Hazard assessment is the first step in evaluating the potential adverse effects of chemicals. Traditionally, toxicological assessment has focused on the exposure, overlooking the impact of the exposed system on the observed toxicity. However, systems toxicology emphasizes how system properties significantly contribute to the observed response. Hence, systems theory states that interactions store more information than individual elements, leading to the adoption of network based models to represent complex systems in many fields of life sciences. Here, they develop a network-based approach to characterize toxicological responses in the context of a biological system, inferring biological system specific networks. They directly link molecular alterations to the adverse outcome pathway (AOP) framework, establishing direct connections between omics data and toxicologically relevant phenotypic events. They apply this framework to a dataset including 31 engineered nanomaterials with different physicochemical properties in two different in vitro and one in vivo models and demonstrate how the biological system is the driving force of the observed response. This work highlights the potential of network-based methods to significantly improve their understanding of toxicological mechanisms from a systems biology perspective and provides relevant considerations and future data-driven approaches for the hazard assessment of nanomaterials and other advanced materials.

The prevalence of hormone-related health issues caused by exposure to endocrine disrupting chemicals (EDCs) is a significant, and increasing, societal challenge. Declining fertility rates together with rising incidence rates of reproductive disorders and other endocrine-related diseases underscores the urgency in taking more action. Addressing the growing threat of EDCs in our environment demands robust and reliable test methods to assess a broad variety of endpoints relevant for endocrine disruption. EDCs also require effective regulatory frameworks, especially as the current move towards greater reliance on non-animal methods in chemical testing puts to test the current paradigm for EDC identification, which requires that an adverse effect is observed in an intact organism. Although great advances have been made in the field of predictive toxicology, disruption to the endocrine system and subsequent adverse health effects may prove particularly difficult to predict without traditional animal models. The MERLON project seeks to expedite progress by integrating multispecies molecular research, new approach methodologies (NAMs), human clinical epidemiology, and systems biology to furnish mechanistic insights and explore ways forward for NAM-based identification of EDCs. The focus is on sexual development and function, from foetal sex differentiation of the reproductive system through mini-puberty and puberty to sexual maturity. The project aims are geared towards closing existing knowledge gaps in understanding the effects of EDCs on human health to ultimately support effective regulation of EDCs in the European Union and beyond.

In the risk assessment of agrochemicals, there has been a historical paucity of using data to refine the default adjustment factors, even though large datasets are available to support this. The current state of the science for addressing uncertainty regarding animal to human extrapolation (AFA) is to develop a \"data-derived\" adjustment factor (DDEF) to quantify such differences, if data are available. Toxicokinetic (TK) and toxicodynamic (TD) differences between species can be utilized for the DDEF, with human datasets being ideal yet rare. We identified a case for a currently registered herbicide, mesotrione, in which human TK and TD are available. This case study outlines an approach for the development of DDEFs using comparative human and animal data and based on an adverse outcome pathway (AOP) for inhibition of 4-hydroxyphenol pyruvate dioxygenase (HHPD). The calculated DDEF for rat to human extrapolation (AFA) for kinetics (AFAK = 2.5) was multiplied by the AFA for dynamics (AFAD = 0.3) resulting in a composite DDEF of ∼1 (AFA = 0.75). This reflects the AOP and available scientific evidence that humans are less sensitive than rats to the effects of HPPD inhibitors. Further analyses were conducted utilizing in vitro datasets from hepatocytes and liver cytosols and extrapolated to whole animal using in vitro to in vivo extrapolation (IVIVE) to support toxicodynamic extrapolation. The in vitro datasets resulted in the same AFAD as derived for in vivo data (AFAD = 0.3). These analyses demonstrate that a majority of the species differences are related to toxicodynamics. Future work with additional in vitro/in vivo datasets for other HPPD inhibitors and cell types will further support this result. This work demonstrates utilization of all available toxicokinetic and toxicodynamic data to replace default uncertainty factors for agrochemical human health risk assessment.

