TRIumph in nanotoxicology: simplifying transcriptomics into a single predictive variable.

The primary aim of our study was to address the problem of transcriptomic data complexity by introducing a novel transcriptomic response index (TRI), compressing the entire transcriptomic space into a single variable, and linking it with the inhaled multiwalled carbon nanotubes (MWCNTs) properties. This methodology allows us to predict fold change values of thousands of differentially expressed genes (DEGs) using a single variable and a single quantitative structure-activity relationship (QSAR) model. In the context of this work, TRI compressed 5167 DEGs into a single variable, explaining 99.

New Approach Methods (NAMs) for genotoxicity assessment of nano- and advanced materials; Advantages and challenges.

Genotoxicity assessment is essential for ensuring chemical safety and mitigating risks to human health and the environment. Traditional methods, reliant on animal models, are time-consuming, costly, and raise ethical concerns. New Approach Methods (NAMs) offer innovative, cost-effective, and ethical alternatives, playing a pivotal role in both traditional and next-generation risk assessment (NGRA) by minimizing the need for animal testing, particularly in genotoxicity evaluations.

The role of machine learning in predicting titanium dioxide nanoparticles induced pulmonary pathology using transcriptomic biomarkers.

This study explores the application of machine learning (ML) in identifying transcriptomic changes associated with pulmonary pathologies induced by titanium dioxide nanoparticles (TiO-NPs). Such an approach significantly contributes to understanding the underlying mode-of-action of TiO-NP inhalation and follows the European Chemicals Agency's recommendations on applying Novel Approach Methodologies designed for reducing animal studies. The lung gene expression profiles from mice exposed via single intratracheal instillations to TiO-NPs with varying physicochemical properties on day 1, and day 28 post-exposure were analyzed to develop computational models for predicting the lung pathologies of rutile TiO-NPs.

Application of Biomimetic Chromatography and QSRR Approach for Characterizing Organophosphate Pesticides.

Biomimetic chromatography is a powerful tool used in the pharmaceutical industry to characterize the physicochemical properties of molecules during early drug discovery. Some studies have indicated that biomimetic chromatography may also be useful for the evaluation of toxicologically relevant molecules. In this study, we evaluated the usefulness of the biomimetic chromatography approach for determining the lipophilicity, affinity to phospholipids, and bind to plasma proteins of selected organophosphate pesticides.

The Impact of Carbon Nanotube Properties on Lung Pathologies and Atherosclerosis Through Acute Inflammation: a New AOP-Anchored in Silico NAM.

In this study, a previously developed approach for creating a quantitative structure-activity relationship model anchored in an Adverse Outcome Pathway framework (AOP-anchored Nano-QSAR) is employed to develop a novel model capable of predicting transcriptomic responses triggered by the inhalation of multiwalled carbon nanotubes (MWCNTs). The acute phase response (AR) signaling pathway, which plays a crucial role in neutrophil influx and initiates the acute immune response is focused. This process involves recruiting pro-inflammatory cells into the lungs and can lead to lung fibrosis, as outlined in AOP33, or atherosclerosis, as per AOP237.

CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials.

The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs, enhancing both regulatory compliance and international collaboration. By building on established nanoinformatics frameworks, such as those developed in the H2020-funded projects NanoSolveIT and NanoCommons, CompSafeNano addresses critical challenges in nanosafety through development and integration of innovative methodologies, including advanced models, approaches including machine learning (ML) and artificial intelligence (AI)-driven predictive models and 1st-principles computational modelling of NMs properties, interactions and effects on living systems.

HBM4EU E-waste study - An untargeted metabolomics approach to characterize metabolic changes during E-waste recycling.

E-waste contains hazardous chemicals that may be a direct health risk for workers involved in recycling. We conducted an untargeted metabolomics analysis of urine samples collected from male e-waste processing workers to explore metabolic changes associated with chemical exposures in e-waste recycling in Belgium, Finland, Latvia, Luxembourg, the Netherlands, Poland, and Portugal. Questionnaire data and urine samples were obtained from workers involved in the processing of e-waste (sorting, dismantling, shredding, pre-processing, metal, and non-metal processing), as well as from controls with no known occupational exposure.

