Search Results (25)

In order to recycle plastic waste back to food contact materials (FCMs), it is necessary to identify hazardous substances in plastic packaging that pose a toxicological risk. Printing inks on plastics are not yet designed to withstand the high heat stress of mechanical recycling processes and therefore require hazard identification. In this study, virgin polypropylene (PP) foils were printed with different types of inks (UV-cured, water-based) and colour shades. Thermal analysis of printed foils and pigments was performed using differential scanning calorimetry (DSC). Samples were then thermally treated below and above measured thermal events at 120 °C, 160 °C, 200 °C or 240 °C for 30 min. Subsequently, migration tests and miniaturised Ames tests were performed. Four out of thirteen printed foils and all three pigments showed positive results for mutagenicity in miniaturised Ames tests after thermal treatment at 240 °C. Additionally, pre-incubation Plate Ames tests (according to OECD 471) were performed on three pigments and one printed foil, yielding two positive results after thermal treatment at 240 °C. These results indicate that certain ink components form hazardous decomposition products when heated up to a temperature of 240 °C. However, further research is needed to gain a better understanding of the chemical processes that occur during high thermal treatment. Full article

Social biases may concentrate the attention of researchers on a small number of well-known molecules/mechanisms leaving others underexplored. In accordance with this view, central to mechanistic toxicology is a narrow range of molecular pathways that are assumed to be involved in a significant part of the responses to toxicity. It is unclear, however, if there are other molecular mechanisms which play an important role in toxicity events but are overlooked by toxicology. To identify overlooked genes sensitive to chemical exposures, we used publicly available databases. First, we used data on the published chemical–gene interactions for 17,338 genes to estimate their sensitivity to chemical exposures. Next, we extracted data on publication numbers per gene for 19,243 human genes from the Find My Understudied Genes database. Thresholds were applied to both datasets using our algorithm to identify chemically sensitive and chemically insensitive genes and well-studied and underexplored genes. A total of 1110 underexplored genes highly sensitive to chemical exposures were used in GSEA and Shiny GO analyses to identify enriched biological categories. The metabolism of fatty acids, amino acids, and glucose were identified as underexplored molecular mechanisms sensitive to chemical exposures. These findings suggest that future effort is needed to uncover the role of xenobiotics in the current epidemics of metabolic diseases. Full article

Poisoning is a common and severe problem worldwide. Due to significant growth in the agricultural, chemical, and pharmaceutical industries over the past few decades, poisoning risks have increased with the use of food, chemicals, and medicines everywhere in the world, especially in Saudi Arabia. Advanced information on acute poisoning patterns is critical for the effective management of poisoning events. This study aimed to examine the characteristics of patients with various patterns of acute poisoning, caused by food, drugs, and chemicals, that were reported to the Department of Toxicology and Poison Center at King Fahad Hospital and the Poison Center in Al-Baha Province, Saudi Arabia. The study also examined the relationship between demographic characteristics, including age, toxin type, and geographical distribution, and poisonings in Baha Province. This retrospective cross-sectional analysis included 622 poisoning cases. The data were collected from 2019 to 2022 and it was found that out of 622 instances, 159 had food poisoning, with more men than females sick (53.5% male and 46.5% female), 377 had drug poisoning (54.1% males and 45.9% females), and 86 had chemical poisoning (74.4% males and 25.6% females). This study found that the most prevalent agents implicated in acute poisoning were medicines, particularly analgesics and antipsychotic drugs. Food poisoning was the second most common acute poisoning, affecting largely males followed by female patients. Finally, chemical poisoning involved acute poisoning, with most cases involving methanol and household items including the strongest bleaches (chlorines) (Clorox^®, Oakland, CA, USA). Insecticides and pesticides were also secondary sources of chemical poisoning. Additional research revealed that the incidence of food, chemical, and drug poisoning was highest in children aged 1–15 years (food poisoning, n = 105, 66%; drug poisoning, n = 120, 31.8%); patients aged 11–20 years had the highest incidence of chemical poisoning (n = 41, 47.7%). Most poisoning incidents among youngsters are caused by easy access to drugs at home. Implementing strategies to enhance public awareness and limit children’s access to drugs would contribute considerably to decreasing the community’s burden of this problem. The findings of this study suggest that Al-Baha should improve its education regarding the rational and safe use of drugs and chemicals. Full article

