Use of metal oxide nanoparticle band gap to develop a predictive paradigm for oxidative stress and acute pulmonary inflammation

Automated machine learning in nanotoxicity assessment: A comparative study of predictive model performance

Computational modeling has earned significant interest as an alternative to animal testing of toxicity assessment. However, the process of selecting an appropriate algorithm and fine-tuning hyperparameters for the developing of optimized models takes considerable time, expertise, and an intensive search. The recent emergence of automated machine learning (autoML) approaches, available as user-friendly platforms, has proven beneficial for individuals with limited knowledge in ML-based predictive model development. These autoML platforms automate crucial steps in model development, including data preprocessing, algorithm selection, and hyperparameter tuning. In this study, we used seven previously published and publicly available datasets for oxides and metals to develop nanotoxicity prediction models. AutoML platforms, namely Vertex AI, Azure, and Dataiku, were employed and performance measures such as accuracy, F1 score, precision, and recall for these autoML-based models were then compared with those of conventional ML-based models. The results demonstrated clearly that the autoML platforms produced more reliable nanotoxicity prediction models, outperforming those built with conventional ML algorithms. While none of the three autoML platforms significantly outperformed the others, distinctions exist among them in terms of the available options for choosing technical features throughout the model development steps. This allows users to select an autoML platform that aligns with their knowledge of predictive model development and its technical features. Additionally, prediction models constructed from datasets with better data quality displayed, enhanced performance than those built from datasets with lower data quality, indicating that future studies with high-quality datasets can further improve the performance of those autoML-based prediction models.

Co-precipitation synthesis of highly pure and Mg-doped CdO nanoparticles: from rod to sphere shapes

This study reports a facile approach for examining surface morphology transitions in semiconductor nanoparticles (NPs), with a focus on pristine and magnesium-doped cadmium oxide NPs. Mg-doped CdO NPs are synthesized via co-precipitation, and their composition, structure, and elemental distribution are analyzed through X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), Raman spectra, and X-ray photoelectron spectroscopy (XPS), along with optical characterization and impedance analysis. Doping with Mg2+ changes the morphology from rod-like to quasi-spherical, reduces the crystallite size, and impacts their structural and functional properties. Optical transmittance analysis revealed that Mg2+ doping resulted in a reduction of the band gap energy. Impedance spectroscopy demonstrates improved dielectric constant and electrical conductivity for Mg-doped CdO NPs. The Nyquist plots show grain effects and the equivalent circuit analysis corresponds to a R(CR)(CR) circuit. These advancements point to the potential of spherical Mg-doped CdO NPs in semiconductor applications due to their superior structural and functional characteristics.

A review on the structural characterization of nanomaterials for nano-QSAR models

Quantitative structure-activity relationship (QSAR) models are routinely used to predict the properties and biological activity of chemicals to direct synthetic advances, perform massive screenings, and even to register new substances according to international regulations. Currently, nanoscale QSAR (nano-QSAR) models, adapting this methodology to predict the intrinsic features of nanomaterials (NMs) and quantitatively assess their risks, are blooming. One of the challenges is the characterization of the NMs. This cannot be done with a simple SMILES representation, as for organic molecules, because their chemical structure is complex, including several layers and many inorganic materials, and their size and geometry are key features. In this review, we survey the literature for existing predictive models for NMs and discuss the variety of calculated and experimental features used to define and describe NMs. In the light of this research, we propose a classification of the descriptors including those that directly describe a component of the nanoform (core, surface, or structure) and also experimental features (related to the nanomaterial's behavior, preparation, or test conditions) that indirectly reflect its structure.

Nanoscience and nanotechnology for water remediation: an earnest hope toward sustainability

Water pollution and the global freshwater crisis are the most alarming concerns of the 21st century, as they threaten the sustainability and ecological balance of the environment. The growth of global population, climate change, and expansion of industrial processes are the main causes of these issues. Therefore, effective remediation of polluted water by means of detoxification and purification is of paramount importance. To this end, nanoscience and nanotechnology have emerged as viable options that hold tremendous potential toward the advancement of wastewater treatment methods to enhance treatment efficiency along with augmenting water supply via utilization of unconventional water sources. Materials at the nano level have shown great promise toward water treatment applications owing to their unique physicochemical properties. In this focus article, we highlight the role of new fundamental properties at the nano scale and material properties that are drastically increased due to the nano dimension (e.g. volume-surface ratio) and highlight their impact and potential toward water treatment. We identify and discuss how nano-properties could improve the three main domains of water remediation: the identification of pollutants, their adsorption and catalytic degradation. After discussing all the beneficial aspects we further discuss the key challenges associated with nanomaterials for water treatment. Looking at the current state-of-the-art, the potential as well as the challenges of nanomaterials, we believe that in the future we will see a significant impact of these materials on many water remediation strategies.

Schottky Barrier-Based Built-In Electric Field for Enhanced Tumor Photodynamic Therapy

Photodynamic therapy's antitumor efficacy is hindered by the inefficient generation of reactive oxygen species (ROS) due to the photogenerated electron-hole pairs recombination of photosensitizers (PS). Therefore, there is an urgent need to develop efficient PSs with enhanced carrier dynamics. Herein, we designed Schottky junctions composed of cobalt tetroxide and palladium nanocubes (Co3O4@Pd) with a built-in electric field as effective PS. The built-in electric field enhanced photogenerated charge separation and migration, resulting in the generation of abundant electron-hole pairs and allowing effective production of ROS. Thanks to the built-in electric field, the photocurrent intensity and carrier lifetime of Co3O4@Pd were approximately 2 and 3 times those of Co3O4, respectively. Besides, the signal intensity of hydroxyl radical and singlet oxygen increased to 253.4% and 135.9%, respectively. Moreover, the localized surface plasmon resonance effect of Pd also enhanced the photothermal conversion efficiency of Co3O4@Pd to 40.50%. In vitro cellular level and in vivo xenograft model evaluations demonstrated that Co3O4@Pd could generate large amounts of ROS, trigger apoptosis, and inhibit tumor growth under near-infrared laser irradiation. Generally, this study reveals the contribution of the built-in electric field to improving photodynamic performance and provides new ideas for designing efficient inorganic PSs.

Machine learning-based models to predict aquatic ecological risk for engineered nanoparticles: using hazard concentration for 5% of species as an endpoint

Assessment and prediction for the ecotoxicity of engineered nanoparticles (ENPs) at the community or ecosystem levels represents a critical step toward a comprehensive understanding of the ecological risks of ENPs. Current studies on predicting the ecotoxicity of ENPs primarily focus on the cellular and individual levels, with limited exploration at the community or ecosystem levels. Herein, we present the first of the reports for the direct prediction of aquatic ecological risk for ENPs at the community level using machine learning (ML) approaches in the field of computational toxicology. Specifically, we extensively collected the threshold concentrations of twelve ENPs including metal- and carbon-based nanoparticles for aquatic species, i.e., hazardous concentrations at which 5% of species are harmed (HC5), established by a species sensitivity distribution. Afterwards, we used eight supervised ML methods including Adaboost, artificial neural network, C4.5 decision tree, K-nearest neighbor, logistic regression, Naive Bayes, random forest, and support vector machine to develop nine classification models and four regression models, respectively, for the qualitative and quantitative prediction of HC5. The evaluation of model performance yielded the internal validation accuracy of all classification models ranging from 71.4 to 100%, and the determination coefficient of regression models ranging from 0.702 to 0.999, indicating that the developed models showed good performance. By using a cross-validation method and an application domain characterization, the selected models were further validated to have powerful predictive ability. Furthermore, the incorporation of three nanostructural descriptors (metal oxide sublimation enthalpy, zeta potential, and specific surface area) linked to toxicity mechanisms (the release of metal ions, the stability of dispersions of particles in aqueous suspensions, and the surface properties of the material) effectively enhanced the prediction power and mechanistic interpretability of the selected models. These findings would not only be beneficial in the screening of ENPs with potential high ecological risks that need to be tested as a priority but also contribute to the development of environmental regulations and standards for ENPs.

