses. The ingestion of natural particles (kaolin) significantly downregulated the expression of genes related to oxidative stress and androgenesis in the liver of juvenile perch, and we found tendencies to downregulated expression of genes related to xenobiotic response, inflammatory response, and thyroid disruption. The present study demonstrated the importance of natural particle inclusion and the potential behavioral toxicity of one of the commercially available biobased and biodegradable polymers.

Exploring the potential of ToxCast™ data for mechanism-based prioritization of chemicals in regulatory context: Case study with priority existing chemicals (PECs) under K-REACH

Recent studies have highlighted the potential of ToxCast™ database to mechanism-based prioritization of chemicals. To explore the applicability of ToxCast data in the context of regulatory inventory chemicals, we screened 510 priority existing chemicals (PECs) regulated under the Act on the Registration and Evaluation of Chemical Substances (K-REACH) using ToxCast bioassays. In our analysis, a hit-call data matrix containing 298984 chemical-gene interactions was computed for 949 bioassays with the intended target genes, which enabled the identification of the putative toxicity mechanisms. Based on the reactivity to the chemicals, we analyzed 412 bioassays whose intended target gene families were cytochrome P450, oxidoreductase, transporter, nuclear receptor, steroid hormone, and DNA-binding. We also identified 141 chemicals based on their reactivity in the bioassays. These chemicals are mainly in consumer products including colorants, preservatives, air fresheners, and detergents. Our analysis revealed that in vitro bioactivities were involved in the relevant mechanisms inducing in vivo toxicity; however, this was not sufficient to predict more hazardous chemicals. Overall, the current results point to a potential and limitation in using ToxCast data for chemical prioritization in regulatory context in the absence of suitable in vivo data.

UV-induced microplastics (MPs) aging leads to comprehensive toxicity

Herein, the toxicity of 4 MPs and additives released from MPs during UV-aging was quantitatively evaluated by the transcriptional effect level index (TELI) based on E. coli whole-cell microarray assay, and MPs-antibiotics complex pollutants. Results showed that MPs and these additives had high toxicity potential, the maximum TELI was 5.68/6.85 for polystyrene (PS)/bis(2-ethylhexyl) phthalate (DEHP). There were many similar toxic pathways between MPs and additives, indicating that part of the toxicity risk of MPs was caused by the release of additives. MPs were compounded with antibiotics, the toxicity value changed significantly. The TELI values of amoxicillin (AMX) + polyvinyl chloride (PVC) and ciprofloxacin (CIP) + PVC were as high as 12.30 and 14.58 (P < 0.05). Three antibiotics all decreased the toxicity of PS and had little effect on polypropylene (PP) and polyethylene (PE). The combined toxicity mechanism of MPs and antibiotics was very complicated, and the results could be divided into four types: MPs (PVC/PE + CIP), antibiotics (PVC + TC, PS + AMX/ tetracycline (TC)/CIP, PE + TC), both (PP + AMX/TC/CIP), or brand-new mechanisms (PVC + AMX).

Insights into the removal of microplastics and microfibres by Advanced Oxidation Processes

Water treatment plants' effluents are hotspots of microplastics (MPs) and microfibres (MFs) released into the aquatic environment because they were not designed to capture these particles. Special attention should be given to MFs, since they mainly come from laundry and are related to one of the main MP shapes detected in water and wastewater treatment plants. In this sense, Advanced Oxidation Processes (AOPs) could be a feasible solution for tackling MP and MF pollution, however, it is still premature to extract conclusions due to the limited number of studies on the degradation of these particles (specifically MFs) using AOPs. This review addresses the impacts of AOPs on MPs/MFs, focusing on their degradation efficiency, toxicity, and sustainability of the processes, among other aspects. The review points out that polyamide MFs can achieve mass loss >90% by photocatalytic system using TiO₂. Also, the low oxidation of MPs (<30 %) by conventional Fenton process affects mainly the surface of the MPs. However, other Fenton-based processes can provide better removal of some types of MPs, mainly using temperatures >100 °C, reaction time ≥ 5 h, and initial pH ≤ 3, achieving MP weight loss up to 96 %. Despite these results, better operating conditions are still required for AOPs since the ones reported so far are not feasible for full-scale application. Additionally, ozonation in treatment plants has increased the fragmentation of MPs (including MFs), leading to a new generation of MPs. More attention is needed on toxicity effects of intermediates and methods of analysis employed for the analysis of MPs/MFs in wastewater effluent should be standardized so that studies can be compared effectively. Future research should focus on the sustainability of the AOP for MP removal in water treatment (power consumption, chemicals consumed and operational costs) for a better understanding of full-scale applicability of AOP adapted to MP treatment.

Using Machine Learning to make nanomaterials sustainable

Sustainable development is a key challenge for contemporary human societies; failure to achieve sustainability could threaten human survival. In this review article, we illustrate how Machine Learning (ML) could support more sustainable development, covering the basics of data gathering through each step of the Environmental Risk Assessment (ERA). The literature provides several examples showing how ML can be employed in most steps of a typical ERA.A key observation is that there are currently no clear guidance for using such autonomous technologies in ERAs or which standards/checks are required. Steering thus seems to be the most important task for supporting the use of ML in the ERA of nano- and smart-materials. Resources should be devoted to developing a strategy for implementing ML in ERA with a strong emphasis on data foundations, methodologies, and the related sensitivities/uncertainties. We should recognise historical errors and biases (e.g., in data) to avoid embedding them during ML programming.

