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There are substantial gaps in our empirical knowledge of the effects of chemical exposure on aquatic life that are unlikely to be filled by traditional laboratory toxicity testing alone. One possible alternative of generating new toxicity data is cross-species extrapolation (CSE), a statistical approach in which existing data are used to predict the effect of a chemical on untested species. Some CSE models use relatedness as a predictor of chemical sensitivity, but relatively little is known about how strongly shared evolutionary history influences sensitivity across all chemicals. To address this question, we conducted a survey of phylogenetic signal in the toxicity data from aquatic animal species for a large set of chemicals using a phylogeny inferred from taxonomy. Strong phylogenetic signal was present in just nine of thirty-six toxicity datasets, and there were no clear shared properties among those datasets with strong signal. Strong signal was rare even among chemicals specifically developed to target insects, meaning that these chemicals may be equally lethal to non-target taxa, including chordates. When signal was strong, distinct patterns of sensitivity were evident in the data, which may be informative when assembling toxicity datasets for regulatory use. Although strong signal does not appear to manifest in aquatic toxicity data for most chemicals, we encourage additional phylogenetic evaluations of toxicity data in order to guide the selection of CSE tools and as a means to explore the patterns of chemical sensitivity across the broad diversity of life. [ABSTRACT FROM AUTHOR]

A vast variety of chemical compounds have been fabricated and commercialized, they not only result in industrial exposure during manufacturing and usage, but also have environmental impacts throughout their whole life cycle. Consequently, attempts to assess the risk of chemicals in terms of toxicology have never ceased. In-silico toxicology, also known as predictive toxicology, has advanced significantly over the last decade as a result of the drawbacks of experimental investigations. In this study, ProTox-III was applied to predict the toxicity of the ligands used for metal–organic framework (MOF) design and synthesis. Initially, 35 ligands, that have been frequently utilized for MOF synthesis and fabrication, were selected. Subsequently, canonical simplified molecular-input line-entry system (SMILES) of ligands were extracted from the PUBCHEM database and inserted into the ProTox-III online server. Ultimately, webserver outputs including LD50 and the probability of toxicological endpoints (cytotoxicity, carcinogenicity, mutagenicity, immunotoxicity, and ecotoxicity) were obtained and organized. According to retrieved LD50 data, the safest ligand was 5-hydroxyisophthalic. In contrast, the most hazardous ligand was 5-chlorobenzimidazole, with an LD50 of 8 mg/kg. Among evaluated endpoints, ecotoxicity was the most active and was detected in several imidazolate ligands. This data can open new horizons in design and development of green MOFs. [ABSTRACT FROM AUTHOR]

The herbicide paraquat (PQ) is responsible for a significant number of fatalities resulting from self-poisoning. Nevertheless, only a limited number of comprehensive studies focusing on fatal PQ poisoning, which include examination of autopsy findings, histopathology, and quantitative analysis of post-mortem samples, have been published. This study aimed to evaluate autopsy findings, histopathology, and quantitative analysis of PQ in post-mortem human serum samples using liquid chromatography-tandem mass spectrometry (LC-MS/MS), a simple, sensitive, and specific method. Autopsies were performed on all deaths due to PQ poisoning, and serum samples were sent to the toxicology laboratory for chemical analysis. The method was successfully applied to seven human serum samples, and the results indicate its reliability for detecting PQ. The study reports fatal serum PQ levels ranging from 0.5 to 372.0 µg/mL. The comprehensive data presented in this study can be useful for further research and practical applications. [ABSTRACT FROM AUTHOR]

In this work, theoretical calculations of o‐phenylphenol‐based non‐oxovanadium(IV) and organotin(IV) complexes, previously prepared and reported by our group, have been carried out by density functional theory (DFT). Density functional theory quantum chemical computations were used to explore the structural and spectroscopic characteristics of the complexes in this study. The inhibitory nature of complexes were revealed via molecular docking research, which were performed against selected breast cancer cell proteins, 5NWH and 3HB5. The optimization and stability of complexes 1–6, were conducted using optimized DFT/B3LYP/6–311++G (d, p) level. Simulated computations of the molecular electrostatic potential surface were also performed to analyze the reactive behavior of the non‐oxovanadium(IV) and organotin(IV) complexes. The stability and molecular reactivity of the molecules were computed using the HOMO‐LUMO energies, energy gap, chemical potential (μ), electronegativity (χ), hardness (η), and softness (S) values. In silico analysis through molecular docking, ADMET properties and toxicity evaluation was used to assess its anticancer activity, drug‐likeness property and toxicity. The binding constant value, evaluated from molecular docking, was found to be very promising, −10.1 kcal mol−1 observed for vanadium complex 5 and the complexes were found to exhibit inhibition constant as low as 0.0378 μMol. Root‐mean‐square deviation (RMSD) has been carried out to validate molecular docking studies, which have been found to be below 2.0 Å for the complexes, indicating successful docking of the ligand‐protein complex by the program. The complexes, evaluated for their toxicity behavior in terms of Lethal Dose, based on Globally Harmonized System (GHS), have been found to be chemical safe falling under the category III and V and hence can find use as future metallo‐based drugs. [ABSTRACT FROM AUTHOR]

The first step in the hazard or risk assessment of chemicals should be to formulate the problem through a systematic and iterative process aimed at identifying and defining factors critical to the assessment. However, no general agreement exists on what components an in silico toxicology problem formulation (PF) should include. The present work aims to develop a PF framework relevant to the application of in silico models for chemical toxicity prediction. We modified and applied a PF framework from the general risk assessment literature to peer reviewed papers describing PFs associated with in silico toxicology models. Important gaps between the general risk assessment literature and the analyzed PF literature associated with in silico toxicology methods were identified. While the former emphasizes the need for PFs to address higher-level conceptual questions, the latter does not. There is also little consistency in the latter regarding the PF components addressed, reinforcing the need for a PF framework that enable users of in silico toxicology models to answer the central conceptual questions aimed at defining components critical to the model application. Using the developed framework, we highlight potential areas of uncertainty manifestation in in silico toxicology PF in instances where particular components are missing or implicitly described. The framework represents the next step in standardizing in silico toxicology PF component. The framework can also be used to improve the understanding of how uncertainty is apparent in an in silico toxicology PF, thus facilitating ways to address uncertainty. [ABSTRACT FROM AUTHOR]