Exploring the relationships between physiochemical properties of nanoparticles and cell damage to combat cancer growth using simple periodic table-based descriptors

A comprehensive knowledge of the physical and chemical properties of nanomaterials (NMs) is necessary to design them effectively for regulated use. Although NMs are utilized in therapeutics, their cytotoxicity has attracted great attention. Nanoscale quantitative structure-property relationship (nano-QSPR) models can help in understanding the relationship between NMs and the biological environment and provide new ways for modeling the structural properties and bio-toxic effects of NMs. The goal of the study is to construct fully validated property-based models to extract relevant features for estimating and influencing the zeta potential and obtaining the toxicity profile regarding cell damage in the treatment of cancer cells. To achieve this, QSPR modeling was first performed with 18 metal oxide (MeOx) NMs to measure their materials properties using periodic table-based descriptors. The features obtained were later applied for zeta potential calculation (imputation for sparse data) for MeOx NMs that lack such information. To further clarify the influence of the zeta potential on cell damage, a QSPR model was developed with 132 MeOx NMs to understand the possible mechanisms of cell damage. The results showed that zeta potential, along with seven other descriptors, had the potential to influence oxidative damage through free radical accumulation, which could lead to changes in the survival rate of cancerous cells. The developed QSPR and quantitative structure-activity relationship models also give hints regarding safer design and toxicity assessment of MeOx NMs.

Cytotoxicity prediction of nano metal oxides on different lung cells via Nano-QSAR

In recent years, nanomaterials have found extensive applications across diverse domains owing to their distinctive physical and chemical characteristics. It is of great importance in theoretical and practical terms to carry out the relationship between structural characteristics of nanomaterials and different cytotoxicity and to achieve practical assessment and prediction of cytotoxicity. This study investigated the intrinsic quantitative constitutive relationships between the cytotoxicity of nano-metal oxides on human normal lung epithelial cells and human lung adenocarcinoma cells. We first employed quasi-SMILES-based nanostructural descriptors by selecting the five physicochemical properties that are most closely related to the cytotoxicity of nanometal oxides, then established SMILES-based descriptors that can effectively describe and characterize the molecular structure of nanometal oxides, and then built the corresponding Nano-Quantitative Structure-Activity Relationship (Nano-QSAR) prediction models, finally, combined with the theory of reactive oxygen species (ROS) biotoxicity, to reveal the mechanism of toxicity and differences between the two cell types. The established model can efficiently and accurately predict the properties of targets, reveal the corresponding toxicity mechanisms, and guide the safe design, synthesis, and application of nanometal oxides.

Surface Chemistry of Biologically Active Reducible Oxide Nanozymes

Reducible metal oxide nanozymes (rNZs) are a subject of intense recent interest due to their catalytic nature, ease of synthesis, and complex surface character. Such materials contain surface sites which facilitate enzyme-mimetic reactions via substrate coordination and redox cycling. Further, these surface reactive sites are shown to be highly sensitive to stresses within the nanomaterial lattice, the physicochemical environment, and to processing conditions occurring as part of their syntheses. When administered in vivo, a complex protein corona binds to the surface, redefining its biological identity and subsequent interactions within the biological system. Catalytic activities of rNZs each deliver a differing impact on protein corona formation, its composition, and in turn, their recognition, and internalization by host cells. Improving the understanding of the precise principles that dominate rNZ surface-biomolecule adsorption raises the question of whether designer rNZs can be engineered to prevent corona formation, or indeed to produce "custom" protein coronas applied either in vitro, and preadministration, or formed immediately upon their exposure to body fluids. Here, fundamental surface chemistry processes and their implications in rNZ material performance are considered. In particular, material structures which inform component adsorption from the application environment, including substrates for enzyme-mimetic reactions are discussed.

Synthesis, Characterization, and Toxicity Assessment of Zinc Oxide-Doped Manganese Oxide Nanoparticles in a Macrophage Model

The doping of engineered nanomaterials (ENMs) is a key tool for manipulating the properties of ENMs (e.g., electromagnetic, optical, etc.) for different therapeutic applications. However, adverse health outcomes and the cellular biointeraction of doped ENMs, compared to undoped counterparts, are not fully understood. Previously, we have shown that doping manganese oxide nanoparticles with ZnO (ZnO-MnO2 NPs) improved their catalytic properties. In this study, we assessed the toxicity of ZnO-MnO2 NPs in Raw 264.7 cells. NPs were prepared via an eco-friendly, co-precipitation method and characterized by several techniques, including transmission and scanning electron microscopy, X-ray diffraction, and Fourier transform infrared. The physicochemical properties of ZnO-MnO2 NPs, including size, morphology, and crystalline structure, were almost identical to MnO2 NPs. However, ZnO-MnO2 NPs showed slightly larger particle aggregates and negative charge in cell culture media. Exposure to ZnO-MnO2 NPs resulted in lower toxicity based on the cell viability and functional assay (phagocytosis) data. Exposure to both NPs resulted in the activation of the cell inflammatory response and the generation of reactive oxygen species (ROS). Despite this, exposure to ZnO-MnO2 NPs was associated with a lower toxicity profile, and it resulted in a higher ROS burst and the activation of the cell antioxidant system, hence indicating that MnO2 NP-induced toxicity is potentially mediated via other ROS-independent pathways. Furthermore, the cellular internalization of ZnO-MnO2 NPs was lower compared to MnO2 NPs, and this could explain the lower extent of toxicity of ZnO-MnO2 NPs and suggests Zn-driven ROS generation. Together, the findings of this report suggest that ZnO (1%) doping impacts cellular biointeraction and the consequent toxicological outcomes of MnO2 NPs in Raw 264.7 cells.

Deciphering Vanadium Speciation in Smelting Ash and Adaptive Responses of Soil Microorganisms

Abundant smelting ash is discharged during pyrometallurgical vanadium (V) production. However, its associated V speciation and resultant ecological impact have remained elusive. In this study, V speciation in smelting ash and its influence on the metabolism of soil microorganisms were investigated. Smelting ashes from V smelters contained abundant V (19.6-115.9 mg/g). V(V) was the dominant species for soluble V, while solid V primarily existed in bioavailable forms. Previously unrevealed V nanoparticles (V-NPs) were prevalently detected, with a peak concentration of 1.3 × 1013 particles/g, a minimal size of 136.0 ± 0.6 nm, and primary constituents comprising FeVO4, VO2, and V2O5. Incubation experiments implied that smelting ash reshaped the soil microbial community. Metagenomic binning, gene transcription, and component quantification revealed that Microbacterium sp. and Tabrizicola sp. secreted extracellular polymeric substances through epsB and yhxB gene regulation for V-NPs aggregation to alleviate toxicity under aerobic operations. The V K-edge X-ray absorption near-edge structure (XANES) spectra suggested that VO2 NPs were oxidized to V2O5 NPs. In the anaerobic case, Comamonas sp. and Achromobacter sp. reduced V(V) to V(IV) for detoxification regulated by the napA gene. This study provides a deep understanding of the V speciation in smelting ash and microbial responses, inspiring promising bioremediation strategies to reduce its negative environmental impacts.