A Comparative Systematic Analysis of The Influence of Microplastics on Colon Cells, Mouse and Colon Organoids

BACKGROUND

Microplastics (MPs) are small fragments from any type of plastic formed from various sources, including plastic waste and microfibers from clothing. MPs degrades slowly, resulting in a high probability of human inhalation, ingestion and accumulation in bodies and tissues. As its impact on humans is a prolonged event, the evaluation of its toxicity and influence on human health are critical. In particular, MPs can enter the human digestive system through food and beverage consumption, and its effect on the human colon needs to be carefully examined.

METHODS

We monitored the influence of small MPs (50 and 100 nm) on human colon cells, human colon organoids and also examined their toxicity and changes in gene expression in vivo in a mouse model.

RESULTS

The data suggested that 5 mg/mL concentrations of 50 and 100 nm MPs induced a > 20% decrease in colon organoid viability and an increase in the expression of inflammatory-, apoptosis- and immunity-related genes. In addition, in vivo data suggested that 50 nm MPs accumulate in various mouse organs, including the colon, liver, pancreas and testicles after 7 d of exposure.

CONCLUSION

Taken together, our data suggest that smaller MPs can induce more toxic effects in the human colon and that human colon organoids have the potential to be used as a predictive tool for colon toxicity.

A Rapid Screening Method for the Detection of Additives in Electronics and Plastic Consumer Products Using AP-MALDI-qTOF-MS

A novel method was developed and optimized for the fast-screening analysis of additives in electronics and plastic consumer products using atmospheric pressure matrix-assisted laser desorption ionization (AP-MALDI) coupled with a high-resolution quadrupole time-of-flight (qTOF) mass spectrometer (MS). To simplify sample preparation and increase sample throughput, an innovative 48 well graphene nanoplatelets (GNP) doped AP-MALDI target plate was developed. The GNP incorporated in the target plate fulfilled the role of the MALDI matrix and, therefore, sample extracts could be directly transferred to the AP-MALDI 48 well target plate and analyzed without a subsequent matrix addition. The homogeneously dispersed and immobilized GNP target plates also provided increased signal intensity and reproducibility. Furthermore, analytical standards of various plastic additives and plastic products with known concentrations of additives were studied to assess the AP-MALDI ionization mechanisms and method capability. The analysis time was 15 s per measurement using an automated sequence. The GNP-doped target plates exhibited high desorption/ionization of low molecular weight molecules (<1000 Da) and can be used in both positive and negative ionization modes. The AP-MALDI-qTOF-MS method was applied to screen for additives in various electronics and plastic consumer products. Suspect screening was performed using a database containing 1366 compounds. A total of 56 additives including antioxidants, flame retardants, plasticizers, UV-stabilizers, and UV-filters were identified (confidence level 4). Identification of certain plastic additives in plastic children's toys may indicate that they are recycled from waste electronic and electronic equipment (WEEE).

Identification of neurotoxic compounds in cyanobacteria exudate mixtures

Release of toxic cyanobacterial secondary metabolites threatens biosecurity, foodwebs and public health. Microcystis aeruginosa (Ma), the dominant species in global freshwater cyanobacterial blooms, produces exudates (MaE) that cause adverse outcomes including nerve damage. Previously, we identified > 300 chemicals in MaE. It is critical to investigate neurotoxicity mechanisms of active substances among this suite of Ma compounds. Here, we screened 103 neurotoxicity assays from the ToxCast database to reveal targets of action of MaE using machine learning. We then built a potential Adverse Outcome Pathway (AOP) to identify neurotoxicity mechanisms of MaE as well as key targets. Finally, we selected potential neurotoxins matched with those targets using molecular docking. We found 38 targets that were inhibited and eight targets that were activated, collectively mainly related to neurotransmission (i.e. cholinergic, dopaminergic and serotonergic neurotransmitter systems). The potential AOP of MaE neurotoxicity could be caused by blocking calcium voltage-gated channel (CACNA1A), because of antagonizing neurotransmitter receptors, or because of inhibiting solute carrier transporters. We identified nine neurotoxic MaE compounds with high affinity to those targets, including LysoPC(16:0), 2-acetyl-1-alkyl-sn-glycero-3-phosphocholine, egonol glucoside, polyoxyethylene (600) monoricinoleate, and phytosphingosine. Our study enhances understanding of neurotoxicity mechanisms and identifies neurotoxins in cyanobacterial bloom exudates, which may help identify priority compounds for cyanobacteria management.

A Critical Review on Artificial Intelligence-Based Microplastics Imaging Technology: Recent Advances, Hot-Spots and Challenges

Due to the rapid artificial intelligence technology progress and innovation in various fields, this research aims to use science mapping tools to comprehensively and objectively analyze recent advances, hot-spots, and challenges in artificial intelligence-based microplastic-imaging field from the Web of Science (2019-2022). By text mining and visualization in the scientific literature we emphasized some opportunities to bring forward further explication and analysis by (i) exploring efficient and low-cost automatic quantification methods in the appearance properties of microplastics, such as shape, size, volume, and topology, (ii) investigating microplastics water-soluble synthetic polymers and interaction with other soil and water ecology environments via artificial intelligence technologies, (iii) advancing efficient artificial intelligence algorithms and models, even including intelligent robot technology, (iv) seeking to create and share robust data sets, such as spectral libraries and toxicity database and co-operation mechanism, (v) optimizing the existing deep learning models based on the readily available data set to balance the related algorithm performance and interpretability, (vi) facilitating Unmanned Aerial Vehicle technology coupled with artificial intelligence technologies and data sets in the mass quantities of microplastics. Our major findings were that the research of artificial intelligence methods to revolutionize environmental science was progressing toward multiple cross-cutting areas, dramatically increasing aspects of the ecology of plastisphere, microplastics toxicity, rapid identification, and volume assessment of microplastics. The above findings can not only determine the characteristics and track of scientific development, but also help to find suitable research opportunities to carry out more in-depth research with many problems remaining.

