A systematic review on the state-of-the-art and research gaps regarding inorganic and carbon-based multicomponent and high-aspect ratio nanomaterials.

This review explores the state-of-the-art with respect to multicomponent nanomaterials (MCNMs) and high aspect ratio nanomaterials (HARNs), with a focus on their physicochemical characterisation, applications, and hazard, fate, and risk assessment. Utilising the PRISMA approach, this study investigates specific MCNMs including cerium-zirconium mixtures (CeZrO) and ZnO nanomaterials doped with transition metals and rare earth elements, as well as Titanium Carbide (TiC) nanomaterials contained in Ti-6Al-4V alloy powders. HARNs of interest include graphene, carbon-derived nanotubes (CNTs), and metallic nanowires, specifically Ag-based nanowires.

NanoBioAccumulate: Modelling the uptake and bioaccumulation of nanomaterials in soil and aquatic invertebrates via the Enalos DIAGONAL Cloud Platform.

is a free-to-use web-based tool hosted on the Enalos DIAGONAL Cloud Platform (https://www.enaloscloud.novamechanics.

In silico assessment of nanoparticle toxicity powered by the Enalos Cloud Platform: Integrating automated machine learning and synthetic data for enhanced nanosafety evaluation.

The rapid advance of nanotechnology has led to the development and widespread application of nanomaterials, raising concerns regarding their potential adverse effects on human health and the environment. Traditional (experimental) methods for assessing the nanoparticles (NPs) safety are time-consuming, expensive, and resource-intensive, and raise ethical concerns due to their reliance on animals. To address these challenges, we propose an workflow that serves as an alternative or complementary approach to conventional hazard and risk assessment strategies, which incorporates state-of-the-art computational methodologies.

Combined toxicity of fluorescent silica nanoparticles with cadmium in Ceriodaphnia dubia: Interactive effects of natural organic matter and green algae feeding.

The environmental risks of silica nanoparticles (SiNP) reported in the literature are contradictory and bring into question its safety for use in consumer applications. Organisms are never exposed to NPs alone in the real environment, while studies of the combined toxicity of SiNP are limited. To address this, we compared the acute toxicity of fluorescent core-shell SiNPs alone and in mixtures with Cd to Ceriodaphnia dubia in the absence and presence of NOM.

An ancestral molecular response to nanomaterial particulates.

The varied transcriptomic response to nanoparticles has hampered the understanding of the mechanism of action. Here, by performing a meta-analysis of a large collection of transcriptomics data from various engineered nanoparticle exposure studies, we identify common patterns of gene regulation that impact the transcriptomic response. Analysis identifies deregulation of immune functions as a prominent response across different exposure studies.

A Systematic Review of Deep Learning Methodologies Used in the Drug Discovery Process with Emphasis on In Vivo Validation.

The discovery and development of new drugs are extremely long and costly processes. Recent progress in artificial intelligence has made a positive impact on the drug development pipeline. Numerous challenges have been addressed with the growing exploitation of drug-related data and the advancement of deep learning technology.

Toxicokinetics and bioaccumulation of silver sulfide nanoparticles in benthic invertebrates in an indoor stream mesocosm.

Mesocosms allow the simulation of environmentally relevant conditions and can be used to establish more realistic scenarios of organism exposure to nanoparticles. An indoor mesocosm experiment simulating an aquatic stream ecosystem was conducted to assess the toxicokinetics and bioaccumulation of silver sulfide nanoparticles (AgS NPs) and AgNO in the freshwater invertebrates Girardia tigrina, Physa acuta and Chironomus riparius, and determine if previous single-species tests can predict bioaccumulation in the mesocosm. Water was daily spiked at 10 μg Ag L.

Toxicokinetics of silver and silver sulfide nanoparticles in Chironomus riparius under different exposure routes.

Engineered nanoparticles released into surface water may accumulate in sediments, potentially threatening benthic organisms. This study determined the toxicokinetics in Chironomus riparius of Ag from pristine silver nanoparticles (Ag NPs), a simulating aged Ag NP form (AgS NPs), and AgNO as an ionic control. Chironomid larvae were exposed to these Ag forms through water, sediment, or food.

European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials.

