Multi-hierarchical profiling the structure-activity relationships of engineered nanomaterials at nano-bio interfaces

Dynamic QSAR modeling for predicting in vivo genotoxicity and inflammation induced by nanoparticles and advanced materials: a time-dose-property/response approach

Predicting the health risks of nanoparticles (NPs) and advanced materials (AdMa) is a critical challenge. Due to the complexity and time-consuming nature of experimental testing, there is a reliance on in silico methods such as quantitative structure-activity relationship (QSAR), which, while effective, often fail to capture the dynamic nature of material activity over time-essential for reliable risk assessment. This study develops dynamic QSAR models using machine learning to predict toxicological responses, such as inflammation and genotoxicity, following pulmonary exposure to 39 AdMa across various post-exposure time points and dose levels. By incorporating exposure time, administered dose, and material properties as independent variables, we successfully developed time-dose-property/response models capable of predicting AdMa-induced in vivo genotoxicity in bronchoalveolar lavage fluid cells, lung and liver tissue, and inflammation in terms of neutrophil influx into the lungs of mice. Key factors driving AdMa-induced toxicity were identified, including exposure dose, post-exposure duration time, aspect ratio, surface area, reactive oxygen species generation, and metal ion release. The time-dose-property/response modeling paradigm presented here provides a practical and robust approach for predicting in vivo genotoxicity and inflammation and supports the comprehensive risk assessment of morphologically diverse AdMa.

Genetic modulation of rare earth nanoparticle biotransformation shapes biological outcomes

The biotransformation of nanoparticles plays a crucial role in determining their biological fate and responses. Although a few engineering strategies (e.g., surface functionalization and shape control) have been employed to regulate the fate of nanoparticles, the genetic control of nanoparticle biotransformation remains an unexplored avenue. Herein, we utilized a CRISPR-based genome-scale knockout approach to identify genes involved in the biotransformation of rare earth oxide (REO) nanoparticles. We found that the biotransformation of REOs in lysosomes could be genetically controlled via SMPD1. Specifically, suppression of SMPD1 inhibited the transformation of La2O3 into sea urchin-shaped structures, thereby protecting against lysosomal damage, proinflammatory cytokine release, pyroptosis and RE-induced pneumoconiosis. Overall, our study provides insight into how to control the biological fate of nanomaterials.

Programmable DNA-Based Nanodevices for Next-Generation Clinical and Healthcare Applications

Deoxyribonucleic acid (DNA) nanotechnology has brought an unparalleled set of possibilities for self-assembled structures emerging as an independent branch of synthetic biology. The field of science uses the molecular properties of DNA to build nanoparticles and nanodevices that have the potential to bring breakthroughs in medical science. On the one hand, their biocompatibility, precision, synthetic ease, and programmability make them an ideal choice in drug delivery and healthcare. On the other, the lack of proper biodistribution profiles, stability inside the system, enzymatic cleavage, immune recognition, and translational barriers are some of the hurdles it faces. Many recent technological advancements are in progress to tackle these challenges, while some already have been used. These tools and technologies need to be understood and studied for the successful transition of these intelligent DNA nanostructures (DNs) to healthcare applications. This review thus, highlights some of the challenges being faced by the DNs in healthcare. Additionally, it provides an overview of the recent trends in using these devices in disease detection and remission and finally talks about the future scope and opportunities for an effective transition from bench to bedside.

Multimodal feature fusion machine learning for predicting chronic injury induced by engineered nanomaterials

Concerns regarding chronic injuries (e.g., fibrosis and carcinogenesis) induced by nanoparticles raised public health concerns and need to be rapidly assessed in hazard identification. Although in silico analysis is commonly used for risk assessment of chemicals, predicting chronic in vivo nanotoxicity remains challenging due to the intricate interactions at multiple interfaces like nano-biofluids and nano-subcellular organelles. Herein, we develop a multimodal feature fusion analysis framework to predict the fibrogenic potential of metal oxide nanoparticles (MeONPs) in female mice. Treating each nano-bio interface as an independent entity, eighty-seven features derived from MeONP-lung interactions are used to develop a machine learning-based predictive framework for lung fibrosis. We identify cell damage and cytokine (IL-1β and TGF-β1) production in macrophages and epithelial cells as key events closely associated with particle size, surface charge, and lysosome interactions. Experimental validations show that the developed in silico model has 85% accuracy. Our findings demonstrate the potential usefulness of this predictive model for risk assessment of nanomaterials and in assisting regulatory decision-making. While the model is developed based on 52 MeONPs, further validation using a larger nanoparticle library is necessary to confirm its broader applicability.

Machine learning models for quantitatively prediction of toxicity in macrophages induced by metal oxide nanoparticles

As nanotechnology advances, metal oxide nanoparticles (MeONPs) increasingly come into contact with humans. The inhaled MeONPs cannot be effectively cleared by cilia or lung mucus. In the last decade, potential immune toxicity arising from exposure to MeONPs has been extensively debated, as lung macrophage is the main pathway for cleaning inhaled exogenous particles. However, their toxicity on lung macrophages has rarely been quantitatively predicted in silico due to the complexity of responses in macrophages and the intricate properties of MeONPs. Here, machine learning (ML) methods were used to establish models for quantitatively predicting the toxicity of MeONPs in macrophages. A multidimensional dataset including 240 data points covering the lethality, biochemical behaviors, and physicochemical properties of 30 MeONPs was obtained. ML models based on different algorithms with high prediction accuracy were constructed by addressing the issue of class imbalance during the training process. The models were verified by 10-fold cross-validation and external validation. The best-performed model has an R2 of 0.85 and 0.90 in the 10-fold cross-validation and external test set, respectively; and Q2 of 0.88 and 0.90 in the 10-fold cross-validation and test set, respectively. Five parameters that impact toxicity were identified and the toxicity mechanisms were elucidated by ML analysis. The prediction results can be used to fill the data gap in the risk assessment of nanomaterials. The framework offers valuable insights for designing and utilizing safe nanoparticles, as well as aiding in decision-making processes aimed at protecting the environment and public health.

Nanomaterials-Induced Pyroptosis: Advancing Novel Therapeutic Pathways in Nanomedicine

Pyroptosis, a form of programmed cell death characterized by cell lysis and inflammation, has significant implications for disease treatment. Nanomaterials (NMs), with their unique physicochemical properties, can precisely modulate pyroptosis, offering novel and intelligent therapeutic strategies for cancer, infectious diseases, and chronic inflammatory conditions with targeted activation and reduced systemic toxicity. This review explores the mechanisms by which NMs regulate pyroptosis, comparing molecular and NM inducers, and examines the role of intrinsic properties such as size, shape, surface charge, and chemical composition in these processes. It also discusses the balance between the beneficial and adverse effects of NM-induced pyroptosis, highlighting targeted delivery systems, surface modifications, and controlled activation as strategies to enhance therapeutic efficacy and intelligence while minimizing toxicity. Notably, mRNA-based nanomedicine can be precisely and intelligently designed to activate pyroptosis, achieving desired therapeutic outcomes tailored to the evolving microenvironment of diseases. By understanding these interactions, the therapeutic potential of NMs can be harnessed to develop innovative treatments and manage pyroptosis-associated diseases safely, effectively, and intelligently. This review also highlights their transformative potential in clinical applications.

Deciphering key nano-bio interface descriptors to predict nanoparticle-induced lung fibrosis

BACKGROUND

The advancement of nanotechnology underscores the imperative need for establishing in silico predictive models to assess safety, particularly in the context of chronic respiratory afflictions such as lung fibrosis, a pathogenic transformation that is irreversible. While the compilation of predictive descriptors is pivotal for in silico model development, key features specifically tailored for predicting lung fibrosis remain elusive. This study aimed to uncover the essential predictive descriptors governing nanoparticle-induced pulmonary fibrosis.