In vitro influence of PEG functionalized ZnO-CuO nanocomposites on bacterial growth

Polyethyleneglycol-coated biocompatible CuO-ZnO nanocomposites were fabricated hydrothermally varying Zn:Cu ratios as 1:1, 2:1, and 1:2, and their antibacterial activity was determined through the well diffusion method against the Gram-negative Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, and the Gram-positive Staphylococcus aureus. The minimum inhibitory concentration and the minimum bactericidal concentration values of the synthesized samples were determined. Subsequently, the time synergy kill assay was performed to elucidate the nature of the overall inhibitory effect against the aforementioned bacterial species. The mean zone of inhibition values for all four samples are presented. The inhibitory effect increased with increasing concentration of the nanocomposite (20, 40 and 60 mg/ml) on all the bacterial species except for S. aureus. According to the MBC/MIC ratio, ZnO was found to be bacteriostatic for E. coli and P. aeruginosa, and bactericidal for S. aureus and K. pneumoniae. Zn:Cu 2:1 was bactericidal on all bacterial species. A bacteriostatic effect was observed on E. coli and P. aeruginosa in the presence of Zn:Cu 1:1 whereas, it showed a bactericidal effect on S. aureus and K. pneumoniae. Zn:Cu 1:2 exhibited a bacteriostatic effect on E. coli while a bactericidal effect was observed for E. coli, P. aeruginosa, and K. pneumoniae. The metal oxide nanocomposites were found to be more sensitive towards the Gram-positive strain than the Gram-negative strains. Further, all the nanocomposites possess anti-oxidant activity as shown by the DPPH assay.

Computational Nanotoxicology Models for Environmental Risk Assessment of Engineered Nanomaterials

Although engineered nanomaterials (ENMs) have tremendous potential to generate technological benefits in numerous sectors, uncertainty on the risks of ENMs for human health and the environment may impede the advancement of novel materials. Traditionally, the risks of ENMs can be evaluated by experimental methods such as environmental field monitoring and animal-based toxicity testing. However, it is time-consuming, expensive, and impractical to evaluate the risk of the increasingly large number of ENMs with the experimental methods. On the contrary, with the advancement of artificial intelligence and machine learning, in silico methods have recently received more attention in the risk assessment of ENMs. This review discusses the key progress of computational nanotoxicology models for assessing the risks of ENMs, including material flow analysis models, multimedia environmental models, physiologically based toxicokinetics models, quantitative nanostructure-activity relationships, and meta-analysis. Several challenges are identified and a perspective is provided regarding how the challenges can be addressed.

Acoustic Shock Wave-Induced Solid-State Fusion of Nanoparticles: A Case Study of the Conversion of One-Dimensional Rod Shape into Three-Dimensional Honeycomb Nanostructures of CdO for High-Performance Energy Storage Materials

Herein, we describe the solid-state fusion of rod-shaped to honeycomb-shaped cadmium oxide particles (CdO NPs) caused by the process of repeated exposure to acoustic shock waves. Significant changes have been observed in structurally and morphologically dependent properties. For instance, at the 200-shocked condition, the high-pressure CdO-B2 phase is present as a secondary phase wherein all of the rod-shaped particles have been transformed into honeycomb-shaped CdO particles which possess comparatively higher specific-capacitance than CdO nanorods (NRs). The computed specific capacitance values for the 0, 100, and 200 shocked samples at a scan rate of 100 m V s-1 are computed to be 433, 415, and 583 F g-1, respectively. The second-stage decomposition temperature points of the CdO NPs have significantly increased in accordance with the morphological changes from rod to honeycomb patterns such that the values are 343, 526, and 534 °C, respectively, for 0, 100, and 200 shocked conditions. Note that such honeycomb nanostructured CdO particles by shock-wave processing have never been observed, to date. Due to the superior energy storage abilities as well as the spectacular high thermal stability of the honeycomb CdO nanostructures compared to CdO NRs, shocked CdO with honeycomb nanostructures can be considered as energy storage materials.

Polyphenol modified CuO nanorods capped by kappa-carrageenan for controlled paclitaxel release in furnishing targeted chemotherapy in breast carcinoma cells

The present work deals with the construction of a nanoscale system that can deliver chemotherapeutic agents to breast cancer cells in a controlled trend. The framework consists of gallic acid functionalized copper oxide nanoparticles (Ga@CuO) loaded with paclitaxel (PTX). To control the release of PTX, Ga@CuO NPs were coated with a red seaweed, Kappa carrageenan (K-carr) layer, and embellished with folic acid (FA) to enhance the targeted chemotherapy approach. Encapsulation efficiency and loading capacity of PTX loaded Ga@CuO@K-carr/FA NPs were estimated to be 84.58 ± 1.85 % and 13.2 ± 0.22 %, respectively. Moreover, the presence of strong cytotoxicity with an IC50 value of 12 ± 2.0 μg/mL and a high percentage of apoptotic cells (40.25 %) within the treated MCF-7 cells provided further evidence of the effective release of PTX from the loaded Ga@CuO@K-carr/FA. Consequently, it was discovered that the altered metabolic activity of cancer cells and the inhibition of cell proliferation are distinct features of apoptotic cell death induced by reactive oxygen species (ROS). Also, it was noted that treatment of MCF-7 cells with Ga@CuO-PTX@K-carr/FA caused a reduction in mitochondrial membrane potential that resulted in cellular apoptosis. Taken together, this study sheds light on the rational design of Ga@CuO-PTX@K-carr/FA, which offers a suitable candidate to transport drugs at an intracellular level for targeted chemotherapy.

Toxicity of Metal Oxide Nanoparticles: Looking through the Lens of Toxicogenomics

The impact of solubility on the toxicity of metal oxide nanoparticles (MONPs) requires further exploration to ascertain the impact of the dissolved and particulate species on response. In this study, FE1 mouse lung epithelial cells were exposed for 2-48 h to 4 MONPs of varying solubility: zinc oxide, nickel oxide, aluminum oxide, and titanium dioxide, in addition to microparticle analogues and metal chloride equivalents. Previously published data from FE1 cells exposed for 2-48 h to copper oxide and copper chloride were examined in the context of exposures in the present study. Viability was assessed using Trypan Blue staining and transcriptomic responses via microarray analysis. Results indicate material solubility is not the sole property governing MONP toxicity. Transcriptional signaling through the 'HIF-1α Signaling' pathway describes the response to hypoxia, which also includes genes associated with processes such as oxidative stress and unfolded protein responses and represents a conserved response across all MONPs tested. The number of differentially expressed genes (DEGs) in this pathway correlated with apical toxicity, and a panel of the top ten ranked DEGs was constructed (Hmox1, Hspa1a, Hspa1b, Mmp10, Adm, Serpine1, Slc2a1, Egln1, Rasd1, Hk2), highlighting mechanistic differences among tested MONPs. The HIF-1α pathway is proposed as a biomarker of MONP exposure and toxicity that can help prioritize MONPs for further evaluation and guide specific testing strategies.

Comparative toxicity assessment of individual, binary and ternary mixtures of SiO2, Fe3O4, and ZnO nanoparticles in freshwater microalgae, Scenedesmus obliquus: Exploring the role of dissolved ions

Metal oxide nanoparticles (NPs) are considered among the most prevalent engineered nanomaterials. To have a deeper understanding of the mode of action of multiple metal oxide nanoparticles in mixtures, we have used a unicellular freshwater microalga Scenedesmus obliquus as a model organism. The toxicity of silicon dioxide (SiO2), iron oxide (Fe3O4), and zinc oxide (ZnO) NPs was studied individually as well as in their binary (SiO2 + Fe3O4, Fe3O4 + ZnO, and ZnO + SiO2) and ternary (SiO2 + Fe3O4 + ZnO) combinations. The effects of metal ions from ZnO and Fe3O4 were investigated as well. The results observed from the study, showed that a significant amount of toxicity was contributed by the dissolved ions in the mixtures of the nanoparticles. Decreases in the cell viability, ROS generation, lipid peroxidation, antioxidant enzyme activity, and photosynthetic efficiency were analyzed. Among all the individual particles, ZnO NPs showed the maximum effects and increased the toxicities of the binary mixtures. The binary and ternary mixtures of the NPs clearly showed increased toxic effects in comparison with the individual entities. However, the ternary combination had lesser toxic effects than the binary combination of Fe3O4 + ZnO. The decline in cell viability and photosynthetic efficiency were strongly correlated with various oxidative stress biomarkers emphasizing the crucial role of reactive oxygen species in inducing the toxic effects. The findings from this study highlight the importance of evaluating the combinatorial effects of various metal oxide NPs as part of a comprehensive ecotoxicity assessment in freshwater microalgae.

