Conventional Toxicity Research Articles

Endocrine system, cell growth and death, and energy metabolism induced by Sb(III) exposure in earthworm (Pheretima guillemi) revealed by transcriptome and metabolome analysis

Antimony (Sb) is known for its severe and extensive toxicity, and earthworms are considered important indicator organisms in soil ecosystems. Therefore, the present study investigated the mechanism of toxicity of the Sb at different concentrations (50, 200 mg/kg) on earthworms using biochemical indicators, pathological sections, as well as metabolomics and transcriptomics analyses. The results showed that as the exposure concentration increased, both the antioxidant system of earthworms, extent of intestinal damage, and their metabolomic characteristics were significantly enhanced. In the 50 and 200 mg/kg Sb treatment group, 30 and 177 significant differentially changed metabolites (DCMs) were identified, respectively, with the most DCMs being down- and up-regulated, respectively. Metabolomics analysis showed that the contents of dl-tryptophan, glutamic acid, glycine, isoleucine, l-methionine, involved in the protein digestion and absorption as well as aminoacyl-tRNA biosynthesis were significantly up-regulated under the 200 mg/kg treatment. At the transcriptional level, Sb mainly affected the immune system, nervous system, amino acid metabolism, endocrine system, and carbohydrate metabolism in earthworms. The integration of transcriptomic and metabolomic data indicated that high doses of Sb regulated the metabolites and genes related to the oxidative phosphorylation pathway in earthworms. Overall, these results revealed global responses beyond the scope of conventional toxicity endpoints and facilitated a more in-depth and comprehensive assessment of the toxic effects of Sb.

Comparative toxicology of algal cell extracts and pure cyanotoxins: insights into toxic effects and mechanisms of harmful cyanobacteria Raphidiopsis raciborskii

Ongoing research on cyanotoxins, driven by the socioeconomic impact of harmful algal blooms, emphasizes the critical necessity of elucidating the toxicological profiles of algal cell extracts and pure toxins. This study comprehensively compares Raphidiopsis raciborskii dissolved extract (RDE) and cylindrospermopsin (CYN) based on Daphnia magna assays. Both RDE and CYN target vital organs and disrupt reproduction, development, and digestion, thereby causing acute and chronic toxicity. Disturbances in locomotion, reduced behavioral activity, and weakened swimming capability in D. magna have also been reported for both RDE and CYN, indicating the insufficiency of conventional toxicity evaluation parameters for distinguishing between the toxic effects of algal extracts and pure cyanotoxins. Additionally, chemical profiling revealed the presence of highly active tryptophan-, humic acid-, and fulvic acid-like fluorescence compounds in the RDE, along with the active constituents of CYN, within a 15-day period, demonstrating the chemical complexity and dynamics of the RDE. Transcriptomics was used to further elucidate the distinct molecular mechanisms of RDE and CYN. They act diversely in terms of cytotoxicity, involving oxidative stress and response, protein content, and energy metabolism, and demonstrate distinct modes of action in neurofunctions. In essence, this study underscores the distinct toxicity mechanisms of RDE and CYN and emphasizes the necessity for context- and objective-specific toxicity assessments, advocating nuanced approaches to evaluate the ecological and health implications of cyanotoxins, thereby contributing to the precision of environmental risk assessments.

In Vitro Toxicity Screening of Fifty Complex Mixtures in HepG2 Cells.