Triclosan (TCS) is a broad-spectrum antibiotic widely used in various personal care products. Research has found that exposure to TCS can cause toxic effects on organisms including neurotoxicity, cardiotoxicity, disorders of lipid metabolism, and abnormal vascular development, and the corresponding toxic mechanisms are gradually delving into the level of abnormal expression of miRNA regulating gene expression. Although the downstream mechanism of TCS targeting miRNA abnormal expression to induce toxicity is gradually improving, its upstream mechanism is still in a fog. Starting from the abnormal expression data of circRNA in zebrafish larvae induced by TCS, this study conducted a hierarchical analysis of the expression levels of all circRNAs, differential circRNAs, and trend circRNAs, and identified 29 key circRNA events regulating miRNA abnormal expression. In combination with GO and KEGG, the effects of TCS exposure were analyzed from the function and signaling pathway of the corresponding circRNA host gene. Furthermore, based on existing literature evidence about the biological toxicity induced by TCS targeting miRNA as data support, a competing endogenous RNAs (ceRNA) network characterizing the regulatory relationship between circRNA and miRNA was constructed and optimized. Finally, a comprehensive Adverse Outcome Pathway (AOP) framework of multiple levels of events including circRNA, miRNA, mRNA, pathway, and toxicity endpoints was established to systematically elucidate the toxic mechanism of TCS. Moreover, the rationality of the AOP framework was verified from the expression level of miRNA and adverse outcomes such as neurotoxicity, cardiotoxicity, oxidative stress, and inflammatory response by knockdown of circRNA48. This paper not only provides the key circRNA events for exploring the upstream mechanism of miRNA regulating gene expression but also provides an AOP framework for comprehensively demonstrating the toxicity mechanism of TCS on zebrafish, which is a theoretical basis for subsequent hazard assessment and prevention and control of TCS.

Octahydro-tetramethyl-naphthalenyl-ethanone (OTNE) is a synthetic fragrance ingredient. OTNE was evaluated in repeated-dose toxicological studies. Target organs via oral and dermal routes were the liver and skin/liver, respectively. Effects were observed on the thyroid and thyroid hormones, suggesting hypothalamic-pituitary-thyroid axis perturbation. We investigated the molecular initiating event(s) (MIEs), key events (KEs), and adverse outcomes of OTNE-induced thyroid perturbation within an adverse outcome pathway (AOP). Data were generated using new approach methodologies (NAMs) on human, mouse, and/or rat receptors exploring MIEs using in vitro receptor ligand-binding assays for androstane receptor variant 3 (CAR), farnesoid X receptor (FXR), liver X receptor alpha (LXRα), peroxisome proliferator-activated receptors alpha, delta, and gamma (PPARα, δ, and γ), pregnane X receptor (PXR), and aryl hydrocarbon receptor (AhR). These data inform an AOP network where CAR, FXR, and PXR activation serve as MIEs with thyroid perturbation occurring as secondary effects. These data represent a robust evaluation using NAMs for mapping OTNE-induced thyroid effects and identifying activation of receptor-ligand binding as MIEs in lieu of additional in vivo experimentation. These data indicate the observed thyroid effects are secondary to liver effects and the thyroid effects, therefore, should not be the basis for assessing potential OTNE-induced human health hazards.

Despite the growing epidemiological evidence of an association between toxin exposure and developmental neurotoxicity (DNT), systematic testing of DNT is not mandatory in international regulations for admission of pharmaceuticals or industrial chemicals. However, to date around 200 compounds, ranging from pesticides, pharmaceuticals and industrial chemicals, have been tested for DNT in the current OECD test guidelines (TG-443 or TG-426). There are calls for the development of new approach methodologies (NAMs) for DNT, which has resulted in a DNT testing battery using in vitro human cell-based assays. These assays provide a means to elucidate the molecular mechanisms of toxicity in humans which is lacking in animal-based toxicity tests. However, cell-based assays do not represent all steps of the complex process leading to DNT. Validated models with a multi-organ network of pathways that interact at the molecular, cellular and tissue level at very specific timepoints in a life cycle are currently missing. Consequently, whole model organisms are being developed to screen for, and causally link, new molecular targets of DNT compounds and how they affect whole brain development and neurobehavioral endpoints. Given the practical and ethical restraints associated with vertebrate testing, lower animal models that qualify as 3 R (reduce, refine and replace) models, including the nematode (Caenorhabditis elegans) and the zebrafish (Danio rerio) will prove particularly valuable for unravelling toxicity pathways leading to DNT. Although not as complex as the human brain, these 3 R-models develop a complete functioning brain with numerous neurodevelopmental processes overlapping with human brain development. Importantly, the main signalling pathways relating to (neuro)development, metabolism and growth are highly conserved in these models. We propose the use of whole model organisms specifically zebrafish and C. elegans for DNT relevant endpoints.