METHODS

We conducted a comprehensive analysis of the trajectory of metal oxide nanoparticles (MeONPs) within pulmonary systems. Two biological media (simulated lung fluid and phagolysosomal simulated fluid) and two cell lines (macrophages and epithelial cells) were meticulously chosen to scrutinize MeONP behaviors. Their interactions with MeONPs, also referred to as nano-bio interactions, can lead to alterations in the properties of the MeONPs as well as specific cellular responses. Physicochemical properties of MeONPs were assessed in biological media. The impact of MeONPs on cell membranes, lysosomes, mitochondria, and cytoplasmic components was evaluated using fluorescent probes, colorimetric enzyme substrates, and ELISA. The fibrogenic potential of MeONPs in mouse lungs was assessed by examining collagen deposition and growth factor release. Random forest classification was employed for analyzing in chemico, in vitro and in vivo data to identify predictive descriptors.

RESULTS

The nano-bio interactions induced diverse changes in the 4 characteristics of MeONPs and had variable effects on the 14 cellular functions, which were quantitatively evaluated in chemico and in vitro. Among these 18 quantitative features, seven features were found to play key roles in predicting the pro-fibrogenic potential of MeONPs. Notably, IL-1β was identified as the most important feature, contributing 27.8% to the model's prediction. Mitochondrial activity (specifically NADH levels) in macrophages followed closely with a contribution of 17.6%. The remaining five key features include TGF-β1 release and NADH levels in epithelial cells, dissolution in lysosomal simulated fluids, zeta potential, and the hydrodynamic size of MeONPs.

CONCLUSIONS

The pro-fibrogenic potential of MeONPs can be predicted by combination of key features at nano-bio interfaces, simulating their behavior and interactions within the lung environment. Among the 18 quantitative features, a combination of seven in chemico and in vitro descriptors could be leveraged to predict lung fibrosis in animals. Our findings offer crucial insights for developing in silico predictive models for nano-induced pulmonary fibrosis.

Chemical screens for particle-induced macrophage death identifies kinase inhibitors of phagocytosis as targets for toxicity

BACKGROUND

Nanoparticles are increasingly being used in medicine, cosmetics, food, and manufacturing. However, potential toxicity may limit the use of newly engineered nanoparticles. Prior studies have identified particle characteristics that are predictive of toxicity, although the mechanisms responsible for toxicity remain largely unknown. Nanoparticle treatment in cell culture, combined with high-throughput chemical screen allows for systematic perturbations of thousands of molecular targets against potential pathways of toxicity. The resulting data matrix, called chemical compendium, can provide insights into the mechanism of toxicity as well as help classify nanoparticles based on toxicity pathway.

RESULTS

We performed unbiased screens of 1280 bioactive chemicals against a panel of four particles, searching for inhibitors of macrophage toxicity. Our hit compounds clustered upon inhibitors of kinases involved in phagocytosis, including focal adhesion kinase (FAK), with varying specificity depending on particles. Interestingly, known inhibitors of cell death including NLRP3 inflammasome inhibitor were unable to suppress particle-induced macrophage death for many of the particles. By searching for upstream receptors of kinases, we identified Cd11b as one of the receptors involved in recognizing a subset of particles. We subsequently used these hit compounds and antibodies to further characterize a larger panel of particles and identified hydrodynamic size as an important particle characteristic in Cd11b-mediated particle uptake and toxicity.

CONCLUSIONS

Our chemical compendium and workflow can be expanded across cell types and assays to characterize the toxicity mechanism of newly engineered nanoparticles. The data in their current form can also be analyzed to help design future high-throughput screening for nanoparticle toxicity.

Engineering Thermally Reduced Graphene Oxide for Synchronously Enhancing Photocatalytic Activity and Photothermal Effect

The structural composition of reduced graphene oxide (rGO) can be modified and controlled by appropriate reduction methods to modulate its electronic structure, rendering it a versatile platform for tailoring optoelectronic and catalytic properties. Nevertheless, it is uncommon to concurrently amplify the photocatalytic and photothermal effects when regulating and utilizing pure rGO. Here, we investigate the impact of structural variations in thermally reduced graphene oxide (TGO) on its photocatalytic and photothermal properties. Various characterization results demonstrate that appropriate thermal reduction facilitates the preservation and transformation of oxygenated groups and structure defects, which in turn encourages the formation of reactive carbon radicals and discrete graphitic domains, thereby strengthening the activation of molecular oxygen and the plasmonic photothermal effect under near-infrared (NIR) light irradiation. Moreover, the optimized TGOs exhibit efficient sterilization with NIR irradiation due to enhanced photocatalytic activities and photothermal effects. This work highlights the potential for developing photocatalytic and photothermal rGO-based materials through structural engineering.

Synthetic vectors for activating the driving axis of ferroptosis

Ferroptosis is a promising strategy for cancer therapy, with numerous inhibitors of its braking axes under investigation as potential drugs. However, few studies have explored the potential of activating the driving axes to induce ferroptosis. Herein, phosphatidylcholine peroxide decorating liposomes (LIPPCPO) are synthesized to induce ferroptosis by targeting divalent metal transporter 1 (DMT1). LIPPCPO is found to boost lysosomal Fe2+ efflux by inducing cysteinylation of lysosomal DMT1, resulting in glutathione peroxidase 4 (GPX4) suppression, glutathione depletion and ferroptosis in breast cancer cells and xenografts. Importantly, LIPPCPO induced ferroptotic cell death is independent of acquired resistance to radiation, chemotherapy, or targeted agents in 11 cancer cell lines. Furthermore, a strong synergistic ferroptosis effect is observed between LIPPCPO and an FDA-approved drug, artesunate, as well as X rays. The formula of LIPPCPO encapsulating artesunate significantly inhibits tumor growth and metastasis and improves the survival rate of breast cancer-bearing female mice. These findings provide a distinct strategy for inducing ferroptosis and highlight the potential of LIPPCPO as a vector to synergize the therapeutic effects of conventional ferroptosis inducers.

Bioinformatics and machine learning to support nanomaterial grouping

Nanomaterials (NMs) offer plenty of novel functionalities. Moreover, their physicochemical properties can be fine-tuned to meet the needs of specific applications, leading to virtually unlimited numbers of NM variants. Hence, efficient hazard and risk assessment strategies building on New Approach Methodologies (NAMs) become indispensable. Indeed, the design, the development and implementation of NAMs has been a major topic in a substantial number of research projects. One of the promising strategies that can help to deal with the high number of NMs variants is grouping and read-across. Based on demonstrated structural and physicochemical similarity, NMs can be grouped and assessed together. Within an established NM group, read-across may be performed to fill in data gaps for data-poor variants using existing data for NMs within the group. Establishing a group requires a sound justification, usually based on a grouping hypothesis that links specific physicochemical properties to well-defined hazard endpoints. However, for NMs these interrelationships are only beginning to be understood. The aim of this review is to demonstrate the power of bioinformatics with a specific focus on Machine Learning (ML) approaches to unravel the NM Modes-of-Action (MoA) and identify the properties that are relevant to specific hazards, in support of grouping strategies. This review emphasizes the following messages: 1) ML supports identification of the most relevant properties contributing to specific hazards; 2) ML supports analysis of large omics datasets and identification of MoA patterns in support of hypothesis formulation in grouping approaches; 3) omics approaches are useful for shifting away from consideration of single endpoints towards a more mechanistic understanding across multiple endpoints gained from one experiment; and 4) approaches from other fields of Artificial Intelligence (AI) like Natural Language Processing or image analysis may support automated extraction and interlinkage of information related to NM toxicity. Here, existing ML models for predicting NM toxicity and for analyzing omics data in support of NM grouping are reviewed. Various challenges related to building robust models in the field of nanotoxicology exist and are also discussed.