Management of nanomaterials and nanosafety data needs to operate under the FAIR (findability, accessibility, interoperability, and reusability) principles and this requires a unique, global identifier for each nanomaterial. Existing identifiers may not always be applicable or sufficient to definitively identify the specific nanomaterial used in a particular study, resulting in the use of textual descriptions in research project communications and reporting. To ensure that internal project documentation can later be linked to publicly released data and knowledge for the specific nanomaterials, or even to specific batches and variants of nanomaterials utilised in that project, a new identifier is proposed: the European Registry of Materials Identifier.

Metal transfer to sediments, invertebrates and fish following waterborne exposure to silver nitrate or silver sulfide nanoparticles in an indoor stream mesocosm.

The fate of engineered nanomaterials in ecosystems is unclear. An aquatic stream mesocosm explored the fate and bioaccumulation of silver sulfide nanoparticles (AgS NPs) compared to silver nitrate (AgNO). The aims were to determine the total Ag in water, sediment and biota, and to evaluate the bioavailable fractions of silver in the sediment using a serial extraction method.

Computational enrichment of physicochemical data for the development of a ζ-potential read-across predictive model with Isalos Analytics Platform.

The physicochemical characterisation data from a library of 69 engineered nanomaterials (ENMs) has been exploited in silico following enrichment with a set of molecular descriptors that can be easily acquired or calculated using atomic periodicity and other fundamental atomic parameters. Based on the extended set of twenty descriptors, a robust and validated nanoinformatics model has been proposed to predict the ENM ζ-potential. The five critical parameters selected as the most significant for the model development included the ENM size and coating as well as three molecular descriptors, metal ionic radius (r), the sum of metal electronegativity divided by the number of oxygen atoms present in a particular metal oxide (Σχ/n) and the absolute electronegativity (χ), each of which is thoroughly discussed to interpret their influence on ζ-potential values.

Effects of sulfidation of silver nanoparticles on the Ag uptake kinetics in Brassica rapa plants.

Land application of sewage sludge containing increasing levels of silver nanoparticles (AgNPs) raises concerns about the risk for plant exposure. This study compared the uptake kinetics and distribution of Ag in Brassica rapa seedlings grown in Lufa 2.2 natural soil spiked with 20 nm AgS NPs, with those from 3 to 8 nm AgNPs, 50 nm AgNPs and AgNO exposures (10 mg Ag/kg dry soil).

Toxicokinetics of silver nanoparticles in the mealworm Tenebrio molitor exposed via soil or food.

Silver nanoparticles (AgNPs) may reach the soil compartment via sewage sludge or nanoagrochemical applications. Understanding how NPs interact with biological systems is crucial for an accurate hazard assessment. Therefore, this study aimed at determining the Ag toxicokinetics in the mealworm Tenebrio molitor, exposed via Lufa 2.

Manually curated transcriptomics data collection for toxicogenomic assessment of engineered nanomaterials.

Toxicogenomics (TGx) approaches are increasingly applied to gain insight into the possible toxicity mechanisms of engineered nanomaterials (ENMs). Omics data can be valuable to elucidate the mechanism of action of chemicals and to develop predictive models in toxicology. While vast amounts of transcriptomics data from ENM exposures have already been accumulated, a unified, easily accessible and reusable collection of transcriptomics data for ENMs is currently lacking.

Can an InChI for Nano Address the Need for a Simplified Representation of Complex Nanomaterials across Experimental and Nanoinformatics Studies?

Chemoinformatics has developed efficient ways of representing chemical structures for small molecules as simple text strings, simplified molecular-input line-entry system (SMILES) and the IUPAC International Chemical Identifier (InChI), which are machine-readable. In particular, InChIs have been extended to encode formalized representations of mixtures and reactions, and work is ongoing to represent polymers and other macromolecules in this way. The next frontier is encoding the multi-component structures of nanomaterials (NMs) in a machine-readable format to enable linking of datasets for nanoinformatics and regulatory applications.

Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data.