Rigorous risk assessment of chemicals in food and feed is essential to address the growing worldwide concerns about food safety. High-quality toxicological data on food-relevant chemicals are fundamental for risk modeling and assessment in the food safety area. The organization and analysis of substantial toxicity information can positively support decision-making by providing insight into toxicity trends. However, it remains challenging to systematically obtain fragmented toxicity data, and related toxicological resources are required to meet the current demands. In this study, we collected 221,439 experimental toxicity records for 5,657 food-relevant chemicals identified from extensive databases and literature, along with their information on chemical identification, physicochemical properties, environmental fates, and biological targets. Based on the aggregated data, a freely available web-based databank, Food-Relevant Available Chemicals Toxicology Databank (FRAC-TD) is presented, which supports multiple browsing ways and search criterions. Applying FRAC-TD for data-driven analysis, we revealed the underlying toxicity profiles of food-relevant chemicals in humans, mammals, and other species in the food chain. Expectantly, FRAC-TD could positively facilitate toxicological studies, toxicity prediction, and risk assessments in the food industry. [ABSTRACT FROM AUTHOR]

The accurate identification of chemicals with ocular toxicity is of paramount importance in health hazard assessment. In contemporary chemical toxicology, there is a growing emphasis on refining, reducing, and replacing animal testing in safety evaluations. Therefore, the development of robust computational tools is crucial for regulatory applications. The performance of predictive models is heavily reliant on the quality and quantity of data. In this investigation, we amalgamated the most extensive dataset (4901 compounds) sourced from governmental GHS‐compliant databases and literature to develop binary classification models of chemical ocular toxicity. We employed 12 molecular representations in conjunction with six machine learning algorithms and two deep learning algorithms to create a series of binary classification models. The findings indicated that the deep learning method GCN outperformed the machine learning models in cross‐validation, achieving an impressive AUC of 0.915. However, the top‐performing machine learning model (RF‐Descriptor) demonstrated excellent performance with an AUC of 0.869 on the test set and was therefore selected as the best model. To enhance model interpretability, we conducted the SHAP method and attention weights analysis. The two approaches offered visual depictions of the relevance of key descriptors and substructures in predicting ocular toxicity of chemicals. Thus, we successfully struck a delicate balance between data quality and model interpretability, rendering our model valuable for predicting and comprehending potential ocular‐toxic compounds in the early stages of drug discovery. Effective identification of chemicals causing ocular toxicity is critical to health hazard assessment. In this study, we carefully integrated the largest dataset (4,901 compounds) from official GHS‐compliant databases and literature. Machine learning and deep learning classification prediction models were constructed, among which the RF‐Descriptor model performed the best. Furthermore, we used the SHAP method and attention weights analysis to enhance the model's interpretability, making it valuable in predicting and understanding potential ocular‐toxic compounds in the early stages of drug discovery. [ABSTRACT FROM AUTHOR]

Background: Toxicology is a critical field that is of significant importance to various industries, including pharmaceuticals, environmental protection, and consumer product safety. It's a multidisciplinary science that often involves time-consuming and expensive toxicity tests, which can delay the development of new products and pose significant risks to public health and the environment. Therefore, there is an ever-growing demand for faster and more efficient toxicity evaluations. Artificial Intelligence (AI) has emerged as a promising solution to address these pressing challenges. By enabling the development of machine learning models that can analyze vast amounts of data. This review article focuses on the potential impact of AI in toxicology and its applications in different areas, such as predictive toxicology, development of toxicity screening assays, assessment of chemical mixtures, interpretation of toxicological data, and forensic toxicology. Methods: This review was done a comprehensive literature search across multiple scientific databases. Searches were conducted in Medline/PubMed, Google Scholar and Web of Science to identify relevant publications. The search terms used included combinations of "artificial intelligence", "toxicology", "toxicity", and related keywords. The final set of articles selected provided a comprehensive overview of the current state of research on the applications of AI techniques in toxicology and chemical risk assessment. Results: The review highlighted a growing body of research exploring the potential role of AI in accelerating and enhancing various aspects of toxicity assessment and chemical risk evaluation. The reviewed studies demonstrate how AI models can be trained on large datasets of chemical structures, in vitro assay results, and toxicological outcomes to predict the toxicity of novel compounds and other fields such as forensic toxicology. On the other hand, legal and ethical aspects of using AI was investigated. Conclusion: Overall, the findings of this review highlight this fact that AI can enable faster, more cost -effective, and more accurate toxicity assessments and ultimately leading to improved chemical safety and risk management practice s. potential role of AI in accelerating and enhancing various aspects of toxicity assessment and chemical risk evaluation. The reviewed studies demonstrate how AI models can be trained on large datasets of chemical structures, in vitro assay results, and toxicological outcomes to predict the toxicity of novel compounds and other fields such as forensic toxicology. On the other hand, legal and ethical aspects of using AI was investigated. [ABSTRACT FROM AUTHOR]

Electronic nicotine delivery systems (ENDSs) are designed as a non-combustible alternative to cigarettes, aiming to deliver nicotine without the harmful byproducts of tobacco combustion. As the category evolves and new ENDS products emerge, it is important to continually assess the levels of toxicologically relevant chemicals in the aerosols and characterize any related toxicology. Herein, we present a proposed framework for characterizing novel ENDS products (i.e., devices and formulations) and determining the reduced risk potential utilizing analytical chemistry and in vitro toxicological studies with a qualitative risk assessment. To demonstrate this proposed framework, long-term stability studies (12 months) analyzing relevant toxicant emissions from six formulations of a next-generation product, JUUL2, were conducted and compared to reference combustible cigarette (CC) smoke under both non-intense and intense puffing regimes. In addition, in vitro cytotoxicity, mutagenicity, and genotoxicity assays were conducted on aerosol and smoke condensates. In all samples, relevant toxicants under both non-intense and intense puffing regimes were substantially lower than those observed in reference CC smoke. Furthermore, neither cytotoxicity, mutagenicity, nor genotoxicity was observed in aerosol condensates generated under both intense and non-intense puffing regimes, in contrast to results observed for reference cigarettes. Following the proposed framework, the results demonstrate that the ENDS products studied in this work generate significantly lower levels of toxicants relative to reference cigarettes and were not cytotoxic, mutagenic, or genotoxic under these in vitro assay conditions. [ABSTRACT FROM AUTHOR]