Nano-microflora Interaction Inducing Pulmonary Inflammation by Pyroptosis

Antimicrobial nanomaterials frequently induce inflammatory reactions within lung tissues and prompt apoptosis in lung cells, yielding a paradox due to the inherent anti-inflammatory character of apoptosis. This paradox accentuates the elusive nature of the signaling cascade underlying nanoparticle (NP)-induced pulmonary inflammation. In this study, we unveil the pivotal role of nano-microflora interactions, serving as the crucial instigator in the signaling axis of NP-induced lung inflammation. Employing pulmonary microflora-deficient mice, we provide compelling evidence that a representative antimicrobial nanomaterial, silver (Ag) NPs, triggers substantial motility impairment, disrupts quorum sensing, and incites DNA leakage from pulmonary microflora. Subsequently, the liberated DNA molecules recruit caspase-1, precipitating the release of proinflammatory cytokines and activating N-terminal gasdermin D (GSDMD) to initiate pyroptosis in macrophages. This pyroptotic cascade culminates in the emergence of severe pulmonary inflammation. Our exploration establishes a comprehensive mechanistic axis that interlinks the antimicrobial activity of Ag NPs, perturbations in pulmonary microflora, bacterial DNA release, macrophage pyroptosis, and consequent lung inflammation, which helps to gain an in-depth understanding of the toxic effects triggered by environmental NPs.

The toxicity of nanoparticles and their interaction with cells: an in vitro metabolomic perspective

Nowadays, nanomaterials (NMs) are widely present in daily life due to their significant benefits, as demonstrated by their application in many fields such as biomedicine, engineering, food, cosmetics, sensing, and energy. However, the increasing production of NMs multiplies the chances of their release into the surrounding environment, making human exposure to NMs inevitable. Currently, nanotoxicology is a crucial field, which focuses on studying the toxicity of NMs. The toxicity or effects of nanoparticles (NPs) on the environment and humans can be preliminary assessed in vitro using cell models. However, the conventional cytotoxicity assays, such as the MTT assay, have some drawbacks including the possibility of interference with the studied NPs. Therefore, it is necessary to employ more advanced techniques that provide high throughput analysis and avoid interferences. In this case, metabolomics is one of the most powerful bioanalytical strategies to assess the toxicity of different materials. By measuring the metabolic change upon the introduction of a stimulus, this technique can reveal the molecular information of the toxicity induced by NPs. This provides the opportunity to design novel and efficient nanodrugs and minimizes the risks of NPs used in industry and other fields. Initially, this review summarizes the ways that NPs and cells interact and the NP parameters that play a role in this interaction, and then the assessment of these interactions using conventional assays and the challenges encountered are discussed. Subsequently, in the main part, we introduce the recent studies employing metabolomics for the assessment of these interactions in vitro.

Oral feeding of nanoplastics affects brain function of mice by inducing macrophage IL-1 signal in the intestine

Nanoplastics (NPs) as contaminants in food and water have drawn increasing public attention. However, little is known about how NPs shape the gut immune landscape after injection. In this study, we fabricate NPs (∼500 nm) and microplastics (MPs) (∼2 μm) and evaluate their in vivo effects by feeding them to mice. The results suggest that NPs show a better ability to induce gut macrophage activation than MPs. In addition, NPs trigger gut interleukin-1 (IL-1)-producing macrophage reprogramming via inducing lysosomal damage. More importantly, IL-1 signaling from the intestine can affect brain immunity, leading to microglial activation and Th17 differentiation, all of which correlates with a decline in cognitive and short-term memory in NP-fed mice. Thus, this study provides insight into the mechanism of action of the gut-brain axis, delineates the way NPs reduce brain function, and highlights the importance of fixing the plastic pollution problem worldwide.

Synthesis, applications, toxicity and toxicity mechanisms of silver nanoparticles: A review

Silver nanoparticles (AgNPs) have become one of the most popular objects of study for the past few decades. The ability to design AgNPs through different synthetic methods according to the application area and desired features is their advantage in many applications. Green synthesis of silver nanoparticles has become one of the most potential synthesis methods. Because of their strong antibacterial activity, AgNPs have been used in a wide range of applications, such as food packaging and medical products and devices. With the increasing application of AgNPs, it is becoming necessary for a better understanding of the toxicity of AgNPs and their potential mechanism of toxicity. In the review, we first describe the synthetic methods of AgNPs. The application of AgNPs in the field is then briefly described. The toxicity of AgNPs and their potential toxicity mechanisms are discussed.

The valence state of iron-based nanomaterials determines the ferroptosis potential in a zebrafish model

Many nanomaterials containing different valences of iron have been designed for applications in biomedicine, energy, catalyzers, nanoenzymes, and so on. However, the toxic effects of the valence state of iron in iron-based nanomaterials are still unclear. Here, three different-valence iron-based nanomaterials (nFe@Fe₃O₄, nFe₃O₄ and nFe₂O₃) were synthesized and exposed to zebrafish embryos and mammalian cardiomyocytes. All of them induced ferroptosis along with an increase in valence through iron overload and the Fenton reaction. Specifically, we exposed Tg (cmlc2:EGFP) zebrafish to the three iron-based nanomaterials and found that nFe@Fe₃O₄ treatments led to enlarged ventricles, while nFe₃O₄ and nFe₂O₃ increased atrial size, which was consistent with the results from hematoxylin-eosin staining and in situ hybridization. Moreover, we used ferroptosis inhibitors (ferrostatin-1 or deferoxamine) to treat zebrafish along with nanoparticles exposure and found that the cardiac developmental defects caused by nFe₃O₄ and nFe₂O₃, but not nFe@Fe₃O₄, could be completely rescued by ferroptosis inhibitors. We further found that nFe@Fe₃O₄, rather than nFe₃O₄ and nFe₂O₃, reduced the dissolved oxygen in the medium, which resulted in hypoxia and acceleration of heart tube formation and ventricular enlargement, and both were fully rescued by oxygen donors combined with ferroptosis inhibitors. Consistently, these findings were also observed in mammalian cardiomyocytes. In summary, our study demonstrates that the valence state of iron-based nanomaterials determines the ferroptosis potential. Our study also clarifies that high-valence iron-based nanomaterials induce an enlarged atrium via ferroptosis, while low-valence ones increase the ventricular size through both hypoxia and ferroptosis, which is helpful to understand the potential adverse effects of different valences of iron-based nanomaterials on environmental health and assure the responsible and sustainable development of nanotechnology.

Metal-free polymer nano-photosensitizer actuates ferroptosis in starved cancer

The microenvironment in solid tumors drives the fate of cancer cells to ferroptosis, yet the underlying mechanism remains incompletely understood. Herein, we report a metal-free polymer photosensitizer (BDPB) as a new type ferroptosis inducer of starved cancer cells. The polymer consists of boron difluoride dipyrromethene dye as the photosensitizing unit and diisopropyl-ethyl amine as the electron-donating unit. Ultrafast spectroscopy and electron spin resonance mechanistically revealed the prolonged charge-separation process in BDPB, enabling complex-I like one-electron transfer effect to produce O₂^●-. Unexpectedly, the O₂^●--generating BDPB nanoparticles (NPs) served to deactivate the AMPK-mTOR signaling pathway in normal-state cancer cells to initiate cell repair activity and survive low-dose phototherapy. However, for cancer cells in a starved state, BDPB NPs triggered glutathione peroxidase 4 downregulation, lipid peroxides accumulation, and death to cancer cells, which was identified as ferroptosis but not apoptosis, necroptosis, or autosis. The application of BDPB NPs sheds new light on the design of individualized ferroptosis inducers for combating cancer progression.

