Grouping of carbonaceous nanomaterials based on association of patterns of inflammatory markers in BAL fluid with adverse outcomes in lungs

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.

Environmental and Health Impacts of Graphene and Other Two-Dimensional Materials: A Graphene Flagship Perspective

Two-dimensional (2D) materials have attracted tremendous interest ever since the isolation of atomically thin sheets of graphene in 2004 due to the specific and versatile properties of these materials. However, the increasing production and use of 2D materials necessitate a thorough evaluation of the potential impact on human health and the environment. Furthermore, harmonized test protocols are needed with which to assess the safety of 2D materials. The Graphene Flagship project (2013-2023), funded by the European Commission, addressed the identification of the possible hazard of graphene-based materials as well as emerging 2D materials including transition metal dichalcogenides, hexagonal boron nitride, and others. Additionally, so-called green chemistry approaches were explored to achieve the goal of a safe and sustainable production and use of this fascinating family of nanomaterials. The present review provides a compact survey of the findings and the lessons learned in the Graphene Flagship.

Sarcoidosis and Autoimmune Inflammatory Syndrome Induced by Adjuvants

Currently, sarcoidosis remains one of the diseases with unknown etiology, which significantly complicates its diagnosis and treatment. Various causes of sarcoidosis have been studied for many years. Both organic and inorganic trigger factors, provoking the development of granulomatous inflammation are considered. However, the most promising and evidence-based hypothesis is the development of sarcoidosis as an autoimmune disease, provoked by various adjuvants in genetic predisposed individuals. This concept fits into the structure of the autoimmune/inflammatory syndrome, induced by adjuvants (ASIA) that was proposed in 2011 by Professor Shoenfeld Y. In this paper, the authors reveal the presence of major and minor ASIA criteria for sarcoidosis, propose a new concept of the course of sarcoidosis within the framework of ASIA, and point out the difficulties in creating a model of the disease and the selection of therapy. It is obvious that the data obtained not only bring us closer to understanding the nature of sarcoidosis, but also potentiate new studies confirming this hypothesis by obtaining a model of the disease.

Surface Functionalization of Graphene-Based Materials: Biological Behavior, Toxicology, and Safe-By-Design Aspects

The increasing exploitation of graphene-based materials (GBMs) is driven by their unique properties and structures, which ignite the imagination of scientists and engineers. At the same time, the very properties that make them so useful for applications lead to growing concerns regarding their potential impacts on human health and the environment. Since GBMs are inert to reaction, various attempts of surface functionalization are made to make them reactive. Herein, surface functionalization of GBMs, including those intentionally designed for specific applications, as well as those unintentionally acquired (e.g., protein corona formation) from the environment and biota, are reviewed through the lenses of nanotoxicity and design of safe materials (safe-by-design). Uptake and toxicity of functionalized GBMs and the underlying mechanisms are discussed and linked with the surface functionalization. Computational tools that can predict the interaction of GBMs behavior with their toxicity are discussed. A concise framing of current knowledge and key features of GBMs to be controlled for safe and sustainable applications are provided for the community.

Postchronic Single-Walled Carbon Nanotube Exposure Causes Irreversible Malignant Transformation of Human Bronchial Epithelial Cells through DNA Methylation Changes

As environmental pollutants and possible carcinogens, carbon nanotubes (CNTs) have recently been found to induce carcinogenesis and tumor metastasis after long-term pulmonary exposure. However, whether CNT-induced carcinogenesis can be inherited and last for generations remains unclear. Herein, postchronic single-walled carbon nanotubes (SWCNTs) exposed human lung cell model (BEAS-2B cells) are established to investigate SWCNT-induced carcinogenesis. At a tolerated sublethal dose level, postchronic SWCNT exposure significantly increases the migration and invasion abilities of BEAS-2B cells, leading to malignant cell transformation. Notably, the malignant transformation of BEAS-2B cells is irreversible within a 60 day recovery period after SWCNT exposure, and the malignant transformation activities of cells gradually increase during the recovery period. Moreover, these transformed cells promote carcinogenesis in vivo, accompanied by a raised level of biomarkers of lung adenocarcinoma. Further mechanism analyses reveal that postchronic exposure to SWCNTs causes substantial DNA methylation and transcriptome dysregulation of BEAS-2B cells. Subsequent enrichment and clinical database analyses reveal that differentially expressed/methylated genes of BEAS-2B cells are enriched in cancer-related biological pathways. These results not only demonstrate that postchronic SWCNT-exposure-induced carcinogenesis is heritable but also uncover a mechanism from the perspective of DNA methylation.

Physicochemical characterization and genotoxicity of the broad class of carbon nanotubes and nanofibers used or produced in U.S. facilities

BACKGROUND

Carbon nanotubes and nanofibers (CNT/F) have known toxicity but simultaneous comparative studies of the broad material class, especially those with a larger diameter, with computational analyses linking toxicity to their fundamental material characteristics was lacking. It was unclear if all CNT/F confer similar toxicity, in particular, genotoxicity. Nine CNT/F (MW #1-7 and CNF #1-2), commonly found in exposure assessment studies of U.S. facilities, were evaluated with reported diameters ranging from 6 to 150 nm. All materials were extensively characterized to include distributions of physical dimensions and prevalence of bundled agglomerates. Human bronchial epithelial cells were exposed to the nine CNT/F (0-24 μg/ml) to determine cell viability, inflammation, cellular oxidative stress, micronuclei formation, and DNA double-strand breakage. Computational modeling was used to understand various permutations of physicochemical characteristics and toxicity outcomes.

RESULTS

Analyses of the CNT/F physicochemical characteristics illustrate that using detailed distributions of physical dimensions provided a more consistent grouping of CNT/F compared to using particle dimension means alone. In fact, analysis of binning of nominal tube physical dimensions alone produced a similar grouping as all characterization parameters together. All materials induced epithelial cell toxicity and micronuclei formation within the dose range tested. Cellular oxidative stress, DNA double strand breaks, and micronuclei formation consistently clustered together and with larger physical CNT/F dimensions and agglomerate characteristics but were distinct from inflammatory protein changes. Larger nominal tube diameters, greater lengths, and bundled agglomerate characteristics were associated with greater severity of effect. The portion of tubes with greater nominal length and larger diameters within a sample was not the majority in number, meaning a smaller percentage of tubes with these characteristics was sufficient to increase toxicity. Many of the traditional physicochemical characteristics including surface area, density, impurities, and dustiness did not cluster with the toxicity outcomes.

CONCLUSION

Distributions of physical dimensions provided more consistent grouping of CNT/F with respect to toxicity outcomes compared to means only. All CNT/F induced some level of genotoxicity in human epithelial cells. The severity of toxicity was dependent on the sample containing a proportion of tubes with greater nominal lengths and diameters.

Models Contribution to the Understanding of Sarcoidosis Pathogenesis: "Are There Good Models of Sarcoidosis?"

Sarcoidosis is a systemic, granulomatous, and noninfectious disease of unknown etiology. The clinical heterogeneity of the disease (targeted tissue(s), course of the disease, and therapy response) supports the idea that a multiplicity of trigger antigens may be involved. The pathogenesis of sarcoidosis is not yet completely understood, although in recent years, considerable efforts were put to develop novel experimental research models of sarcoidosis. In particular, sarcoidosis patient cells were used within in vitro 3D models to study their characteristics compared to control patients. Likewise, a series of transgenic mouse models were developed to highlight the role of particular signaling pathways in granuloma formation and persistence. The purpose of this review is to put in perspective the contributions of the most recent models in the understanding of sarcoidosis.