In vitro to in vivo benchmark dose comparisons to inform risk assessment of quantum dot nanomaterials

An update on the biological effects of quantum dots: From environmental fate to risk assessment based on multiple biological models

Quantum dots (QDs) are zero-dimension nanomaterials with excellent physical and chemical properties, which have been widely used in environmental science and biomedicine. Therefore, QDs are potential to cause toxicity to the environment and enter organisms through migration and bioenrichment effects. This review aims to provide a comprehensive and systematic analysis on the adverse effects of QDs in different organisms based on recently available data. Following PRISMA guidelines, this study searched PubMed database according to the pre-set keywords, and included 206 studies according to the inclusion and elimination criteria. CiteSpace software was firstly used to analyze the keywords of included literatures, search for breaking points of former studies, and summarize the classification, characterization and dosage of QDs. The environment fate of QDs in the ecosystems were then analyzed, followed with comprehensively summarized toxicity outcomes at individual, system, cell, subcellular and molecular levels. After migration and degradation in the environment, aquatic plants, bacteria, fungi as well as invertebrates and vertebrates have been found to be suffered from toxic effects caused by QDs. Aside from systemic effects, toxicity of intrinsic QDs targeting to specific organs, including respiratory system, cardiovascular system, hepatorenal system, nervous system and immune system were confirmed in multiple animal models. Moreover, QDs could be taken up by cells and disturb the organelles, which resulted in cellular inflammation and cell death, including autophagy, apoptosis, necrosis, pyroptosis and ferroptosis. Recently, several innovative technologies, like organoids have been applied in the risk assessment of QDs to promote the surgical interventions of preventing QDs' toxicity. This review not only aimed at updating the research progress on the biological effects of QDs from environmental fate to risk assessment, but also overcame the limitations of available reviews on basic toxicity of nanomaterials by interdisciplinarity and provided new insights for better applications of QDs.

Application of Inorganic Nanomaterials in Cultural Heritage Conservation, Risk of Toxicity, and Preventive Measures

Nanotechnology has allowed for significant progress in architectural, artistic, archaeological, or museum heritage conservation for repairing and preventing damages produced by deterioration agents (weathering, contaminants, or biological actions). This review analyzes the current treatments using nanomaterials, including consolidants, biocides, hydrophobic protectives, mechanical resistance improvers, flame-retardants, and multifunctional nanocomposites. Unfortunately, nanomaterials can affect human and animal health, altering the environment. Right now, it is a priority to stop to analyze its advantages and disadvantages. Therefore, the aims are to raise awareness about the nanotoxicity risks during handling and the subsequent environmental exposure to all those directly or indirectly involved in conservation processes. It reports the human-body interaction mechanisms and provides guidelines for preventing or controlling its toxicity, mentioning the current toxicity research of main compounds and emphasizing the need to provide more information about morphological, structural, and specific features that ultimately contribute to understanding their toxicity. It provides information about the current documents of international organizations (European Commission, NIOSH, OECD, Countries Normative) about worker protection, isolation, laboratory ventilation control, and debris management. Furthermore, it reports the qualitative risk assessment methods, management strategies, dose control, and focus/receptor relationship, besides the latest trends of using nanomaterials in masks and gas emissions control devices, discussing their risk of toxicity.

Aerosol physicochemical determinants of carbon black and ozone inhalation co-exposure induced pulmonary toxicity

Air pollution accounts for more than 7 million premature deaths worldwide. Using ultrafine carbon black (CB) and ozone (O3) as a model for an environmental co-exposure scenario, the dose response relationships in acute pulmonary injury and inflammation were determined by generating, characterizing, and comparing stable concentrations of CB aerosols (2.5, 5.0, 10.0 mg/m3), O3 (0.5, 1.0, 2.0 ppm) with mixture CB + O3 (2.5 + 0.5, 5.0 + 1.0, 10.0 + 2.0). C57BL6 male mice were exposed for 3 h by whole body inhalation and acute toxicity determined after 24 h. CB itself did not cause any alteration, however, a dose response in pulmonary injury/inflammation was observed with O3 and CB + O3. This increase in response with mixtures was not dependent on the uptake but was due to enhanced reactivity of the particles. Benchmark dose modeling showed several-fold increase in potency with CB + O3 compared with CB or O3 alone. Principal component analysis provided insight into response relationships between various doses and treatments. There was a significant correlation in lung responses with charge-based size distribution, total/alveolar deposition, oxidant generation, and antioxidant depletion potential. Lung tissue gene/protein response demonstrated distinct patterns that are better predicted by either particle dose/aerosol responses (interleukin-1β, keratinocyte chemoattractant, transforming growth factor beta) or particle reactivity (thymic stromal lymphopoietin, interleukin-13, interleukin-6). Hierarchical clustering showed a distinct signature with high dose and a similarity in mRNA expression pattern of low and medium doses of CB + O3. In conclusion, we demonstrate that the biological outcomes from CB + O3 co-exposure are significantly greater than individual exposures over a range of aerosol concentrations and aerosol characteristics can predict biological outcome.