Role of RNA m6A modification in titanium dioxide nanoparticle-induced acute pulmonary injury: An in vitro and in vivo study

RNA N⁶-methyladenosine (m⁶A) modification regulates the cell stress response and homeostasis, but whether titanium dioxide nanoparticle (nTiO₂)-induced acute pulmonary injury is associated with the m⁶A epitranscriptome and the underlying mechanisms remain unclear. Here, the potential association between m⁶A modification and the bioeffects of several engineered nanoparticles (nTiO₂, nAg, nZnO, nFe₂O₃, and nCuO) were verified thorough in vitro experiments. nFe₂O₃, nZnO, and nTiO₂ exposure significantly increased the global m⁶A level in A549 cells. Our study further revealed that nTiO₂ can induce m⁶A-mediated acute pulmonary injury. Mechanistically, nTiO₂ exposure promoted methyltransferase-like 3 (METTL3)-mediated m⁶A signal activation and thus mediated the inflammatory response and IL-8 release through the degeneration of anti-Mullerian hormone (AMH) and Mucin5B (MUC5B) mRNAs in a YTH m⁶A RNA-binding protein 2 (YTHDF2)-dependent manner. Moreover, nTiO₂ exposure stabilized METTL3 protein by the lipid reactive oxygen species (ROS)-activated ERK1/2 pathway. The scavenging of ROS with ferrostatin-1 (Fer-1) alleviates the ERK1/2 activation, m⁶A upregulation, and the inflammatory response caused by nTiO₂ both in vitro and in vivo. In conclusion, our study demonstrates that m⁶A is a potential intervention target for alleviating the adverse effects of nTiO₂-induced acute pulmonary injury in vitro and in vivo, which has far-reaching implications for protecting human health and improving the sustainability of nanotechnology.

Lighting Nanoscale Insulators by Steric Restriction-Induced Emissions

Luminescence detection is a sensitive approach for high-resolution visualization of nano-/macrosized objects, but it is challenging to light invisible insulators owing to their inert surfaces. Herein, we discovered a steric restriction-induced emission (SRIE) effect on nanoscale insulators to light them by fluorogenic probes. The SRIE effect enabled us to specifically differentiate a representative nanoscale insulator, boron nitride (BN) nanosheets, from 18 tested nanomaterials with 420-fold increments of photoluminescence intensity and displayed 3 orders of magnitude linearity for quantitative analysis as well as single-particle level detection. Molecular dynamics simulations indicated that the hydrophobic and electron-resistant surfaces of BN nanosheets restricted intramolecular motions of fluorogenic molecules for blockage of the nonradiative path of excited electrons and activation of the radiative electron transition. Moreover, the lighted BN nanosheets could be successfully visualized in complex cellular and tissue biocontexts. Overall, the SRIE effect will inspire more analytical techniques for inert materials.

Coronas of micro/nano plastics: a key determinant in their risk assessments

As an emerging pollutant in the life cycle of plastic products, micro/nanoplastics (M/NPs) are increasingly being released into the natural environment. Substantial concerns have been raised regarding the environmental and health impacts of M/NPs. Although diverse M/NPs have been detected in natural environment, most of them display two similar features, i.e.,high surface area and strong binding affinity, which enable extensive interactions between M/NPs and surrounding substances. This results in the formation of coronas, including eco-coronas and bio-coronas, on the plastic surface in different media. In real exposure scenarios, corona formation on M/NPs is inevitable and often displays variable and complex structures. The surface coronas have been found to impact the transportation, uptake, distribution, biotransformation and toxicity of particulates. Different from conventional toxins, packages on M/NPs rather than bare particles are more dangerous. We, therefore, recommend seriously consideration of the role of surface coronas in safety assessments. This review summarizes recent progress on the eco-coronas and bio-coronas of M/NPs, and further discusses the analytical methods to interpret corona structures, highlights the impacts of the corona on toxicity and provides future perspectives.

Colloidal stability classification of TiO2 nanoparticles in artificial and in natural waters by cluster analysis and a global stability index: Influence of standard and natural colloidal particles

In the field of exposure-driven risk assessment of engineered nanoparticles (NPs), the highly complex interactions of NPs with natural components in surface waters are considered key factors to understand their fate and behavior in the environment. However, since experimental approaches aiming at imitating environmentally relevant conditions include many parameters and lead to a high number of outcomes, statistical tools can be extremely useful to support the results' interpretation. In this context, a multimethod approach was applied to investigate the colloidal behavior of TiO₂ NPs in both artificial waters and natural brackish water (from the Venice lagoon, Italy), in the presence of standard kaolinite and natural organic matter (NOM), or of the fine fraction of natural colloidal particles (NCPs) from the lagoon sediment. In detail, the experimental data obtained, i.e. hydrodynamic size, surface charge and sedimentation velocity values, were i) statistically treated by hierarchical clustering and ii) merged into a global stability index (I_G). The hierarchical clustering allowed to group the dispersions into three colloidal stability classes, where the main discriminant was the medium composition (i.e. ionic strength and presence of NOM), while the I_G allowed to establish a colloidal stability ranking of the dispersions within each class. Moreover, the comparison among the different dispersions suggested that kaolinite could be considered as a suitable surrogate for NCPs, to estimate the colloidal behavior and environmental fate of TiO₂ NPs in natural aqueous media.

MetHoS: a platform for large-scale processing, storage and analysis of metabolomics data

BACKGROUND

Modern mass spectrometry has revolutionized the detection and analysis of metabolites but likewise, let the data skyrocket with repositories for metabolomics data filling up with thousands of datasets. While there are many software tools for the analysis of individual experiments with a few to dozens of chromatograms, we see a demand for a contemporary software solution capable of processing and analyzing hundreds or even thousands of experiments in an integrative manner with standardized workflows.

RESULTS

Here, we introduce MetHoS as an automated web-based software platform for the processing, storage and analysis of great amounts of mass spectrometry-based metabolomics data sets originating from different metabolomics studies. MetHoS is based on Big Data frameworks to enable parallel processing, distributed storage and distributed analysis of even larger data sets across clusters of computers in a highly scalable manner. It has been designed to allow the processing and analysis of any amount of experiments and samples in an integrative manner. In order to demonstrate the capabilities of MetHoS, thousands of experiments were downloaded from the MetaboLights database and used to perform a large-scale processing, storage and statistical analysis in a proof-of-concept study.

CONCLUSIONS

MetHoS is suitable for large-scale processing, storage and analysis of metabolomics data aiming at untargeted metabolomic analyses. It is freely available at: https://methos.cebitec.uni-bielefeld.de/ . Users interested in analyzing their own data are encouraged to apply for an account.

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.

Toxicological Mechanism of Individual Susceptibility to Formaldehyde-Induced Respiratory Effects

Understanding the mechanisms of individual susceptibility to exposure to environmental pollutants has been a challenge in health risk assessment. Here, an integrated approach combining a CRISPR screen in human cells and epidemiological analysis was developed to identify the individual susceptibility to the adverse health effects of air pollutants by taking formaldehyde (FA) and the associated chronic obstructive pulmonary disease (COPD) as a case study. Among the primary hits of CRISPR screening of FA in human A549 cells, HTR4 was the only gene genetically associated with COPD susceptibility in global populations. However, the association between HTR4 and FA-induced respiratory toxicity is unknown in the literature. Adverse outcome pathway (AOP) network analysis of CRISPR screen hits provided a potential mechanistic link between activation of HTR4 (molecular initiating event) and FA-induced lung injury (adverse outcome). Systematic toxicology tests (in vitro and animal experiments) were conducted to reveal the HTR4-involved biological mechanisms underlying the susceptibility to adverse health effects of FA. Functionality and enhanced expression of HTR4 were required for susceptibility to FA-induced lung injury, and FA-induced epigenetic changes could result in enhanced expression of HTR4. Specific epigenetic and genetic characteristics of HTR4 were associated with the progression and prevalence of COPD, respectively, and these genetic risk factors for COPD could be potential biomarkers of individual susceptibility to adverse respiratory effects of FA. These biomarkers could be of great significance for defining subpopulations susceptible to exposure to FA and reducing uncertainty in the next-generation health risk assessment of air pollutants. Our study delineated a novel toxicological pathway mediated by HTR4 in FA-induced lung injury, which could provide a mechanistic understanding of the potential biomarkers of individual susceptibility to adverse respiratory effects of FA.

