Unlocking the Power of Transcriptomic Biomarkers in Qualitative and Quantitative Genotoxicity Assessment of Chemicals.

To modernize genotoxicity assessment and reduce reliance on experimental animals, new approach methodologies (NAMs) that provide human-relevant dose-response data are needed. Two transcriptomic biomarkers, GENOMARK and TGx-DDI, have shown a high classification accuracy for genotoxicity. As these biomarkers were extracted from different training sets, we investigated whether combining the two biomarkers in a human-derived metabolically competent cell line (i.e., HepaRG) provides complementary information for the classification of genotoxic hazard identification and potency ranking. First, the applicability of GENOMARK to TempO-Seq, a high-throughput transcriptomic technology, was evaluated. HepaRG cells were exposed for 72 h to increasing concentrations of 10 chemicals (i.e., eight known in vivo genotoxicants and two in vivo nongenotoxicants). Gene expression data were generated using the TempO-Seq technology. We found a prediction performance of 100%, confirming the applicability of GENOMARK to TempO-Seq. Classification using TGx-DDI was then compared to GENOMARK. For the chemicals identified as genotoxic, benchmark concentration modeling was conducted to perform potency ranking. The high concordance observed for both hazard classification and potency ranking by GENOMARK and TGx-DDI highlights the value of integrating these NAMs in a weight of evidence evaluation of genotoxicity.

Recent advances and current challenges of new approach methodologies in developmental and adult neurotoxicity testing.

Adult neurotoxicity (ANT) and developmental neurotoxicity (DNT) assessments aim to understand the adverse effects and underlying mechanisms of toxicants on the human nervous system. In recent years, there has been an increasing focus on the so-called new approach methodologies (NAMs). The Organization for Economic Co-operation and Development (OECD), together with European and American regulatory agencies, promote the use of validated alternative test systems, but to date, guidelines for regulatory DNT and ANT assessment rely primarily on classical animal testing. Alternative methods include both non-animal approaches and test systems on non-vertebrates (e.g., nematodes) or non-mammals (e.g., fish). Therefore, this review summarizes the recent advances of NAMs focusing on ANT and DNT and highlights the potential and current critical issues for the full implementation of these methods in the future. The status of the DNT in vitro battery (DNT IVB) is also reviewed as a first step of NAMs for the assessment of neurotoxicity in the regulatory context. Critical issues such as (i) the need for test batteries and method integration (from in silico and in vitro to in vivo alternatives, e.g., zebrafish, C. elegans) requiring interdisciplinarity to manage complexity, (ii) interlaboratory transferability, and (iii) the urgent need for method validation are discussed.

Analysis of preservatives and fragrances in topical medical devices: The need for more stringent regulation.

INTRODUCTION: Medical devices (MDs) have a long history of use, and come with regulatory frameworks to ensure user safety. Although topically applied MDs in the form of gels and creams might be used on damaged skin, their composition is often similar to that of cosmetic products applicable to intact skin, especially in terms of preservatives and fragrances. However, unlike cosmetics, these products are not subject to compound-specific restrictions when used in MDs. OBJECTIVE: This study aimed to identify and quantify preservatives and fragrances in topically applied MDs and assess their safety towards the Cosmetic Regulation (EC) 1223/2009. METHOD: Sixty-nine MDs available on the EU market were subjected to previously validated liquid chromatography tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS) methods to identify and quantify occurring preservatives and fragrances. RESULTS: Findings revealed that 32% of the examined MDs did not provide comprehensive ingredient lists, leaving users uninformed about potential risks associated with product use. Furthermore, 30% of these MDs would not meet safety standards for cosmetic products and, most significantly, 13% of the analysed samples contained ingredients that are prohibited in leave-on cosmetics. CONCLUSION: Results highlight the pressing demand for more stringent requirements regarding the labelling and composition of MDs to enhance patient safety. Improved regulation and transparency can mitigate potential risks associated with the use of topically applied MDs.

Lipofection-Based Delivery of CRISPR/Cas9 Ribonucleoprotein for Gene Editing in Male Germline Stem Cells.

