Machine Learning Allowed Interpreting Toxicity of a Fe-Doped CuO NM Library Large Data Set─An Environmental In Vivo Case Study.

The wide variation of nanomaterial (NM) characters (size, shape, and properties) and the related impacts on living organisms make it virtually impossible to assess their safety; the need for modeling has been urged for long. We here investigate the custom-designed 1-10% Fe-doped CuO NM library. Effects were assessed using the soil ecotoxicology model Enchytraeus crypticus (Oligochaeta) in the standard 21 days plus its extension (49 days). Results showed that 10%Fe-CuO was the most toxic (21 days reproduction EC50 = 650 mg NM/kg soil) and Fe3O4 NM was the least toxic (no effects up to 3200 mg NM/kg soil). All other NMs caused similar effects to E. crypticus (21 days reproduction EC50 ranging from 875 to 1923 mg NM/kg soil, with overlapping confidence intervals). Aiming to identify the key NM characteristics responsible for the toxicity, machine learning (ML) modeling was used to analyze the large data set [9 NMs, 68 descriptors, 6 concentrations, 2 exposure times (21 and 49 days), 2 endpoints (survival and reproduction)]. ML allowed us to separate experimental related parameters (e.g., zeta potential) from particle-specific descriptors (e.g., force vectors) for the best identification of important descriptors. We observed that concentration-dependent descriptors (environmental parameters, e.g., zeta potential) were the most important under standard test duration (21 day) but not for longer exposure (closer representation of real-world conditions). In the longer exposure (49 days), the particle-specific descriptors were more important than the concentration-dependent parameters. The longer-term exposure showed that the steepness of the concentration-response decreased with an increased Fe content in the NMs. Longer-term exposure should be a requirement in the hazard assessment of NMs in addition to the standard in OECD guidelines for chemicals. The progress toward ML analysis is desirable given its need for such large data sets and significant power to link NM descriptors to effects in animals. This is beyond the current univariate and concentration-response modeling analysis.

Graphene Oxide Nanosheets Toxicity in Mice Is Dependent on Protein Corona Composition and Host Immunity.

Two-dimension graphene oxide (GO) nanosheets with high and low serum protein binding profiles (high/low hard-bound protein corona/HChigh/low) are used in this study as model materials and screening tools to investigate the underlying roles of the protein corona on nanomaterial toxicities in vivo. We proposed that the in vivo biocompatibility/nanotoxicity of GO is protein corona-dependent and host immunity-dependent. The hypothesis was tested by injecting HChigh/low GO nanosheets in immunocompetent ICR/CD1 and immunodeficient NOD-scid II2rγnull mice and performed histopathological and hematological evaluation studies on days 1 and 14 post-injection. HClow GO induced more severe acute lung injury compared to HChigh GO in both immunocompetent and immunodeficient mice, with the effect being particularly pronounced in immunocompetent animals. Additionally, HClow GO caused more significant liver injury in both types of mice, with immunodeficient mice being more susceptible to its hepatotoxic effects. Moreover, administration of HClow GO resulted in increased hematological toxicity and elevated levels of serum pro-inflammatory cytokines in immunocompromised and immunocompetent mice, respectively. Correlation studies were conducted to explore the impact of distinct protein corona compositions on resulting toxicities in both immunocompetent and immunodeficient mice. This facilitated the identification of consistent patterns, aligning with those observed in vitro, thus indicating a robust in vitro-in vivo correlation. This research will advance our comprehension of how hard corona proteins interact with immune cells, leading to toxicity, and will facilitate the development of improved immune-modulating nanomaterials for therapeutic purposes.

Biodistribution of cerium dioxide and titanium dioxide nanomaterials in rats after single and repeated inhalation exposures.