A structure-activity approach towards the toxicity assessment of multicomponent metal oxide nanomaterials

The increase of human and environmental exposure to engineered nanomaterials (ENMs) due to the emergence of nanotechnology has raised concerns over their safety. The challenging nature of in vivo and in vitro toxicity assessment methods for ENMs, has led to emerging in silico techniques for ENM toxicity assessment, such as structure-activity relationship (SAR) models. Although such approaches have been extensively developed for the case of single-component nanomaterials, the case of multicomponent nanomaterials (MCNMs) has not been thoroughly addressed. In this paper, we present a SAR approach for the case metal and metal oxide MCNMs. The developed SAR framework is built using a dataset of 796 individual toxicity measurements for 340 different MCNMs, towards human cells, mammalian cells, and bacteria. The novelty of the approach lies in the multicomponent nature of the nanomaterials, as well as the size, diversity and heterogeneous nature of the dataset used. Furthermore, the approach used to calculate descriptors for surface loaded MCNMs, and the mechanistic insight provided by the model results can assist the understanding of MCNM toxicity. The developed models are able to correctly predict the toxic class of the MCNMs in the heterogeneous dataset, towards a wide range of human cells, mammalian cells and bacteria. Using the abovementioned approach, the principal toxicity pathways and mechanisms are identified, allowing a more holistic understanding of metal oxide MCNM toxicity.

Facile one-pot hydrothermal synthesis of a zinc oxide/curcumin nanocomposite with enhanced toxic activity against breast cancer cells

Zinc oxide/Curcumin (Zn(CUR)O) nanocomposites were prepared via hydrothermal treatment of Zn(NO3)2 in the presence of hexamethylenetetramine as a stabilizing agent and CUR as a bioactive element. Three ZnO : CUR ratios were investigated, namely 57 : 43 (Zn(CUR)O-A), 60 : 40 (Zn(CUR)O-B) and 81 : 19 (Zn(CUR)O-C), as assessed by thermogravimetric analyses, with an average hydrodynamic diameter of nanoaggregates in the range of 223 to 361 nm. The interaction of CUR with ZnO via hydroxyl and ketoenol groups (as proved by X-ray photoelectron spectroscopy analyses) was found to significantly modify the key properties of ZnO nanoparticles with the obtainment of a bilobed shape (as shown by scanning electron microscopy), and influenced the growth process of the composite nanoparticles as indicated by the varying particle sizes determined by powder X-ray diffraction. The efficacy of Zn(CUR)O as anticancer agents was evaluated on MCF-7 and MDA-MB-231 cancer cells, obtaining a synergistic activity with a cell viability depending on the CUR amount within the nanocomposite. Finally, the determination of reactive oxygen species production in the presence of Zn(CUR)O was used as a preliminary evaluation of the mechanism of action of the nanocomposites.

Gold-semiconductor nanohybrids as advanced phototherapeutics

Phototherapeutics is gaining momentum as a mainstream treatment for cancer, with gold-semiconductor nanocomposites showing promise as potent phototherapeutic agents due to their structural tunability, biocompatibility and functional diversity. Such nanohybrids possess plasmonic characteristics in the presence of gold and the catalytic nature of semiconductor units, as well as the unexpected physicochemical properties arising from the contact interface. This perspective provides an overview of the latest research on gold-semiconductor nanocomposites for photodynamic, photothermal and photocatalytic therapy. The relationship between the spatial configuration of these nanohybrids and their practical performance was explored to deliver comprehensive insights and guidance for the design and fabrication of novel composite nanoplatforms to enhance the efficiency of phototherapeutics, promoting the development of nanotechnology-based advanced biomedical applications.

An ancestral molecular response to nanomaterial particulates

The varied transcriptomic response to nanoparticles has hampered the understanding of the mechanism of action. Here, by performing a meta-analysis of a large collection of transcriptomics data from various engineered nanoparticle exposure studies, we identify common patterns of gene regulation that impact the transcriptomic response. Analysis identifies deregulation of immune functions as a prominent response across different exposure studies. Looking at the promoter regions of these genes, a set of binding sites for zinc finger transcription factors C2H2, involved in cell stress responses, protein misfolding and chromatin remodelling and immunomodulation, is identified. The model can be used to explain the outcomes of mechanism of action and is observed across a range of species indicating this is a conserved part of the innate immune system.

Physico-Chemical Approaches to Investigate Surface Hydroxyls as Determinants of Molecular Initiating Events in Oxide Particle Toxicity

The study of molecular recognition patterns is crucial for understanding the interactions between inorganic (nano)particles and biomolecules. In this review we focus on hydroxyls (OH) exposed at the surface of oxide particles (OxPs) which can play a key role in molecular initiating events leading to OxPs toxicity. We discuss here the main analytical methods available to characterize surface OH from a quantitative and qualitative point of view, covering thermogravimetry, titration, ζ potential measurements, and spectroscopic approaches (NMR, XPS). The importance of modelling techniques (MD, DFT) for an atomistic description of the interactions between membranes/proteins and OxPs surfaces is also discussed. From this background, we distilled a new approach methodology (NAM) based on the combination of IR spectroscopy and bioanalytical assays to investigate the molecular interactions of OxPs with biomolecules and membranes. This NAM has been already successfully applied to SiO₂ particles to identify the OH patterns responsible for the OxPs' toxicity and can be conceivably extended to other surface-hydroxylated oxides.

Copper oxide nanoparticles: In vitro and in vivo toxicity, mechanisms of action and factors influencing their toxicology

Copper oxide nanoparticles (CuO NPs) have received increasing interest due to their distinctive properties, including small particle size, high surface area, and reactivity. Due to these properties, their applications have been expanded rapidly in various areas such as biomedical properties, industrial catalysts, gas sensors, electronic materials, and environmental remediation. However, because of these widespread uses, there is now an increased risk of human exposure, which could lead to short- and long-term toxicity. This review addresses the underlying toxicity mechanisms of CuO NPs in cells which include reactive oxygen species generation, leaching of Cu ion, coordination effects, non-homeostasis effect, autophagy, and inflammation. In addition, different key factors responsible for toxicity, characterization, surface modification, dissolution, NPs dose, exposure pathways and environment are discussed to understand the toxicological impact of CuO NPs. In vitro and in vivo studies have shown that CuO NPs cause oxidative stress, cytotoxicity, genotoxicity, immunotoxicity, neurotoxicity, and inflammation in bacterial, algal, fish, rodents, and human cell lines. Therefore, to make CuO NPs a more suitable candidate for various applications, it is essential to address their potential toxic effects, and hence, more studies should be done on the long-term and chronic impacts of CuO NPs at different concentrations to assure the safe usage of CuO NPs.