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data

The development of toxicity classification models using the ToxCast database has been extensively studied. Machine learning approaches are effective in identifying the bioactivity of untested chemicals. However, ToxCast assays differ in the amount of data and degree of class imbalance (CI). Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. In this study, the effects of CI and data scarcity (DS) on the performance of binary classification models were investigated using ToxCast bioassay data. An assay matrix based on CI and DS was prepared for 335 assays with biologically intended target information, and 28 CI assays and 3 DS assays were selected. Thirty models established by combining five molecular fingerprints (i.e., Morgan, MACCS, RDKit, Pattern, and Layered) and six algorithms [i.e., gradient boosting tree, random forest (RF), multi-layered perceptron, k-nearest neighbor, logistic regression, and naive Bayes] were trained using the selected assay data set. Of the 30 trained models, MACCS-RF showed the best performance and thus was selected for analyses of the effects of CI and DS. Results showed that recall and F1 were significantly lower when training with the CI assays than with the DS assays. In addition, hyperparameter tuning of the RF algorithm significantly improved F1 on CI assays. This study provided a basis for developing a toxicity classification model with improved performance by evaluating the effects of data set characteristics. This study also emphasized the importance of using appropriate evaluation metrics and tuning hyperparameters in model development.

Tyre particle exposure affects the health of two key estuarine invertebrates

Tyre wear particles may be the largest source of microplastic to the natural environment, yet information on their biological impacts is inadequate. Two key estuarine invertebrates; the clam Scrobicularia plana and the ragworm Hediste diversicolor were exposed to 10% tyre particles in sediment for three days. Both species consumed the particles, although S. plana consumed 25x more than H. diversicolor (967 compared with 35 particles.g^-1 wet weight, respectively). We then investigated the impact of 21 days exposure to different concentrations of tyre particles in estuarine sediments (0.2, 1, and 5% dry weight sediment) on aspects of the health of S. plana and H. diversicolor. Reductions in feeding and burial rates were observed for S. plana but not H. diversicolor, whilst both species showed a decrease in protein content in response to the greatest tyre particle concentration (5%), linked to an 18% decrease in energy reserves for H. diversicolor. Five percent tyre particle exposure led to an increase in total glutathione in the tissues of H. diversicolor, whilst lipid peroxidation decreased in the digestive glands of S. plana, possibly due to an increase in cell turnover. This study found that S. plana's health was impacted at lower concentrations than H. diversicolor, likely due to its consumption of large quantities of sediment. At the high exposure concentration (5%), the health of both invertebrates was impacted. This study did not separate the effects caused by the microplastic particles versus the effects of the chemical additives leaching from these particles, but our results do indicate that future studies should investigate effects in isolation and in combination, to determine the main drivers of toxicity.

Characterization of microparticles derived from waste plastics and their bio-interaction with human lung A549 cells

Microplastics (MPs) represent a worldwide emerging relevant concern toward human and environmental health due to their intentional or unintentional release. Human exposure to MPs by inhalation is predicted to be among the most hazardous. MPs include both engineered, or primary MPs, and secondary MPs, materials obtained by fragmentation from any plastic good. The major part of the environmental MPs is constituted by the second ones that are irregular in size, shape and composition. These features make the study of the biological impact of heterogenous MPs of extremely high relevance to better estimate the real toxicological hazards of these materials on human and environmental organisms. The smallest fractions of plastic granules, relying on the micron-sized scale, can be considered as the most abundant component of the environmental MPs, and for this reason, they are typically used to perform toxicity tests using in vitro systems representative of an inhalation exposure scenario. In the present work, MPs obtained from industrial treatment of waste plastics (wMPs < 50 μm) were investigated, and after the physico-chemical characterization, the cytotoxic, inflammatory and genotoxic responses, as well as the modality of wMPs interactions with alveolar lung cells, were determined. Obtained results indicated that, at high concentrations (100 μg/ml) and prolonged exposure time (48 h), wMPs affect biological responses by inducing inflammation and genotoxicity, as a result of the cell-wMP interactions, also including the uptake of the smaller particles.

Application of ToxCast/Tox21 data for toxicity mechanism-based evaluation and prioritization of environmental chemicals: Perspective and limitations

In response to the need to minimize the use of experimental animals, new approach methodologies (NAMs) using advanced technology have emerged in the 21st century. ToxCast/Tox21 aims to evaluate the adverse effects of chemicals quickly and efficiently using a high-throughput screening and to transform the paradigm of toxicity assessment into mechanism-based toxicity prediction. The ToxCast/Tox21 database, which contains extensive data from over 1400 assays with numerous biological targets and activity data for over 9000 chemicals, can be used for various purposes in the field of chemical prioritization and toxicity prediction. In this study, an overview of the database was explored to aid mechanism-based chemical prioritization and toxicity prediction. Implications for the utilization of the ToxCast/Tox21 database in chemical prioritization and toxicity prediction were derived. The research trends in ToxCast/Tox21 assay data were reviewed in the context of toxicity mechanism identification, chemical priority, environmental monitoring, assay development, and toxicity prediction. Finally, the potential applications and limitations of using ToxCast/Tox21 assay data in chemical risk assessment were discussed. The analysis of the toxicity mechanism-based assays of ToxCast/Tox21 will help in chemical prioritization and regulatory applications without the use of laboratory animals.

Cytotoxicity of nanomixture: Combined action of silver and plastic nanoparticles on immortalized human lymphocytes

BACKGROUND

Silver nanoparticles (AgNP) are one of the most commercialized types of nanomaterials, with a wide range of applications owing to their antimicrobial activity. They are particularly important in hospitals and other healthcare settings, where they are used to maintain sterility of surfaces, textiles, catheters, medical implants, and more. However, AgNP can not only harm bacteria, but also damage mammalian cells and tissue. While the potential toxicity of AgNP is an understood risk, there is a lack of data on their toxicity in combination with polymeric materials, especially plastic nanoparticles such as polystyrene nanoparticles (PSNP) that can be released from surfaces of polystyrene devices during their medical use.