Particle Safety Assessment in Additive Manufacturing: From Exposure Risks to Advanced Toxicology Testing

Additive manufacturing (AM) or industrial three-dimensional (3D) printing drives a new spectrum of design and production possibilities; pushing the boundaries both in the application by production of sophisticated products as well as the development of next-generation materials. AM technologies apply a diversity of feedstocks, including plastic, metallic, and ceramic particle powders with distinct size, shape, and surface chemistry. In addition, powders are often reused, which may change the particles' physicochemical properties and by that alter their toxic potential. The AM production technology commonly relies on a laser or electron beam to selectively melt or sinter particle powders. Large energy input on feedstock powders generates several byproducts, including varying amounts of virgin microparticles, nanoparticles, spatter, and volatile chemicals that are emitted in the working environment; throughout the production and processing phases. The micro and nanoscale size may enable particles to interact with and to cross biological barriers, which could, in turn, give rise to unexpected adverse outcomes, including inflammation, oxidative stress, activation of signaling pathways, genotoxicity, and carcinogenicity. Another important aspect of AM-associated risks is emission/leakage of mono- and oligomers due to polymer breakdown and high temperature transformation of chemicals from polymeric particles, both during production, use, and in vivo, including in target cells. These chemicals are potential inducers of direct toxicity, genotoxicity, and endocrine disruption. Nevertheless, understanding whether AM particle powders and their byproducts may exert adverse effects in humans is largely lacking and urges comprehensive safety assessment across the entire AM lifecycle-spanning from virgin and reused to airborne particles. Therefore, this review will detail: 1) brief overview of the AM feedstock powders, impact of reuse on particle physicochemical properties, main exposure pathways and protective measures in AM industry, 2) role of particle biological identity and key toxicological endpoints in the particle safety assessment, and 3) next-generation toxicology approaches in nanosafety for safety assessment in AM. Altogether, the proposed testing approach will enable a deeper understanding of existing and emerging particle and chemical safety challenges and provide a strategy for the development of cutting-edge methodologies for hazard identification and risk assessment in the AM industry.

A generic self-assembly approach towards phototheranostics for NIR-II fluorescence imaging and phototherapy

Controllable self-assembly of photonic molecules for precise biomedicine is highly desirable but challenging to prepare multifunctional nano-phototheranostics. Herein, we developed a generic self-assembly approach to design nano-phototheranostics that provides NIR-II fluorescence imaging and phototherapy. We first designed and synthesized two amphiphilic photonic molecules, PEG₂₀₀₀-IR806 and BODIPY. Then, we prepared the co-self-assembled phototheranostic agents, PEG₂₀₀₀-IR806/BODIPY nanoparticles (PIBY NPs). The morphology of the PIBY NPs is controllable by adjusting the ratio of PEG₂₀₀₀-IR806 and BODIPY during self-assembly. The NIR-II fluorescence properties and phototherapy capability of the PIBY NPs were demonstrated in vitro and in vivo. By tuning the ratio of PEG₂₀₀₀-IR806 and BODIPY, the PIBY NPs showed various morphologies (e.g. spherical nanoparticles, nanovesicles and rod-like nanoparticles). The PEG₂₀₀₀-IR806 plays two roles in the co-self-assemblies, one is second near-infrared (NIR-II, 1000-1700 nm) agent, the other is the surfactant for BODIPY encapsulation. The phototherapeutic PIBY NPs all show bright NIR-II fluorescence and effective phototherapeutic (photothermal and photodynamic) properties, which are attributed to IR806 and BODIPY, respectively. The driving force of the self-assembly can be attributed to the electrostatic interaction between NIR806 and BODIPY and their hydrophobicity. The rod-like PIBY NPs (rPIBY NPs) demonstrated a low half inhibitory concentration (IC₅₀) of 3.96 µg/mL on U87MG cells. The NIR-II imaging showed the accumulation of rPIBY NPs in the tumor region. After systemic injection of rPIBY NPs at low dose (0.5 mg/kg), the tumor growth was greatly inhibited upon laser irradiation without noticeable side effects. This study provides a generic self-assembly approach to fabricate NIR-II imaging and phototherapeutic platform for cancer phototheranostics. STATEMENT OF SIGNIFICANCE: Nanophototheranostics providing NIR-II fluorescence imaging and phototherapy are expected to play a critical role in modern precision medicine. Controllable self-assembly of optical molecules for the fabrication of efficient nanophototheranostics is highly desirable but challenging. This work reports for the first time the co-assembly of a NIR-II imaging contrast agent and a phototherapeutic agent to yield nanophototheranostics with various morphologies. The design of molecular co-assembly with complementary optical functions can be a generic method for future the development of phototheranostics.

Fungal-Mineral Interactions Modulating Intrinsic Peroxidase-like Activity of Iron Nanoparticles: Implications for the Biogeochemical Cycles of Nutrient Elements and Attenuation of Contaminants

Fungal-mediated extracellular reactive oxygen species (ROS) are essential for biogeochemical cycles of carbon, nitrogen, and contaminants in terrestrial environments. These ROS levels may be modulated by iron nanoparticles that possess intrinsic peroxidase (POD)-like activity (nanozymes). However, it remains largely undescribed how fungi modulate the POD-like activity of the iron nanoparticles with various crystallinities and crystal facets. Using well-controlled fungal-mineral cultivation experiments, here, we showed that fungi possessed a robust defect engineering strategy to modulate the POD-like activity of the attached iron minerals by decreasing the catalytic activity of poorly ordered ferrihydrite but enhancing that of well-crystallized hematite. The dynamics of POD-like activity were found to reside in molecular trade-offs between lattice oxygen and oxygen vacancies in the iron nanoparticles, which may be located in a cytoprotective fungal exoskeleton. Together, our findings unveil coupled POD-like activity and oxygen redox dynamics during fungal-mineral interactions, which increase the understanding of the catalytic mechanisms of POD-like nanozymes and microbial-mediated biogeochemical cycles of nutrient elements as well as the attenuation of contaminants in terrestrial environments.

Harnessing reactive oxygen/nitrogen species and inflammation: Nanodrugs for liver injury

Overall, 12% of the global population (800 million) suffers from liver disease, which causes 2 million deaths every year. Liver injury involving characteristic reactive oxygen/nitrogen species (RONS) and inflammation plays a key role in progression of liver disease. As a key metabolic organ of the human body, the liver is susceptible to injury from various sources, including COVID-19 infection. Owing to unique structural features and functions of the liver, most current antioxidants and anti-inflammatory drugs are limited against liver injury. However, the characteristics of the liver could be utilized in the development of nanodrugs to achieve specific enrichment in the liver and consequently targeted treatment. Nanodrugs have shown significant potential in eliminating RONS and regulating inflammation, presenting an attractive therapeutic tool for liver disease through controlling liver injury. Therefore, the main aim of the current review is to provide a comprehensive summary of the latest developments contributing to our understanding of the mechanisms underlying nanodrugs in the treatment of liver injury via harnessing RONS and inflammation. Meanwhile, the prospects of nanodrugs for liver injury therapy are systematically discussed, which provides a sound platform for novel therapeutic insights and inspiration for design of nanodrugs to treat liver disease.