BACKGROUND: Physiologically based kinetic models facilitate the safety assessment of inhaled engineered nanomaterials (ENMs). To develop these models, high quality datasets on well-characterized ENMs are needed. However, there are at present, several data gaps in the systemic availability of poorly soluble particles after inhalation. The aim of the present study was therefore to acquire two comparable datasets to parametrize a physiologically-based kinetic model. METHOD: Rats were exposed to cerium dioxide (CeO2, 28.4 ± 10.4 nm) and titanium dioxide (TiO2, 21.6 ± 1.5 nm) ENMs in a single nose-only exposure to 20 mg/m3 or a repeated exposure of 2 × 5 days to 5 mg/m3. Different dose levels were obtained by varying the exposure time for 30 min, 2 or 6 h per day. The content of cerium or titanium in three compartments of the lung (tissue, epithelial lining fluid and freely moving cells), mediastinal lymph nodes, liver, spleen, kidney, blood and excreta was measured by Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) at various time points post-exposure. As biodistribution is best studied at sub-toxic dose levels, lactate dehydrogenase (LDH), total protein, total cell numbers and differential cell counts were determined in bronchoalveolar lavage fluid (BALF). RESULTS: Although similar lung deposited doses were obtained for both materials, exposure to CeO2 induced persistent inflammation indicated by neutrophil granulocytes influx and exhibited an increased lung elimination half-time, while exposure to TiO2 did not. The lavaged lung tissue contained the highest metal concentration compared to the lavage fluid and cells in the lavage fluid for both materials. Increased cerium concentrations above control levels in secondary organs such as lymph nodes, liver, spleen, kidney, urine and faeces were detected, while for titanium this was found in lymph nodes and liver after repeated exposure and in blood and faeces after a single exposure. CONCLUSION: We have provided insight in the distribution kinetics of these two ENMs based on experimental data and modelling. The study design allows extrapolation at different dose-levels and study durations. Despite equal dose levels of both ENMs, we observed different distribution patterns, that, in part may be explained by subtle differences in biological responses in the lung.

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.

Engineered nanomaterials exert sublethal bacterial stress at very low doses: Effects of concentration, light, and media on cell membrane permeability.

Engineered nanomaterials (ENMs) can alter surface properties of cells and disturb cellular functions and gene expression through direct and indirect contact, exerting unintended impacts on human and ecological health. However, the effects of interactions among environmental factors, such as light, surrounding media, and ENM mixtures, on the mechanisms of ENM toxicity, especially at sublethal concentrations, are much less explored and understood. Therefore, we evaluated cell viability and outer membrane permeability of E. coli as a function of exposure to environmentally relevant concentrations of ENMs, including metal (n-Ag) and metal oxide (n-TiO2, n-Al2O3, n-ZnO, n-CuO, and n-SiO2) nanoparticles under dark and simulated sunlight illumination in MOPS, a synthetic buffer, and Lake Michigan Water (LMW), a freshwater medium. We found that light activates the phototoxicity of n-TiO2 and n-Ag by inducing significant increases in bacterial outer membrane permeability at sublethal doses (< 1 mg/L). Other ENMs, including n-ZnO, n-CuO, n-Al2O3, and n-SiO2, have small to minimal impacts. Toxicities of ENMs were greater in LMW than MOPS due to their different ionic strength and chemical composition. Physical and chemical interactions between n-TiO2 and n-Ag lead to amplified toxic effects of the ENM mixtures that are greater than the additive effects of individual ENMs acting alone. Our results revealed the significant sublethal bacterial stress exerted by ENMs and ENM mixtures at the cell surface in natural environments at low doses, which can potentially lead to further cellular damage and eventually impact overall ecological health.

Microbial response to the chronic toxicity effect of graphene and graphene oxide nanomaterials within aerobic granular sludge systems.

Nanomaterials present in wastewater can pose a significant threat to aerobic granular sludge (AGS) systems. Herein, we found that compared to graphene nanomaterials (G-NMs), the long-term presence (95 days) of graphene oxide nanomaterials (GO-NMs) resulted in an increased proliferation of filamentous bacteria, poorer sedimentation performance (SVI30 of 74.1 mL/g) and smaller average particle size (1224.4 µm) of the AGS. In particular, the GO-NMs posed a more significant inhibitory effect to the total nitrogen removal efficiency of AGS (decreased by 14.3 %), especially for the denitrification process. The substantial accumulation of GO-NMs within the sludge matrix resulted in a higher level of reactive oxygen species in AGS compared to G-NMs, thereby inducing lactate dehydrogenase release, and enhancing superoxide oxidase and catalase activities. Such excessive oxidative stress could potentially result in a significant reduction in the activity of nitrogen metabolism enzymes (e.g., nitrate reductase and nitrite reductase) and the expression of key functional genes (e.g., nirS and nirK). Altogether, compared to G-NMs, prolonged exposure to GO-NMs had a more significant chronic toxicity effect on AGS systems. These findings implied that the presence of G-NMs and GO-NMs is a hidden danger to biological nitrogen removal and should receive more attention.