AIM

This study aimed to investigate combined effect of AgNP and nanoplastics on human immune response.

METHODS

Cells were treated with a range of PSNP and AgNP concentrations, either applied alone or in combination. Cytotoxicity, induction of apoptosis, generation of oxidative stress, uptake efficiency, intracellular localization and nanomechanical cell properties were selected as exposure biomarkers.

RESULTS

Collected experimental data showed that nanomixture induced oxidative stress, apoptosis and mortality of Jurkat cells stronger than its individual components. Cell treatment with AgNP/PSNP mixture also significantly changed cell mechanical properties, evidenced by reduction of cells' Young Modulus.

CONCLUSION

AgNP and PSNP showed additive toxic effects on immortalized human lymphocytes, evidenced by increase in cellular oxidative stress, induction of apoptosis, and reduction of cell stiffness. These results have important implications for using AgNP and PSNP in medical contexts, particularly for long-term medical implants.

Artificial Intelligence-Based Toxicity Prediction of Environmental Chemicals: Future Directions for Chemical Management Applications

Recently, research on the development of artificial intelligence (AI)-based computational toxicology models that predict toxicity without the use of animal testing has emerged because of the rapid development of computer technology. Various computational toxicology techniques that predict toxicity based on the structure of chemical substances are gaining attention, including the quantitative structure-activity relationship. To understand the recent development of these models, we analyzed the databases, molecular descriptors, fingerprints, and algorithms considered in recent studies. Based on a selection of 96 papers published since 2014, we found that AI models have been developed to predict approximately 30 different toxicity end points using more than 20 toxicity databases. For model development, molecular access system and extended-connectivity fingerprints are the most commonly used molecular descriptors. The most used algorithm among the machine learning techniques is the random forest, while the most used algorithm among the deep learning techniques is a deep neural network. The use of AI technology in the development of toxicity prediction models is a new concept that will aid in achieving a scientific accord and meet regulatory applications. The comprehensive overview provided in this study will provide a useful guide for the further development and application of toxicity prediction models.

The polymers and their additives in particulate plastics: What makes them hazardous to the fauna?

Due to the increasing concerns on global ecosystems and human health, the environmental risks posed by microplastics (MPs) and nanoplastics (NPs) have become an important topic of research. Their ecological impacts on various faunal species have been extensively researched and reviewed. However, the majority of those studies perceive these micro(nano)-plastics (MNPs) as a single entity rather than a collective term for a group of chemically distinct polymeric particulates. Each of the plastic polymers can possess unique physical and chemical behavior, which, in turn, can determine the possible environmental impacts. Furthermore, many studies explore the adsorption, absorption, and release of other environmental pollutants by MNPs. But only a handful of them explore the leaching of additives possessed by these polymers. Data on the environmental behavior and toxicity of individual additives associated with different polymer particulates are scarce. Knowledge about the leachability and ecotoxicity of the additives associated with environmental MNPs (unlike large plastic particles) remains limited. The ecological impacts of different MNPs together with their additives and the basis of their toxicity have not been explored yet. The present review systematically explores the potential implications of environmentally predominant polymers and their associated additives and discusses their physicochemical characteristics. The review ultimately aims to provide novel insights on what components precisely make MNPs hazardous to the fauna. The paper also discusses the major challenges proposed in the available literature along with recommendations for future research to throw light on possible solutions to overcome the hazards of MNPs.

Polymer prioritization framework: A novel multi-criteria framework for source mapping and characterizing the environmental risk of plastic polymers

Plastics are an intrinsic part of modern life with many beneficial uses for society. Yet, there is increasing evidence that plastic and microplastic pollution poses a risk to the environment and human health. Microplastics are increasingly grouped as a complex mix of polymers with different physicochemical and toxicological properties. This study attempts to assess the hazardous properties of common polymer types through the development of an integrated multi-criteria framework. The framework establishes a systematic approach to identify plastic polymers of concern. A semi-quantitative method was devised using twenty-one criteria. We used a case study from Victoria, Australia, to evaluate the effectiveness of the framework to characterize the environmental risk of common polymer types. A wide range of data sources were interrogated to complete an in-depth analysis across the material life cycle. We found that three polymers had the highest risk of harm: polyvinyl chloride, polypropylene, and polystyrene; with dominant sectors being: building and construction, packaging, consumer and household, and automotive sectors; and greatest leakage of plastics at the end-of-life stages. Our findings illustrate the complexity of microplastics as an emerging contaminant, and its scalability supports decision-makers globally to identify and prioritize management strategies to address the risks posed by plastics. ENVIRONMENTAL IMPLICATION: The hazardous nature of mismanaged plastics is an international concern. The negative impacts on the environment and human health are increasingly coming to light. Consequently, resource constraints limits the ability to address all problems. Our work adopts a holistic approach to evaluate the risk of harm from microplastics across the entire life cycle to allow for targeted management measures. The hazard assessment of common polymer types developed using a multi-criteria framework, presents a systematic approach to prioritize polymers at any scale. This allows for the development of optimal investments and interventions to ensure that high-risk environmental problems are addressed first.