To develop the risk prediction technology for mixture toxicity, a reliable and extensive dataset of experimental results is required. However, most published literature only provides data on combinations containing two or three substances, resulting in a limited dataset for predicting the toxicity of complex mixtures. Complex mixtures may have different mode of actions (MoAs) due to their varied composition, posing difficulty in the prediction using conventional toxicity prediction models, such as the concentration addition (CA) and independent action (IA) models. The aim of this study was to generate an experimental dataset comprising complex mixtures. To identify the target complex mixtures, we referred to the findings of the HBM4EU project. We identified three groups of seven to ten components that were commonly detected together in human bodies, namely environmental phenols, perfluorinated compounds, and heavy metal compounds, assuming these chemicals to have different MoAs. In addition, a separate mixture was added consisting of seven organophosphate flame retardants (OPFRs), which may have similar chemical structures. All target substances were tested for cytotoxicity using HepG2 cell lines, and subsequently 50 different complex mixtures were randomly generated with equitoxic mixtures of EC10 levels. To determine the interaction effect, we calculated the model deviation ratio (MDR) by comparing the observed EC10 with the predicted EC10 from the CA model, then categorized three types of interactions: antagonism, additivity, and synergism. Dose-response curves and EC values were calculated for all complex mixtures. Out of 50 mixtures, none demonstrated synergism, while six mixtures exhibited an antagonistic effect. The remaining mixtures exhibited additivity with MDRs ranging from 0.50 to 1.34. Our experimental data have been formatted to and constructed for the database. They will be utilized for further research aimed at developing the combined CA/IA approaches to support mixture risk assessment.

Interpretable attention-based multi-encoder transformer based QSPR model for assessing toxicity and environmental impact of chemicals

The rising demand from consumer goods and pharmaceutical industry is driving a fast expansion of newly developed chemicals. The conventional toxicity testing of unknown chemicals is expensive, time-consuming, and raises ethical concerns. The quantitative structure–property relationship (QSPR) is an efficient computational method because it saves time, resources, and animal experimentation. Advances in machine learning have improved chemical analysis in QSPR studies, but the real-world application of machine learning-based QSPR studies was limited by the unexplainable ‘black box’ feature of the machine learnings. In this study, multi-encoder structure-to-toxicity (S2T)-transformer based QSPR model was developed to estimate the properties of polychlorinated biphenyls (PCBs) and endocrine disrupting chemicals (EDCs). Simplified molecular input line entry systems (SMILES) and molecular descriptors calculated by the Dragon 6 software, were simultaneously considered as input of QSPR model. Furthermore, an attention-based framework is proposed to describe the relationship between the molecular structure and toxicity of hazardous chemicals. The S2T-transformer model achieved the highest R2 scores of 0.918, 0.856, and 0.907 for logarithm of octanol-water partition coefficient (Log KOW), octanol-air partition coefficient (Log KOA), and bioconcentration factor (Log BCF) estimation of PCBs, respectively. Moreover, the attention weights were able to properly interpret the lateral (meta, para) chlorination associated with PCBs toxicity and environmental impact.

Biological Impact of Organic Extracts from Urban-Air Particulate Matter: An In Vitro Study of Cytotoxic and Metabolic Effects in Lung Cells

Atmospheric particulate matter (PM) with diameters below 10 µm (PM10) may enter the lungs through inhalation and are linked to various negative health consequences. Emergent evidence emphasizes the significance of cell metabolism as a sensitive target of PM exposure. However, the current understanding of the relationship between PM composition, conventional toxicity measures, and the rewiring of intracellular metabolic processes remains limited. In this work, PM10 sampled at a residential area (urban background, UB) and a traffic-impacted location (roadside, RS) of a Portuguese city was comprehensively characterized in terms of polycyclic aromatic hydrocarbons and plasticizers. Epithelial lung cells (A549) were then exposed for 72 h to PM10 organic extracts and different biological outcomes were assessed. UB and RS PM10 extracts dose-dependently decreased cell viability, induced reactive oxygen species (ROS), decreased mitochondrial membrane potential, caused cell cycle arrest at the G0/G1 phase, and modulated the intracellular metabolic profile. Interestingly, the RS sample, richer in particularly toxic PAHs and plasticizers, had a greater metabolic impact than the UB extract. Changes comprised significant increases in glutathione, reflecting activation of antioxidant defences to counterbalance ROS production, together with increases in lactate, NAD+, and ATP, which suggest stimulation of glycolytic energy production, possibly to compensate for reduced mitochondrial activity. Furthermore, a number of other metabolic variations hinted at changes in membrane turnover and TCA cycle dynamics, which represent novel clues on potential PM10 biological effects.