The emergence of nanoinformatics as a key component of nanotechnology and nanosafety assessment for the prediction of engineered nanomaterials (NMs) properties, interactions, and hazards, and for grouping and read-across to reduce reliance on animal testing, has put the spotlight firmly on the need for access to high-quality, curated datasets. To date, the focus has been around what constitutes data quality and completeness, on the development of minimum reporting standards, and on the FAIR (findable, accessible, interoperable, and reusable) data principles. However, moving from the theoretical realm to practical implementation requires human intervention, which will be facilitated by the definition of clear roles and responsibilities across the complete data lifecycle and a deeper appreciation of what metadata is, and how to capture and index it.

Predicting Cytotoxicity of Metal Oxide Nanoparticles using Isalos Analytics Platform.

A literature curated dataset containing 24 distinct metal oxide (MeO) nanoparticles (NPs), including 15 physicochemical, structural and assay-related descriptors, was enriched with 62 atomistic computational descriptors and exploited to produce a robust and validated in silico model for prediction of NP cytotoxicity. The model can be used to predict the cytotoxicity (cell viability) of MeO NPs based on the colorimetric lactate dehydrogenase (LDH) assay and the luminometric adenosine triphosphate (ATP) assay, both of which quantify irreversible cell membrane damage. Out of the 77 total descriptors used, 7 were identified as being significant for induction of cytotoxicity by MeO NPs.

Impact of AgS NPs on soil bacterial community - A terrestrial mesocosm approach.

Soils might be a final sink for AgS nanoparticles (NPs). Still, there are limited data on their effects on soil bacterial communities (SBC). To bridge this gap, we investigated the effects of AgS NPs (10 mg kg soil) on the structure and function of SBC in a terrestrial indoor mesocosm, using a multi-species design.

Effect of the Albumin Corona on the Toxicity of Combined Graphene Oxide and Cadmium to and Integration of the Datasets into the NanoCommons Knowledge Base.

In this work, we evaluated the effect of protein corona formation on graphene oxide (GO) mixture toxicity testing (i.e., co-exposure) using the model and assessing acute toxicity determined as immobilisation.

NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for nanosafety assessment.

Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals.

Zeta-Potential Read-Across Model Utilizing Nanodescriptors Extracted via the NanoXtract Image Analysis Tool Available on the Enalos Nanoinformatics Cloud Platform.

Zeta potential is one of the most critical properties of nanomaterials (NMs) which provides an estimation of the surface charge, and therefore electrostatic stability in medium and, in practical terms, influences the NM's tendency to form agglomerates and to interact with cellular membranes. This paper describes a robust and accurate read-across model to predict NM zeta potential utilizing as the input data a set of image descriptors derived from transmission electron microscopy (TEM) images of the NMs. The image descriptors are calculated using NanoXtract (http://enaloscloud.

Synthesis and characterization of Zr- and Hf-doped nano-TiO as internal standards for analytical quantification of nanomaterials in complex matrices.

The reliable quantification of nanomaterials (NMs) in complex matrices such as food, cosmetics and biological and environmental compartments can be challenging due to interactions with matrix components and analytical equipment (vials and tubing). The resulting losses along the analytical process (sampling, extraction, clean-up, separation and detection) hamper the quantification of the target NMs in these matrices as well as the compatibility of results and meaningful interpretations in safety assessments. These issues can be overcome by the addition of known amounts of internal/recovery standards to the sample prior to analysis.

Microscopy-based high-throughput assays enable multi-parametric analysis to assess adverse effects of nanomaterials in various cell lines.

Manufactured nanomaterials (MNMs) selected from a library of over 120 different MNMs with varied compositions, sizes, and surface coatings were tested by four different laboratories for toxicity by high-throughput/-content (HT/C) techniques. The selected particles comprise 14 MNMs composed of CeO, Ag, TiO, ZnO and SiO with different coatings and surface characteristics at varying concentrations. The MNMs were tested in different mammalian cell lines at concentrations between 0.

Corneal confocal microscopy findings in sporadic cases of pre-descemet corneal dystrophy.

Purpose: To present corneal confocal microscopy (CCM) findings in a series of patients with pre-Descemet corneal dystrophy (PDCD).

Methods: A 28-year-old man, a 50-year-old man, a 30-year-old woman, and a 31-year-old man were clinically diagnosed with PDCD on slit lamp microscopic evaluation. All patients were evaluated by means of CCM.