Identification of emerging organic pollutants from solid waste incinerations by FT-ICR-MS and GC/Q-TOF-MS and their potential toxicities

Emissions from the incineration of solid waste are a global public health concern, but little attention has been paid to previously unrecognized chemical compounds that are generated by waste incineration and released into the atmosphere. We conducted nontarget analysis of organic chemicals formed during waste incineration by Fourier-transform ion cyclotron resonance mass spectrometry and gas chromatography-quadrupole time-of-flight mass spectrometry. Using toxicity data in the ToxCast library and predicted toxicity data for traditional priority polycyclic aromatic hydrocarbons and 2,3,7,8-tetrachlorodibenzo-p-dioxin, we prioritized 13 compounds including hexachloro-1,3-butadiene, 9 of which are reported here for the first time as constituents of emissions from the incineration of solid waste and hexachloro-1,3-butadiene was included in the Stockholm Convention in 2017. The predicted activity of these pollutants to androgen receptors and to the aryl hydrocarbon receptor were comparable to, or higher than, the 2,3,7,8-tetrachlorodibenzo-p-dioxin and benzo[a]pyrene. In addition, some alkylated polycyclic aromatic hydrocarbons and heteroatom polycyclic aromatic hydrocarbons were also identified in solid waste incineration processes, peak areas of which were 1-2 orders of magnitude higher than dioxins and 1-3 orders of magnitude lower than their parent polycyclic aromatic hydrocarbons. Our study can provide information for better recognizing and regulating the emissions of organic pollutants formed by the incineration of solid waste.

Aggregate exposure pathways for microplastics (mpAEP): An evidence-based framework to identify research and regulatory needs

Microplastics as emerging contaminants have been detected from peaks to poles. High concerns on the risks of microplastic pollution to humans and ecosystems have therefore been raised in the past decade. While a large number of studies have been conducted to investigate the environmental levels and toxicity of microplastics, the information generated to support risk assessment is fragmented and the coherence between different types of study is largely lacking. Here we introduced the Aggregate Exposure Pathway (AEP), a conceptual framework originally proposed for chemical exposure assessment, to facilitate organization, visualization and evaluation of existing information generated from microplastic research, and to efficiently identify future knowledge and regulatory needs. A putative microplastic AEP network (mpAEP) was developed to demonstrate the concept and model development strategies. Two mpAEP case studies, with polyethylene (PE) as a prototype, were then presented based on existing environmental exposure data collected from the Changjiang Estuary and the East China Sea (Case I), and the Oslo Fjord (Case II), respectively. Weight of evidence (WoE) assessment of the mpAEPs were performed for evaluating the essentiality, theoretical plausibility, empirical evidence and quantitative understanding of the evidence and relationships in the AEPs. Both cases showed moderate/high WoE to support the strength of the models, whereas also displayed clear knowledge gaps, thus providing guidance for future investigations and regulations. The mpAEP framework introduced herein presents a novel strategy for organizing fragmented information from diverse types of microplastic research, enhancing mechanistic understanding of causal relationships and facilitating the development of quantitative prediction models for research and regulation in the future.

Micro/nano-plastics occurrence, identification, risk analysis and mitigation: challenges and perspectives

Micro/nanoplastics (MP/NPs) are emerging global pollutants that garnered enormous attention due to their potential threat to the ecosystem in virtue of their persistence and accumulation. Notably, United Nations Environment Programme (UNEP) yearbook in 2014 proposed MPs as one among ten emergent issues that the Earth is facing today. MP/NPs can be found in most regularly used products (primary microplastics) or formed by the fragmentation of bigger plastics (secondary microplastics) and are inextricably discharged into the environment by terrestrial and land-based sources, particularly runoff. They are non-degradable, biologically incompatible, and their presence in the air, soil, water, and food can induce ecotoxicological issues and also a menace to the environment. Due to micro size and diverse chemical nature, MP/NPs easily infiltrate wastewater treatment processes. This communication reviews the current understanding of MP/NPs occurrence, mobility, aggregation behavior, and degradation/assimilation in terrestrial, aquatic (fresh & marine), atmospheric depositions, wetlands and trophic food chain. This communication provide current perspectives and understanding on MP/NPs concerning (1) Source, occurrence, distribution, and properties (2) Impact on the ecosystem and its services, (3) Techniques in detection and identification and (4) Strategies to manage and mitigation.

Tiered testing of micro- and nanoplastics using intestinal in vitro models to support hazard assessments

The uncertainty of potential risks associated with micro- and nanoplastics (MNPs) are of growing public concern. However, the diversity of MNPs in the environment makes a systematic analysis of potential health effects challenging. New tools and approaches are necessary to investigate biological effects of MNPs. With this quick scoping review, we aim to analyse the suitability of in vitro models for assessing the interaction of MNPs with intestinal cells. Our analysis revealed that currently the majority of in vitro tests are based on the three cell lines Caco-2, HT-29, and HCT-116. They have particularly been used to assess endpoints related to basal cytotoxicity, the internalisation of MNPs and effects on the intestinal barrier. When co-cultured with various cell lines, they also allow to investigate additional effects such as inflammation, metabolic actions and the relevance of the intestinal mucus. However, methodological gaps remain regarding the assessment of a potential accumulation of MNPs, leaching of additives/impurities and in resulting long-term effects as well as cell-type specific toxicities. In addition, only few in vitro studies investigated effects of MNPs on the microbiome. Stem cell-based assays using, for example, the emerging organoid technology are promising for analysing MNP effects on tissue-like structures, while avoiding the particular characteristics of the currently used cancer derived cell lines. The various cell lines and culture techniques can be combined in testing strategies, to better elucidate potential biological interaction of MNPs with biological systems. We suggest to implement a tiered testing strategy, in which monocultures can serve as a tool for high-throughput testing of MNPs. In the next steps co-cultures can be used to assess the potential of a systemic uptake of MNPs and organ-on-a-chip models will provide more reliable insights into relevant doses triggering biological effects. Finally, organoids can help to discover new and more complex reactions initiated by MNPs.