Transcriptome analysis of a springtail, Folsomia candida, reveals energy constraint and oxidative stress during petroleum hydrocarbon exposure

Petroleum hydrocarbon (PHC) contamination in soil is ubiquitous and poses harmful consequences to many organisms. The toxicity of PHC-impacted soil is difficult to predict due to variations in mixture composition and the impacts of natural weathering processes. Hence, high-throughput methods to assess PHC-impacted soils is required to expedite land management decisions. Next-generation sequencing is a robust tool that allows researchers to investigate the effects of contaminants on the transcriptome of organisms and identify molecular biomarkers. In this study, the effects of PHCs on conventional endpoints (i.e., survival and reproduction) and gene expression rates of a model springtail species, Folsomia candida were investigated. Age-synchronized F. candida were exposed to ecologically-relevant concentrations of soils spiked with fresh crude oil to calculate the reproductive EC25 and EC50 values using conventional toxicity testing. Soils spiked to these concentrations were then used to evaluate effects on the F. candida transcriptome over a 7-day exposure period. RNA-seq analysis found 98 and 132 differentially expressed genes when compared to the control for the EC25 and EC50 treatment groups, respectively. The majority of up-regulated genes were related to xenobiotic biotransformation reactions and oxidative stress response, while down-regulated genes coded for carbohydrate and peptide metabolic processes. Promotion of the pentose phosphate pathway was also found. Results suggest that the decreased reproduction rates of F. candida exposed to PHCs is due to energy constraints caused by inhibition of carbohydrate metabolic processes and allocation of remaining energy to detoxify xenobiotics. These findings provide insights into the molecular effects in F. candida following exposure to crude oil for seven days and highlight their potential to be used as a high-throughput screening test for PHC-contaminated sites. Adverse molecular effects can be measured as early as 24 h following exposure, whereas conventional toxicity tests may require a minimum of four weeks.

Hi-MGT: A hybrid molecule graph transformer for toxicity identification

Conventional toxicity testing methods that rely on animal experimentation are resource-intensive, time-consuming, and ethically controversial. Therefore, the development of alternative non-animal testing approaches is crucial. This study proposes a novel hybrid graph transformer architecture, termed Hi-MGT, for the toxicity identification. An innovative aggregation strategy, referred to as GNN-GT combination, enables Hi-MGT to simultaneously and comprehensively aggregate local and global structural information of molecules, thus elucidating more informative toxicity information hidden in molecule graphs. The results show that the state-of-the-art model outperforms current baseline CML and DL models on a diverse range of toxicity endpoints and is even comparable to large-scale pretrained GNNs with geometry enhancement. Additionally, the impact of hyperparameters on model performance is investigated, and a systematic ablation study is conducted to demonstrate the effectiveness of the GNN-GT combination. Moreover, this study provides valuable insights into the learning process on molecules and proposes a novel similarity-based method for toxic site detection, which could potentially facilitate toxicity identification and analysis. Overall, the Hi-MGT model represents a significant advancement in the development of alternative non-animal testing approaches for toxicity identification, with promising implications for enhancing human safety in the use of chemical compounds.

Toxicity of ionic liquids against earthworms (Eisenia fetida)

Ionic liquids (ILs) are widely used in frontier fields because of their highly tunable properties. Although ILs may have adverse effects on organisms, few studies have focused on their effect on earthworm gene expression. Herein we investigated the toxicity mechanism of different ILs towards Eisenia fetida using transcriptomics. Earthworms were exposed to soil containing different concentrations and types of ILs, and behavior, weight, enzymatic activity and transcriptome were analyzed. Earthworms exhibited avoidance behavior towards ILs and growth was inhibited. ILs also affected antioxidant and detoxifying enzymatic activity. These effects were concentration and alkyl chain length-dependent. Analysis of intrasample expression levels and differences in transcriptome expression levels showed good parallelism within groups and large differences between groups. Based on functional classification analysis, we speculate that toxicity mainly occurs through translation and modification of proteins and intracellular transport functions, which affect protein-related binding functions and catalytic activity. KEGG pathway analysis revealed that ILs may damage the digestive system of earthworms, among other possible pathological effects. Transcriptome analysis reveals mechanisms that cannot be observed by conventional toxicity endpoints. This is useful to evaluate the potential environmental adverse effects of the industrial use of ILs.

