Nanotoxicology最新文献

Nanoparticles have been used extensively in different scientific fields. Due to the possible destructive effects of nanoparticles on the environment or the biological systems, their toxicity evaluation is a crucial phase for studying nanomaterial safety. In the meantime, experimental approaches for toxicity assessment of various nanoparticles are expensive and time-consuming. Thus, an alternative technique, such as artificial intelligence (AI), could be valuable for predicting nanoparticle toxicity. Therefore, in this review, the AI tools were investigated for the toxicity assessment of nanomaterials. To this end, a systematic search was performed on PubMed, Web of Science, and Scopus databases. Articles were included or excluded based on pre-defined inclusion and exclusion criteria, and duplicate studies were excluded. Finally, twenty-six studies were included. The majority of the studies were conducted on metal oxide and metallic nanoparticles. In addition, Random Forest (RF) and Support Vector Machine (SVM) had the most frequency in the included studies. Most of the models demonstrated acceptable performance. Overall, AI could provide a robust, fast, and low-cost tool for the evaluation of nanoparticle toxicity.

Nanotechnology applications are fast-growing in many industrial fields. Consequently, health effects of engineered nanomaterials (ENMs) should be investigated. Within the EU-Life project NanoExplore, we developed a harmonized protocol of an international multicenter prospective cohort study of workers in ENM-producing companies. This article describes the development of the protocol, sample size calculation, data collection and management procedures and discusses its relevance with respect to research needs. Within this protocol, workers' ENM exposure will be assessed over four consecutive working days during the initial recruitment campaign and the subsequent follow-up campaigns. Biomonitoring using noninvasive sampling of exhaled breath condensate (EBC), exhaled air, and urine will be collected before and after 4-day exposure monitoring. Both exposure and effect biomarkers, will be quantified along with pulmonary function tests and diagnosed diseases reported using a standardized epidemiological questionnaire available in four languages. Until now, this protocol was implemented at seven companies in Switzerland, Spain and Italy. The protocol is well standardized, though sufficiently flexible to include company-specific conditions and occupational hygiene measures. The recruitment, to date, of 140 participants and collection of all data and samples, enabled us launching the first international cohort of nanotechnology workers. All companies dealing with ENMs could join the NanoExplore Consortium, apply this harmonized protocol and enter in the cohort, concieved as an open cohort. Its protocol meets all requirements of a hypotheses-driven prospective study, which will assess and reassess effects of ENM exposure on workers' health by updating the follow-up of the cohort. New hypothesis could be also considered.

The availability of experimental nanotoxicity data is in general limited which warrants both the use of in silico methods for data gap filling and exploring novel methods for effective modeling. Read-Across Structure-Activity Relationship (RASAR) is an emerging cheminformatic approach that combines the usefulness of a QSAR model and similarity-based Read-Across predictions. In this work, we have generated simple, interpretable, and transferable quantitative-RASAR (q-RASAR) models which can efficiently predict the cytotoxicity of TiO₂-based multi-component nanoparticles. A data set of 29 TiO₂-based nanoparticles with specific amounts of noble metal precursors was rationally divided into training and test sets, and the Read-Across-based predictions for the test set were generated. The optimized hyperparameters and the similarity approach, which yield the best predictions, were used to calculate the similarity and error-based RASAR descriptors. A data fusion of the RASAR descriptors with the chemical descriptors was done followed by the best subset feature selection. The final set of selected descriptors was used to develop the q-RASAR models, which were validated using the stringent OECD criteria. Finally, a random forest model was also developed with the selected descriptors, which could efficiently predict the cytotoxicity of TiO₂-based multi-component nanoparticles superseding previously reported models in the prediction quality thus showing the merits of the q-RASAR approach. To further evaluate the usefulness of the approach, we have applied the q-RASAR approach also to a second cytotoxicity data set of 34 heterogeneous TiO₂-based nanoparticles which further confirmed the enhancement of external prediction quality of QSAR models after incorporation of RASAR descriptors.