Is the potential for bioaccumulation of cannabinoids underestimated? Insights from biomimetic chromatography in cannabinoid exposure evaluation.

The use of cannabis-related products is currently experiencing extraordinary growth in popularity in the European and US markets. A wide variety of cannabis-related products have emerged, including oils, tinctures, edibles, topicals, cosmetics, and even beverages and sweets, offering the purported medical benefits without the psychoactive effects associated with Cannabis sativa. However, there is a significant gap in our understanding of bioaccumulation processes and their long-term effects, particularly as cannabinoids are highly lipophilic molecules.

Toward the Integration of Machine Learning and Molecular Modeling for Designing Drug Delivery Nanocarriers.

The pioneering work on liposomes in the 1960s and subsequent research in controlled drug release systems significantly advances the development of nanocarriers (NCs) for drug delivery. This field is evolved to include a diverse array of nanocarriers such as liposomes, polymeric nanoparticles, dendrimers, and more, each tailored to specific therapeutic applications. Despite significant achievements, the clinical translation of nanocarriers is limited, primarily due to the low efficiency of drug delivery and an incomplete understanding of nanocarrier interactions with biological systems.

Evaluation of Physicochemical Properties of Ipsapirone Derivatives Based on Chromatographic and Chemometric Approaches.

Drug discovery is a challenging process, with many compounds failing to progress due to unmet pharmacokinetic criteria. Lipophilicity is an important physicochemical parameter that affects various pharmacokinetic processes, including absorption, metabolism, and excretion. This study evaluated the lipophilic properties of a library of ipsapirone derivatives that were previously synthesized to affect dopamine and serotonin receptors.

Environmental impact of PFAS: Filling data gaps using theoretical quantum chemistry and QSPR modeling.

Per- and polyfluorinated alkyl substances (PFAS), known for their widespread environmental presence and slow degradation, pose significant concerns. Of the approximately 10,000 known PFAS, only a few have undergone comprehensive testing, resulting in limited experimental data. In this study, we employed a combination of physics-based methods and data-driven models to address gaps in PFAS bioaccumulation potential.

A bibliometric analysis of the recent achievements in pulmonary safety of nanoparticles.

Assessing research activity is an important step for planning future initiatives oriented toward filling the remaining gaps in a field. Therefore, the objective of the current study was to review recently published research on pulmonary toxicity caused by nanomaterials. However, here, instead of reviewing possible toxic effects and discussing their mode of action, the goal was to establish trends considering for example examined so far nanomaterials or used testing strategies.

Toward Nano-Specific In Silico NAMs: How to Adjust Nano-QSAR to the Recent Advancements of Nanotoxicology?

The rapid development of engineered nanomaterials (ENMs) causes humans to become increasingly exposed to them. Therefore, a better understanding of the health impact of ENMs is highly demanded. Considering the 3Rs (Replacement, Reduction, and Refinement) principle, in vitro and computational methods are excellent alternatives for testing on animals.

The Effects of Two Kinds of Dietary Interventions on Serum Metabolic Profiles in Haemodialysis Patients.

The goal of this study was to evaluate the effects of two kinds of 24-week dietary interventions in haemodialysis patients, a traditional nutritional intervention without a meal before dialysis (HG1) and implementation of a nutritional intervention with a meal served just before dialysis (HG2), in terms of analysing the differences in the serum metabolic profiles and finding biomarkers of dietary efficacy. These studies were performed in two homogenous groups of patients (n = 35 in both groups). Among the metabolites with the highest statistical significance between HG1 and HG2 after the end of the study, 21 substances were putatively annotated, which had potential significance in both of the most relevant metabolic pathways and those related to diet.

Core, Coating, or Corona? The Importance of Considering Protein Coronas in nano-QSPR Modeling of Zeta Potential.