Kigelia africana plant is multipurpose plant whose therapeutic potential has been thoroughly investigated. The physicochemical, solubilities, ADMET, pharmacological, and drug-like properties of this plant have not been reported in details. This study makes use of the information that is currently known on the chemical make-up of the plant to forecast its overall toxicity as well as the potential for the phytochemicals it contains to be employed in medication discovery. The study also employed free web servers for the lipophilicity, water solubility, drug-likeness, bioavailability score, medicinal chemistry and toxicological profiling of the compounds of K. africana. Artemether, a known antimalaria drug was used to validate the potentials of the phytochemicals to serve as precursor to valuable drugs. Findings from our study revealed that a larger percentage of these compounds passed the physicochemical properties analysis, low lipophilicities, high-water solubilities, obeyed the drug-likeness rules, had high gastrointestinal absorption, high bloodbarrier permeant, low permeability glycoprotein and hence bioavailable. The toxicological profile additionally showed that majority of the compounds possessed low toxicities and thus can be a potential drug candidate in the drug development industry. The profile of the well-known artemether supported the study's findings that a higher proportion of the K. africana compounds have potential drug-like molecules. [ABSTRACT FROM AUTHOR]

Natural radioactivity has been a part of the environment since the creation of earth. Natural elements like uranium and its by-products can be reason of health problems if they are present in groundwater at excessive amount. Uranium is very harmful because it is very toxic. This study gives the information about the uranium concentration in 40 groundwater samples collected from different water sources like hand pump and tube wells of different depths from numerous locations of Jhajjar district of Haryana, India. Uranium concentration was measured using the LED fluorimetry technique. The observed value of uranium concentration ranged from 5 μgL-1 to 91 μgL-1 with mean value of 28.49 μgL-1. The mean value of uranium concentration is below the safe limit suggested by World Health Organisation (WHO) and Atomic Energy Regulatory Board (AERB), India. The uranium concentration in some region is high because of nearby industries, increasing uses of fertilizer for agriculture and the local subsurface geology of the region. The calculated risk factors for lifelong cancer morbidity and mortality are not significant because they are much lower than the permitted hazard limits. The chemical toxicity of uranium is measured in form of LADD (Lifetime Average Daily Dose) value was ranging from 0.39 to 6.67 μg kg-1 day-1 with mean value of 2.02 μg kg-1 day-1g which is more than the WHO recommended daily consumption threshold of LADD of 1.0 μg kg-1 day-1. Values of annual effective dose is varying from 0.89-15.16 μSv/Y with mean value is 4.74 μSv/Y, which is below the safe limit of 100 μSv/y (WHO). [ABSTRACT FROM AUTHOR]

The anthropogenic release of Hg is associated with an increased human exposure risk. Since Hg2+ and MeHg+ have a high affinity for thiols, their interaction with L-glutathione (GSH) within mammalian cells is fundamentally involved in their toxicological chemistry and excretion. To gain insight into the interaction of these mercurials with multiple small molecular weight thiols, we have investigated their competitive interactions with GSH and N-acetylcysteine (NAC) at near-physiological conditions, using a liquid chromatographic approach. This approach involved the injection of each mercurial onto a reversed-phase (RP)-HPLC column (37 °C) using a PBS buffer mobile phase containing 5.0 mM GSH to simulate cytosolic conditions with Hg being detected in the column effluent by an inductively coupled plasma atomic emission spectrometer (ICP-AES). When the 5.0 mM GSH mobile phase was amended with up to 10 mM NAC, gradually increasing retention times of both mercurials were observed. To explain this behavior, the experiment with 5.0 mM NAC and 5.0 mM GSH was replicated using 50 mM Tris buffer (pH 7.4), and the Hg-containing fractions were analyzed by electrospray ionization mass spectrometry. The results revealed the presence of Hg(GS)(NAC) and Hg(NAC)2 for Hg2+ and MeHg(GS) and MeHg(NAC) for MeHg+, which suggests that the coordination/displacement of GS-moieties from each mercurial by the more hydrophobic NAC can explain their retention behavior. Since the biotransformations of both mercurials were observed at near-physiological conditions, they are of toxicological relevance as they provide a biomolecular explanation for some results that were obtained when animals were administered with each mercurial and NAC. [ABSTRACT FROM AUTHOR]

Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop's objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples. Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work. [ABSTRACT FROM AUTHOR]

Pretilachlor is an extensively used herbicide worldwide that mimics the clinical presentation of Organophosphorus (OP) poisoning upon ingestion. Misdiagnosis can be a major setback and lead to inappropriate patient management. In this report, we discuss the case of a young man who presented with an alleged history of consumption of an unknown chemical compound, which was later confirmed to be pretilachlor. He had multiple episodes of emesis since the event, and the only systemic abnormality was a low heart rate of approximately 50 beats/min. Other cholinergic symptoms were absent, and atropine was administered after initial resuscitation and stabilization, with suspected OP poisoning as the top differential diagnosis. All laboratory findings, including pseudocholinesterase, were normal, which was unlikely to happen in the case of OP poisoning. Later, the consumption of the chemical pretilachlor, by the patient was confirmed. The patient was weaned off atropine and managed by systemic support and symptomatic treatment. He fully recovered within 4-5 days and was discharged in a stable condition with no risk of post-discharge complications. [ABSTRACT FROM AUTHOR]

Although chronic low-level exposure to Hg2+ and Cd2+ causes human nephrotoxicity, the bioinorganic processes that deliver them to their target organs are poorly understood. Since the plasma protein human serum albumin (HSA) has distinct binding sites for these metal ions, we wanted to gain insight into these translocation processes and have employed size-exclusion chromatography coupled on-line to an inductively coupled plasma atomic emission spectrometer using phosphate-buffered saline mobile phases. When HSA 'labeled' with Hg2+ and Cd2+ (1:0.1:0.1) using 300 μM of L-methionine was analyzed, the co-elution of a single C, S, Cd, and Hg peak was observed, which implied the intact bis-metalated HSA complex. Since human plasma contains small molecular weight thiols and sulfur-containing metabolites, we analyzed the bis-metalated HSA complex with mobile phases containing 50–200 µM of L-cysteine (Cys), D,L-homocysteine (hCys), or glutathione (GSH), which provided insight into the comparative mobilization of each metal from their respective binding sites on HSA. Interestingly, 50 µM Cys, hCys, or GSH mobilized Hg2+ from its HSA binding site but only partially mobilized Cd2+ from its binding site. Since these findings were obtained at conditions simulating near-physiological conditions of plasma, they provide a feasible explanation for the higher 'mobility' of Hg2+ and its concomitant interaction with mammalian target organs compared to Cd2+. Furthermore, 50 µM Cys resulted in the co-elution of similar-sized Hg and Cd species, which provides a biomolecular explanation for the nephrotoxicity of Hg2+ and Cd2+. [ABSTRACT FROM AUTHOR]