Nanostructured Magnetic Particles for Removing Cyanotoxins: Assessing Effectiveness and Toxicity In Vitro.

The rise in cyanobacterial blooms due to eutrophication and climate change has increased cyanotoxin presence in water. Most current water treatment plants do not effectively remove these toxins, posing a potential risk to public health. This study introduces a water treatment approach using nanostructured beads containing magnetic nanoparticles (MNPs) for easy removal from liquid suspension, coated with different adsorbent materials to eliminate cyanotoxins. Thirteen particle types were produced using activated carbon, CMK-3 mesoporous carbon, graphene, chitosan, 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-oxidised cellulose nanofibers (TOCNF), esterified pectin, and calcined lignin as an adsorbent component. The particles' effectiveness for detoxification of microcystin-LR (MC-LR), cylindrospermopsin (CYN), and anatoxin-A (ATX-A) was assessed in an aqueous solution. Two particle compositions presented the best adsorption characteristics for the most common cyanotoxins. In the conditions tested, mesoporous carbon nanostructured particles, P1-CMK3, provide good removal of MC-LR and Merck-activated carbon nanostructured particles, P9-MAC, can remove ATX-A and CYN with high and fair efficacy, respectively. Additionally, in vitro toxicity of water treated with each particle type was evaluated in cultured cell lines, revealing no alteration of viability in human renal, neuronal, hepatic, and intestinal cells. Although further research is needed to fully characterise this new water treatment approach, it appears to be a safe, practical, and effective method for eliminating cyanotoxins from water.

Nanometabolomics Elucidated Biological Prospective of Mo4/3B2-x Nanosheets: Toward Metabolic Reprogramming of Amino Acid Metabolism.

Mo4/3B2-x nanosheets are newly developed, and 2D transition metal borides (MBene) were reported in 2021, but there is no report on their further applications and modification; hence, this article sheds light on the significance of potential biological prospects for future biomedical applications. Therefore, elucidation of the biocompatibility, biotoxicology, and bioactivity of Mo4/3B2-x nanosheets has been an urgent need to be fulfilled. Nanometabolomics (also referred as nanomaterials-based metabolomics) was first proposed and utilized in our previous work, which specialized in interpreting nanomaterials-induced metabolic reprogramming through aqueous metabolomics and lipidomics approach. Hence, nanometabolomics could be considered as a novel concept combining nanoscience and metabolomics to provide bioinformation on nanomaterials' biomedical applications. In this work, the safe range of concentration (<50 mg/L) with good biosafety toward human umbilical vein endothelial cells (HUVECs) was discovered. The low concentration (5 mg/L) and high concentration (50 mg/L) of Mo4/3B2-x nanosheets were utilized for the in vitro Mo4/3B2-x-cell interaction. Nanometabolomics has elucidated the biological prospective of Mo4/3B2-x nanosheets via monitoring its biocompatibility and metabolic shift of HUVECs. The results revealed that 50 mg/L Mo4/3B2-x nanosheets could lead to a stronger alteration of amino acid metabolism with disturbance of the corresponding amino acid-related pathways (including amino acid metabolism, amino acid degradation, fatty acid biosynthesis, and lipid biosynthesis and metabolism). These interesting results were closely involved with the oxidative stress and production of excess ROS. This work could be regarded as a pathbreaking study on Mo4/3B2-x nanosheets at a biological level, which also designates their further biochemical, medical, and industrial application and development based on nanometabolomics bioinformation.

Worse pulmonary function in association with cumulative exposure to nanomaterials. Hints of a mediation effect via pulmonary inflammation.