Toxicogenomics scoring system: TGSS, a novel integrated risk assessment model for chemical carcinogenicity prediction

BackgroundGiven the increasing exposure of humans to environmental chemicals and the limitations of conventional toxicity test, there is an urgent need to develop next-generation risk assessment methods. ObjectivesThis study aims to establish a novel computational system named Toxicogenomics Scoring System (TGSS) to predict the carcinogenicity of chemicals coupling chemical-gene interactions with multiple cancer transcriptomic datasets. MethodsChemical-related gene signatures were derived from chemical-gene interaction data from the Comparative Toxicogenomics Database (CTD). For each cancer type in TCGA, genes were ranked by their effects on tumorigenesis, which is based on the differential expression between tumor and normal samples. Next, we developed carcinogenicity scores (C-scores) using pre-ranked GSEA to quantify the correlation between chemical-related gene signatures and ranked gene lists. Then we established TGSS by systematically evaluating the C-scores in multiple chemical-tumor pairs. Furthermore, we examined the performance of our approach by ROC curves or prognostic analyses in TCGA and multiple independent cancer cohorts. ResultsForty-six environmental chemicals were finally included in the study. C-score was calculated for each chemical-tumor pair. The C-scores of IARC Group 3 chemicals were significantly lower than those of chemicals in Group 1 (P-value = 0.02) and Group 2 (P-values = 7.49 ×10−5). ROC curves analysis indicated that C-score could distinguish “high-risk chemicals” from the other compounds (AUC = 0.67) with a specificity and sensitivity of 0.86 and 0.57. The results of survival analysis were also in line with the assessed carcinogenicity in TGSS for the chemicals in Group 1. Finally, consistent results were further validated in independent cancer cohorts. ConclusionTGSS highlighted the great potential of integrating chemical-gene interactions with gene-cancer relationships to predict the carcinogenic risk of chemicals, which would be valuable for systems toxicology.

PH/ROS dual-responsive nanoparticles with curcumin entrapment to promote antitumor efficiency in triple negative breast cancer

Triple negative breast cancer (TNBC) remains a serious carcinoma threatening women's life. Natural compounds such as curcumin (CUR) have shown promising potential in TNBC therapy without conventional toxicity like chemotherapeutics. To improve the therapeutic efficiency, a pH/redox nanocarrier (CUR@PCPP NPs) was developed for tumor specific delivery of CUR. CUR@PCPP NPs showed good size distribution, encapsulation efficiency and stability under physiological conditions. Detachment of polyethylene glycol (PEG) facilitated cellular uptake of CUR@PCPP NPs after exposure to extracellular tumor pH. Subsequently CUR was released due to the intracellular redox environment. Thereafter, released CUR could efficiently induce apoptosis and cycle arrest, and inhibit TNBC cells. We further verified the biodistribution and antitumor effects in vivo and the results showed that CUR@PCPP NPs demonstrated high tumor specific accumulation and effectively suppressed tumor growth without noticeable toxicity.

Rapid Macular Thinning Is an Early Indicator of Hydroxychloroquine Retinal Toxicity

To demonstrate rapid macular thinning as an early and objective sign of hydroxychloroquine retinopathy. Retrospective case cohort. Cohort of 301 patients receiving long-term hydroxychloroquine therapy at Kaiser Permanente Northern California who underwent a minimum of 4 OCT studies that included Early Treatment Diabetic Retinopathy Study (ETDRS) retinal thickness values over a minimum of 4 years. Creation of sequential retinal thickness plots to show the rate of change in macular thickness within ETDRS regions. Identification of rapid macular thinning, comparison of patients with rapid thinning to those with stable macular thickness, and comparison of rapid thinning patients with and without conventional OCT or 10-2 visual field signs of hydroxychloroquine toxicity. Retina thinning in 219 stable patients receiving long-term hydroxychloroquine therapy averaged (mean ± standard deviation) 0.62 ± 0.45 μm/year, whereas 82 patients showed a period of relatively linear rapid thinning with a loss of 3.75 ± 1.34 μm/year. Of the patients with rapid thinning, 38 eventually demonstrated conventional OCT or 10-2 visual field signs of hydroxychloroquine retinal toxicity. The cumulative retinal thinning in these patients was 25.1 ± 6.2 μm compared with 15.7 ± 4.0 μm in those without conventional toxicity (P<0.01). Retinal thickness remains stable for many years in most patients receiving long-term hydroxychloroquine therapy, but after a critical point, the retina may begin to thin rapidly. Sequential plots of inner and outer ETDRS ring macular thickness provide objective evidence of this early structural change several years before conventional signs appear. This approach can alert patients and prescribing physicians to potential retinal damage and uses readily available OCT measurements that could be automated by manufacturers for use in comprehensive eye care settings.