The use of ergogenic substances, those have the property of altering the physical performance, is old, since man has always had difficulties in accepting his physical and mental limitations. In the context of sports competitions, new techniques and chemical products have been used by athletes, which challenge the analytical techniques currently employed in chemical doping tests. In this sense, the search for improvement in the doping control becomes essential for the sports community that aims to make competitions more egalitarian. Our aim was to analyze the samples currently used in the detection of doping and compare them with alternative matrices that have been studied, highlighting the advantages and disadvantages of each one. The results demonstrated that "alternative" samples (hair/body hair, saliva and exhaled air) could improve the analyzes performed on blood and urine samples, considered currently the gold-standard. With some advantages, the alternative matrices could complement and solve some analytical biases. The constant rise of ergogenic methods requires that doping control is also in constant improvement. In order to comply with sports legislation, analytical techniques can find advancement when using new biological samples. [ABSTRACT FROM AUTHOR]

This article provides a brief outline of the history and teaching of the discipline "Toxicological Chemistry" on the chair of pharmaceutical and toxicological chemistry of the First MSMU named after M.I. Sechenov.

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Prenatal exposure to a mixture (MIX N) of eight endocrine-disrupting chemicals has been associated with language delay in children in a Swedish pregnancy cohort. A novel approach was proposed linking this epidemiological association with experimental evidence, where the effect of MIX N on thyroid hormone signaling was assessed using the Xenopus eleuthero-embryonic thyroid assay (XETA OECD TG248). From this experimental data, a point of departure (PoD) was derived based on OECD guidance. Our aim in the current study was to use updated toxicokinetic models to compare exposures of women of reproductive age in the US population to MIX N using a Similar Mixture Approach (SMACH). Based on our findings, 66% of women of reproductive age in the US (roughly 38 million women) had exposures sufficiently similar to MIX N. For this subset, a Similar Mixture Risk Index (SMRIHI) was calculated comparing their exposures to the PoD. Women with SMRIHI > 1 represent 1.1 million women of reproductive age. Older women, Mexican American and other/multi race women were less likely to have high SMRIHI values compared to Non-Hispanic White women. These findings indicate that a reference mixture of chemicals identified in a Swedish cohort—and tested in an experimental model for establishment of (PoDs)—is also of health relevance in a US population. [ABSTRACT FROM AUTHOR]

The exposure of humans to Cd exerts adverse human health effects at low chronic exposure doses, but the underlying biomolecular mechanisms are incompletely understood. To gain insight into the toxicologically relevant chemistry of Cd2+ in the bloodstream, we employed an anion-exchange HPLC coupled to a flame atomic absorption spectrometer (FAAS) using a mobile phase of 100 mM NaCl with 5 mM Tris-buffer (pH 7.4) to resemble protein-free blood plasma. The injection of Cd2+ onto this HPLC-FAAS system was associated with the elution of a Cd peak that corresponded to [CdCl3]−/[CdCl4]2− complexes. The addition of 0.1–10 mM L-cysteine (Cys) to the mobile phase significantly affected the retention behavior of Cd2+, which was rationalized by the on-column formation of mixed CdCysxCly complexes. From a toxicological point of view, the results obtained with 0.1 and 0.2 mM Cys were the most relevant because they resembled plasma concentrations. The corresponding Cd-containing (~30 μM) fractions were analyzed by X-ray absorption spectroscopy and revealed an increased sulfur coordination to Cd2+ when the Cys concentration was increased from 0.1 to 0.2 mM. The putative formation of these toxicologically relevant Cd species in blood plasma was implicated in the Cd uptake into target organs and underscores the notion that a better understanding of the metabolism of Cd in the bloodstream is critical to causally link human exposure with organ-based toxicological effects. [ABSTRACT FROM AUTHOR]

Dough rheology improvers, which often are oxidative reagents in nature, have long been used in bread-making industry to enhance protein crosslinking and subsequently improve the dough rheological properties and bread qualities. Numerous studies were conducted to explore the effects of these oxidative agents on dough quality improving, however, the underlying mechanism of their action during dough development has not been fully understood. Due to the public health concerns, multiple oxidative reagents were banned in some countries across the world, while others are still permitted in accordance with regulations. Therefore, a comprehensive understanding of their application, significance, and safety in bread manufacturing is necessary. This review aims to provide a detailed information about the evolutionary history of several commonly used oxidants acting as dough rheology improvers, their mechanisms of action, as well as their potential toxicity. [ABSTRACT FROM AUTHOR]

BACKGROUND: The survival rate of experimental animals is a very important index in chemical toxicity evaluation experiments. The calculation of nematode survival rate is used in many experiments. OBJECTIVE: Traditional survival rate quantification methods require manual counting. This is a time-consuming and laborious work when using 384-well plate for high-throughput chemical toxicity assessment experiments. At present, there is a great need for an automatic method to identify the survival rate of nematodes in the experiment of chemical toxicity evaluation. METHODS: We designed an automatic nematode survival rate recognition method by combining the bright field experimental image of nematodes and the dark field image of nematodes which is captured after adding Propidium Iodide dye, and used it to calculate the nematode survival rate in different chemical environments. Experiment results show that the survival rate obtained by our automatic counting method is very similar to the survival rate obtained by manual counting. RESULTS: Through several different chemical experiments, we can see that chemicals with different toxicity have different effects on the survival rate of nematodes. And the survival rate of nematodes under different chemical concentrations has an obvious gradient trend from high concentration to low concentration. In addition, our method can quantify the motility of nematodes. There are also significant differences in the motility of nematodes cultured in different chemical environments. Moreover, the nematode motility under different chemical concentrations showed an obvious gradient change trend from high concentration to low concentration. CONCLUSION: Our study provides an accurate and efficient nematode survival rate recognition method for chemical toxicology research. [ABSTRACT FROM AUTHOR]