Toxicokinetics, dose-response, and risk assessment of nanomaterials: Methodology, challenges, and future perspectives

The rapid growth of nanomaterial applications has raised safety concerns for human health. A number of studies have been conducted to assess the toxicokinetics, toxicology, dose-response, and risk assessment of different nanomaterials using in vitro and in vivo animal and human models. However, current studies cannot meet the demand for efficient assessment of toxicokinetics, dose-response relationships, or the toxicological risk arising from the rapidly increasing number of newly synthesized nanomaterials. In this article, we review the methods for conducting toxicokinetics, hazard identification, dose-response, exposure, and risk assessment studies of nanomaterials, identify the knowledge gaps, and discuss the challenges remaining. We provide the rationale behind the appropriate design of nanomaterial plasma toxicokinetic and tissue distribution studies, including caveats on the interpretation and correlation of in vitro and in vivo toxicology studies. The potential of using physiologically based pharmacokinetic (PBPK) models to extrapolate toxicokinetic and toxicity findings from in vitro to in vivo and from animals to humans is discussed, and the knowledge gaps of PBPK modeling for nanomaterials are identified. While challenges still exist, there has been progress in the toxicokinetics, hazard identification, and risk assessment of nanomaterials in the past two decades. Recent advancements in the field are highlighted with relevant examples. We also share latest guidelines as well as our perspectives on future studies needed to characterize the toxicokinetics, toxicity, and dose-response relationship in support of nanomaterial risk assessment. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine.

Approach toward In Vitro-Based Human Toxicity Effect Factors for the Life Cycle Impact Assessment of Inhaled Low-Solubility Particles

Today's scarcity of animal toxicological data for nanomaterials could be lifted by substituting in vivo data with in vitro data to calculate nanomaterials' effect factors (EF) for Life Cycle Assessment (LCA). Here, we present a step-by-step procedure to calculate in vitro-to-in vivo extrapolation factors to estimate human Benchmark Doses and subsequently in vitro-based EFs for several inhaled nonsoluble nanomaterials. Based on mouse data, the in vitro-based EF of TiO₂ is between 2.76 · 10^-4 and 1.10 · 10^-3 cases/(m²/g·kg intake), depending on the aerodynamic size of the particle, which is in good agreement with in vivo-based EFs (1.51 · 10^-4-5.6 · 10^-2 cases/(m²/g·kg intake)). The EF for amorphous silica is in a similar range as for TiO₂, but the result is less robust due to only few in vivo data available. The results based on rat data are very different, confirming the importance of selecting animal species representative of human responses. The discrepancy between in vivo and in vitro animal data in terms of availability and quality limits the coverage of further nanomaterials. Systematic testing on human and animal cells is needed to reduce the variability in toxicological response determined by the differences in experimental conditions, thus helping improve the predictivity of in vitro-to-in vivo extrapolation factors.

Cytotoxicity and transcriptome changes triggered by CuInS2/ZnS quantum dots in human glial cells