Human epidemiological studies with biomarkers of effect play an invaluable role in identifying health effects with chemical exposures and in disease prevention. Effect biomarkers that measure genetic damage are potent tools to address the carcinogenic and/or mutagenic potential of chemical exposures, increasing confidence in regulatory risk assessment decision-making processes. The micronucleus (MN) test is recognized as one of the most successful and reliable assays to assess genotoxic events, which are associated with exposures that may cause cancer. To move towards the next generation risk assessment is crucial to establish bridges between standard approaches, new approach methodologies (NAMs) and tools for increase the mechanistically-based biological plausibility in human studies, such as the adverse outcome pathways (AOPs) framework. This paper aims to highlight the still active role of MN as biomarker of effect in the evolution and applicability of new methods and approaches in human risk assessment, with the positive consequence, that the new methods provide a deeper knowledge of the mechanistically-based biology of these endpoints.

Drug induced fatty liver disease (DIFLD) is a form of drug-induced liver injury (DILI), which can also be included in the more general metabolic dysfunction-associated steatotic liver disease (MASLD), which specifically refers to the accumulation of fat in the liver unrelated to alcohol intake. A bi-directional relationship between DILI and MASLD is likely to exist: while certain drugs can cause MASLD by acting as pro-steatogenic factors, MASLD may make hepatocytes more vulnerable to drugs. Having a pre-existing MASLD significantly heightens the likelihood of experiencing DILI from certain medications. Thus, the prevalence of steatosis within DILI may be biased by pre-existing MASLD, and it can be concluded that the genuine true incidence of DIFLD in the general population remains unknown. In certain individuals, drug-induced steatosis is often accompanied by concomitant injury mechanisms such as oxidative stress, cell death, and inflammation, which leads to the development of drug-induced steatohepatitis (DISH). DISH is much more severe from the clinical point of view, has worse prognosis and outcome, and resembles MASH (metabolic-associated steatohepatitis), as it is associated with inflammation and sometimes with fibrosis. A literature review of clinical case reports allowed us to examine and evaluate the clinical features of DIFLD and their association with specific drugs, enabling us to propose a classification of DIFLD drugs based on clinical outcomes and pathological severity: Group 1, drugs with low intrinsic toxicity (e.g., ibuprofen, naproxen, acetaminophen, irinotecan, methotrexate, and tamoxifen), but expected to promote/aggravate steatosis in patients with pre-existing MASLD; Group 2, drugs associated with steatosis and only occasionally with steatohepatitis (e.g., amiodarone, valproic acid, and tetracycline); and Group 3, drugs with a great tendency to transit to steatohepatitis and further to fibrosis. Different mechanisms may be in play when identifying drug mode of action: (1) inhibition of mitochondrial fatty acid β-oxidation; (2) inhibition of fatty acid transport across mitochondrial membranes; (3) increased de novo lipid synthesis; (4) reduction in lipid export by the inhibition of microsomal triglyceride transfer protein; (5) induction of mitochondrial permeability transition pore opening; (6) dissipation of the mitochondrial transmembrane potential; (7) impairment of the mitochondrial respiratory chain/oxidative phosphorylation; (8) mitochondrial DNA damage, degradation and depletion; and (9) nuclear receptors (NRs)/transcriptomic alterations. Currently, the majority of, if not all, adverse outcome pathways (AOPs) for steatosis in AOP-Wiki highlight the interaction with NRs or transcription factors as the key molecular initiating event (MIE). This perspective suggests that chemical-induced steatosis typically results from the interplay between a chemical and a NR or transcription factors, implying that this interaction represents the primary and pivotal MIE. However, upon conducting this exhaustive literature review, it became evident that the current AOPs tend to overly emphasize this interaction as the sole MIE. Some studies indeed support the involvement of NRs in steatosis, but others demonstrate that such NR interactions alone do not necessarily lead to steatosis. This view, ignoring other mitochondrial-related injury mechanisms, falls short in encapsulating the intricate biological mechanisms involved in chemically induced liver steatosis, necessitating their consideration as part of the AOP\'s map road as well.