Screening and prioritization of nano- and microplastic particle toxicity studies for evaluating human health risks - development and application of a toxicity study assessment tool

Concern regarding the human health implications that exposure to nano- and microplastic particles (NMPs) potentially represents is increasing. While there have been several years of research reporting on the ecotoxicological effects of NMPs, human health toxicology studies have only recently emerged. The available human health hazard data are thus limited, with potential concern regarding the relevance and reliability for understanding the potential human health implications. In this study we develop and apply a NMP toxicity screening assessment tool (NMP-TSAT) for evaluating human health effects studies against a suite of quality assurance and quality control (QA/QC) criteria for both in vivo and in vitro studies. A total of 74 studies representing either inhalation or oral exposure pathways were identified and evaluated. Assessment categories include particle characterization, experimental design, and applicability for risk assessment; with critical and non-critical criteria organized to allow screening and prioritization. It is observed that the majority of studies evaluated using the NMP-TSAT have been performed on monodisperse particles, predominately spheres (≈60%), consisting of polystyrene (≈46%). The majority of studies have tested particles < 5 μm, with a minimal particle size of 10 nm and a maximum particle size of about 200 μm. The total assessment score (TAS) possible for in vivo studies is 52, whereas for in vitro studies it is 46, which is based on receiving a maximum score of 2 against 26 and 23 criteria, respectively. The evaluated TAS ranged from between 12 and 44 and 16-34, for in vivo and in vitro studies, respectively. Given the challenges associated with prioritizing studies based on ranking them according to their TAS we propose a Tiered approach, whereby studies are initially screened based on how they score against various critical criteria, which have been defined for their relevance for assessing the hazards and risks for human health. In this instance, studies that score a minimum of '1' against each of the critical criteria, regardless of how they rank according to their TAS, are prioritized as part of a Tier 1 screening and prioritization phase, which would then be followed by an expert evaluation, representing a Tier 2 level of assessment. Using this approach we identify 10 oral ingestion and 2 inhalation studies that score at least 1 against all critical criteria. Lastly, several key observations for strengthening future effects studies are identified, these include a need for the generation and access to standard reference materials representative of human exposure to NMPs for use in toxicity test systems and/or the improved characterization and verification of test particle characteristics, and the adoption of study design guidance, such as recommended by OECD, when conducting either in vivo inhalation or oral ingestion toxicity tests.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s43591-021-00023-x.

A review on microplastic pollution in the mangrove wetlands and microbial strategies for its remediation

Mangroves are one of the most productive ecosystems in the world harboring huge biological diversity. The prime ecological roles of mangroves are prevention of coastal erosion and shoreline protection. Mangroves face varying degrees of threats due to overexploitation, conversion of mangrove habitats for agriculture, settlement and industrial purposes, illegal encroachment, global warming, sea-level rise, El Nino, and pollution. Among them, microplastic (MP) pollution is a major concern threatening not only the mangroves per se but also the rich biodiversity that it shelters. In general, the microbial communities which are paramount to nutrient recycling and ecological dynamics undergo substantial changes upon MP exposure. If the MP pollution in the mangrove habitats continues unabated in the coming decades, there may be serious consequences on the already threatened mangrove ecosystems and the coastal communities. This review article attempts to consolidate MP pollution of mangrove wetlands, its impact on mangroves and associated microbiota, and the microbial solution for its remediation as a sustainable strategy.

Acute and subacute repeated oral toxicity study of fragmented microplastics in Sprague-Dawley rats

Polypropylene (PP) is the second most highly produced plastic worldwide, and its microplastic forms are found in water and food matrices. However, the effects of PP microplastics on human health remain largely unknown. Here, we prepared 85.2 µm-sized weathered PP (w-PP) microplastics by sieving the microplastic particles after fragmentation and accelerated weathering processes. The prepared particles are irregular in shape and no chemical additives including phthalates and bisphenol A were not released in simulated body fluids. Then, the w-PP samples were gavaged to rats for acute and subacute toxicity testing in accordance to the Organization for Economic Co-operation and Development (OECD) test guidelines under good laboratory practice regulations. The highest dose for gavaging to rats was 25 mg/kg bw/day, which was the maximum feasible dose based on the dispersibility of microplastics. Both toxicity testings for w-PP microplastics showed no adverse effects and mutagenicity. Thus, the no observed adverse effect level (NOAEL) of w-PP microplastics is higher than 25 mg/kg bw/day. Furthermore, the w-PP microplastics did not show any skin or eye irritation potentials in the 3-dimensional reconstructed human skin or corneal culture model. The dose of 25 mg/kg of w-PP microplastics is roughly equal to 2.82 × 105 particles/kg, which suggests that human exposure to w-PP microplastics in a real-life situation may not have any adverse effects.

Microplastics intake and excretion: Resilience of the intestinal microbiota but residual growth inhibition in common carp

Aquatic animals can be influenced by exposure to microplastics (MPs), but little is known about their recovery capacity following MPs excretion. Here, common carp were exposed to environmentally relevant concentrations of MPs for 30 days and followed by MPs excretion for another 30 days. Growth, isotopic and elemental compositions and intestinal microbiota were investigated. We found that fish growth was not influenced by exposed to MPs but was significantly reduced following MPs excretion, indicating a delayed effect on growth. MPs intake and excretion, however, had no obvious effects on isotopic and elemental compositions. MPs altered the community structure and composition of intestinal microbiota and might reduce functional diversity. After MPs excretion, interestingly, bacterial community structures of MPs treatments were grouped together with the control, suggesting the general resilience of fish intestinal microbiota. Nevertheless, high abundance of pathogenic Shewanella, Plesiomonas and Flavobacterium was observed in MPs treatments but did not affect the functional potential of intestinal microbiota. The results of this study provide new information for the application of adverse outcome pathway (AOP) in MPs, suggesting the necessity of paying attention to recovery assay following MPs intake in the development of AOP frameworks.