BACKGROUND: Today, nanomaterials are broadly used in a wide range of industrial applications. Such large utilization and the limited knowledge on to the possible health effects have raised concerns about potential consequences on human health and safety, beyond the environmental burden. Given that inhalation is the main exposure route, workers exposed to nanomaterials might be at risk of occurrence of respiratory morbidity and/or reduced pulmonary function. However, epidemiological evidence regarding the association between cumulative exposure to nanomaterials and respiratory health is still scarce. This study focused on the association between cumulative exposure to nanomaterials and pulmonary function among 136 workers enrolled in the framework of the European multicentric NanoExplore project. RESULTS: Our findings suggest that, independently of lifelong tobacco smoking, ethnicity, age, sex, body mass index and physical activity habits, 10-year cumulative exposure to nanomaterials is associated to worse FEV1 and FEF25 - 75%, which might be consistent with the involvement of both large and small airway components and early signs of airflow obstruction. We further explored the hypothesis of a mediating effect via airway inflammation, assessed by interleukin (IL-)10, IL-1ß and Tumor Necrosis Factor alpha (TNF-α), all quantified in the Exhaled Breath Condensate of workers. The mediation analysis results suggest that IL-10, TNF-α and their ratio (i.e., anti-pro inflammatory ratio) may fully mediate the negative association between cumulative exposure to nanomaterials and the FEV1/FVC ratio. This pattern was not observed for other pulmonary function parameters. CONCLUSIONS: Safeguarding the respiratory health of workers exposed to nanomaterials should be of primary importance. The observed association between cumulative exposure to nanomaterials and worse pulmonary function parameters underscores the importance of implementing adequate protective measures in the nanocomposite sector. The mitigation of harmful exposures may ensure that workers can continue to contribute productively to their workplaces while preserving their respiratory health over time.

FAIR assessment of nanosafety data reusability with community standards.

Nanomaterials hold great promise for improving our society, and it is crucial to understand their effects on biological systems in order to enhance their properties and ensure their safety. However, the lack of consistency in experimental reporting, the absence of universally accepted machine-readable metadata standards, and the challenge of combining such standards hamper the reusability of previously produced data for risk assessment. Fortunately, the research community has responded to these challenges by developing minimum reporting standards that address several of these issues. By converting twelve published minimum reporting standards into a machine-readable representation using FAIR maturity indicators, we have created a machine-friendly approach to annotate and assess datasets' reusability according to those standards. Furthermore, our NanoSafety Data Reusability Assessment (NSDRA) framework includes a metadata generator web application that can be integrated into experimental data management, and a new web application that can summarize the reusability of nanosafety datasets for one or more subsets of maturity indicators, tailored to specific computational risk assessment use cases. This approach enhances the transparency, communication, and reusability of experimental data and metadata. With this improved FAIR approach, we can facilitate the reuse of nanosafety research for exploration, toxicity prediction, and regulation, thereby advancing the field and benefiting society as a whole.

Assessing the role of the graphene family nanomaterials (GFNs: Graphene, GO, rGO) in modifying the toxicity potential and environmental risk of flame retardant, tetrabromobisphenol-A (TBBPA) in the marine microalgae Chlorella sp.

In recent years, a growing concern has emerged regarding the environmental implications of flame retardants (FRs) like tetrabromobisphenol-A (TBBPA) and graphene family nanomaterials (GFNs), such as graphene, graphene oxide (GO), and reduced graphene oxide (rGO), on marine biota. Despite these substances' well-established individual toxicity profiles, there is a notable gap in understanding the physicochemical interactions within the binary mixtures and consequent changes in the toxicity potential. Therefore, our research focuses on elucidating the individual and combined toxicological impacts of TBBPA and GFNs on the marine alga Chlorella sp. Employing a suite of experimental methodologies, including Raman spectroscopy, contact angle measurements, electron microscopy, and chromatography, we examined the physicochemical interplay between the GFNs and TBBPA. The toxicity potentials of individual constituents and their binary combinations were assessed through growth inhibition assays, quantifying reactive oxygen species (ROS) generation and malondialdehyde (MDA) production, photosynthetic activity analyses, and various biochemical assays. The toxicity of TBBPA and graphene-based nanomaterials (GFNs) was examined individually and in combinations. Both pristine TBBPA and GFNs showed dose-dependent toxicity. While lower TBBPA concentrations exacerbated toxicity in binary mixtures, higher TBBPA levels reduced the toxic effects compared to pristine TBBPA treatments. The principal mechanism underlying toxicity was ROS generation, resulting in membrane damage and perturbation of photosynthetic parameters. Cluster heatmap and Pearson correlation were employed to assess correlations between the biological parameters. Finally, ecological risk assessment was undertaken to evaluate environmental impacts of the individual components and the mixture in the algae.