The increased commercial use and spread of nanoceria raises concerns about the risks associated with its effects on living organisms. Although Pseudomonas aeruginosa may be ubiquitous in nature, it is largely found in locations closely linked with human activity. P. aeruginosa san ai was used as a model organism for a deeper understanding of the interaction between biomolecules of the bacteria with this intriguing nanomaterial. A comprehensive proteomics approach along with analysis of altered respiration and production of targeted/specific secondary metabolites was conducted to study the response of P. aeruginosa san ai to nanoceria. Quantitative proteomics found that proteins associated with redox homeostasis, biosynthesis of amino acids, and lipid catabolism were upregulated. Proteins from outer cellular structures were downregulated, including transporters responsible for peptides, sugars, amino acids and polyamines, and the crucial TolB protein of the Tol-Pal system, required for the structural formation of the outer membrane layer. In accordance with the altered redox homeostasis proteins, an increased amount of pyocyanin, a key redox shuttle, and the upregulation of the siderophore, pyoverdine, responsible for iron homeostasis, were found. Production of extracellular molecules, e.g. pyocyanin, pyoverdine, exopolysaccharides, lipase, and alkaline protease, was significantly increased in P. aeruginosa san ai exposed to nanoceria. Overall, nanoceria at sublethal concentrations induces profound metabolic changes in P. aeruginosa san ai and provokes increased secretion of extracellular virulence factors, revealing the powerful influence this nanomaterial has on the vital functions of the microorganism.

Particulate and soluble debris are generated by mechanical and non-mechanical degradation of implanted medical devices. Debris containing cobalt and chromium (CoCr) is known to cause adverse biological reactions. Implant-related complications are often diagnosed using radiography, which results in more frequent patient exposure to ionizing radiation. The aim of this study was to evaluate the potential for increased toxicity due to combined radiation and CoCr exposure. This was investigated using a controlled in vitro model consisting of commercially available CoCr debris that was generated from components of hip replacements and human cell lines relevant to the joint environment: endothelial HMEC-1 and synovial SW982. Particle sizes and shapes were heterogenous. Cells tended to internalize smaller particles, as observed by electron microscopy. Indicators of toxicity were measured after short (24 h after radiation) or extended (12-14 d after radiation) exposure timelines. In the short-term, CoCr reduced cell viability, increased apoptosis, and increased oxidative stress. The effects of radiation were not apparent until the timeline was extended. CoCr and radiation reduced cell survival, with both additive and synergistic effects. Mechanisms for reduced survival included rapid cell death caused by CoCr and senescence caused by radiation. In conclusion, results showed combined toxicological effects of CoCr and radiation at the doses and timelines used for this in vitro model. These observations warrant further investigation using other experimental models to determine translational impact.

Mesoporous carbon nanotubes (mCNTs) hold great promise interests, owing to their superior nano-platform properties for biomedicine. To fully utilize this potential, the toxicity and biodistribution of pristine and surface-modified mCNTs (-OH/-COOH) should preferentially be addressed. The results of cell viability suggested that pristine mCNTs induced cell death in a concentration-dependent manner. As evidence of reactive oxygen species (ROS), malondialdehyde (MDA) and superoxide dismutase (SOD), pristine mCNTs induced noticeable redox imbalance. ^99mTc tracing data suggested that the cellular uptake of pristine mCNTs posed a concentrate-dependent and energy-dependent manner via macropinocytotic and clathrin-dependent pathways, and the main accumulated organs were lung, liver and spleen. With OH modification, the ROS generation, MDA deposition and SOD consumption were evidently reduced compared with the pristine mCNTs at 24/48 h high-dose exposure. With COOH modification, the modified mCNTs only showed a significant difference in SOD consumption at 24/48 h exposure, but there was no significant difference in the measurement of ROS and MDA. The internalization mechanism and organ distribution of modified mCNTs were basically invariant. Together, our study provides evidence that mCNTs and the modified mCNTs all could induce oxidative damage and thereby impair cells. ^99mTc-mCNTs can effectively trace the distribution of nanotubes in vivo.