Passive sampling device (PSD) extracts paired with developmental toxicity assays in Danio Rerio (zebrafish) are excellent sensors for whole mixture toxicity associated with the bioavailable non-polar organics at environmental sites. We expand this concept by incorporating RNA-Seq in 48-h post fertilization zebrafish statically exposed to PSD extracts from two Portland Harbor Superfund Site locations: river mile 6.5W (RM 6.5W) and river mile 7W (RM 7W). RM 6.5W contained higher concentrations of polycyclic aromatic hydrocarbons (PAHs), but the diagnostic ratios of both extracts indicated similar PAH sourcing and composition. Developmental screens determined RM 6.5W to be more toxic with the most sensitive endpoint being a "wavy" notochord malformation. Differential gene expression from exposure to both extracts was largely parallel, although more pronounced for RM 6.5W. When compared to the gene expression associated with individual chemical exposures, PSD extracts produced some gene signatures parallel to PAHs but were more closely matched by oxygenated-PAHs. Additionally, differential expression, reminiscent of the wavy notochord phenotype, was not accounted for by either class of chemical, indicating the potential of other contaminants driving mixture toxicity. These techniques offer a compelling method for non-targeted hazard characterization of whole mixtures in an in vivo vertebrate system without requiring complete chemical characterization. [ABSTRACT FROM AUTHOR]

Recently, an article by Seneff et al. entitled "Innate immunosuppression by SARS-CoV-2 mRNA vaccinations: The role of G-quadruplexes, exosomes, and MicroRNAs" was published in Food and Chemical Toxicology (FCT). Here, we describe why this article, which contains unsubstantiated claims and misunderstandings such as "billions of lives are potentially at risk" with COVID-19 mRNA vaccines, is problematic and should be retracted. We report here our request to the editor of FCT to have our rebuttal published, unfortunately rejected after three rounds of reviewing. Fighting the spread of false information requires enormous effort while receiving little or no credit for this necessary work, which often even ends up being threatened. This need for more scientific integrity is at the heart of our advocacy, and we call for large support, especially from editors and publishers, to fight more effectively against deadly disinformation. [ABSTRACT FROM AUTHOR]

Differential scanning calorimetry (DSC) is a tool particularly recommended for rapid compatibility screening between active pharmaceutical ingredients (APIs) and excipients, whereas thermogravimetric analysis (TGA), a complementary technique to DSC, is primarily used to assess the thermal stability of APIs and excipients. Both DSC and TGA data can be converted using multivariate statistical methods, which are profitable tools in the detection of compatibility between ingredients. Principal component analysis (PCA) enables identification of compatibility by grouping samples into two clusters in a PCA score plot: acetazolamide and mixture with its highest content, and optionally a 1:1 mixture form one cluster, excipient and mixture with its highest quantity, and optionally a 1:1 mixture the second. Any variation from the arrangement of samples in the abovementioned clusters indicates incompatibility. By using cluster analysis, compatibility can be determined by four clusters, the first consisting of API, the second of groups mixture at the ratio of 7:3 and the third of two mixtures at ratios of 3:7 and 1:1, with the excipient in the remaining fourth cluster. Generally, the combination of DSC and TGA techniques with advanced statistical methods is favorable for the qualitative assessment of compatibility in acetazolamide mixtures with excipients such as mannitol, meglumine, lactose, magnesium stearate, β-cyclodextrin, chitosan, methylcellulose, starch 1500 and PVP K-30. In addition, PXRD revealed that acetazolamide retains its crystalline form after mixing. Accordingly, incompatibilities in acetazolamide mixtures can be attributed to chemical reactions. [ABSTRACT FROM AUTHOR]

Acute toxicity caused by illicit substance use is a common reason for emergency department (ED) presentation. Knowledge of the substances involved is helpful for predicting and managing potential toxicity, but limited information is available about the accuracy of patient-reported substance exposure. This study assessed the accuracy of the history of exposure in those reporting use of a single substance by comparison with those identified by detailed toxicological analysis, focusing on synthetic cannabinoid receptor agonists (SCRA). Adults (≥16 years) presenting between March 2015 and July 2021 to participating UK hospitals with toxicity after reporting use of a single illicit substance were included. Exposure details were documented from medical records and blood and/or urine samples analysed using high-resolution accurate mass liquid chromatography-mass spectrometry (HRAM LCMS). Sensitivity, specificity, and positive and negative predictive values of the exposure history were calculated by comparison with biological sample analysis ("gold standard"). Single substance exposure was reported for 474 (median age 33 years, IQR: 18 range 16–75, 80% males) patients. Analysis commonly identified multiple substances (Median 3, IQR 2–5). A history of exposure was documented for 121 of 151 patients where a SCRA or metabolite was detected on analysis (sensitivity 80.1%, 95% CI 72.9, 86.2%). Corresponding proportions were lower for 3,4-methylenedioxymethamphetamine (MDMA, 44/70, 62.9%., 95% CI 50.5%, 74.1%), heroin 41/108 (38.0% 95% CI 28.8–47.8%) and cocaine (22/56, 31.3%, 95% CI 20.9, 43.6%). Multiple undeclared substances were detected analytically in most patients reporting single substance use. Clinicians should be alert to the potential presence and toxicity of unreported substances when managing patients presenting after substance misuse. [ABSTRACT FROM AUTHOR]

Throughout the cold and the warm periods of 2020, chemical and toxicological characterization of the water-soluble fraction of size segregated particulate matter (PM) (<0.49, 0.49–0.95, 0.95–1.5, 1.5–3.0, 3.0–7.2 and >7.2 μm) was conducted in the urban agglomeration of Thessaloniki, northern Greece. Chemical analysis of the water-soluble PM fraction included water-soluble organic carbon (WSOC), humic-like substances (HULIS), and trace elements (V, Cr, Mn, Fe, Ni, Cu, Zn, As, Cd and Pb). The bulk (sum of all size fractions) concentrations of HULIS were 2.5 ± 0.5 and 1.2 ± 0.3 μg m−3, for the cold and warm sampling periods, respectively with highest values in the <0.49 μm particle size fraction. The total HULIS-C/WSOC ratio ranged from 17 to 26% for all sampling periods, confirming that HULIS are a significant part of WSOC. The most abundant water-soluble metals were Fe, Zn, Cu, and Mn. The oxidative PM activity was measured abiotically using the dithiothreitol (DTT) assay. In vitro cytotoxic responses were investigated using mitochondrial dehydrogenase (MTT). A significant positive correlation was found between OPmDTT, WSOC, HULIS and the MTT cytotoxicity of PM. Multiple Linear Regression (MLR) showed a good relationship between OPMDTT, HULIS and Cu. [ABSTRACT FROM AUTHOR]