Machine learning-driven QSAR models for predicting the mixture toxicity of nanoparticles

Research on theoretical prediction methods for the mixture toxicity of engineered nanoparticles (ENPs) faces significant challenges. The application of in silico methods based on machine learning is emerging as an effective strategy to address the toxicity prediction of chemical mixtures. Herein, we combined toxicity data generated in our lab with experimental data reported in the literature to predict the combined toxicity of seven metallic ENPs for Escherichia coli at different mixing ratios (22 binary combinations). We thereafter applied two machine learning (ML) techniques, support vector machine (SVM) and neural network (NN), and compared the differences in the ability to predict the combined toxicity by means of the ML-based methods and two component-based mixture models: independent action and concentration addition. Among 72 developed quantitative structure-activity relationship (QSAR) models by the ML methods, two SVM-QSAR models and two NN-QSAR models showed good performance. Moreover, an NN-based QSAR model combined with two molecular descriptors, namely enthalpy of formation of a gaseous cation and metal oxide standard molar enthalpy of formation, showed the best predictive power for the internal dataset (R²_test = 0.911, adjusted R²_test = 0.733, RMSE_test = 0.091, and MAE_test = 0.067) and for the combination of internal and external datasets (R²_test = 0.908, adjusted R²_test = 0.871, RMSE_test = 0.255, and MAE_test = 0.181). In addition, the developed QSAR models performed better than the component-based models. The estimation of the applicability domain of the selected QSAR models showed that all the binary mixtures in training and test sets were in the applicability domain. This study approach could provide a methodological and theoretical basis for the ecological risk assessment of mixtures of ENPs.

Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation

Decades of nanotoxicology research have generated extensive and diverse data sets. However, data is not equal to information. The question is how to extract critical information buried in vast data streams. Here we show that artificial intelligence (AI) and molecular simulation play key roles in transforming nanotoxicity data into critical information, i.e., constructing the quantitative nanostructure (physicochemical properties)-toxicity relationships, and elucidating the toxicity-related molecular mechanisms. For AI and molecular simulation to realize their full impacts in this mission, several obstacles must be overcome. These include the paucity of high-quality nanomaterials (NMs) and standardized nanotoxicity data, the lack of model-friendly databases, the scarcity of specific and universal nanodescriptors, and the inability to simulate NMs at realistic spatial and temporal scales. This review provides a comprehensive and representative, but not exhaustive, summary of the current capability gaps and tools required to fill these formidable gaps. Specifically, we discuss the applications of AI and molecular simulation, which can address the large-scale data challenge for nanotoxicology research. The need for model-friendly nanotoxicity databases, powerful nanodescriptors, new modeling approaches, molecular mechanism analysis, and design of the next-generation NMs are also critically discussed. Finally, we provide a perspective on future trends and challenges.

Lessons Learned from the Grouping of Chemicals to Assess Risks to Human Health

In analogy to the periodic system that groups elements by their similarity in structure and chemical properties, the hazard of chemicals can be assessed in groups having similar structures and similar toxicological properties. Here we review case studies of chemical grouping strategies that supported the assessment of hazard, exposure, and risk to human health. By the EU-REACH and the US-TSCA New Chemicals Program, structural similarity is commonly used as the basis for grouping, but that criterion is not always adequate and sufficient. Based on the lessons learned, we derive ten principles for grouping, including: transparency of the purpose, criteria, and boundaries of the group; adequacy of methods used to justify the group; and inclusion or exclusion of substances in the group by toxicological properties. These principles apply to initial grouping to prioritize further actions as well as to definitive grouping to generate data for risk assessment. Both can expedite effective risk management.

Lessons from the history of inorganic nanoparticles for inhalable diagnostics and therapeutics

The respiratory tract is one of the most accessible ones to exogenous nanoparticles, yet drug delivery by their means to it is made extraordinarily challenging because of the plexus of aerodynamic, hemodynamic and biomolecular factors at cellular and extracellular levels that synergistically define the safety and efficacy of this process. Here, the use of inorganic nanoparticles (INPs) for inhalable diagnostics and therapies of the lung is viewed through the prism of the history of studies on the interaction of INPs with the lower respiratory tract. The most conceptually and methodologically innovative and illuminative studies are referred to in the chronological order, as they were reported in the literature, and the trends in the progress of understanding this interaction of immense therapeutic and toxicological significance are being deduced from it. The most outstanding actual trends delineated include the diminishment of toxicity via surface functionalization, cell targeting, tagging and tracking via controlled binding and uptake, hybrid INP treatments, magnetic guidance, combined drug and gene delivery, use as adjuvants in inhalable vaccines, and other. Many of the understudied research directions, which have been accomplished by the nanostructured organic polymers in the pulmonary niche, are discussed. The progress in the use of INPs as inhalable diagnostics or therapeutics has been hampered by their well-recognized inflammatory potential and toxicity in the respiratory tract. However, the annual numbers of methodologically innovative studies have been on the rise throughout the past two decades, suggesting that this is a prolific direction of research, its comparatively poor commercial takings notwithstanding. Still, the lack of consensus on the effects of many INP compositions at low but therapeutically effective doses, the plethora of contradictory reports on ostensibly identical chemical compositions and NP properties, and the many cases of antagonism in combinatorial NP treatments imply that the rational design of inhalable medical devices based on INPs must rely on qualitative principles for the most part and embrace a partially stochastic approach as well. At the same time, the fact that the most studied INPs for pulmonary applications have been those with some of the thickest records of pulmonary toxicity, e.g., carbon, silver, gold, silica and iron oxide, is a silent call for the expansion of the search for new inorganic compositions for use in inhalable therapies to new territories.

A Novel Vision of Reinforcing Nanofibrous Masks with Metal Nanoparticles: Antiviral Mechanisms Investigation

Prevention of spreading viral respiratory disease, especially in case of a pandemic such as coronavirus disease of 2019 (COVID-19), has been proved impossible without considering obligatory face mask-wearing protocols for both healthy and contaminated populations. The widespread application of face masks for long hours and almost everywhere increases the risks of bacterial growth in the warm and humid environment inside the mask. On the other hand, in the absence of antiviral agents on the surface of the mask, the virus may have a chance to stay alive and be carried to different places or even put the wearers at risk of contamination when touching or disposing the masks. In this article, the antiviral activity and mechanism of action of some of the potent metal and metal oxide nanoparticles in the role of promising virucidal agents have been reviewed, and incorporation of them in an electrospun nanofibrous structure has been considered an applicable method for the fabrication of innovative respiratory protecting materials with upgraded safety levels.

Graphical Abstract

Cu-doped TiO2 nanoparticles improve local antitumor immune activation and optimize dendritic cell vaccine strategies

Nanoparticle-mediated cancer immunotherapy holds great promise, but more efforts are needed to obtain nanoformulations that result in a full scale activation of innate and adaptive immune components that specifically target the tumors. We generated a series of copper-doped TiO₂ nanoparticles in order to tune the kinetics and full extent of Cu²⁺ ion release from the remnant TiO₂ nanocrystals. Fine-tuning nanoparticle properties resulted in a formulation of 33% Cu-doped TiO₂ which enabled short-lived hyperactivation of dendritic cells and hereby promoted immunotherapy. The nanoparticles result in highly efficient activation of dendritic cells ex vivo, which upon transplantation in tumor bearing mice, exceeded the therapeutic outcomes obtained with classically stimulated dendritic cells. Efficacious but simple nanomaterials that can promote dendritic cancer cell vaccination strategies open up new avenues for improved immunotherapy and human health.