As a newly developed cadmium-free quantum dot (QD), CuInS₂/ZnS has great application potential in many fields, but its biological safety has not been fully understood. In this study, the in vitro toxicity of CuInS₂/ZnS QDs on U87 human glioma cell line was explored. The cells were treated with different concentrations of QDs (12.5, 25, 50 and 100 μg/mL), and the uptake of QDs by the U87 cells was detected by fluorescence imaging and flow cytometry. The cell viability was observed by MTT assay, and the gene expression profile was analyzed by transcriptome sequencing. These results showed that QDs could enter the cells and mainly located in the cytoplasm. The uptake rate was over 90 % when the concentration of QDs reached 25 μg/mL. The cell viability (50 and 100 μg/mL) increased at 24 h (P < 0.05), but no significant difference after 48 h and 72 h treatment. The results of differential transcription showed that coding RNA accounted for the largest proportion (62.15 %), followed by long non-coding RNA (18.65 %). Total 220 genes were up-regulated and 1515 genes were down-regulated, and significantly altered gene functions included nucleosome, chromosome-DNA binding, and chromosome assembly. In conclusion, CuInS₂/ZnS QDs could enter U87 cells, did not reduce the cell viability, but would obviously alter the gene expression profile. These findings provide valuable information for a proper understanding of the toxicity risk of CuInS₂/ZnS QD and promote the rational utilization of QDs in the future.

Rationale and decision rules behind the ECETOC NanoApp to support registration of sets of similar nanoforms within REACH

New registration requirements for nanomaterials under REACH consider the possibility to form 'sets of similar nanoforms' for a joined human health and environmental hazard, exposure and risk assessment. We developed a tool to create and justify sets of similar nanoforms and to ensure that each of the nanoforms is sufficiently similar to all other nanoforms. The decision logic is following the ECHA guidance in a transparent and evidence-based manner. For each two nanoforms the properties under consideration are compared and corresponding thresholds for maximal differences are proposed. In tier1, similarity is assessed based on intrinsic properties that mostly correspond to those required for nanoform identification under REACH: composition, impurities/additives, size, crystallinity, shape and surface treatment. Moreover, potential differences in the agglomeration/aggregation state resulting from different production processes are considered. If nanoforms were not sufficiently similar based on tier1 criteria, additional data from functional assays are required in tier2. In rare cases, additional short-term in vivo rodent data could be required in a third tier. Data required by tier 2 are triggered by the intrinsic properties in the first tier that did not match the similarity criteria. Most often this will be data on dissolution and surface reactivity followed by in vitro toxicity, dispersion stability, dustiness. Out of several nanoforms given by the user, the tool concludes which nanoforms could be justified to be in the same set and which nanoforms are outside. It defines the boundaries of sets of similar nanoforms and generates a justification for the REACH registration.

Benchmark dose analyses of toxic endpoints in lung cells provide sensitivity and toxicity ranking across metal oxide nanoparticles and give insights into the mode of action

INTRODUCTION

The benchmark dose (BMD) is a dose that produces a predetermined change in the response rate of an adverse effect. This approach is increasingly utilized to analyze quantitative dose-response relationships. To proof this concept, statistical analysis was compared with the BMD approach in order to rank the sensitivity as well as the toxicity and to describe the mode of action.

METHODS

Bronchial (BEAS-2B) and alveolar epithelial cells (A549) were exposed to a wide concentration range (0.4-100 μg/mL) of five metal oxide nanoparticles (CeO₂, CuO, TiO₂, ZnO, ZrO₂). Eight toxicity endpoints were determined representing integrity of lysosomal and cell membrane, oxidative stress level, glutathione based detoxification (glutathione S-transferase), oxidative metabolism (cytochrome P450), alteration of the mitochondrial membrane potential, alteration of phase II antioxidative enzyme (NAD(P)H:quinone oxidoreductase), and de novo DNA synthesis.

RESULTS

Based on the BMD calculated for the most sensitive test, the toxicity decreased in the following order: ZnO > CuO > TiO₂>ZrO₂>CeO₂ in BEAS-2B. Both statistical evaluation methods revealed a higher sensitivity of BEAS-2B cells. The BMD-derived mode of action for CuO confirmed the existing hypotheses and provided insights into less known mechanisms.

CONCLUSION

The findings proofed that BMD analysis is an effective tool to evaluate different aspects of risk assessment.