For over a decade, New Approach Methodologies (NAMs) such as structure-activity/read-across, -omics technologies, and Adverse Outcome Pathway (AOP), have been considered within regulatory communities as alternative sources of chemical and biological information potentially relevant to human health risk assessment. Integration of NAMs into applications such as chemical mixtures risk assessment has been limited due to the lack of validation of qualitative and quantitative application to adverse health outcomes in vivo, and acceptance by risk assessors. However, leveraging existent hazard and dose–response information, including NAM-based data, for mixture component chemicals across one or more levels of biological organization using novel approaches such as AOP 'footprinting' proposed herein, may significantly advance mixtures risk assessment. AOP footprinting entails the systematic stepwise profiling and comparison of all known or suspected AOPs involved in a toxicological effect at the level of key event (KE). The goal is to identify key event(s) most proximal to an adverse outcome within each AOP suspected of contributing to a given health outcome at which similarity between mixture chemicals can be confidently determined. These key events are identified as the 'footprint' for a given AOP. This work presents the general concept, and a hypothetical example application, of AOP footprinting as a key methodology for the integration of NAM data into mixtures risk assessment. [ABSTRACT FROM AUTHOR]

Chlorpyrifos is one of the most employed insecticides worldwide. It is moderately persistent in the environment. It degrades to 3, 5, 6-trichloro-2-pyridinol (TCP), the metabolite of toxicological concern to both human health and the environment. In the field, pesticides point contaminations occur during the operation of the application machinery. Biobeds made up of a biomixture containing straw, peat, and soil have been successfully developed to minimise these incidents. The retained pesticides are degraded by the microorganisms in the biomixture. Although the dissipation of chlorpyrifos in different biobeds has been studied, the fate of TCP received scarce attention. Biodegradation in specific bioreactors can only be assessed if it is evaluated through proper analytical methods. In this work chlorpyrifos and TCP dissipation in biobeds was studied with a previously fit for purpose analytical method. The lyophilised biomixture was extracted with ethyl acetate in an aqueous solution of NaCl and sodium tetraborate. The extract was cleaned up with alumina. Chlorpyrifos was determined by gas chromatography with electron capture and mass spectrometer detectors and TCP by liquid chromatography coupled to tandem mass spectrometry, using the negative Multiple Ion Mode. Recoveries of the two analytes, up to 2 mg kg−1, were between 70% and 113% with RSDs below 16% and RSDwR below 19%. Further TCP confirmation was evaluated through Enhanced Product Ion mode for each ion. The dissipation of both analytes in laboratory biobeds inoculated with Abortiporus biennis using two different types of Uruguayan soils was assayed. Both bioreactors were able to dissipate the compounds after 60 days following different dissipation kinetics. Similar results were obtained after scaling up in a biobed under field conditions. [ABSTRACT FROM AUTHOR]

Entropy is essential. Entropy is a measure of a system's molecular disorder or unpredictability, since work is produced by organized molecular motion. Entropy theory offers a profound understanding of the direction of spontaneous change for many commonplace events. A formal definition of a random graph exists. It deals with relational data's probabilistic and structural properties. The lower-order distribution of an ensemble of attributed graphs may be used to describe the ensemble by considering it to be the results of a random graph. Shannon's entropy metric is applied to represent a random graph's variability. A structural or physicochemical characteristic of a molecule or component of a molecule is known as a molecular descriptor. A mathematical correlation between a chemical's quantitative molecular descriptors and its toxicological endpoint is known as a QSAR model for predictive toxicology. Numerous physicochemical, toxicological, and pharmacological characteristics of chemical substances help to foretell their type and mode of action. Topological indices were developed some 150 years ago as an alternative to the Herculean, and arduous testing is needed to examine these features. This article uses various computational and mathematical techniques to calculate atom–bond connectivity entropy, atom–bond sum connectivity entropy, the newly defined Albertson entropy using the Albertson index, and the IRM entropy using the IRM index. We use the subdivision and line graph of the H 3 B O 3 layer structure, which contains one boron atom and three oxygen atoms to form the chemical boric acid. [ABSTRACT FROM AUTHOR]

The unprovoked invasion of Ukraine by the Russian Federation has resulted in the largest humanitarian crisis in Europe since World War II. As fighting intensifies throughout Ukraine, there is an increasing concern that the Russian Federation may consider the direct use of chemical or radiological weapons against military personnel and civilians in Ukraine. Despite prohibition of chemical weapons from the Chemical Weapons Convention of 1997, recent evidence has demonstrated that state actors will continue to use these agents as weapons of war and terror, despite publicly denying their use. We review chemical weapons produced and used by the Russian Federation (or its allies) to identify plausible risks in the Russian war in Ukraine. We also provide rapid assessment and treatment guidelines to recognize and manage these acute exposures. [ABSTRACT FROM AUTHOR]

Ecotoxicological research has increasingly focused on the interactive effects of chemical mixtures on biological models, emphasising additive, synergistic, or antagonistic interactions. However, these combination studies often test chemicals at unique concentrations (e.g. x:y), limiting our understanding of the effects across the full spectrum of possible combinations. Evidence from human toxicology suggests that interactive effects among chemicals can vary significantly with total concentration (e.g. x:y vs. 2x:2y), their ratio (e.g. x:2y vs. 2x:y), and the magnitude of the tested effect (e.g. LC 10 vs. LC 50). Our non-exhaustive review of studies on binary mixtures in bee ecotoxicology reveals that such parameters are frequently neglected. Of the 60 studies we examined, only two utilised multiple total concentrations and ratios, thus exploring a broad range of possible combinations. In contrast, 26 studies tested only a single concentration of each chemical, resulting in incomplete interpretations of the potential interactive effects. Other studies utilised various concentrations and/or ratios but failed to capture a broad spectrum of possible combinations. We also discuss potential discrepancies in interactive effects based on different metrics and exposure designs. We advocate for future ecotoxicological studies to investigate a wider spectrum of chemical combinations, including various concentrations and ratios, and to address different levels of effects. [ABSTRACT FROM AUTHOR]

Our capability to predict the impact of exposure to chemical mixtures on environmental and human health is limited in comparison to the advances on the chemical characterization of the exposome. Current approaches, such as new approach methodologies, rely on the characterization of the chemicals and the available toxicological knowledge of individual compounds. In this study, we show a new methodological approach for the assessment of chemical mixtures based on a proteome-wide identification of the protein targets and revealing the relevance of new targets based on their role in the cellular function. We applied a proteome integral solubility alteration assay to identify 24 protein targets from a chemical mixture of 2,3,7,8-tetrachlorodibenzo- p- dioxin, alpha-endosulfan, and bisphenol A among the HepG2 soluble proteome, and validated the chemical mixture-target interaction orthogonally. To define the range of interactive capability of the new targets, the data from intrinsic properties of the targets were retrieved. Introducing the target properties as criteria for a multi-criteria decision-making analysis called the analytical hierarchy process, the prioritization of targets was based on their involvement in multiple pathways. This methodological approach that we present here opens a more realistic and achievable scenario to address the impact of complex and uncharacterized chemical mixtures in biological systems. [Display omitted] • New protein targets for a chemical mixture were identified. • Targets were ranked according to disturbance of cellular function. • Incorporating data from intrinsic properties of proteins prevents the exclusion of unstudied targets. • This approach improves the prediction of the impact of complex or uncharacterized mixtures. [ABSTRACT FROM AUTHOR]