Mechanisms of surface groups regulating developmental toxicity of graphene-based nanomaterials via glycerophospholipid metabolic pathway.

Surface modification of graphene-based nanomaterials (GBNs) may occur in aquatic environment and during intentional preparation. However, the influence of the surface groups on the developmental toxicity of GBNs has not been determined. In this study, we evaluated the developmental toxicity of three GBNs including GO (graphene oxide), RGO (reduced GO) and RGO-N (aminated RGO) by employing zebrafish embryos at environmentally relevant concentrations (1-100 µg/L), and the underlying metabolic mechanisms were explored. The results showed that both GO and RGO-N disturbed the development of zebrafish embryos, and the adverse effect of GO was greater than that of RGO-N. Furthermore, the oxygen-containing groups of GBNs play a more important role in inducing developmental toxicity compared to size, defects and nitrogen-containing groups. Specifically, the epoxide and hydroxyl groups of GBNs increased their intrinsic oxidative potential, promoted the generation of ROS, and caused lipid peroxidation. Moreover, a significant decrease in guanosine and abnormal metabolism of multiple glycerophospholipids were observed in all three GBN-treated groups. Nevertheless, GO exposure triggered more metabolic activities related to lipid peroxidation than RGO or RGO-N exposure, and the disturbance intensity of the same metabolite was greater than that of the other two agents. These findings reveal underlying metabolic mechanisms of GBN-induced developmental toxicity.

Emerging concern of nano-pollution in agro-ecosystem: Flip side of nanotechnology.

Nanomaterials (NMs) have proven to be a game-changer in agriculture, showcasing their potential to boost plant growth and safeguarding crops. The agricultural sector has widely adopted NMs, benefiting from their small size, high surface area, and optical properties to augment crop productivity and provide protection against various stressors. This is attributed to their unique characteristics, contributing to their widespread use in agriculture. Human exposure from various components of agro-environmental sectors (soil, crops) NMs residues are likely to upsurge with exposure paths may stimulates bioaccumulation in food chain. With the aim to achieve sustainability, nanotechnology (NTs) do exhibit its potentials in various domains of agriculture also have its flip side too. In this review article we have opted a fusion approach using bibliometric based analysis of global research trend followed by a holistic assessment of pros and cons i.e. toxicological aspect too. Moreover, we have also tried to analyse the current scenario of policy associated with the application of NMs in agro-environment.

Building species trait-specific nano-QSARs: Model stacking, navigating model uncertainties and limitations, and the effect of dataset size.

A strong need exists for broadly applicable nano-QSARs, capable of predicting toxicological outcomes towards untested species and nanomaterials, under different environmental conditions. Existing nano-QSARs are generally limited to only a few species but the inclusion of species characteristics into models can aid in making them applicable to multiple species, even when toxicity data is not available for biological species. Species traits were used to create classification- and regression machine learning models to predict acute toxicity towards aquatic species for metallic nanomaterials. Afterwards, the individual classification- and regression models were stacked into a meta-model to improve performance. Additionally, the uncertainty and limitations of the models were assessed in detail (beyond the OECD principles) and it was investigated whether models would benefit from the addition of more data. Results showed a significant improvement in model performance following model stacking. Investigation of model uncertainties and limitations highlighted the discrepancy between the applicability domain and accuracy of predictions. Data points outside of the assessed chemical space did not have higher likelihoods of generating inadequate predictions or vice versa. It is therefore concluded that the applicability domain does not give complete insight into the uncertainty of predictions and instead the generation of prediction intervals can help in this regard. Furthermore, results indicated that an increase of the dataset size did not improve model performance. This implies that larger dataset sizes may not necessarily improve model performance while in turn also meaning that large datasets are not necessarily required for prediction of acute toxicity with nano-QSARs.