To control stability in a biological medium, several factors affecting the zeta potential (ζ) of nanoparticles (NPs) must be considered, including complex interactions between the nanostructure and the composition of the protein corona (PC). Effective methods (based on machine learning and quantitative structure-property relationship (QSPR) models) could help predict and characterize the relationship between the physicochemical properties of NP and the formation of PC and biological outcomes in the medium at an early stage of the experiment. However, the models currently developed are limited to simple descriptors that do not represent the complex interactions between the core, the coating, and their PC fingerprints.

Representing and describing nanomaterials in predictive nanoinformatics.

Engineered nanomaterials (ENMs) enable new and enhanced products and devices in which matter can be controlled at a near-atomic scale (in the range of 1 to 100 nm). However, the unique nanoscale properties that make ENMs attractive may result in as yet poorly known risks to human health and the environment. Thus, new ENMs should be designed in line with the idea of safe-and-sustainable-by-design (SSbD).

Predicting electrophoretic mobility of TiO, ZnO, and CeO nanoparticles in natural waters: The importance of environment descriptors in nanoinformatics models.

Natural and engineered nanoparticles (NPs) entering the environment are influenced by many physicochemical processes and show various behavior in different systems (e.g., natural waters showing different characteristics).

AOP173 key event associated pathway predictor - online application for the prediction of benchmark dose lower bound (BMDLs) of a transcriptomic pathway involved in MWCNTs-induced lung fibrosis.

Nano-QSAR model allows for prediction of the toxicity of materials that have not been experimentally tested before by linking the nano-related structural properties with the biological responses induced by nanomaterials. Prediction of adverse effects caused by substances without having to perform time- and cost-consuming experiments makes QSAR models promising tools for supporting risk assessment. However, very often, newly developed nano-QSAR models are not used in practice due to the complexity of their algorithms, the necessity to have experience in chemoinformatics, and their poor accessibility.

HBM4EU Chromates Study: Urinary Metabolomics Study of Workers Exposed to Hexavalent Chromium.

Exposure to hexavalent chromium Cr(VI) may occur in several occupational activities, placing workers in many industries at risk for potential related health outcomes. Untargeted metabolomics was applied to investigate changes in metabolic pathways in response to Cr(VI) exposure. We obtained our data from a study population of 220 male workers with exposure to Cr(VI) and 102 male controls from Belgium, Finland, Poland, Portugal and the Netherlands within the HBM4EU Chromates Study.

to extrapolation to support the development of the next generation risk assessment (NGRA) strategy for nanomaterials.

There is growing interest in developing novel strategies to support assessment of human health risks due to chemicals. Regulatory and decision-making agencies have recommended that non-animal-based alternatives should be applied whenever possible instead of experimentation on living animals. These alternative methods are beneficial because they are ethical, inexpensive, and rapid.

Comparative studies on vitamin B deficiency inwholeblood of chronically haemodialysed patients: chromatographic, fluorimetricandPCAstudy.

The levels of thiamine diphosphate (ThDP), the most active biologically form of vitamin B, were assessed in whole blood oflong-term haemodialysed patients (n = 50), by applying chromatographic methods based on RP-HPLC technique with isocratic elution and fluorescence detection. The target analyte, thiochrome diphosphate (ThODP), was obtained by pre-column derivatization of vitamin B contained in blood samples, applying deproteination with trichloroacetic acid, following by oxidation with alkaline solution of potassium ferricyanide(III) and stabilization with DTT before assays. A simple and sensitive assay was developed, and the results were referenced to the commercially available test.

A strategy towards the generation of testable adverse outcome pathways for nanomaterials.

Manufactured nanomaterials (NMs) are increasingly used in a wide range of industrial applications leading to a constant increase in the market size of nano-enabled products. The increased production and use of NMs are raising concerns among different stakeholder groups with regard to their effects on human and environmental health. Currently, nanosafety hazard assessment is still widely performed using in vivo (animal) models, however the development of robust and reg­ulatory relevant strategies is required to prioritize and/or reduce animal testing.