Hierarchical Particle Approach for Co-Precipitated Amorphous Solid Dispersions for Use in Preclinical In Vivo Studies.

Amorphous solid dispersions (ASD) have become a well-established strategy to improve exposure for compounds with insufficient aqueous solubility. Of methods to generate ASDs, spray drying is a leading route due to its relative simplicity, availability of equipment, and commercial scale capacity. However, the broader industry adoption of spray drying has revealed potential limitations, including the inability to process compounds with low solubility in volatile solvents, inconsistent molecular uniformity of spray dried amorphous dispersions, variable physical properties across batches and scales, and challenges containing potent compounds. In contrast, generating ASDs via co-precipitation to yield co-precipitated amorphous dispersions (cPAD) offers solutions to many of those challenges and has been shown to achieve ASDs comparable to those manufactured via spray drying. This manuscript applies co-precipitation for early safety studies, developing a streamlined process to achieve material suitable for dosing as a suspension in conventional toxicity studies. Development targets involved achieving a rapid, safely contained process for generating ASDs with high recovery yields. Furthermore, a hierarchical particle approach was used to generate composite particles where the cPAD material is incorporated in a matrix of water-soluble excipients to allow for rapid re-dispersibility in the safety study vehicle to achieve a uniform suspension for consistent dosing. Adopting such an approach yielded a co-precipitated amorphous dispersion with comparable stability, thermal properties, and in vivo pharmacokinetics to spray dried amorphous materials of the same composition.

On-line monitoring of water quality with a floating microbial fuel cell biosensor: field test results

Real-time biomonitoring using microbial fuel cell (MFC) based biosensors have been demonstrated in several laboratory studies, but field validation is lacking. This study describes the long-term performance of an MFC based biosensor developed for real-time monitoring of changes in the water quality of a metal-contaminated stream. After a startup in the laboratory, biosensors were deployed in a stream close to an active mining complex in Sudbury, ON, Canada. Three sites within the stream were selected for biosensors installation based on their positions relative to the mining complex discharge points - upstream (lowest heavy metals concentration), midpoint and downstream. The biosensors installed at these sites were able to detect, in real-time, temporal changes in the water quality over a 2-month period. The biosensor response was confirmed by the results of a conventional toxicity assay (48-h acute Daphnia magna) as well as analytical measurements of heavy metals concentration in the stream. We conclude that the biosensor could detect changes in the overall water quality of the stream despite the uncontrolled situations typical for field operations as compared to laboratory conditions. To further explain the results observed during the field test, the rapid Microtox bioassay and D. magna assay were used to investigate the possible contributions of the two dominant mining metals (Nickel and Copper) to water toxicity in the test area.