Toxicological studies have demonstrated the hepatic toxicity of several bisphenol analogs (BPs), a prevalent type of endocrine disruptor. The development of Adverse Outcome Pathway (AOP) has substantially contributed to the rapid risk assessment for human health. However, the lack of in vitro and in vivo data for the emerging BPs has limited the hazard assessment of these synthetic chemicals. Here, we aimed to develop a new strategy to rapidly predict BPs\' hepatotoxicity using network analysis coupled with machine learning models. Considering the structural and functional similarities shared by BPs with Bisphenol A (BPA), we first integrated hepatic disease related genes from multiple databases into BPA-Gene-Phenotype-hepatic toxicity network and subjected it to the computational AOP (cAOP). Through cAOP network and conventional machine learning approaches, we scored the hepatotoxicity of 20 emerging BPs and provided new insights into how BPs\' structure features contributed to biologic functions with limited experimental data. Additionally, we assessed the interactions between emerging BPs and ESR1 using molecular docking and proposed an AOP framework wherein ESR1 was a molecular initiating event. Overall, our study provides a computational approach to predict the hepatotoxicity of emerging BPs.

UNASSIGNED: This non-systematic narrative review aims to summarize the results of clinical studies evaluating the effectiveness of antidepressants used to treat mental illnesses including major depressive disorder, obsessive-compulsive disorder, somatization disorder, and anxiety disorders in Turkey. Conclusions drawn from this article can guide ongoing efforts by Turkish health policymakers to improve public health development in the country by further regulating the prescription of antidepressants.
UNASSIGNED: Relevant articles regarding the effectiveness of antidepressant use were collected in June 2021 using Cumulative Index to Nursing and Allied Health Literature (CINAHL) Plus and Academic Search Complete online databases. The collected articles were then appraised using the Critical Appraisal Skills Programme to determine the reliability and quality of each article and to assess the risk of bias in each article. The summary of key findings/evidence, Critical Appraisal Skills Programme appraisal summary results, funding, study designs applied, settings covered, period covered (years), and additional comments were extracted from each article for analysis. The inclusion criteria involved articles that recounted adverse effects and effectiveness of antidepressant use in Turkey to treat mental illnesses, including anxiety disorders, major depressive disorder, somatization disorder, and obsessive-compulsive disorder. The exclusion criteria consisted of articles that included participants who resided outside of the geographic region of Turkey, abstracts, the pharmacology of antidepressant use, antidepressant off-label use, and alternative treatments.
UNASSIGNED: A total of 15 articles out of the 104 derived from the databases were included in the study that fell into 1 of the following main themes, \"adverse effects\" and \"mixed results,\" which accounted for 53% (8 articles) and 40% (6 articles), respectively. One outlying article was identified (7%).
UNASSIGNED: Totally 8 out of 15 articles that recounted antidepressants prescribed for mental illnesses produced adverse effects without treatment success and 6 out of 15 articles recounted adverse effects with treatment success. One outlying article found a confound that precluded determining whether an adverse effect was caused by antidepressant use or confounded by pre-existing conditions. Given that 14 out of 15 articles recounted adverse effects associated with antidepressant use and 6 out of 15 articles recounted antidepressant treatment success, Turkish policymakers are encouraged to adopt a restrictive drug policy strategy. To sum up, antidepressant prescription and consumption should be conducted with caution to limit unnecessary risk of exposure to adverse effects associated with antidepressant use. Limitations in the research included using a non-systematic tool instead of conducting a systematic review, a limited number of articles (15 out of 104), and risk of bias was detected from appraising the articles via Critical Appraisal Skills Programme.