Investigation of the effects and mechanisms of manganese-based NMs on rice growth.

Manganese-based (Mn-based) nanomaterials (NMs) have great potential as alternatives to conventional Mn fertilizers. Yet, its environmental risks and effects on plant growth are not completely well understood. This study investigated the physiological effects of manganese dioxide (MnO2) and manganese tetroxide (Mn3O4) NMs on inter-root exposure (0-500 mg/L) of hydroponically grown rice. The results showed that on inter-root exposure, 50 mg/L Mn-based NMs promoted the uptake of mineral elements and enhanced the enzymatic activities of antioxidant systems (CAT and SOD) in rice, whereas 500 mg/L Mn3O4 NMs disrupted the mineral element homeostasis and led to phytotoxicity. The promotion effect of MnO2 NMs was better, firstly because MnO2 NMs treatment had lower Mn content in the plant than Mn3O4 NMs. In addition, MnO2 NMs are more transported and absorbed in the plant in ionic form, while Mn3O4 NMs exist in granular form. MnO2 NMs and Mn3O4 NMs both can be used as nano-fertilizers to improve the growth of rice by inter-root application, but the doses should be carefully selected.

Effects of dissolved organic matter on the environmental behavior and toxicity of metal nanomaterials: A review.

Metal nanomaterials (MNMs) have been released into the environment during their usage in various products, and their environmental behaviors directly impact their toxicity. Numerous environmental factors potentially affect the behaviors and toxicity of MNMs with dissolved organic matter (DOM) playing the most essential role. Abundant facts showing contradictory results about the effects of DOM on MNMs, herein the occurrence of DOM on the environmental process change of MNMs such as dissolution, dispersion, aggregation, and surface transformation were summarized. We also reviewed the effects of MNMs on organisms and their mechanisms in the environment such as acute toxicity, oxidative stress, oxidative damage, growth inhibition, photosynthesis, reproductive toxicity, and malformation. The presence of DOM had the potential to reduce or enhance the toxicity of MNMs by altering the reactive oxygen species (ROS) generation, dissolution, stability, and electrostatic repulsion of MNMs. Furthermore, we summarized the factors that affected different toxicity including specific organisms, DOM concentration, DOM types, light conditions, detection time, and production methods of MNMs. However, the more detailed mechanism of interaction between DOM and MNMs needs further investigation.

Exposure to nanoplastics and nanomaterials either single and combined affects the gill-associated microbiome of the Antarctic soft-shelled clam Laternula elliptica.

Nanoplastics and engineering nanomaterials (ENMs) are contaminants of emerging concern (CECs), increasingly being detected in the marine environment and recognized as a potential threat for marine biota at the global level including in polar areas. Few studies have assessed the impact of these anthropogenic nanoparticles in the microbiome of marine invertebrates, however combined exposure resembling natural scenarios has been overlooked. The present study aimed to evaluate the single and combined effects of polystyrene nanoparticles (PS NP) as proxy for nanoplastics and nanoscale titanium dioxide (nano-TiO2) on the prokaryotic communities associated with the gill tissue of the Antarctic soft-shell clam Laternula elliptica, a keystone species of marine benthos Wild-caught specimens were exposed to two environmentally relevant concentrations of carboxylated PS NP (PS-COOH NP, ∼62 nm size) and nano-TiO2 (Aeroxide P25, ∼25 nm) as 5 and 50 µg/L either single and combined for 96h in a semi-static condition.Our findings show a shift in microbiome composition in gills of soft-shell clams exposed to PS NP and nano-TiO2 either alone and in combination with a decrease in the relative abundance of OTU1 (Spirochaetaceae). In addition, an increase of gammaproteobacterial OTUs affiliated to MBAE14 and Methylophagaceae (involved in ammonia denitrification and associated with low-quality water), and the OTU Colwellia rossensis (previously recorded in polluted waters) was observed. Our results suggest that nanoplastics and nano-TiO2 alone and in combination induce alterations in microbiome composition by promoting the increase of negative taxa over beneficial ones in the gills of the Antarctic soft-shell clam. An increase of two low abundance OTUs in PS-COOH NPs exposed clams was also observed. A predicted gene function analysis revealed that sugar, lipid, protein and DNA metabolism were the main functions affected by either PS-COOH NP and nano-TiO2 exposure. The molecular functions involved in the altered affiliated OTUs are novel for nano-CEC exposures.