Relationships between toxicity and chemical hydrophobicity have been known for nearly 100 years in mammals and fish, typically using the log of the octanol:water partition coefficient (Kow). The current study reassessed the influence of mode of action (MOA) on acute aquatic toxicity-log Kow relationships using a comprehensive database of 617 organic chemicals with curated and standardized acute toxicity data that did not exceed solubility limits, their consensus log Kow values, and weight of evidence-based MOA classifications (including 6 broad and 26 specific MOAs). A total of 166 significant (p < 0.05) log Kow-toxicity models were developed across six taxa groups that included QSARs for 5 of the broad and 13 of the specific MOAs. In this study, we demonstrate that QSARs based on MOAs can significantly increase LC50 prediction accuracy for specific acting chemicals. Prediction accuracy increases when QSARs are built based on highly specific MOAs, rather than broad MOA classifications. Additionally, we demonstrate that building QSAR models with chemicals in specific MOA groupings, rather than broader MOA groups leads to significantly better estimates. We also evaluated the differences between models developed from mass-based (µg/L) and mole-based (µmol/L) toxicity data and demonstrate that both are suitable for QSAR development with no clear trend in greater model accuracy. Overall, the results reveal that, despite high variance in all taxa and MOA groups, specific MOA-based models can improve the accuracy of aquatic toxicity predictions over more general groupings.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.The affiliations are correct. [ABSTRACT FROM AUTHOR]

Siofor (metformin hydrochloride) is widely used to maintain weight in the second type of diabetes and as a complex treatment of obesity, as well as a slimming agent in biologically active supplements under various names. The presence of metformin hydrochloride with the strong effect of reducing sibutramine in Reduksin Forte capsules, taking it together with other disproportionate drugs causes an increase in cases of acute poisoning. In such cases, in order to provide quick medical assistance to patients, in order to obtain quick and accurate results in forensic chemistry practice, specific chemical toxicological analysis conditions are needed. The results of the analysis of Siofor (metformin hydrochloride) presented in this scientific article by thin layer chromatography and UV-spectrophotometry methods are closely related to forensic chemistry practice. [ABSTRACT FROM AUTHOR]

We report a novel and as yet undescribed clinical scenario in a young girl with liver failure, in whom, the liver histopathology was suggestive of alcoholic hepatitis in the background of hepatoportal sclerosis and incomplete septal cirrhosis. An extensive clinical and investigational evaluation revealed chronic consumption of multiple Ayurvedic herbal medications for seizure disease. Six months after stopping herbal medicines, the repeat liver biopsy demonstrated resolution of alcohol-related changes but persistence of classical features of non-cirrhotic portal hypertension. Analysis of the retrieved agents, including state of the art chemical and toxicology analysis, using gas chromatography and mass spectroscopy methods demonstrated multiple organic and inorganic toxins associated with acute alcohol and arsenic poisoning related hepatoportal sclerosis/incomplete septal cirrhosis in the young girl. [ABSTRACT FROM AUTHOR]

Background: Nephrotoxicity of drugs contributes to acute kidney injury with high mortality and morbidity, which crucially limits the application and development of drugs. Although many publications on nephrotoxicity have been conducted globally, there needs to be a scientometric study to systematically analyze the intellectual landscape and frontiers research trends in the future. Methods: Publications on nephrotoxicity from 2011 to 2021 were collected to perform bibliometric visualization using VOSviewer, CiteSpace, and Scimago Graphica software based on the Web of Science Core Collection. Results: A total of 9,342 documents were analyzed, which were primarily published in the United States (1,861), China (1,724), and Egypt (701). For institutions, King Saud University (166) had the most publications; Food and Chemical Toxicology, PLOS One, and Antimicrobial Agents and Chemotherapy were productive journals, primarily concentrating on the mechanisms of nephrotoxicity and renoprotective in cisplatin and antibiotics, especially in oxidative stress. Burst detection suggested that cisplatin, piperacillintazobactam, vancomycin-induced nephrotoxicity, antioxidants, and new biomaterials are frontiers of research. Conclusion: This study first provides an updated perspective on nephrotoxicity and renoprotective strategies and mechanisms. This perspective may benefit researchers in choosing suitable journals and collaborators and assisting them in the deep understanding of the nephrotoxicity and renoprotective hotspots and frontiers. [ABSTRACT FROM AUTHOR]

ObjectiveTo develop a method for the simultaneous and rapid detection of five mushroom toxins （α-amanitin， phallacidin， muscimol， muscarine and psilocin） in blood by ultra-high performance liquid chromatography-high resolution mass spectrometry （UPLC-HRMS）.MethodsThe blood samples were precipitated with acetonitrile-water solution（Vacetonitril∶Vwater=3∶1） and PAX powder， then separated on ACQUITY Premier C18 column， eluted gradient. Five kinds of mushroom toxins were monitored by FullMS-ddMS2/positive ion scanning mode， and qualitative and quantitative analysis was conducted according to the accurate mass numbers of primary and secondary fragment ions.ResultsAll the five mushroom toxins had good linearity in their linear range， with a determination coefficient （R2）≥0.99. The detection limit was 0.2-20 ng/mL. The ration limit was 0.5-50 ng/mL. The recoveries of low， medium and high additive levels were 89.6%-101.4%， the relative standard deviation was 1.7%-6.7%， the accuracy was 90.4%-101.3%， the intra-day precision was 0.6%-9.0%， the daytime precision was 1.7%-6.3%， and the matrix effect was 42.2%-129.8%.ConclusionThe method is simple， rapid， high recovery rate， and could be used for rapid and accurate qualitative screening and quantitative analysis of various mushroom toxins in biological samples at the same time， so as to provide basis for the identification of mushroom poisoning events.