Property-activity relationship between physicochemical properties of PM2.5 and their activation of NLRP3 inflammasome

Air pollution is becoming severe environment factor affecting human health. More and more research has indicated that fine particulate matter (PM_2.5) plays a critical role in causing pulmonary inflammation or fibrosis, which potentially is ascribed to the activation of nucleotide-binding domain and leucine-rich repeat protein 3 (NLRP3) inflammasome. However, the underlying property-activity relationship between the physicochemical properties of PM_2.5 and their activation of NLRP3 inflammasome remains unclear. Herein, various ways, such as metal chelation, organic extraction, ROS consumption, charge neutralization and particle dispersion, were applied to interfere with the effects of metal ion, polycyclic aromatic hydrocarbons (PAHs), reactive oxygen species (ROS), charge and size. It was found that aggregated size and PAHs could activate the NLRP3 inflammasome through lysosome rupture and potassium efflux, respectively. Metal ion, PAHs and surface ROS could also activate the NLRP3 inflammasome through mitochondrial ROS production. However, neutralization of PM_2.5 with the negative surface charge could not relieve the activation of NLRP3 inflammasome. Furthermore, oropharyngeal aspiration of various modified PM_2.5 were adopted to explore their effects on lung fibrosis, which showed the consistent results with those in cellular levels. Removal of metal ion, PAHs and ROS as well as reduction of size of PM_2.5 could reduce collagen deposition in the lung tissue of mice, while the charge neutralization of PM_2.5 increased this collagen deposition. This study provides great insights to clarify the property-activity relationship of PM_2.5.

How can we justify grouping of nanoforms for hazard assessment? Concepts and tools to quantify similarity

The risk of each nanoform (NF) of the same substance cannot be assumed to be the same, as they may vary in their physicochemical characteristics, exposure and hazard. However, neither can we justify a need for more animal testing and resources to test every NF individually. To reduce the need to test all NFs, (regulatory) information requirements may be fulfilled by grouping approaches. For such grouping to be acceptable, it is important to demonstrate similarities in physicochemical properties, toxicokinetic behaviour, and (eco)toxicological behaviour. The GRACIOUS Framework supports the grouping of NFs, by identifying suitable grouping hypotheses that describe the key similarities between different NFs. The Framework then supports the user to gather the evidence required to test these hypotheses and to subsequently assess the similarity of the NFs within the proposed group. The evidence needed to support a hypothesis is gathered by an Integrated Approach to Testing and Assessment (IATA), designed as decision trees constructed of decision nodes. Each decision node asks the questions and provides the methods needed to obtain the most relevant information. This White paper outlines existing and novel methods to assess similarity of the data generated for each decision node, either via a pairwise analysis conducted property-by-property, or by assessing multiple decision nodes simultaneously via a multidimensional analysis. For the pairwise comparison conducted property-by-property we included in this White paper: The x-fold, Bayesian and Arsinh-OWA distance algorithms performed comparably in the scoring of similarity between NF pairs. The Euclidean distance was also useful, but only with proper data transformation. The x-fold method does not standardize data, and thus produces skewed histograms, but has the advantage that it can be implemented without programming knowhow. A range of multidimensional evaluations, using for example dendrogram clustering approaches, were also investigated. Multidimensional distance metrics were demonstrated to be difficult to use in a regulatory context, but from a scientific perspective were found to offer unexpected insights into the overall similarity of very different materials. In conclusion, for regulatory purposes, a property-by-property evaluation of the data matrix is recommended to substantiate grouping, while the multidimensional approaches are considered to be tools of discovery rather than regulatory methods.

Tailoring the physicochemical properties of nanomaterials for immunomodulation

Immunomodulation is poised to revolutionize the treatment of cancer, autoimmune diseases, and many other inflammation-related disorders. The immune system in these conditions can be either activated or suppressed by nanocarriers loaded with bioactive molecules. Although immunomodulation via these therapeutics has long been recognized, and a broad range of nanocarriers have been designed to accommodate varied usages, less studies have focused on the effects of nanomaterial physicochemical properties on immune responses, especially the immunity altered by nanocarrier materials alone. Conclusions are sometimes seemly inconsistent due to the complexities of nanomaterials and the immune system. An in-depth understanding of the nanocarrier-induced immune responses is essential for clinical applications. In this review, we summarize recent studies of the immune responses influenced by nanomaterial physicochemical properties with an emphasis on the intrinsic features of nanomaterials that modulate the innate and adaptive immunities. We then provide our perspectives on the design of nanomaterials for immunomodulation.

Electrostatic attraction of cationic pollutants by microplastics reduces their joint cytotoxicity

Microplastic (MP) pollution causes global concerns regarding the consequential impacts on human health. In particular, MPs may act as vectors for various contaminants to induce adverse effects in human. In this work, the joint cytotoxicity of two different MPs co-exposed with diverse ionic pollutants was investigated in two cell lines from human digestive system: human gastric epithelium (GES-1) and colorectal mucosa (FHC) cell lines. The results indicated that the cytotoxicity of cationic pollutants was alleviated by MPs more significantly than that of anionic pollutants in both culture medium and river water. The electrostatic attraction between the negatively charged MPs and cations was a key factor in determining the ultimate joint toxicity. Our findings indicate that the joint cytotoxicity of MP-pollutant mixtures may be proactively reduced by modulating the surface charge of MPs.

Understanding nanoparticle endocytosis to improve targeting strategies in nanomedicine

Nanoparticles (NPs) have attracted considerable attention in various fields, such as cosmetics, the food industry, material design, and nanomedicine. In particular, the fast-moving field of nanomedicine takes advantage of features of NPs for the detection and treatment of different types of cancer, fibrosis, inflammation, arthritis as well as neurodegenerative and gastrointestinal diseases. To this end, a detailed understanding of the NP uptake mechanisms by cells and intracellular localization is essential for safe and efficient therapeutic applications. In the first part of this review, we describe the several endocytic pathways involved in the internalization of NPs and we discuss the impact of the physicochemical properties of NPs on this process. In addition, the potential challenges of using various inhibitors, endocytic markers and genetic approaches to study endocytosis are addressed along with the principal (semi) quantification methods of NP uptake. The second part focuses on synthetic and bio-inspired substances, which can stimulate or decrease the cellular uptake of NPs. This approach could be interesting in nanomedicine where a high accumulation of drugs in the target cells is desirable and clearance by immune cells is to be avoided. This review contributes to an improved understanding of NP endocytic pathways and reveals potential substances, which can be used in nanomedicine to improve NP delivery.

DNA Nanostructures: Current Challenges and Opportunities for Cellular Delivery

DNA nanotechnology has produced a wide range of self-assembled structures, offering unmatched possibilities in terms of structural design. Because of their programmable assembly and precise control of size, shape, and function, DNA particles can be used for numerous biological applications, including imaging, sensing, and drug delivery. While the biocompatibility, programmability, and ease of synthesis of nucleic acids have rapidly made them attractive building blocks, many challenges remain to be addressed before using them in biological conditions. Enzymatic hydrolysis, low cellular uptake, immune cell recognition and degradation, and unclear biodistribution profiles are yet to be solved. Rigorous methodologies are needed to study, understand, and control the fate of self-assembled DNA structures in physiological conditions. In this review, we describe the current challenges faced by the field as well as recent successes, highlighting the potential to solve biology problems or develop smart drug delivery tools. We then propose an outlook to drive the translation of DNA constructs toward preclinical design. We particularly believe that a detailed understanding of the fate of DNA nanostructures within living organisms, achieved through thorough characterization, is the next required step to reach clinical maturity.