Recent advances on environmental behavior of Cu-based nanomaterials in soil-plant system: A review.

In recent years, copper-based nanomaterials (Cu-based NMs) have shown great potential in promoting agriculture development due to their special physicochemical characteristics. With the mass production and overuse of Cu-based NMs, there are potential effects on the soil-plant environment. Soil organisms, especially soil microorganisms, play a significant part in terrestrial or soil ecosystems; plants, as indirect organisms with soil-related Cu-based NMs, may affect human health through plant agricultural products. Understanding the accumulation and transformation of Cu-based NMs in soil-plant systems, as well as their ecotoxicological effects and potential mechanisms, is a prerequisite for the scientific assessment of environmental risks and safe application. Therefore, based on the current literature, this review: (i) introduces the accumulation and transformation behaviors of Cu-based NMs in soil and plant systems; (ii) focuses on the ecotoxicological effects of Cu-based NMs on a variety of organisms (microorganisms, invertebrates, and plants); (iii) reveals their corresponding toxicity mechanisms. It appears from studies hitherto made that both Cu-based NMs and released Cu2+ may be the main reasons for toxicity. When Cu-based NMs enter the soil-plant environment, their intrinsic physicochemical properties, along with various environmental factors, could also affect their transport, transformation, and biotoxicity. Therefore, we should push for intensifying the multi-approach research that focuses on the behaviors of Cu-based NMs in terrestrial exposure environments, and mitigates their toxicity to ensure the promotion of Cu-based NMs.

Gene expression profiles and protein-protein interaction networks in THP-1 cells exposed to metal-based nanomaterials.

We analyzed gene expression in THP-1 cells exposed to metal-based nanomaterials (NMs) [TiO2 (NM-100), ZnO (NM-110), SiO2 (NM-200), Ag (NM-300 K)]. A functional enrichment analysis of the significant differentially expressed genes (DEGs) identified the key modulated biological processes and pathways. DEGs were used to construct protein-protein interaction networks. NM-110 and NM-300 K induced changes in the expression of genes involved in oxidative and genotoxic stress, immune response, alterations of cell cycle, detoxification of metal ions and regulation of redox-sensitive pathways. Both NMs shared a number of highly connected protein nodes (hubs) including CXCL8, ATF3, HMOX1, and IL1B. NM-200 induced limited transcriptional changes, mostly related to the immune response; however, several hubs (CXCL8, ATF3) were identical with NM-110 and NM-300 K. No effects of NM-100 were observed. Overall, soluble nanomaterials NM-110 and NM-300 K exerted a wide variety of toxic effects, while insoluble NM-200 induced immunotoxicity; NM-100 caused no detectable changes on the gene expression level.

Nanomaterials-induced programmed cell death: Focus on mitochondria.

Nanomaterials are widely utilized in several domains, such as everyday life, societal manufacturing, and biomedical applications, which expand the potential for nanomaterials to penetrate biological barriers and interact with cells. Multiple studies have concentrated on the particular or improper utilization of nanomaterials, resulting in cellular death. The primary mode of cell death caused by nanotoxicity is programmable cell death, which includes apoptosis, ferroptosis, necroptosis, and pyroptosis. Based on our prior publications and latest research, mitochondria have a vital function in facilitating programmed cell death caused by nanomaterials, as well as initiating or transmitting death signal pathways associated with it. Therefore, this review takes mitochondria as the focal point to investigate the internal molecular mechanism of nanomaterial-induced programmed cell death, with the aim of identifying potential targets for prevention and treatment in related studies.