The impact of exposure to multiple chemicals raises concerns for human and environmental health. The adverse outcome pathway method offers a framework to support mechanism-based assessment in environmental health starting by describing which mechanisms are triggered upon interaction with different stressors. The identification of the molecular initiating event and the molecular interaction between a chemical and a protein target is still a challenge for the development of adverse outcome pathways. The cellular response to chemical exposure studied with omics could not directly identify the protein targets. However, recent mass spectrometry-based methods are offering a proteome-wide identification of protein targets interacting with s but unrevealing a molecular initiating event from a set of targets is still dependent on available knowledge. Here, we directly coupled the target identification findings from the proteome integral solubility alteration assay with an analytical hierarchy process for the prediction of a prioritized molecular initiating event. We demonstrate the applicability of this combination of methodologies with a test compound (TCDD), and it could be further studied and integrated into AOPs. From the eight protein targets identified by the proteome integral solubility alteration assay after analyzing 2824 human hepatic proteins, the analytical hierarchy process can select the most suitable protein for an AOP. Our combined method solves the missing links between high-throughput target identification and prediction of the molecular initiating event. We anticipate its utility to decipher new molecular initiating events and support more sustainable methodologies to gain time and resources in chemical assessment. Full article

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. Full article

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. Full article

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway (AOP), which is well-established in regulatory toxicology. This framework aims to model the sequence of events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how those eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues. Full article

The use, production, and disposal of engineering nanomaterials (ENMs), including graphene-related materials (GRMs), raise concerns and questions about possible adverse effects on human health and the environment, considering the lack of harmonized toxicological data on ENMs and the ability of these materials to be released into the air, soil, or water during common industrial processes and/or accidental events. Within this context, the potential release of graphene particles, their agglomerates, and aggregates (NOAA) as a result of sanding of a battery of graphene-based polyester resin composite samples intended to be used in a building was examined. The analyzed samples were exposed to different weathering conditions to evaluate the influence of the weathering process on the morphology and size distribution of the particles released. Sanding studies were conducted in a tailored designed sanding bench connected to time and size resolving measurement devices. Particle size distributions and particle number concentration were assessed using an optical particle counter (OPC) and a condensation particle counter (CPC), respectively, during the sanding operation. A scanning electron microscope/energy dispersive X-ray (SEM/EDX) analysis was performed to adequately characterize the morphology, size, and chemical composition of the released particles. A toxicity screening study of pristine and graphene-based nanocomposites released using the aquatic macroinvertebrate Daphnia magna and relevant human cell lines was conducted to support risk assessment and decision making. The results show a significant release of nanoscale materials during machining operations, including differences attributed to the % of graphene and weathering conditions. The cell line tests demonstrated a higher effect in the human colon carcinoma cell line Caco2 than in the human fibroblasts (A549 cell line), which means that composites released to the environment could have an impact on human health and biota. Full article

Engineered nanoscale amorphous silica nanomaterials are widespread and used in many industrial sectors. Currently, some types of silicon-based nanozeolites (NZs) have been synthesized, showing potential advantages compared to the analogous micro-forms; otherwise, few studies are yet available regarding their potential toxicity. In this respect, the aim of the present work is to investigate the potential exposure to airborne Linde Type A (LTA) NZs on which toxicological effects have been already assessed. Moreover, the contributions to the background related to the main emission sources coming from the outdoor environment (i.e., vehicular traffic and anthropogenic activities) were investigated as possible confounding factors. For this purpose, an LTA NZ production line in an industrial factory has been studied, according to the Organisation for Economic Cooperation and Development (OECD) guidelines on multi-metric approach to investigate airborne nanoparticles at the workplace. The main emission sources of nanoparticulate matter within the working environment have been identified by real-time measurements (particle number concentration, size distribution, average diameter, and lung-deposited surface area). Events due to LTA NZ spillage in the air during the cleaning phases have been chemically and morphologically characterized by ICP-MS and SEM analysis, respectively. Full article