Gene editing in the murine germline is a valuable approach to investigate germ cell maturation and generate mouse models. Several studies demonstrated that CRISPR/Cas9 alters the genome of cultured male mouse germline stem cells delivered by electroporation of plasmids. Recently, we showed proof-of-principle that gene knockout can be effectively targeted in mouse germline stem cells by lipofecting Cas9:gRNA ribonucleoproteins. In this protocol, we describe a simple, fast, and cheap workflow for gene editing via the lipofection of non-integrative ribonucleoproteins in murine male germline stem cells.

Spermatogenesis in mouse testicular organoids with testis-specific architecture, improved germ cell survival and testosterone production.

This study presents a biphasic approach to overcome the limitations of current testicular organoid (TO) cultures, including histological heterogeneity, germ cell loss and absence of spermatogenesis. Agarose microwells were utilized to create TOs from prepubertal C57BL/6 J testicular cells. First emphasis was on improving germ cell survival during the initial 2-week reorganization phase by comparingα-MEM + 10% knockout serum replacement (KSR) medium, known to support TO generation in mice, to three optimized media (1-3). Cell densities and culture dynamics were also tested to recreate histological resemblance to testes. After optimizing germ cell survival and cell organization, the effect of growth factors and immunomodulation through CD45+immune cell depletion or dexamethasone (DEX) supplementation were assessed for enhancing spermatogenesis during the subsequent differentiation phase. Testicular cells self-reorganized into organoids resembling the testicular anatomical unit, characterized by one tubule-like structure surrounded by interstitium. Media 1-3 proved superior for organoid growth during the reorganization phase, with TOs in medium 3 exhibiting germ cell numbers (7.4% ± 4.8%) comparable to controls (9.3% ± 5.3%). Additionally, 37% ± 30% demonstrated organized histology from 32 × 103cells under static conditions. Switching toα-MEM + 10% KSR during the differentiation phase increased formation efficiency to 85 ± 7%, along with elevated germ cell numbers, testosterone production (3.1 ± 0.9 ng ml-1) and generation ofγ-H2AX+spermatid-like cells (steps 8-11, 1.2% ± 2.2% of the total). Adding differentiation factors to theα-MEM increased spermatid-like cell numbers to 2.9% ± 5.9%, confirmed through positive staining for CREM, transition protein 1, and peanut agglutinin. Although, these remained diploid with irregular nuclear maturation. DEX supplementation had no additional effect, and immune cell depletion adversely impacted TO formation. The manipulability of TOs offers advantages in studying male infertility and exploring therapies, with scalability enabling high-throughput chemical screening and reducing animal usage in reproductive toxicity and drug discovery studies.

Mouse In Vitro Spermatogenesis on 3D Bioprinted Scaffolds.

Testes have a complex architecture that is compartmentalized into seminiferous tubules with a diameter of approximatively 200 µm in which the germ cells differentiate, surrounded by a basement membrane and interstitium. 3D bioprinting might be used to recreate the compartmentalized testicular architecture in vitro. Directed by a software program, pneumatic microextrusion printers can deposit 3D layers of hydrogel-encapsulated interstitial cells in a controlled manner by applying pressure. Once macroporous-shaped scaffolds resembling seminiferous tubules have been bioprinted with interstitial cells, the epithelial cell fraction can be seeded in the macropores to resemble the in vivo testicular architecture. Moreover, macropores can serve as a delimitation for all testicular cells to reorganize and improve the supply of nutrients to cells through the 3D constructs.

The Immunological Profile of Adipose Mesenchymal Stromal/Stem Cells after Cell Expansion and Inflammatory Priming.

BACKGROUND: AT-MSCs display great immunoregulatory features, making them potential candidates for cell-based therapy. This study aimed to evaluate the "RBC lysis buffer" isolation protocol and immunological profiling of the so-obtained AT-MSCs. METHODS: We established an immune-comparative screening of AT-MSCs throughout in vitro cell expansion (PM, P1, P2, P3, P4) and inflammatory priming regarding the expression of 28 cell-surface markers, 6 cytokines/chemokines, and 10 TLR patterns. FINDINGS: AT-MSCs were highly expandable and sensitive to microenvironment challenges, hereby showing plasticity in distinct expression profiles. Both cell expansion and inflammation differentially modulated the expression profile of CD34, HLA-DR, CD40, CD62L, CD200 and CD155, CD252, CD54, CD58, CD106, CD274 and CD112. Inflammation resulted in a significant increase in the expression of the cytokines IL-6, IL-8, IL-1ß, IL-1Ra, CCL5, and TNFα. Depending on the culture conditions, the expression of the TLR pattern was distinctively altered with TLR1-4, TLR7, and TLR10 being increased, whereas TLR6 was downregulated. Protein network and functional enrichment analysis showed that several trophic and immune responses are likely linked to these immunological changes. CONCLUSIONS: AT-MSCs may sense and actively respond to tissue challenges by modulating distinct and specific pathways to create an appropriate immuno-reparative environment. These mechanisms need to be further characterized to identify and assess a molecular target that can enhance or impede the therapeutic ability of AT-MSCs, which therefore will help improve the quality, safety, and efficacy of the therapeutic strategy.