Translating nanoparticle dosimetry from conventional in vitro systems to occupational inhalation exposures

As encouraged by Toxicity Testing in the 21st Century, researchers increasingly apply high-throughput in vitro approaches to identify and characterize nanoparticle hazards, including conventional aqueous cell culture systems to assess respiratory hazards. Translating nanoparticle dose from conventional toxicity testing systems to relevant human exposures remains a major challenge for assessing occupational risk of nanoparticle exposures. Here, we explored existing computational tools and data available to translate nanoparticle dose metrics from cellular test systems to inhalation exposures of silver nanoparticles in humans. We used the Multiple-Path Particle Dosimetry (MPPD) Model to predict nanoparticle deposition of humans exposed to 20 and 110 nm silver nanoparticles at 0.9 μg/m3 over an 8 h period, the proposed National Institute of Occupational Safety and Health (NIOSH) recommended exposure limit (REL). MPPD predicts 8.1 and 3.7 μg of silver deposited in an 8 h period for 20 and 110 nm nanoparticles, respectively, with 20 nm particles displaying nearly 11-fold higher total surface area deposited. Peak deposited nanoparticle concentrations occurred more proximal in the pulmonary tract compared to mass deposition patterns (generation 4 vs. generations 20–21, respectively) due to regional differences in lung lining fluid volumes. Assuming 0.4% nanoparticle dissolution by mass measured in previous studies predicted peak concentrations of silver ions in cells of 1.06 and 0.89 μg/mL for 20 and 110 nm particles, respectively. Both predicted concentrations are below the measured toxic threshold of 1.7 μg/mL of silver ions in cells from in vitro assessments. Assuming 4% dissolution by mass predicted 10-fold higher silver concentrations in tissues, peaking at 10.6 and 8.9 μg/mL, for 20 and 110 nm nanoparticles respectively, exceeding the observed in vitro toxic threshold and highlighting the importance and sensitivity of dissolution rates. Overall, this approach offers a framework for extrapolating nanotoxicity results from in vitro cell culture systems to human exposures. Aligning appropriate dose metrics from in vitro and in vivo hazard characterizations and human pulmonary doses from occupational exposures are critical components for successful nanoparticle risk assessment and worker protection providing guidance for designing future in vitro studies aimed at relevant human exposures.

In vivo toxicometabolomics reveals multi-organ and urine metabolic changes in mice upon acuteexposure to human-relevant doses of 3,4-methylenedioxypyrovalerone (MDPV).

3,4-Methylenedioxypyrovalerone (MDPV) is consumed worldwide, despite its potential to cause toxicity in several organs and even death. There is a recognized need to clarify the biological pathways throughwhich MDPV elicits general and target-organ toxicity. In this work, a comprehensive untargeted GC-MS-based metabolomics analysis was performed, aiming to detect metabolic changes in putative target organs (brain, heart, kidneys and liver) but also in urine of mice after acute exposure to human-relevant doses of MDPV. Male CD-1 mice received binge intraperitoneal administrations of saline or MDPV (2.5mg/kg or 5mg/kg) every 2h, for a total of three injections. Twenty-four hours after the first administration, target organs, urine and blood samples were collected for metabolomics, biochemical and histological analysis. Hepatic and renal tissues of MDPV-treated mice showed moderate histopathological changes but no significant differences were found in plasma and tissue biochemical markers of organ injury. In contrast, the multivariate analysis significantly discriminated the organs and urine of MDPV-treated mice from the control (except for the lowest dose in the brain), allowing the identification of a panoply of metabolites. Those levels were significantly deviated in relation to physiological conditions and showed an organ specific response towards the drug. Kidneys and liver showed the greatest metabolic changes. Metabolites related with energetic metabolism, antioxidant defenses and inflammatory response were significantly changed in the liver of MDPV-dosed animals, while the kidneys seem to have developed an adaptive response against oxidative stress caused by MDPV. On the other hand, the dysregulation of metabolites that contribute to metabolic acidosis was also observed in this organ. The heart showed an increase of fatty acid biosynthesis, possibly as an adaptation to maintain the cardiac energy homeostasis. In the brain, changes in 3-hydroxybutyric acid levels may reflect the activation of a neurotoxic pathway. However, the increase in metabolites with neuroprotective properties seems to counteract this change. Metabolic profiling of urine from MDPV-treated mice suggested that glutathione-dependent antioxidant pathways may be particularly involved in the compensatory mechanism to counteract oxidative stress induced by MDPV. Overall, this study reports, for the first time, the metabolic profile of liver, kidneys, heart, brain, and urine of MDPV-dosed mice, providing unique insights into the biological pathways of toxicity. Our findings also underline the value of toxicometabolomics as a robust and sensitive tool for detecting adaptive/toxic cellular responses upon exposure to a physiologically relevant dose of a toxic agent, earlier than conventional toxicity tests.

