Chemical Research in Toxicology最新文献

Tobacco and cannabis smoke are both complex chemical mixtures generated through combustion of biomass material. The presence of free radicals in tobacco smoke has been established for nearly seven decades. Despite similarities between cannabis and tobacco smoke and the known presence of radicals in the latter, analysis of free radicals in cannabis smoke has yet to be conducted. In this work, electron paramagnetic resonance (EPR) spectroscopy was used to detect short-lived radicals and environmentally persistent free radicals (EPFRs) in cannabis smoke. Spin-trapping techniques were employed to aid in identification of the short-lived radicals. Congruent with findings from studies conducted on tobacco smoke, short-lived free radicals were detected in the gas phase, and EPFRs were detected in the particle phase of cannabis smoke. Gas phase results indicate the presence of oxygen-centered radicals in cannabis smoke, though the shape of the resulting EPR spectra differs slightly from that of tobacco smoke. Particle phase results for cannabis match well with those from previous studies conducted on tobacco smoke, regardless of the spin trap used (or lack thereof). Quantitative findings indicate that cannabis smoke contains approximately the same radical concentration as tobacco smoke, on the order of 10¹⁵ gas-phase spins and 10¹⁴ particle-phase spins per cannabis preroll or tobacco cigarette. The impacts of burning method (continuous vs puffing) and cannabinoid composition on radical concentrations were also investigated here. While puffing was observed to lower radical concentrations, the cannabinoid composition of the strain of cannabis burned had no observable impact on the amount or identity of free radicals detected.

Nicotine has been used in e-cigarettes for many years; however, recently, nicotine analogs have risen in popularity. E-cigarettes containing nicotine analogs such as nicotinamide and 6-methylnicotine are currently sold without regulatory oversight. They are marketed as safer alternatives to nicotine-containing products, although there is little or no scientific evidence to support this claim. This study investigated the nicotine analog, nicotinamide (NA), along with its major degradant, 3-cyanopyridine (3CP), which is produced when NA is vaped. Upon heating and aerosolization, both chemicals are present in the exposure dose. Dose–response curves are created for relative concentrations of NA and 3CP, and an isobologram is formed to investigate their mixture effects. NA is toxic at concentrations greater than 2637 ppm; however, 3CP is harmful in concentrations as low as 0.0001 ppm. The most significant finding is that the isobologram indicates that the mixture effects are synergistic, where a decrease in viability can be seen in minimal doses of 3CP (i.e., 0.000001 ppm) and 1350 ppm of NA. The interaction index was calculated for each point, and all values were less than 1, indicating a statistically synergistic biological response. The study highlights how such small levels of 3CP can play a large role in inducing toxic responses of a presumed safe chemical (i.e., nicotinamide or niacinamide, a form of vitamin B3 (niacin)). These results indicate that chemical and biochemical reactions, as well as interactions between e-cigarette aerosol components, including nicotine analogs, warrant further investigation.

Allergic diseases affect over one billion people worldwide as a common chronic condition. Conventional treatments often relieve symptoms but lack long-term efficacy or safety. Over the past decade, nanomedicine, i.e., nanoscale drugs and delivery systems, has emerged as a promising alternative that leverages the tunable physicochemical properties of nanoparticles (NPs) and enhances both diagnosis and treatment of hypersensitivity disorders. In diagnostics, nanoparticle-based biosensors have achieved detection limits as low as 42 fg/mL with specificity exceeding 90% for food and aeroallergen proteins. Therapeutic applications comprise various NPs, including gold, silver, iron oxide, carbon-based, lipid-mediated, polymeric, dendrimeric, and virus-like, as delivery vehicles and as immunomodulators. Preclinical models detect >50% reductions in pro-inflammatory cytokines (IL-4, IL-5) and two- to 3-fold reductions in eosinophil infiltration following NP-augmented allergen immunotherapy, with antigen-specific IgE titers reduced by up to 70%. Although such advancement has occurred, nanotoxicology studies highlight dose-dependent organ concentration and prolonged pulmonary half-lives that necessitate rigorous biosafety evaluation. Regulatory and manufacturability concerns remain significant hurdles for clinical translation. This article reviews up-to-date quantitative performance metrics for nanoparticle therapeutics and diagnostics in allergy control, critically examines the toxicity profiles and translational issues, and brings out directions toward individualized, safe nanotheranostic platforms.