Possible Interaction between ZnS Nanoparticles and Phosphonates on Mediterranean Clams Ruditapes decussatus

This study aims to evaluate the toxicity of ZnS nanoparticles (ZnS NP50 = 50 µg/L and ZnS NP100 = 100 µg/L) and diethyl (3-cyano-1-hydroxy-2-methyl-1-phenylpropyl)phosphonate or P (P50 = 50 µg/L and P100 = 100 µg/L) in the clams Ruditapes decussatus using chemical and biochemical approaches. The results demonstrated that clams accumulate ZnS NPs and other metallic elements following exposure. Moreover, ZnS NPs and P separately lead to ROS overproduction, while a mixture of both contaminants has no effect. In addition, data showed that exposure to P100 resulted in increased levels of oxidative stress enzyme activities catalase (CAT) in the gills and digestive glands. A similar trend was also observed in the digestive glands of clams treated with ZnS100. In contrast, CAT activity was decreased in the gills at the same concentration. Exposure to ZnS100 and P100 separately leads to a decrease in acetylcholinesterase (AChE) levels in both gills and digestive glands. Thus, AChE and CAT after co-exposure to an environmental mixture of nanoparticles (ZnS100) and phosphonate (P100) did not show any differences between treated and non-treated clams. The outcome of this work certifies the use of biomarkers and chemical assay when estimating the effects of phosphonate and nanoparticles as part of an ecotoxicological assessment program. An exceptional focus was given to the interaction between ZnS NPs and P. The antioxidant activity of P has been demonstrated to have an additive effect on metal accumulation and antagonistic agents against oxidative stress in clams treated with ZnS NPs.

Novel Microwave Synthesis of Copper Oxide Nanoparticles and Appraisal of the Antibacterial Application

The exceptional characteristics of bio-synthesized copper oxide nanoparticles (CuO NPs), including high surface-to-volume ratio and high-profit strength, are of tremendous interest. CuO NPs have cytotoxic, catalytic, antibacterial, and antioxidant properties. Fruit peel extract has been recommended as a valuable alternative method due to the advantages of economic prospects, environment-friendliness, improved biocompatibility, and high biological activities, such as antioxidant and antimicrobial activities, as many physical and chemical methods have been applied to synthesize metal oxide NPs. In the presence of apple peel extract and microwave (MW) irradiation, CuO NPs are produced from the precursor CuCl₂. 2H₂O. With the help of TEM analysis, and BET surface area, the average sizes of the obtained NPs are found to be 25-40 nm. For use in antimicrobial applications, CuO NPs are appropriate. Disk diffusion tests were used to study the bactericidal impact in relation to the diameter of the inhibition zone, and an intriguing antibacterial activity was confirmed on both the Gram-positive bacterial pathogen Staphylococcus aureus and Gram-negative bacterial pathogen Escherichia coli. Moreover, CuO NPs did not have any toxic effect on seed germination. Thus, this study provides an environmentally friendly material and provides a variety of advantages for biomedical applications and environmental applications.

Antibacterial Nanomaterials: Mechanisms, Impacts on Antimicrobial Resistance and Design Principles

Antimicrobial resistance (AMR) is one of the biggest threats to the environment and health. AMR rapidly invalidates conventional antibiotics, and antimicrobial nanomaterials have been increasingly explored as alternatives. Interestingly, several antimicrobial nanomaterials show AMR-independent antimicrobial effects without detectable new resistance and have therefore been suggested to prevent AMR evolution. In contrast, some are found to trigger the evolution of AMR. Given these seemingly conflicting findings, a timely discussion of the two faces of antimicrobial nanomaterials is urgently needed. This review systematically compares the killing mechanisms and structure-activity relationships of antibiotics and antimicrobial nanomaterials. We then focus on nano-microbe interactions to elucidate the impacts of molecular initiating events on AMR evolution. Finally, we provide an outlook on future antimicrobial nanomaterials and propose design principles for the prevention of AMR evolution.

Enhanced osteoarthritis therapy by nanoengineered mesenchymal stem cells using biomimetic CuS nanoparticles loaded with plasmid DNA encoding TGF-β1

Mesenchymal stem cells (MSCs) therapy shows the potential benefits to relieve clinical symptoms of osteoarthritis (OA), but it is uncertain if it can repair articular cartilage lesions — the main pathology of OA. Here, we prepared biomimetic cupper sulfide@phosphatidylcholine (CuS@PC) nanoparticles (NPs) loaded with plasmid DNA (pDNA) encoding transforming growth factor-beta 1 (TGF-β1) to engineer MSCs for enhanced OA therapy via cartilage regeneration. We found that the NPs not only promoted cell proliferation and migration, but also presented a higher pDNA transfection efficiency relative to commercial transfection reagent lipofectamine 3000. The resultant CuS/TGF-β1@PC NP-engineered MSCs (termed CTP-MSCs) were better than pure MSCs in terms of chondrogenic gene expression, glycosaminoglycan deposition and type II collagen formation, favoring cartilage repair. Further, CTP-MSCs inhibited extracellular matrix degradation in interleukin-1β-induced chondrocytes. Consequently, intraarticular administration of CTP-MSCs significantly enhanced the repair of damaged cartilage, whereas pure MSCs exhibited very limited effects on cartilage regeneration in destabilization of the medial meniscus (DMM) surgical instability mice. Hence, this work provides a new strategy to overcome the limitation of current stem cell therapy in OA treatment through developing more effective nanoengineered MSCs.

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Biomimetic CuS nanoparticles (NPs) loaded with TGF-β1 pDNA are prepared for nanoengineering of MSCs.

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CuS/TGF-β1@PC NPs are more efficient than commercial transfection agent in terms of pDNA transfection.

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The NP-engineered CTP-MSCs exhibit enhanced migration, chondrogenesis and inhibition of ECM degradation.

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CTP-MSCs effectively treat osteoarthritis (OA) mice models via cartilage regeneration.

Influence of Impurities from Manufacturing Process on the Toxicity Profile of Boron Nitride Nanotubes

The toxicity of boron nitride nanotubes (BNNTs) has been the subject of conflicting reports, likely due to differences in the residuals and impurities that can make up to 30-60% of the material produced based on the manufacturing processes and purification employed. Four BNNTs manufactured by induction thermal plasma process with a gradient of BNNT purity levels achieved through sequential gas purification, water and solvent washing, allowed assessing the influence of these residuals/impurities on the toxicity profile of BNNTs. Extensive characterization including infrared and X-ray spectroscopy, thermogravimetric analysis, size, charge, surface area, and density captured the alteration in physicochemical properties as the material went through sequential purification. The material from each step is screened using acellular and in vitro assays for evaluating general toxicity, mechanisms of toxicity, and macrophage function. As the material increased in purity, there are more high-aspect-ratio particulates and a corresponding distinct increase in cytotoxicity, nuclear factor-κB transcription, and inflammasome activation. There is no alteration in macrophage function after BNNT exposure with all purity grades. The cytotoxicity and mechanism of screening clustered with the purity grade of BNNTs, illustrating that greater purity of BNNT corresponds to greater toxicity.

A Nanomedicine Structure-Activity Framework for Research, Development, and Regulation of Future Cancer Therapies

Despite their clinical success in drug delivery applications, the potential of theranostic nanomedicines is hampered by mechanistic uncertainty and a lack of science-informed regulatory guidance. Both the therapeutic efficacy and the toxicity of nanoformulations are tightly controlled by the complex interplay of the nanoparticle's physicochemical properties and the individual patient/tumor biology; however, it can be difficult to correlate such information with observed outcomes. Additionally, as nanomedicine research attempts to gradually move away from large-scale animal testing, the need for computer-assisted solutions for evaluation will increase. Such models will depend on a clear understanding of structure-activity relationships. This review provides a comprehensive overview of the field of cancer nanomedicine and provides a knowledge framework and foundational interaction maps that can facilitate future research, assessments, and regulation. By forming three complementary maps profiling nanobio interactions and pathways at different levels of biological complexity, a clear picture of a nanoparticle's journey through the body and the therapeutic and adverse consequences of each potential interaction are presented.