Effects of sediment-associated Cu on Tubifex tubifex – Insights gained by standard ecotoxicological and novel, but simple, bioturbation endpoints

Sediments serve as both source and sink of contaminants (e.g., Cu) and biologically important materials (e.g., metals, nutrients). Bioturbation by benthic organisms is ecologically relevant as bioturbation affects the physio-chemical characteristics of sediments, thus altering nutrient and contaminant distribution and bioavailability. We examined the effects of sediment-associated Cu on T. tubifex with conventional toxicity endpoints, such as mortality and growth, and less commonly used non-destructive endpoints, such as bioturbation and feeding. An experimental approach was developed to examine the applicability of simple methods to detect effects on bioturbation and feeding. Two experiments were conducted with 7-day exposures to uncontaminated or Cu-spiked natural sediment at six Cu concentrations to examine Cu bioaccumulation and effects. Endpoints included worm mortality, feeding rate and growth (experiment A) and worm bioturbation (particle diffusion and maximum penetration depth, experiment B). A microparticle tracer was placed on the sediment surface and vertical particle transport was followed over time. Adverse effects were detected for all endpoints (bioturbation, feeding rate, growth and survival): a slight positive effect at the lowest Cu concentrations followed by adverse effects at higher concentrations indicating hormesis. These simple, non-destructive endpoints, provided valuable information and demonstrated that sediment-associated contaminants, such as Cu, can influence bioturbation activity, which in turn may affect the distribution of sediment-bound or particulate pollutants, such as the plastic microparticles studied here. Thus, we suggest to use simple endpoints, such as bioturbation and feeding rate, in ecotoxicity testing since these endpoint account for the influence of interactions between pollutants and benthos and, thus, increase ecological relevance.

Interference: A Much-Neglected Aspect in High-Throughput Screening of Nanoparticles.

Despite several studies addressing nanoparticle (NP) interference with conventional toxicity assay systems, it appears that researchers still rely heavily on these assays, particularly for high-throughput screening (HTS) applications in order to generate "big" data for predictive toxicity approaches. Moreover, researchers often overlook investigating the different types of interference mechanisms as the type is evidently dependent on the type of assay system implemented. The approaches implemented in the literature appear to be not adequate as it often addresses only one type of interference mechanism with the exclusion of others. For example, interference of NPs that have entered cells would require intracellular assessment of their interference with fluorescent dyes, which has so far been neglected. The present study investigated the mechanisms of interference of gold NPs and silver NPs in assay systems implemented in HTS including optical interference as well as adsorption or catalysis. The conventional assays selected cover all optical read-out systems, that is, absorbance (XTT toxicity assay), fluorescence (CytoTox-ONE Homogeneous membrane integrity assay), and luminescence (CellTiter Glo luminescent assay). Furthermore, this study demonstrated NP quenching of fluorescent dyes also used in HTS (2',7'-dichlorofluorescein, propidium iodide, and 5,5',6,6'-tetrachloro-1,1',3,3'-tetraethyl-benzamidazolocarbocyanin iodide). To conclude, NP interference is, as such, not a novel concept, however, ignoring this aspect in HTS may jeopardize attempts in predictive toxicology. It should be mandatory to report the assessment of all mechanisms of interference within HTS, as well as to confirm results with label-free methodologies to ensure reliable big data generation for predictive toxicology.

Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects.