Antibacterial activity of positively charged carbon quantum dots without detectable resistance for wound healing with mixed bacteria infection

Widespread bacterial infection and the spread of antibiotic resistance exhibit increasing threat to the public and thus require new antibacterial strategies. Carbon quantum dots (CQDs) have been extensively investigated to play fluorescent, catalytic roles and even potential biomedical functions containing sterilization. However, synthetic understanding of the interaction of CQDs and bacteria, the exhibition of antibacterial ability, and the risk of resistance evolution remain lacking. Herein, a simple one-pot method was fabricated to prepare positively charged CQDs (PC-CQDs) as a broad-spectrum antibacterial agent. PC-CQDs possessed effective antibacterial activity against all tested Gram-positive, Gram-negative, and drug-resistant bacteria. Investigation of the antibacterial mechanism of PC-CQDs indicated that small-sized PC-CQDs functionalized with -NH₂ and -NH induced strong adherence behavior on the bacterial cell membrane. Moreover, the entry of PC-CQDs caused conformational changes in the genes and generation of reactive oxygen species in the bacteria. Safety evaluation illustrated that PC-CQDs did not trigger detectable drug resistance or hemolysis. Furthermore, PC-CQDs effectively promoted the antibacterial treatment of mixed Staphylococcus aureus and Escherichia coli infected wound in rats with low in vivo toxicity. These results suggested that PC-CQDs are a potential antibacterial candidate for real wound healing applications in complex bacterial infections and even resistant bacteria-caused infections.

Nanoparticle-induced ferroptosis: detection methods, mechanisms and applications

Although ferroptosis is an iron-dependent cell death mechanism involved in the development of some severe diseases (e.g., Parkinsonian syndrome, stroke and tumours), the combination of nanotechnology with ferroptosis for the treatment of these diseases has attracted substantial research interest. However, it is challenging to differentiate nanoparticle-induced ferroptosis from other types of cell deaths (e.g., apoptosis, pyroptosis, and necrosis), elucidate the detailed mechanisms and identify the key property of nanoparticles responsible for ferroptotic cell deaths. Therefore, a summary of these aspects from current research on nano-ferroptosis is important and timely. In this review, we endeavour to summarize some convincing techniques that can be employed to specifically examine ferroptotic cell deaths. Then, we discuss the molecular initiating events of nanosized ferroptosis inducers and the cascade signals in cells, and therefore elaborate the ferroptosis mechanisms. Besides, the key physicochemical properties of nano-inducers are also discussed to acquire a fundamental understanding of nano-structure-activity relationships (nano-SARs) involved in ferroptosis, which may facilitate the design of nanomaterials to deliberately tune ferroptosis. Finally, future perspectives on the fundamental understanding of nanoparticle-induced ferroptosis and its applications are provided.

Untargeted metabolomics for Achilles heel of engineered nanomaterials' risk assessment

Owing to the superlative properties, engineered nanomaterials (ENM) are being used in food, cosmetics, medicine, and electronics. Therefore, exogenous ENM can be housed into humans through a multitude of exposure routes, leading to compromise of the biomolecules' functionalities through structural deformations, and even at the metabolic level. Consequently, it is of great importance to understand the perturbations introduced at the metabolic level for the timely risk assessment (RA) of ENM. Current technological advancements in metabolomics empower us to visualize the metabolic dysregulations in biological cells, tissues, and living objects, instigated by the ENM. Given the fact, we propose multitiered untargeted metabolomics for the risk assessment of ENM. We propose largely validated experimental design principles that enable the well-organized and authentic identification of metabolic dysregulation connected with a newly engineered nanomaterial. Our scheme could participate in the enhanced transparency of the RA course of rapidly emerging ENM.

Research on nanoparticles in human perfused placenta: State of the art and perspectives

Increasing human exposure to nanoparticles (NPs) from various sources raises concerns for public health, especially for vulnerable risk groups like pregnant women and their developing fetuses. However, nanomedicine and the prospect of creating safe and effective NP-based formulations of drugs hold great promise to revolutionize treatment during pregnancy. With maternal and fetal health at stake, risks and opportunities of NPs in pregnancy need to be carefully investigated. Importantly, a comprehensive understanding of NP transport and effects at the placenta is urgently needed considering the central position of the placenta at the maternal-fetal interface and its many essential functions to enable successful pregnancy. The perfusion of human placental tissue provides a great opportunity to achieve predictive human relevant insights, circumventing uncertainties due to considerable differences in placental structure and function across species. Here, we have reviewed the current literature on the ex vivo human placenta perfusion of NPs. From 16 available studies, it was evident that placental uptake and transfer of NPs are highly dependent on their characteristics like size and surface modifications, which is in line with previous observations from in vitro and animal transport studies. These studies further revealed that special considerations apply for the perfusion of NPs and we identified relevant controls that should be implemented in future perfusion studies. While current studies mostly focused on placental transfer of NPs to conclude on potential fetal exposure, the ex vivo placental perfusion model has considerable potential to reveal novel insights on NP effects on placental tissue functionality and signaling that could indirectly affect maternal-fetal health.

Evaluation of Nanoparticle Penetration in the Tumor Spheroid Using Two-Photon Microscopy

Mesoporous silica nanoparticles (MSNs) have emerged as a prominent nanomedicine platform, especially for tumor-related nanocarrier systems. However, there is increasing concern about the ability of nanoparticles (NPs) to penetrate solid tumors, resulting in compromised antitumor efficacy. Because the physicochemical properties of NPs play a significant role in their penetration and accumulation in solid tumors, it is essential to systematically study their relationship in a model system. Here, we report a multihierarchical assessment of the accumulation and penetration of fluorescence-labeled MSNs with nine different physicochemical properties in tumor spheroids using two-photon microscopy. Our results indicated that individual physicochemical parameters separately could not define the MSNs' ability to accumulate in a deeper tumor region; their features are entangled. We observed that the MSNs' stability determined their success in reaching the hypoxia region. Moreover, the change in the MSNs' penetration behavior postprotein crowning was associated with both the original properties of NPs and proteins on their surfaces.

The Inclusion of a Matrix Metalloproteinase-9 Responsive Sequence in Self-assembled Peptide-based Brain-Targeting Nanoparticles Improves the Efficiency of Nanoparticles Crossing the Blood-Brain Barrier at Elevated MMP-9 Levels

This study investigated whether the inclusion of a matrix metalloproteinase-9 (MMP-9) responsive sequence in self-assembled peptide-based brain-targeting nanoparticles (NPs) would enhance the blood-brain barrier (BBB) penetration when MMP-9 levels are elevated both in the brain and blood circulation. Brain-targeting peptides were conjugated at the N-terminus to MMP-9-responsive peptides, and these were conjugated at the N-terminus to lipid moiety (cholesteryl chloroformate or palmitic acid). Two constructs did not have MMP-9-responsive peptides. NPs were characterised for size, charge, critical micelle concentration, toxicity, blood compatibility, neural cell uptake, release profiles, and in vitro BBB permeability simulating normal or elevated MMP-9 levels. The inclusion of MMP-9-sensitive sequences did not improve the release of a model drug in the presence of active MMP-9 from NPs compared to distilled water. ¹⁹F NMR studies suggested the burial of MMP-9-sensitive sequences inside the NPs making them inaccessible to MMP-9. Only cholesterol-GGGCKAPETALC (responsive to MMP-9) NPs showed <5% haemolysis, <1 pg/mL release of IL-1β at 500 μg/mL from THP1 cells, with 70.75 ± 5.78% of NPs crossing the BBB at 24 h in presence of active MMP-9. In conclusion, brain-targeting NPs showed higher transport across the BBB model when MMP-9 levels were elevated and the brain-targeting ligand was responsive to MMP-9.