Predicting nanomaterials pulmonary toxicity in animals by cell culture models: Achievements and perspectives

Animal experiments are highly relevant models for the assessment of toxicological effects of engineered nanomaterials (ENMs), due to lack of biomonitoring and epidemiological studies. However, the expanding number of ENMs with different physico-chemical properties strains this approach, as there are ethical concerns and economical challenges with the use of animals in toxicology. There is an urgent need for cell culture models that predict the level of toxicological responses in vivo, consequently reducing or replacing the use of animals in nanotoxicology. However, there is still a limited number of studies on in vitro-in vivo correlation of toxicological responses following ENMs exposure. In this review, we collected studies that have compared in vitro and in vivo toxic effects caused by ENMs. We discuss the influence of cell culture models and exposure systems on the predictability of in vitro models to equivalent toxic effects in animal lungs after pulmonary exposure to ENMs. In addition, we discuss approaches to qualitatively or quantitatively compare the effects in vitro and in vivo. The magnitude of toxicological responses in cells that are exposed in submerged condition is not systematically different from the response in cells exposed in air-liquid interface systems, and there appears to be similar ENMs hazard ranking between the two exposure systems. Overall, we show that simple in vitro models with cells exposed to ENMs in submerged condition can be used to predict toxic effects in vivo, and identify future strategies to improve the associations between in vitro and in vivo ENMs-induced pulmonary toxicity. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials.

Pulmonary Toxicity and Proteomic Analysis in Bronchoalveolar Lavage Fluids and Lungs of Rats Exposed to Copper Oxide Nanoparticles

Copper oxide nanoparticles (CuO NPs) were intratracheally instilled into lungs at concentrations of 0, 0.15, and 1.5 mg/kg bodyweight to 7-week-old Sprague-Dawley rats. The cytotoxicity, immunotoxicity, and oxidative stress were evaluated, followed by proteomic analysis of bronchoalveolar lavage fluid (BALF) and lungs of rats. The CuO NPs-exposed groups revealed dose-dependent increases in total cells, polymorphonuclear leukocytes, lactate dyhydrogenase, and total protein levels in BALF. Inflammatory cytokines, including macrophage inflammatory protein-2 and tumor necrosis factor-α, were increased in the CuO NPs-treated groups. The expression levels of catalase, glutathione peroxidase-1, and peroxiredoxin-2 were downregulated, whereas that of superoxide dismutase-2 was upregulated in the CuO NPs-exposed groups. Five heat shock proteins were downregulated in rats exposed to high concentrations of CuO NPs. In proteomic analysis, 17 proteins were upregulated or downregulated, and 6 proteins were validated via Western blot analysis. Significant upregulation of 3-hydroxy-3-methylglutaryl-CoA synthase and fidgetin-like 1 and downregulation of annexin II, HSP 47 and proteasome α1 occurred in the CuO NPs exposed groups. Taken together, this study provides additional insight into pulmonary cytotoxicity and immunotoxicity as well as oxidative stress in rats exposed to CuO NPs. Proteomic analysis revealed potential toxicological biomarkers of CuO NPs, which also reveals the toxicity mechanisms of CuO NPs.

Advances and opportunities in nanoimaging agents for the diagnosis of inflammatory lung diseases

The development of rapid, noninvasive diagnostics to detect lung diseases is a great need after the COVID-2019 outbreak. The nanotechnology-based approach has improved imaging and facilitates the early diagnosis of inflammatory lung diseases. The multifunctional properties of nanoprobes enable better spatial-temporal resolution and a high signal-to-noise ratio in imaging. Targeted nanoimaging agents have been used to bind specific tissues in inflammatory lungs for early-stage diagnosis. However, nanobased imaging approaches for inflammatory lung diseases are still in their infancy. This review provides a solution-focused approach to exploring medical imaging technologies and nanoprobes for the detection of inflammatory lung diseases. Prospects for the development of contrast agents for lung disease detection are also discussed.

Cellular and molecular mechanisms of NiONPs toxicity on eel hepatocytes HEPA-E1: An illustration of the impact of Ni release from mining activity in New Caledonia

Anthropic activities such as open pit mining, amplify the natural erosion of metals contained in the soils, particularly in New Caledonia, leading to atmospheric emission of nickel oxide nanoparticles (NiONPs). These particles are produced during extraction end up in aquatic ecosystems through deposition or leaching in the rivers. Despite alarming freshwater Ni concentrations, only few studies have focused on the cellular and molecular mechanisms of NiONPs toxicity on aquatic organisms and particularly on eels. Those fish are known to be sensitive to metal contamination, especially their liver, which is a key organ for lipid metabolism, detoxification and reproduction. The objective of this study was to assess in vitro the cytotoxic effects of NiONPs on Anguilla japonica hepatocytes, HEPA-E1. HEPA-E1 were exposed to NiONPs (0.5-5 μg/cm²) for 4 or 24 h. Several endpoints were studied: (i) viability, (ii) ROS production, SOD activity and selected anti-oxidant genes expression, (iii) inflammation, (iv) calcium signalling, (v) mitochondrial function and (vi) apoptosis. The results evidenced that NiONPs induce a decrease of cell viability and an increase in oxidative stress with a significant superoxide anion production. An increase of mitochondrial calcium concentration and a decrease of mitochondrial membrane potential were observed, leading to apoptosis. These results underline the potential toxic impact of NiONPs on eels living in mining areas. Therefore, eel exposure to NiONPs can affect their migration and reproduction in New Caledonia.

Antagonistic Skin Toxicity of Co-Exposure to Physical Sunscreen Ingredients Zinc Oxide and Titanium Dioxide Nanoparticles

Being the main components of physical sunscreens, zinc oxide nanoparticles (ZnO NPs) and titanium dioxide nanoparticles (TiO₂ NPs) are often used together in different brands of sunscreen products with different proportions. With the broad use of cosmetics containing these nanoparticles (NPs), concerns regarding their joint skin toxicity are becoming more and more prominent. In this study, the co-exposure of these two NPs in human-derived keratinocytes (HaCaT) and the in vitro reconstructed human epidermis (RHE) model EpiSkin was performed to verify their joint skin effect. The results showed that ZnO NPs significantly inhibited cell proliferation and caused deoxyribonucleic acid (DNA) damage in a dose-dependent manner to HaCaT cells, which could be rescued with co-exposure to TiO₂ NPs. Further mechanism studies revealed that TiO₂ NPs restricted the cellular uptake of both aggregated ZnO NPs and non-aggregated ZnO NPs and meanwhile decreased the dissociation of Zn²⁺ from ZnO NPs. The reduced intracellular Zn²⁺ ultimately made TiO₂ NPs perform an antagonistic effect on the cytotoxicity caused by ZnO NPs. Furthermore, these joint skin effects induced by NP mixtures were validated on the epidermal model EpiSkin. Taken together, the results of the current research contribute new insights for understanding the dermal toxicity produced by co-exposure of different NPs and provide a valuable reference for the development of formulas for the secure application of ZnO NPs and TiO₂ NPs in sunscreen products.

NanoMixHamster: a web-based tool for predicting cytotoxicity of TiO2-based multicomponent nanomaterials toward Chinese hamster ovary (CHO-K1) cells

Nano-QSAR models can be effectively used for prediction of the biological activity of nanomaterials that have not been experimentally tested before. However, their use is associated with the need to have appropriate knowledge and skills in chemoinformatics. Thus, they are mainly aimed at specialists in the field. This significantly limits the potential group of recipients of the developed solutions. In this perspective, the purpose of the presented research was to develop an easily accessible and user-friendly web-based application that could enable the prediction of TiO₂-based multicomponent nanomaterials cytotoxicity toward Chinese Hamster Ovary (CHO-K1) cells. The graphical user interface is clear and intuitive and the only information required from the user is the type and concentration of the metals which will be modifying TiO₂-based nanomaterial. Thanks to this, the application will be easy to use not only by cheminformatics but also by specialists in the field of nanotechnology or toxicology, who will be able to quickly predict cytotoxicity of desired nanoclusters. We have performed case studies to demonstrate the features and utilities of developed application. The NanoMixHamster application is freely available at https://nanomixhamster.cloud.nanosolveit.eu/.