The starting point of successful hazard assessment is the generation of unbiased and trustworthy data. Conventional toxicity testing deals with extensive observations of phenotypic endpoints in vivo and complementing in vitro models. The increasing development of novel materials and chemical compounds dictates the need for a better understanding of the molecular changes occurring in exposed biological systems. Transcriptomics enables the exploration of organisms’ responses to environmental, chemical, and physical agents by observing the molecular alterations in more detail. Toxicogenomics integrates classical toxicology with omics assays, thus allowing the characterization of the mechanism of action (MOA) of chemical compounds, novel small molecules, and engineered nanomaterials (ENMs). Lack of standardization in data generation and analysis currently hampers the full exploitation of toxicogenomics-based evidence in risk assessment. To fill this gap, TGx methods need to take into account appropriate experimental design and possible pitfalls in the transcriptomic analyses as well as data generation and sharing that adhere to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. In this review, we summarize the recent advancements in the design and analysis of DNA microarray, RNA sequencing (RNA-Seq), and single-cell RNA-Seq (scRNA-Seq) data. We provide guidelines on exposure time, dose and complex endpoint selection, sample quality considerations and sample randomization. Furthermore, we summarize publicly available data resources and highlight applications of TGx data to understand and predict chemical toxicity potential. Additionally, we discuss the efforts to implement TGx into regulatory decision making to promote alternative methods for risk assessment and to support the 3R (reduction, refinement, and replacement) concept. This review is the first part of a three-article series on Transcriptomics in Toxicogenomics. These initial considerations on Experimental Design, Technologies, Publicly Available Data, Regulatory Aspects, are the starting point for further rigorous and reliable data preprocessing and modeling, described in the second and third part of the review series.

Integration of transcriptomics and metabolomics reveals the responses of earthworms to the long-term exposure of TiO2 nanoparticles in soil

Titanium dioxide nanoparticles (nTiO2) are widely used and their environmental occurrence has raised concerns about the potential toxicity to biota. However, few studies have investigated the effect of long-term exposure to nTiO2 on soil invertebrates. This study therefore for the first time investigated the long-term (120 days) effect of nTiO2 (0, 5, 50, and 500 mg/kg) on the phenotypes, transcriptomic, and metabolomic profiles of earthworm (Eisenia fetida) in soil. The results showed that the long-term exposure to nTiO2 did not significantly affect the growth, reproduction, and Ti content of earthworms. However, the antioxidant system and the transcriptomic and metabolomic profiles of earthworms were significantly affected. The superoxide dismutase (SOD) activity and the reduced glutathione/oxidized glutathione (GSH/GSSG) ratio significantly decreased under the 500 mg/kg nTiO2 treatment. The metabolomics analysis showed that glycine and pyroglutamic acid contents involved in the GSH metabolism were significantly altered under the 500 mg/kg treatment. Moreover, transcriptomics and metabolomics data revealed that the long-term exposure to nTiO2 affected the synthesis of carbohydrates, proteins, and lipids. However, the transcriptomics results indicated that the genes involved in ribosome biogenesis in eukaryotes pathway and TGF-beta signaling pathway were upregulated, which could explain why the growth and reproduction of earthworms were apparently not affected by the nTiO2 exposure. The combination of transcriptomics and metabolomics reveals the global responses that cannot be observed by conventional toxicity endpoints, facilitating the assessment of long-term ecological effect of engineered nanoparticles in the environment.

Pathogen inactivation method using ultraviolet C light

Since the end of the 1990s pathogen inactivation methods were being gradually implemented into routine work of blood transfusion establishments in many countries with regard to blood components dedicated for clinical use. The developed pathogen inactivation methods were either based on chemical compounds eg. the solvent detergent (SD) inactivation method or on photochemical and photodynamic reactions eg. inactivation methods with methylene blue, amotosalen hydrochloride and riboflavin. Blood components inactivated with any of the above mentioned methods still had traces of chemical compounds although removal steps were added (an exception here is the method with riboflavin). Attempts were therefore undertaken to develop an inactivation method based not on chemical compounds but on specific wavelength irradiation. An example of such inactivation method solely based on properties of short-wave UVC-light (UVC) with no photosensitizing chemicals is the Theraflex UV-Platelets system dedicated to platelet concentrates (PCs). The system uses 254 nm wavelength irradiation which is not absorbed by proteins so conventional toxicity tests are not required. The method is effective for clinically significant both G (+) and G (-) bacteria as well as viruses and protozoa. Clinical trials demonstrated reduced recovery of UVC-irradiated platelets and shorter survival time in the recipient’s organism.