The application of natural language processing for the extraction of mechanistic information in toxicology.

To study the ways in which compounds can induce adverse effects, toxicologists have been constructing Adverse Outcome Pathways (AOPs). An AOP can be considered as a pragmatic tool to capture and visualize mechanisms underlying different types of toxicity inflicted by any kind of stressor, and describes the interactions between key entities that lead to the adverse outcome on multiple biological levels of organization. The construction or optimization of an AOP is a labor intensive process, which currently depends on the manual search, collection, reviewing and synthesis of available scientific literature. This process could however be largely facilitated using Natural Language Processing (NLP) to extract information contained in scientific literature in a systematic, objective, and rapid manner that would lead to greater accuracy and reproducibility. This would support researchers to invest their expertise in the substantive assessment of the AOPs by replacing the time spent on evidence gathering by a critical review of the data extracted by NLP. As case examples, we selected two frequent adversities observed in the liver: namely, cholestasis and steatosis denoting accumulation of bile and lipid, respectively. We used deep learning language models to recognize entities of interest in text and establish causal relationships between them. We demonstrate how an NLP pipeline combining Named Entity Recognition and a simple rules-based relationship extraction model helps screen compounds related to liver adversities in the literature, but also extract mechanistic information for how such adversities develop, from the molecular to the organismal level. Finally, we provide some perspectives opened by the recent progress in Large Language Models and how these could be used in the future. We propose this work brings two main contributions: 1) a proof-of-concept that NLP can support the extraction of information from text for modern toxicology and 2) a template open-source model for recognition of toxicological entities and extraction of their relationships. All resources are openly accessible via GitHub (https://github.com/ontox-project/en-tox).

A quantitative weight-of-evidence method for confidence assessment of adverse outcome pathway networks: A case study on chemical-induced liver steatosis.

The field of chemical toxicity testing is undergoing a transition to overcome the limitations of in vivo experiments. This evolution involves implementing innovative non-animal approaches to improve predictability and provide a more precise understanding of toxicity mechanisms. Adverse outcome pathway (AOP) networks are pivotal in organizing existing mechanistic knowledge related to toxicological processes. However, these AOP networks are dynamic and require regular updates to incorporate the latest data. Regulatory challenges also persist due to concerns about the reliability of the information they offer. This study introduces a generic Weight-of-Evidence (WoE) scoring method, aligned with the tailored Bradford-Hill criteria, to quantitatively assess the confidence levels in key event relationships (KERs) within AOP networks. We use the previously published AOP network on chemical-induced liver steatosis, a prevalent form of human liver injury, as a case study. Initially, the existing AOP network is optimized with the latest scientific information extracted from PubMed using the free SysRev platform for artificial intelligence (AI)-based abstract inclusion and standardized data collection. The resulting optimized AOP network, constructed using Cytoscape, visually represents confidence levels through node size (key event, KE) and edge thickness (KERs). Additionally, a Shiny application is developed to facilitate user interaction with the dataset, promoting future updates. Our analysis of 173 research papers yielded 100 unique KEs and 221 KERs among which 72 KEs and 170 KERs, respectively, have not been previously documented in the prior AOP network or AOP-wiki. Notably, modifications in de novo lipogenesis, fatty acid uptake and mitochondrial beta-oxidation, leading to lipid accumulation and liver steatosis, garnered the highest KER confidence scores. In conclusion, our study delivers a generic methodology for developing and assessing AOP networks. The quantitative WoE scoring method facilitates in determining the level of support for KERs within the optimized AOP network, offering valuable insights into its utility in both scientific research and regulatory contexts. KERs supported by robust evidence represent promising candidates for inclusion in an in vitro test battery for reliably predicting chemical-induced liver steatosis within regulatory frameworks.