The Potential for PE Microplastics to Affect the Removal of Carbamazepine Medical Pollutants from Aqueous Environments by Multiwalled Carbon Nanotubes

Microplastics are ubiquitous in aquatic environments and interact with other kinds of pollutants, which affects the migration, transformation, and fate of those other pollutants. In this study, we employ carbamazepine (CBZ) as the contaminant to study the influence of polyethylene (PE) microplastics on the adsorption of CBZ pollutants by multiwalled carbon nanotubes (MCNTs) in aqueous solution. The adsorption capacity of CBZ by MCNTs in the presence of PE microplastics was obviously lower than that by MCNTs alone. The influencing factors, including the dose of microplastics, pH, and CBZ solution concentration, on the adsorption of CBZ by MCNTs and MCNTs-PE were thoroughly investigated. The adsorption rate of CBZ by MCNTs decreased from 97.4% to 90.6% as the PE microplastics dose increased from 2 g/L to 20 g/L. This decrease occurred because the MCNTs were coated on the surface of the PE microplastics, which further decreased the effective adsorption area of the MCNTs. This research provides a framework for revealing the effect of microplastics on the adsorption of pollutants by carbon materials in aqueous environments.

How mangrove plants affect microplastic distribution in sediments of coastal wetlands: Case study in Shenzhen Bay, South China

Microplastic pollution is common in marine and coastal ecosystems, especially in mangrove wetlands. However, factors affecting the distribution of microplastics, such as plants, have not been sufficiently studied. We investigated the effect of different plant species on the distribution of sediment microplastics in two Nature Reserves in South China, viz. Futian Mangrove and Mai Po Mangrove. In Futian Mangrove, the abundance of total microplastics among three monospecific mangrove stands dominated by Sonneratia caseolaris, Kandelia obovata, and Sonneratia apetala was similar. The abundance of microplastics in the mudflat was similar to that in the forest interior, except for the fact that more fiber was found in the mudflat than in the interior of Sonneratia apetala. This suggested that the dense pneumatophores at the fringe prevented fibers from entering the mangrove forest. The significant positive dependence (p < 0.05) between the density of Sonneratia pneumatophores and the abundance of fibers highlighted the importance of pneumatophores. The abundance of total microplastics, predominantly in the form of fibers, in sediments at the forest fringe (2835 ± 713 items/kg d.w. and 2070 ± 224 items/kg d.w. in Futian and Mai Po, respectively) was higher than that in the forest interior and mudflat. There was no difference between the two latter locations in both mangroves, which demonstrated the significance of the fringe effect. This paper reports for the first time that the spatial distribution of microplastics in mangrove sediments was affected by plant species, which provides useful information for environmental processes of microplastics in coastal wetlands.

Plastic additives: challenges in ecotox hazard assessment

The risk of plastic debris, and specifically micro(nano)plastic particles, to ecosystems remains to be fully characterized. One particular issue that warrants further characterization is the hazards associated with chemical additives within micro(nano)plastic as they are not chemically bound within the polymers and can be persistent and biologically active. Most plastics contain additives and are therefore potential vectors for the introduction of these chemicals into the environment as they leach from plastic, a process that can be accelerated through degradation and weathering processes. There are knowledge gaps on the ecotoxicological effects of plastic additives and how they are released from parent plastic materials as they progressively fragment from the meso to micro and nano scale. This review summarizes the current state of knowledge of the ecotoxicity of plastic additives and identifies research needs to characterize the hazard they present to exposed biota. The potential ecological risk of chemical additives is of international concern so key differences in governance between the European Union and New Zealand to appropriately characterize their risk are highlighted.

Performance of preclinical models in predicting drug-induced liver injury in humans: a systematic review

Drug-induced liver injury (DILI) causes one in three market withdrawals due to adverse drug reactions, causing preventable human suffering and massive financial loss. We applied evidence-based methods to investigate the role of preclinical studies in predicting human DILI using two anti-diabetic drugs from the same class, but with different toxicological profiles: troglitazone (withdrawn from US market due to DILI) and rosiglitazone (remains on US market). Evidence Stream 1: A systematic literature review of in vivo studies on rosiglitazone or troglitazone was conducted (PROSPERO registration CRD42018112353). Evidence Stream 2: in vitro data on troglitazone and rosiglitazone were retrieved from the US EPA ToxCast database. Evidence Stream 3: troglitazone- and rosiglitazone-related DILI cases were retrieved from WHO Vigibase. All three evidence stream analyses were conducted according to evidence-based methodologies and performed according to pre-registered protocols. Evidence Stream 1: 9288 references were identified, with 42 studies included in analysis. No reported biomarker for either drug indicated a strong hazard signal in either preclinical animal or human studies. All included studies had substantial limitations, resulting in "low" or "very low" certainty in findings. Evidence Stream 2: Troglitazone was active in twice as many in vitro assays (129) as rosiglitazone (60), indicating a strong signal for more off-target effects. Evidence Stream 3: We observed a fivefold difference in both all adverse events and liver-related adverse events reported, and an eightfold difference in fatalities for troglitazone, compared to rosiglitazone. In summary, published animal and human trials failed to predict troglitazone's potential to cause severe liver injury in a wider patient population, while in vitro data showed marked differences in the two drugs' off-target activities, offering a new paradigm for reducing drug attrition in late development and in the market. This investigation concludes that death and disability due to adverse drug reactions may be prevented if mechanistic information is deployed at early stages of drug development by pharmaceutical companies and is considered by regulators as a part of regulatory submissions.