Although chronic low-level exposure to Hg2+ and Cd2+ causes human nephrotoxicity, the bioinorganic processes that deliver them to their target organs are poorly understood. Since the plasma protein human serum albumin (HSA) has distinct binding sites for these metal ions, we wanted to gain insight into these translocation processes and have employed size-exclusion chromatography coupled on-line to an inductively coupled plasma atomic emission spectrometer using phosphate-buffered saline mobile phases. When HSA ‘labeled’ with Hg2+ and Cd2+ (1:0.1:0.1) using 300 μM of L-methionine was analyzed, the co-elution of a single C, S, Cd, and Hg peak was observed, which implied the intact bis-metalated HSA complex. Since human plasma contains small molecular weight thiols and sulfur-containing metabolites, we analyzed the bis-metalated HSA complex with mobile phases containing 50–200 µM of L-cysteine (Cys), D,L-homocysteine (hCys), or glutathione (GSH), which provided insight into the comparative mobilization of each metal from their respective binding sites on HSA. Interestingly, 50 µM Cys, hCys, or GSH mobilized Hg2+ from its HSA binding site but only partially mobilized Cd2+ from its binding site. Since these findings were obtained at conditions simulating near-physiological conditions of plasma, they provide a feasible explanation for the higher ‘mobility’ of Hg2+ and its concomitant interaction with mammalian target organs compared to Cd2+. Furthermore, 50 µM Cys resulted in the co-elution of similar-sized Hg and Cd species, which provides a biomolecular explanation for the nephrotoxicity of Hg2+ and Cd2+.

Difenoconazole is a chemical entity containing two chiral centers and having four stereoisomers: (2R,4R)-, (2R,4S)-, (2S,4R)- and (2S,4S)-difenoconazole, the marketed product containing a mixture of these isomers. Residues of difenoconazole have been identified in many agricultural products and drinking water. A computational approach has been used to evaluate the toxicological effects of the difenoconazole stereoisomers on humans. It integrates predictions of absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles, prediction of metabolism sites, and assessment of the interactions of the difenoconazole stereoisomers with human cytochromes, nuclear receptors and plasma proteins by molecular docking. Several toxicological effects have been identified for all the difenoconazole stereoisomers: high plasma protein binding, inhibition of cytochromes, possible hepatotoxicity, neurotoxicity, mutagenicity, skin sensitization potential, moderate potential to produce endocrine disrupting effects. There were small differences in the predicted probabilities of producing various biological effects between the distinct stereoisomers of difenoconazole. Furthermore, there were significant differences between the interacting energies of the difenoconazole stereoisomers with plasma proteins and human cytochromes, the spectra of the hydrogen bonds and aromatic donor–acceptor interactions being quite distinct. Some distinguishing results have been obtained for the (2S,4S)-difenoconazole: it registered the highest value for clearance, exposed reasonable probabilities to produce cardiotoxicity and carcinogenicity and negatively affected numerous nuclear receptors. [ABSTRACT FROM AUTHOR]

Oxamyl is a highly toxic carbamate molecule with toxicological risk from contamination, used as an insecticide, nematicide, and acaricide on many field crops, vegetables, fruits, and ornamentals. Suspected poisoned animals and baits were collected between January 2018 and August 2021 from Lombardy and Emilia-Romagna regions and analyzed at the chemical toxicology laboratory of the Experimental Zooprophylactic Institute of Lombardy and Emilia-Romagna, located in Brescia. The analyses were carried out by an ion trap GC-MS system in 2467 suspected samples and showed the presence of oxamyl in 67 of these. In this study, we analyzed 47 (out of 67) positive baits: the provinces in which more cases have been recorded are Mantua, Ferrara, and Cremona, which overall had 72% of positivity. The nature of the analyzed samples was mostly corn (55.3%), followed by bird carcasses (19.1%), apples (14.8%), meatballs (2.1%), bread (2.1%), and other (8.5%). The use of oxamyl to produce poisoned baits is constantly increasing, proving that it must be considered as a public health risk for the possible consequences on target and non-target organisms, including humans. [ABSTRACT FROM AUTHOR]

Prior to registering and marketing any new pharmaceutical, (agro)chemical or food ingredient product manufacturers must, by law, generate data to ensure human safety. Safety testing requirements vary depending on sector, but generally repeat-dose testing in animals form the basis for human health risk assessments. Dose level selection is an important consideration when designing such studies, to ensure that exposure levels that lead to relevant hazards are identified. Advice on dose level selection is provided in test guidelines and allied guidance documents, but it is not well harmonised, particularly for selection of the highest dose tested. This paper further builds on concepts developed in a technical report by the European Centre for Ecotoxicology and Toxicology of Chemicals (ECETOC) which recommends pragmatic approaches to dose selection considering regulatory requirements, animal welfare and state of the art scientific approaches. Industry sectors have differing degrees of freedom to operate regarding dose level selection, depending on the purpose of the studies and the regulatory requirements/legislation, and this is reflected in the overall recommended approaches. An understanding of systemic exposure should be utilised where possible (e.g., through toxicokinetic approaches) and used together with apical endpoints from existing toxicity studies to guide more appropriate dose level selection. The highest dose should be limited to a reasonable level, causing minimal but evident toxicity to the test animals without significantly compromising their well-being. As the science of predictive human exposure further develops and matures, this will provide exciting and novel opportunities for more human-relevant approaches to dose level selection. [ABSTRACT FROM AUTHOR]

The quantitative structure–activity relationship (QSAR) modelling of mixtures is not as simple as that for individual chemicals, and it needs additional care to avoid overestimation of the performance. In this research, we have developed a 2D-QSAR model using only 2D interpretable and reproducible descriptors to predict the aquatic toxicity of mixtures of polar and non-polar narcotic substances present in the environment. Partial least squares (PLS) regression has been used to model the response variable (log 1/EC50 against Photobacterium phosphoreum) and the structural features of 84 binary mixtures of polar and nonpolar narcotic toxicants complying with the Organization of Economic Co-operation and Development (OECD) protocols. The model was cross-validated by mixtures-out and compounds-out cross-validation to nullify the developmental bias. The reliability of prediction of the model has been judged by the Prediction Reliability Indicator (PRI) tool using a newly designed set. The new model is robust, reproducible, extremely predictive, easily interpretable, and can be used for reliable prediction of aquatic toxicity of any untested chemical mixtures within the applicability domain. We have additionally used a machine learning-based chemical read-across algorithm in this study to improve the quality of predictions for the toxicity of the mixtures with the modelled descriptors. [ABSTRACT FROM AUTHOR]