Under the name of lipophilic marine toxins, there are included more than 1000 toxic secondary metabolites, produced by phytoplankton, with the common chemical property of lipophilicity. Due to toxicological effects and geographical distribution, in European legislation relevant compounds are regulated, and their determination is accomplished with the reference liquid chromatography-tandem mass spectrometry method. In this study a modified ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method has been developed for the identification and quantification of EU-regulated lipophilic toxins. The method optimization included a refinement of SPE-C18 clean-up, in order to reduce matrix interferences. Improved LC conditions and upgraded chromatographic ammonia-based gradient ensured the best separation of all analytes and, in particular, of the two structural isomers (OA and DTX2). Also, different MS parameters were tested, and confirmation criteria finally established. The validation studies confirmed that all parameters were satisfactory. The requirements for precision (RSD% < 11.8% for each compound), trueness (recoveries from 73 to 101%) and sensitivity (limits of quantification in the range 3–8 µg kg⁻¹) were fulfilled. The matrix effect, ranging from −9 to 19%, allowed the use of a calibration curve in solvent (3–320 µg kg⁻¹ in matrix) for quantification of real samples. Method relative uncertainty ranged from 12 to 20.3%. Additionally, a total of 1000 shellfish samples was analysed, providing a first preliminary surveillance study that may contribute to the knowledge of lipophilic marine toxins contamination. Increase in algae proliferation events and intoxication cases, EFSA suggestions for modification of maximum permitted levels and toxicity equivalency factors, and new studies of important toxic effects underline that implementation of reference methods still represents an important task for health and food safety laboratories. Full article

Molecular design and evaluation for drug development and chemical safety assessment have been advanced by quantitative structure–activity relationship (QSAR) using artificial intelligence techniques, such as deep learning (DL). Previously, we have reported the high performance of prediction models molecular initiation events (MIEs) on the adverse toxicological outcome using a DL-based QSAR method, called DeepSnap-DL. This method can extract feature values from images generated on a three-dimensional (3D)-chemical structure as a novel QSAR analytical system. However, there is room for improvement of this system’s time-consumption. Therefore, in this study, we constructed an improved DeepSnap-DL system by combining the processes of generating an image from a 3D-chemical structure, DL using the image as input data, and statistical calculation of prediction-performance. Consequently, we obtained that the three prediction models of agonists or antagonists of MIEs achieved high prediction-performance by optimizing the parameters of DeepSnap, such as the angle used in the depiction of the image of a 3D-chemical structure, data-split, and hyperparameters in DL. The improved DeepSnap-DL system will be a powerful tool for computer-aided molecular design as a novel QSAR system. Full article

Cellular adaptive mechanisms emerging after exposure to low levels of toxic agents or stressful stimuli comprise an important biological feature that has gained considerable scientific interest. Investigations of low-dose exposures to diverse chemical compounds signify the non-linear mode of action in the exposed cell or organism at such dose levels in contrast to the classic detrimental effects induced at higher ones, a phenomenon usually referred to as hormesis. The resulting phenotype is a beneficial effect that tests our physiology within the limits of our homeostatic adaptations. Therefore, doses below the region of adverse responses are of particular interest and are specified as the hormetic gain zone. The manifestation of redox adaptations aiming to prevent from disturbances of redox homeostasis represent an area of particular interest in hormetic responses, observed after exposure not only to stressors but also to compounds of natural origin, such as phytochemicals. Findings from previous studies on several agents demonstrate the heterogeneity of the specific zone in terms of the molecular events occurring. Major factors deeply involved in these biphasic phenomena are the bioactive compound per se, the dose level, the duration of exposure, the cell, tissue or even organ exposed to and, of course, the biomarker examined. In the end, the molecular fate is a complex toxicological event, based on beneficial and detrimental effects, which, however, are poorly understood to date. Full article