Aquatic toxicity of chemically defined microplastics can be explained by functional additives

A novel, systematic approach to relate plastic toxicity with chemical composition is undertaken. Using industrial methods, three petroleum-based polymers, low-density polyethylene (PE), polyvinyl chloride (PVC), and polyamide (PA), and the biopolymer polyhydroxybutyrate (PHB) were manufactured in different formularies including conventional and alternative additives, and microplastics of two sizes (<250 and <20 µm) were obtained with the aim to relate their composition with environmental impact in aquatic environments. Internationally accepted standard tests of regulatory use with marine organisms representative of microalgae (Tisochrysis lutea population growth), crustaceans (Acartia clausi larval survival), and echinoderms (Paracentrotus lividus sea-urchin embryo test) support the following conclusions. Aquatic toxicity of microplastics made from conventional oil-based polymers is due to leaching of chemical additives, and not to ingestion of microplastics. Use of alternative formulations based on natural rather than synthetic chemical additives did not consistently reduce aquatic toxicity except for the replacement of triclosan by the alternative biocide lawsone. In contrast, the biopolymer tested, PHB, seemed to impact marine plankton through different mechanisms associated to the higher abundance of plastic particles within the nanometric range found in this resin and absent in other materials.

The potential connections of adverse outcome pathways with the hazard identifications of typical organophosphate esters based on toxicity mechanisms

Following the world-wide ban of brominated flame retardants (BFRs), organophosphate esters (OPEs), which could potentially affect human health and ecosystem safety, have been frequently detected in various environmental media. However, the knowledge regarding the underlying toxicity effects of OPEs remains limited. In order to address these issues, this study reviewed the related reports which have been published in recent years. This analysis process included 12 OPEs, 10 model organisms, and 15 cell lines, which were used to systematically examine the mechanisms of endocrine disruption, neurotoxicity, hepatotoxicity, and cardiotoxicity, as well as reproductive and developmental toxicity. Subsequently, an adverse outcome pathway (AOP) framework of the toxicological effects of OPEs was built. The results demonstrated that multiple different pathways may lead to a single same adverse outcome (AO), and there was a certain degree of correlation among the different AOs. It was found that among all the 12 OPEs, tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) may potentially be the most toxic. In addition, rather than the parent chemicals, the metabolites of OPEs may also have different degrees of toxicity effects on aquatic organisms and humans. Overall, the results of the present study also suggested that an AOP framework should be built via fully utilizing the existing toxicity data of OPEs based on in vivo-in vitro-in silico to completely and deeply understand the toxic mechanisms of OPEs. This improved knowledge could then provide a theoretical basis for ecological risk assessments and water quality criteria research in the near future.

Bringing together scientific disciplines for collaborative undertakings: a vision for advancing the adverse outcome pathway framework

BACKGROUND

Decades of research to understand the impacts of various types of environmental occupational and medical stressors on human health have produced a vast amount of data across many scientific disciplines. Organizing these data in a meaningful way to support risk assessment has been a significant challenge. To address this and other challenges in modernizing chemical health risk assessment, the Organisation for Economic Cooperation and Development (OECD) formalized the adverse outcome pathway (AOP) framework, an approach to consolidate knowledge into measurable key events (KEs) at various levels of biological organisation causally linked to disease based on the weight of scientific evidence (http://oe.cd/aops). Currently, AOPs have been considered predominantly in chemical safety but are relevant to radiation. In this context, the Nuclear Energy Agency's (NEA's) High-Level Group on Low Dose Research (HLG-LDR) is working to improve research co-ordination, including radiological research with chemical research, identify synergies between the fields and to avoid duplication of efforts and resource investments. To this end, a virtual workshop was held on 7 and 8 October 2020 with experts from the OECD AOP Programme together with the radiation and chemical research/regulation communities. The workshop was a coordinated effort of Health Canada, the Electric Power Research Institute (EPRI), and the Nuclear Energy Agency (NEA). The AOP approach was discussed including key issues to fully embrace its value and catalyze implementation in areas of radiation risk assessment.

CONCLUSIONS

A joint chemical and radiological expert group was proposed as a means to encourage cooperation between risk assessors and an initial vision was discussed on a path forward. A global survey was suggested as a way to identify priority health outcomes of regulatory interest for AOP development. Multidisciplinary teams are needed to address the challenge of producing the appropriate data for risk assessments. Data management and machine learning tools were highlighted as a way to progress from weight of evidence to computational causal inference.

A toxicity pathway-oriented approach to develop adverse outcome pathway: AHR activation as a case study

With numerous new chemicals introduced into the environment everyday, identification of their potential hazards to the environment and human health is a considerable challenge. Developing adverse outcome pathway (AOP) framework is promising in helping to achieve this goal as it can bring In Vitro testing into toxicity measurement and understanding. To explore the toxic mechanism underlying environmental chemicals via the AOP approach, an integration of adequate experimental data with systems biology understanding is preferred. Here, we describe a novel method to develop reliable and sensible AOPs that relies on chemical-gene interactions, toxicity pathways, molecular regulations, phenotypes, and outcomes information obtained from comparative toxicogenomics database (CTD) and Ingenuity Pathway Analysis (IPA). Using Benzo(a)pyrene (BaP), a highly studied chemical as a stressor, we identified the pivotal IPA toxicity pathways, the molecular initiating event (MIE), and candidate key events (KEs) to structure AOPs in the liver and lung, respectively. Further, we used the corresponding CTD information of multiple typical AHR-ligands, including 2,3,7,8-tetrachlorodibenzoparadioxin (TCDD), valproic acid, quercetin, and particulate matter, to validate our AOP networks. Our approach is likely to speed up AOP development as providing a time- and cost-efficient way to collect all fragmented bioinformation in published studies. It also facilitates a better understanding of the toxic mechanism of environmental chemicals, and potentially brings new insights into the screening of critical paths in the AOP network.