Application of cell-based biological bioassays for health risk assessment of PM2.5 exposure in three megacities, China

The determination of PM_2.5-induced biological response is essential for understanding the adverse health risk associated with PM_2.5 exposure. In this study, we conducted cell-based bioassays to measure the toxic effects of PM_2.5 exposure, including cytotoxicity, oxidative stress, genotoxicity and inflammatory response. The concentration-response relationship was analyzed by benchmark dose (BMD) modeling and the BMDL₁₀ was used to estimate the biological potency of PM_2.5 exposure. PM_2.5 samples were collected from three typical megacities of China (Beijing, BJ; Wuhan, WH; Guangzhou, GZ) in typical seasons (winter and summer). The total PM, water-soluble fractions (WSF), and organic extracts (OE) were prepared and subjected to examination of toxic effects. The biological potencies for cytotoxicity, oxidative stress and genotoxicity were generally higher in winter samples, while the inflammatory potency of PM_2.5 was higher in summer samples. The relative health risk (RHR) was determined by integration of the biological potencies and the cumulative exposure level, and the ranks of RHR were BJ-W > WH-W > BJ-S > WH-S > GZ-W > GZ-S. Notably, we note that different PM_2.5 compositions were associated with distinct biological effects, and the health effects distribution of PM_2.5 varied in regions and seasons. These findings demonstrate that the approach of integrated cell-based bioassays could be used for the evaluation of health effects of PM_2.5 exposure.

CdTe and CdTe@ZnS quantum dots induce IL-1ß-mediated inflammation and pyroptosis in microglia

CdTe quantum dots (QDs) are still widely considered as excellent fluorescent probes because of their far more superior optical performance and fluorescence efficiency than non‑cadmium QDs. Thus, it is important to find ways to control their toxicity. In this study, CdTe QDs and CdTe@ZnS QDs both could cause IL-1ß-mediated inflammation following with pyroptosis in BV2 cells, but the toxic effects caused by CdTe@ZnS QDs was weaker than CdTe QDs, which demonstrated the partial protection of ZnS shell. When investigating the molecular mechanisms of QDs causing the inflammatory injury, the findings suggested that cadmium-containing QDs exposure activated NF-κB that participated in the NLRP3 inflammasome priming and pro-IL-1ß expression. After that, QDs-induced excessive ROS generation triggered the NLRP3 inflammasome activation and resulted in active caspase-1 to process pro-IL-1ß into mature IL-1ß release and inflammatory cell death, i.e. pyroptosis. Fortunately, the inhibitions of caspase-1, NF-κB and ROS or knocking down of NLRP3 all effectively attenuated the increases in the IL-1ß secretion and cell death caused by QDs in BV2 cells. This study provided two methods to alleviate the toxicity of cadmium-containing QDs, in which one is to encapsulate bare-core QDs with a shell and the other is to inhibit their toxic pathways. Since the latter way is more effective than the former one, it is significant to evaluate QDs through a mechanism-based risk assessment to identify controllable toxic targets.

The development of a cell-based model for the assessment of carcinogenic potential upon long-term PM2.5 exposure

To assess the carcinogenic potential of PM2.5 exposure, we developed a cell-based experimental protocol to examine the cell transformation activity of PM2.5 samples from different regions in China. The seasonal ambient PM2.5 samples were collected from three megacities, Beijing (BJ), Wuhan (WH), and Guangzhou (GZ), from November 2016 to October 2017. The mean concentrations of PM2.5 were much higher in the winter season (BJ: 109.64 μg/m³, WH: 79.99 μg/m³, GZ: 49.99 μg/m³) than that in summer season (BJ: 42.40 μg/m³, WH: 25.82 μg/m³, GZ: 19.82 μg/m³). The organic extracts (OE) of PM2.5 samples from combined summer (S) (June, July, August) or winter (W) (November, December, January) seasons were subjected to characterization of chemical components. We treated human bronchial epithelial (HBE) cells expressing CYP1A1 (HBE-1A1) with PM2.5 samples at doses ranging from 0 to 100 μg/mL (0, 1.563, 3.125, 6.25, 12.5, 25, 50, 100 μg/mL) and determined the phenotype of malignant cell transformation. A dose-response relationship was analyzed by benchmark dose (BMD) modeling, and the potential were indicated by BMDL₁₀. The order of the carcinogenic risk of seasonal PM2.5 samples from high to low was BJ-W, WH-W, GZ-W, WH-S, BJ-S, and GZ-S. Notably, we found that the alteration in the lung cancer-related biomarkers, KRAS, PTEN, p53, c-Myc, PCNA, pAKT/AKT, and pERK/ERK was congruent with the activity of cell transformation and the content of specific components of polycyclic aromatic hydrocarbon (PAHs) bound to PM2.5. Taken together, we have successfully developed a cell-based alternative model for the evaluation of potent carcinogenicity upon long-term PM2.5 exposure.