In silico approaches have been studied intensively to assess the toxicological risk of various chemical compounds as alternatives to traditional in vivo animal tests. Among these approaches, quantitative structure–activity relationship (QSAR) analysis has the advantages that it is able to construct models to predict the biological properties of chemicals based on structural information. Previously, we reported a deep learning (DL) algorithm-based QSAR approach called DeepSnap-DL for high-performance prediction modeling of the agonist and antagonist activity of key molecules in molecular initiating events in toxicological pathways using optimized hyperparameters. In the present study, to achieve high throughput in the DeepSnap-DL system–which consists of the preparation of three-dimensional molecular structures of chemical compounds, the generation of snapshot images from the three-dimensional chemical structures, DL, and statistical calculations—we propose an improved DeepSnap-DL approach. Using this improved system, we constructed 59 prediction models for the agonist and antagonist activity of key molecules in the Tox21 10K library. The results indicate that modeling of the agonist and antagonist activity with high prediction performance and high throughput can be achieved by optimizing suitable parameters in the improved DeepSnap-DL system. Full article

Botulinum toxins or neurotoxins (BoNTs) are the most potent neurotoxins known, and are currently extensively studied, not only for their potential lethality, but also for their possible therapeutic and cosmetic uses. Currently, seven types of antigenically distinct toxins are known and characterized, produced by a rod-shaped bacterium, Clostridium botulinum. Human poisoning by botulism (presenting with severe neuromuscular paralytic disease) is usually caused by toxins A, B, E, and F type. Poisoning from contaminated food preparations is the most common cause of noniatrogenic botulism. The spores are highly resistant to heat but are easily destroyed at 80 °C for thirty minutes. Type A and B toxins are resistant to digestion by the enzymes of the gastrointestinal system. After their entry, BoNTs irreversibly bind to cholinergic nerve endings and block the release of acetylcholine from the synapses. In contrast, in wound botulism, the neurotoxin is instead product by the growth of C. botulium in infected tissues. The contamination by BoNT inhalation does not occur by a natural route but it is certainly the most dangerous. It can be caused by the dispersion of the botulinum toxin in the atmosphere in the form of an aerosol and therefore can be deliberately used for bioterrorist purposes (e.g., during CBRN (chemical, biological, radiological, and nuclear) unconventional events). In addition, BoNTs are currently used to treat a variety of diseases or alleviate their symptoms, such as the onabotulinumtoxinA for migraine attacks and for cosmetic use. Indeed, this paper aims to report on updated knowledge of BoNTs, both their toxicological mechanisms and their pharmacological action. Full article

The Adverse Outcome Pathway (AOP) framework has been considered the most innovative tool to collect, organize, and evaluate relevant information on the toxicological effects of chemicals, facilitating the establishment of links between molecular events and adverse outcomes at the critical level of biological organization. Considering the combination of the high volume of toxicological and ecotoxicological data produced and the application of artificial intelligence algorithms from the last few years, not only can higher mechanistic interpretability be reached with new in silico models, but also a potential increase in predictivity in hazard assessments and the identification of new potential biomarkers can be achieved. The current paper aims to discuss some potential challenges and ways of integrating in silico models and AOPs to predict toxicological effects and to set and relate new biomarkers for defined purposes. With the use of the AOP framework to organize the ecotoxicological, toxicological, and structural data generated from in chemico, in vitro, ex vivo, in vivo, and population studies, it is expected that the generated biological and chemical construct will improve its application, establishing a knowledge platform to set and relate new biomarkers by key event relationships (KERs). Full article