Nanoparticles (NPs) are a wide class of materials currently used in several industrial and biomedical applications. Due to their small size (1-100 nm), NPs can easily enter the human body, inducing tissue damage. NP toxicity depends on physical and chemical NP properties (e.g., size, charge and surface area) in ways and magnitudes that are still unknown. We assess the average as well as the individual importance of NP atomic descriptors, along with chemical properties and experimental conditions, in determining cytotoxicity endpoints for several nanomaterials. We employ a multicenter cytotoxicity nanomaterial database (12 different materials with first and second dimensions ranging between 2.70 and 81.2 nm and between 4.10 and 4048 nm, respectively). We develop a regressor model based on extreme gradient boosting with hyperparameter optimization. We employ Shapley additive explanations to obtain good cytotoxicity prediction performance. Model performances are quantified as statistically significant Spearman correlations between the true and predicted values, ranging from 0.5 to 0.7. Our results show that i) size in situ and surface areas larger than 200 nm and 50 m2/g, respectively, ii) primary particles smaller than 20 nm; iii) irregular (i.e., not spherical) shapes and iv) positive Z-potentials contribute the most to the prediction of NP cytotoxicity, especially if lactate dehydrogenase (LDH) assays are employed for short experimental times. These results were moderately stable across toxicity endpoints, although some degree of variability emerged across dose quantification methods, confirming the complexity of nano-bio interactions and the need for large, systematic experimental characterization to reach a safer-by-design approach.

Opportunities for the exposure of pregnant women to engineered nanoparticles have been increasing with the expanding use of these materials. Therefore, there are concerns that nanoparticles could have adverse effects on the establishment and maintenance of pregnancy. The effects of nanoparticles on the mother and fetus have been evaluated from this perspective, but there is still little knowledge about the effects on placentation and function acquisition, which are essential for the successful establishment and maintenance of pregnancy. Formation of the syncytiotrophoblast is indispensable for the acquisition of placental function, and impairment of syncytialization inevitably affects pregnancy outcomes. Here, we assessed the effect of nanoparticles on placental formation by using forskolin-treated BeWo cells, a typical in vitro model of trophoblast syncytialization. Immunofluorescence staining analysis revealed that silver nanoparticles with a diameter of 10 nm (nAg10) (at 0.156 µg/mL) significantly decreased the proportion of syncytialized BeWo cells, but gold nanoparticles with a diameter of 10 nm did not. Consistently, only nAg10 (at 0.156 µg/mL) significantly suppressed forskolin-induced elevation of CGB and SDC1 mRNA expression levels and human chorionic gonadotropin β production in a dose-dependent manner; these molecules are all markers of syncytialization. Besides, nAg10 significantly decreased the expression of ERVFRD-1, which encodes proteins associated with cell fusion. Moreover, nAg10 tended to suppress the expression of sFlt-1 e15a, a placental angiogenesis marker. Collectively, our data suggest that nAg10 could suppress formation of the syncytiotrophoblast and that induce placental dysfunction and the following poor pregnancy outcomes.

Recently a new International Standard for testing nanomaterial photocatalytic activity under physiological conditions was issued by Technical Committee 229 (Nanotechnologies) of the International Organization for Standardization (ISO 20814:2019 Nanotechnologies-Testing the photocatalytic activity of nanoparticles for NADH oxidation). The document offers a robust, high throughput photocatalytic assay using a bio-compatible indicator nicotinamide amide dinucleotide (NAD) and provides a screening tool to gauge nanomaterial potency for phototoxicity. This paper describes the measurement principles behind this assay, the scope of the standard and its validation through an interlaboratory comparison study using a traceable standard reference material (SRM 1898).