Engineering Fe-N Doped Graphene to Mimic Biological Functions of NADPH Oxidase in Cells

NADPH oxidase (NOX) as a transmembrane enzyme complex controls the generation of superoxide that plays important roles in immune signaling pathway. NOX inactivation may elicit immunodeficiency and cause chronic granulomatous disease (CGD). Biocompatible synthetic materials with NOX-like activities would therefore be interesting as curative and/or preventive approaches in case of NOX deficiency. Herein, we synthesized a Fe-N doped graphene (FeNGR) nanomaterial that could mimic the activity of NOX by efficiently catalyzing the conversion of NADPH into NADP+ and triggering the generation of oxygen radicals. The resulting FeNGR nanozyme had similar cellular distribution to NOX and is able to mimic the enzyme function in NOX-deficient cells by catalyzing the generation of superoxide and retrieving the immune activity, evidenced by TNF-α, IL-1β, and IL-6 production in response to Alum exposure. Overall, our study discovered a synthetic material (FeNGR) to mimic NOX and demonstrated its biological function in immune activation of NOX-deficient cells.

Uptake of iron oxide nanoparticles inhibits the photosynthesis of the wheat after foliar exposure

Iron oxide nanoparticles (nFe₂O₃)-filled materials have been widely employed in various products and their effects on plants have attracted considerable attention because of their potential release into the environment. Currently, numerous studies reporting the influences of iron-bearing nanoparticles on plants are focused on root or seed exposure. However, plants exposed to atmospheric iron-bearing nanoparticles through the leaves and their impacts on plants are still not well understood. This study focused on the uptake, translocation, and effects of foliar exposure of nFe₂O₃ on wheat seedlings. Wheat seedlings were foliar applied to various concentrations of nFe₂O₃ (0, 60 and 180 μg per plant) for 1, 7, 14 or 21 d. Our results demonstrated that after exposure for 21 d, the concentrations of Fe in leaves, stems, and roots were 1100, 280 and 160 μg kg^-1, respectively. Scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS), as well as the backscattered electron (BSE) images, revealed the stomatal opening was likely the pathway for nFe₂O₃ uptake. Analysis of the transfer rate, translocation of Fe from leaves to stems and roots, suggested the involvement of plant Fe regulation processes. Particularly, the antioxidant enzymatic activities and malondialdehyde levels in leaves were modified, which was ascribed to the excessive hydroxyl radical (OH) generated via the Fenton-like reaction mediated by nFe₂O₃. Finally, the OH facilitated the degradation of chlorophyll, posting a negative impact on the photosynthesis, and thus inhibited the biomass production. These findings are meaningful to understand the fate and physiological effects of atmospheric nFe₂O₃ in crops.

Multiparametric Profiling of Engineered Nanomaterials: Unmasking the Surface Coating Effect

Despite considerable efforts, the properties that drive the cytotoxicity of engineered nanomaterials (ENMs) remain poorly understood. Here, the authors inverstigate a panel of 31 ENMs with different core chemistries and a variety of surface modifications using conventional in vitro assays coupled with omics-based approaches. Cytotoxicity screening and multiplex-based cytokine profiling reveals a good concordance between primary human monocyte-derived macrophages and the human monocyte-like cell line THP-1. Proteomics analysis following a low-dose exposure of cells suggests a nonspecific stress response to ENMs, while microarray-based profiling reveals significant changes in gene expression as a function of both surface modification and core chemistry. Pathway analysis highlights that the ENMs with cationic surfaces that are shown to elicit cytotoxicity downregulated DNA replication and cell cycle responses, while inflammatory responses are upregulated. These findings are validated using cell-based assays. Notably, certain small, PEGylated ENMs are found to be noncytotoxic yet they induce transcriptional responses reminiscent of viruses. In sum, using a multiparametric approach, it is shown that surface chemistry is a key determinant of cellular responses to ENMs. The data also reveal that cytotoxicity, determined by conventional in vitro assays, does not necessarily correlate with transcriptional effects of ENMs.

Molecular Mechanisms, Characterization Methods, and Utilities of Nanoparticle Biotransformation in Nanosafety Assessments

It is a big challenge to reveal the intrinsic cause of a nanotoxic effect due to diverse branches of signaling pathways induced by engineered nanomaterials (ENMs). Biotransformation of toxic ENMs involving biochemical reactions between nanoparticles (NPs) and biological systems has recently attracted substantial attention as it is regarded as the upstream signal in nanotoxicology pathways, the molecular initiating event (MIE). Considering that different exposure routes of ENMs may lead to different interfaces for the arising of biotransformation, this work summarizes the nano-bio interfaces and dose calculation in inhalation, dermal, ingestion, and injection exposures to humans. Then, five types of biotransformation are shown, including aggregation and agglomeration, corona formation, decomposition, recrystallization, and redox reactions. Besides, the characterization methods for investigation of biotransformation as well as the safe design of ENMs to improve the sustainable development of nanotechnology are also discussed. Finally, future perspectives on the implications of biotransformation in clinical translation of nanomedicine and commercialization of nanoproducts are provided.

Vacancies on 2D transition metal dichalcogenides elicit ferroptotic cell death

Sustainable developments of nanotechnology necessitate the exploration of structure-activity relationships (SARs) at nano-bio interfaces. While ferroptosis may contribute in the developments of some severe diseases (e.g., Parkinson's disease, stroke and tumors), the cellular pathways and nano-SARs are rarely explored in diseases elicited by nano-sized ferroptosis inducers. Here we find that WS2 and MoS2 nanosheets induce an iron-dependent cell death, ferroptosis in epithelial (BEAS-2B) and macrophage (THP-1) cells, evidenced by the suppression of glutathione peroxidase 4 (GPX4), oxygen radical generation and lipid peroxidation. Notably, nano-SAR analysis of 20 transition metal dichalcogenides (TMDs) disclosures the decisive role of surface vacancy in ferroptosis. We therefore develop methanol and sulfide passivation as safe design approaches for TMD nanosheets. These findings are validated in animal lungs by oropharyngeal aspiration of TMD nanosheets. Overall, our study highlights the key cellular events as well as nano-SARs in TMD-induced ferroptosis, which may facilitate the safe design of nanoproducts.

Quantitative Structure-Activity Relationship Models for Predicting Inflammatory Potential of Metal Oxide Nanoparticles

BACKGROUND

Although substantial concerns about the inflammatory effects of engineered nanomaterial (ENM) have been raised, experimentally assessing toxicity of various ENMs is challenging and time-consuming. Alternatively, quantitative structure-activity relationship (QSAR) models have been employed to assess nanosafety. However, no previous attempt has been made to predict the inflammatory potential of ENMs.

OBJECTIVES

By employing metal oxide nanoparticles (MeONPs) as a model ENM, we aimed to develop QSAR models for prediction of the inflammatory potential by their physicochemical properties.

METHODS

We built a comprehensive data set of 30 MeONPs to screen a proinflammatory cytokine interleukin (IL)-1 beta (IL- 1 β ) release in THP-1 cell line. The in vitro hazard ranking was validated in mouse lungs by oropharyngeal instillation of six randomly selected MeONPs. We established QSAR models for prediction of MeONP-induced inflammatory potential via machine learning. The models were further validated against seven new MeONPs. Density functional theory (DFT) computations were exploited to decipher the key mechanisms driving inflammatory responses of MeONPs.

RESULTS

Seventeen out of 30 MeONPs induced excess IL- 1 β production in THP-1 cells. In vivo disease outcomes were highly relevant to the in vitro data. QSAR models were developed for inflammatory potential, with predictive accuracy (ACC) exceeding 90%. The models were further validated experimentally against seven independent MeONPs (ACC = 86 % ). DFT computations and experimental results further revealed the underlying mechanisms: MeONPs with metal electronegativity lower than 1.55 and positive ζ -potential were more likely to cause lysosomal damage and inflammation.

CONCLUSIONS

IL- 1 β released in THP-1 cells can be an index to rank the inflammatory potential of MeONPs. QSAR models based on IL- 1 β were able to predict the inflammatory potential of MeONPs. Our approach overcame the challenge of time- and labor-consuming biological experiments and allowed for computational assessment of MeONP inflammatory potential by characterization of their physicochemical properties. https://doi.org/10.1289/EHP6508.