Reactive Oxygen Species Formed by Metal and Metal Oxide Nanoparticles in Physiological Media—A Review of Reactions of Importance to Nanotoxicity and Proposal for Categorization

Diffusely dispersed metal and metal oxide nanoparticles (NPs) can adversely affect living organisms through various mechanisms and exposure routes. One mechanism behind their toxic potency is their ability to generate reactive oxygen species (ROS) directly or indirectly to an extent that depends on the dose, metal speciation, and exposure route. This review provides an overview of the mechanisms of ROS formation associated with metal and metal oxide NPs and proposes a possible way forward for their future categorization. Metal and metal oxide NPs can form ROS via processes related to corrosion, photochemistry, and surface defects, as well as via Fenton, Fenton-like, and Haber–Weiss reactions. Regular ligands such as biomolecules can interact with metallic NP surfaces and influence their properties and thus their capabilities of generating ROS by changing characteristics such as surface charge, surface composition, dissolution behavior, and colloidal stability. Interactions between metallic NPs and cells and their organelles can indirectly induce ROS formation via different biological responses. H₂O₂ can also be generated by a cell due to inflammation, induced by interactions with metallic NPs or released metal species that can initiate Fenton(-like) and Haber–Weiss reactions forming various radicals. This review discusses these different pathways and, in addition, nano-specific aspects such as shifts in the band gaps of metal oxides and how these shifts at biologically relevant energies (similar to activation energies of biological reactions) can be linked to ROS production and indicate which radical species forms. The influences of kinetic aspects, interactions with biomolecules, solution chemistry (e.g., Cl⁻ and pH), and NP characteristics (e.g., size and surface defects) on ROS mechanisms and formation are discussed. Categorization via four tiers is suggested as a way forward to group metal and metal oxide NPs based on the ROS reaction pathways that they may undergo, an approach that does not include kinetics or environmental variations. The criteria for the four tiers are based on the ability of the metallic NPs to induce Fenton(-like) and Haber–Weiss reactions, corrode, and interact with biomolecules and their surface catalytic properties. The importance of considering kinetic data to improve the proposed categorization is highlighted.

Nano-read-across predictions of toxicity of metal oxide engineered nanoparticles (MeOx ENPS) used in nanopesticides to BEAS-2B and RAW 264.7 cells

The demand for nutrients and new technologies has increased with population growth. The agro-technological revolution with metal oxide engineered nanoparticles (MeOx ENPs) has the potential to reform the resilient agricultural system while maintaining the security of food. When utilized extensively, MeOx ENPs may have unintended toxicological effects on both target and non-targeted species. Since limited information about nanopesticides' pernicious effects is available, in silico modeling can be done to explore these issues. Hence, in the present work, we have applied computational modeling to explore the influence of metal oxide nanoparticles on the toxicity of bronchial epithelial (BEAS-2B) and murine myeloid (RAW 264.7) cells to bridge the data gap relating to the toxicity of MeOx NPs. Initially, partial least squares (PLS) regression models were developed applying the Small Dataset Modeler software (http://teqip.jdvu.ac.in/QSAR_Tools/DTCLab/) using four datasets having effective concentration (EC₅₀%) as the endpoints and employing only periodic table descriptors. To further explore the predictions, we applied a read-across approach using the descriptors selected in the QSAR models. Also, the inter-endpoint cytotoxicity relationship modeling (quantitative toxicity-toxicity relationship or QTTR) was conducted. It was found that the result obtained by nano-read-across provided a similar level of accuracy as provided by QSAR. The information derived from the PLS models of both the cell lines suggested that metal cation formation, and bond-forming capacity influence the toxicity whereas the presence of metal has an influential impact on the ecotoxicological effects. Thus, it is feasible to design safe nanopesticides that could be more effective than conventional analogs.

Use of dissociation degree in lysosomes to predict metal oxide nanoparticle toxicity in immune cells: Machine learning boosts nano-safety assessment

Potential immune responses resulting from exposure to metal oxide nanoparticles (MeONPs) have been the subject of intensive discussion in the last decade. Despite the extensive use of MeONPs in several applications, their toxic effects on immune cells have rarely been predicted in silico because of the complexity of immune responses and the complicated properties of MeONPs. In the present study, machine learning (ML) methods coupled with high-throughput in vitro bioassays were used to develop models for predicting the toxicity of MeONPs in immune cells. An ML model with a high prediction accuracy (97% and 96% in the training and test sets, respectively) was constructed by resolving the class imbalance problem in training and applying an ensembled algorithm. Further, to verify the model, MeONPs outside the scope of the datasets were selected to examine their cytotoxicity experimentally. The model was validated against independent MeONPs, with an accuracy of 91%. ML methods coupled with intracellular imaging revealed that the toxic ions released in the lysosome were an important determinant of toxicity in immune cells. Furthermore, ζ-potential, electronegativity, and size are crucial factors for predicting nanotoxicity. We believe the established modeling framework will provide useful insights for designing and applying safe nanoparticles and facilitating decision-making for environmental and health protection.

Copper oxide nanoparticles trigger macrophage cell death with misfolding of Cu/Zn superoxide dismutase 1 (SOD1)

Background

Copper oxide (CuO) nanoparticles (NPs) are known to trigger cytotoxicity in a variety of cell models, but the mechanism of cell death remains unknown. Here we addressed the mechanism of cytotoxicity in macrophages exposed to CuO NPs versus copper chloride (CuCl₂).

Methods

The mouse macrophage cell line RAW264.7 was used as an in vitro model. Particle uptake and the cellular dose of Cu were investigated by transmission electron microscopy (TEM) and inductively coupled plasma mass spectrometry (ICP-MS), respectively. The deposition of Cu in lysosomes isolated from macrophages was also determined by ICP-MS. Cell viability (metabolic activity) was assessed using the Alamar Blue assay, and oxidative stress was monitored by a variety of methods including a luminescence-based assay for cellular glutathione (GSH), and flow cytometry-based detection of mitochondrial superoxide and mitochondrial membrane potential. Protein aggregation was determined by confocal microscopy using an aggresome-specific dye and protein misfolding was determined by circular dichroism (CD) spectroscopy. Lastly, proteasome activity was investigated using a fluorometric assay.

Results

We observed rapid cellular uptake of CuO NPs in macrophages with deposition in lysosomes. CuO NP-elicited cell death was characterized by mitochondrial swelling with signs of oxidative stress including the production of mitochondrial superoxide and cellular depletion of GSH. We also observed a dose-dependent accumulation of polyubiquitinated proteins and loss of proteasomal function in CuO NP-exposed cells, and we could demonstrate misfolding and mitochondrial translocation of superoxide dismutase 1 (SOD1), a Cu/Zn-dependent enzyme that plays a pivotal role in the defense against oxidative stress. The chelation of copper ions using tetrathiomolybdate (TTM) prevented cell death whereas inhibition of the cellular SOD1 chaperone aggravated toxicity. Moreover, CuO NP-triggered cell death was insensitive to the pan-caspase inhibitor, zVAD-fmk, and to wortmannin, an inhibitor of autophagy, implying that this was a non-apoptotic cell death. ZnO NPs, on the other hand, triggered autophagic cell death.

Conclusions

CuO NPs undergo dissolution in lysosomes leading to copper-dependent macrophage cell death characterized by protein misfolding and proteasomal insufficiency. Specifically, we present novel evidence for Cu-induced SOD1 misfolding which accords with the pronounced oxidative stress observed in CuO NP-exposed macrophages. These results are relevant for our understanding of the consequences of inadvertent human exposure to CuO NPs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12989-022-00467-w.