Oxidative stress contributes to the damage of biological molecules and is linked to the development of multiple diseases, including liver disorders, such as metabolic dysfunction-associated steatotic liver disease (MASLD). In mammals, reduced glutathione (GSH) is a pivotal antioxidant that regulates cellular responses to redox imbalances caused by reactive oxygen and nitrogen species. The presence of reduced GSH within mitochondria is especially crucial for preserving the organelle’s routine performance by eliminating hydrogen peroxide generated under both physiological and pathological conditions. Cumulative evidence indicates that MASLD is associated with a diminished mitochondrial GSH (mGSH) pool, attributed to alterations in mitochondrial membrane fluidity due to cholesterol accumulation. Therefore, strategies aimed at boosting mGSH may offer therapeutic benefits against MASLD-associated liver injury. This study aims to investigate whether l-cysteine-glutathione disulfide (l-CySSG), a proposed GSH donor and precursor, can effectively restore total and mGSH in vitro and in vivo in mice fed cholesterol-enriched (HC) or methionine-choline-deficient (MCD) diets. Additionally, S-adenosylmethionine (SAM), a compound that serves as both a GSH precursor and a membrane fluidizer, along with N-acetylcysteine (NAC), a GSH precursor by providing cysteine, was used as the control molecules in the study. Our findings show that l-CySSG has great potential as a liver protector, especially due to its good oral bioavailability. Although it does not restore GSH levels in the mitochondria as efficiently as SAM does, l-CySSG can still offer protection against liver damage, possibly through mechanisms that are not yet fully understood. Overall, l-CySSG emerges as a promising alternative for treating conditions related to oxidative stress and mitochondrial dysfunction, paving the way for future research and therapeutic development.

The mutational outcome of DNA damage as a direct result of constant chemical assault is governed by major factors, including the structure and nature of damage, replication, and repair machinery in vivo. The role of the size of the adduct, adduct-flanking bases, and the type of polymerase involved in the replication pathway is prominently seen through existing in vitro and in vivo studies. In this work, machine learning methods have been developed to predict the critical parameters for the mutational outcome of the adducts when they encounter polymerase in a particular sequence context. We carried out the analysis with three different classification models: Logistic Regression (LR), Decision Tree (DT), and Support Vector Machine (SVM). Using the literature data, mutational results of covalent DNA adducts and abasic sites were used to train the classification models. Following this, we used a generative network method with the available information on the structure of the DNA damage, polymerase, and sequence context to generate synthetic data that accurately mirrors the real data. Further, we employed an Extreme Gradient Boosting Classifier to identify the parameter that most influences the DNA mutational outcome. Metrics such as Accuracy, Sensitivity, Precision, F1 score, and AUC value have been used to evaluate the performance of classifier methods. The proposed Bootstrapped-Variational Autoencoder (BT-VAE) model enhanced the overall prediction accuracy of classifiers by 40%. The SVM model delivered the best performance across all classification metrics in predicting mutational outcomes among the three classification models evaluated. By providing the size of the carcinogen/covalent DNA adduct, polymerase, and flanking base as input, the proposed BT-VAE framework can predict the mutational outcome (match or mismatch for covalent DNA adducts and adenine or nonadenine for abasic site), an additional tool for in vivo and in vitro studies in the field of toxicology.

The Nonclinical Translation Working Group of the IQ Drug-Induced Liver Injury (DILI) Consortium conducted two surveys in 2023 and 2017 to canvas member companies on approaches and experiences in the preceding 5-year periods that inform how DILI risk assessment has evolved in the past decade. Surveys comprised 53 detailed questions to understand the current status, temporal changes, and future direction and to gain insights. Focusing on the 2023 survey for the most contemporary data, responses indicated that DILI still remains a problem during drug development, with 41% of companies in the 2023 survey (50% in 2017) filing at least one clinical expedited safety report in the last 5 years. Most companies have common nonclinical screening approaches, with the majority of companies incorporating target safety assessments, considering physicochemical properties and dose, and using multiple in vitro approaches including cytotoxicity, mitotoxicity, BSEP inhibition, and various reactive metabolite assays, with the utilization of many of these being increased in the 2023 survey compared to the 2017 survey. The impact of in vivo toxicology studies on clinical study design and compound progression is also reviewed in both the 2023 and 2017 surveys. A large majority of companies now report having new modality drugs in their portfolios, including antibody-based and oligonucleotide-based modalities, cell therapies, protein degraders, and peptide-based medicines; yet only 1 or 2 companies report having modality-specific approaches to assess DILI risk despite these modalities having very different mechanisms of causing DILI compared to small molecules. This is a key area for growth in the nonclinical assessment of hepatotoxicity to support these emerging modalities and the tremendous potential that they offer for unmet clinical needs. Collaborative partnerships will be key to driving new capabilities forward in this area, contributing to the development of safer novel therapeutics for patients.

Olaparib, an anticancer drug, has been recently associated with major side effects (hepatotoxicity and hematotoxicity). Human CYP450 3A4/5 metabolizes olaparib and forms dehydrogenated (M11) and hydroxylated (M6, M15) metabolites. The major (dehydrogenated: M11) metabolite is unreactive due to the stability of its amide bonds. Thus, the recently reported toxicities (hepato- and hemato) remain mysterious. Here, we investigate olaparib’s metabolic pathways using Cpd I model systems to gain insights into metabolic preferences, reactive metabolite formation, and associated toxicities. Potential energy surface (PES) analysis using activation (ΔG^‡), reaction (ΔG°) free energies, and molecular docking, dynamics-based accessibility (distance of site of metabolism: SOM from heme-Fe) is utilized to explain metabolic preferences. Quantum chemical calculations showed that the formation of dehydrogenated (M11) and hydroxylated (M6) metabolites is favored relative to aromatic hydroxylated (M15) metabolites (reaction free energies: k_BT = 18.5 kcal/mol as cutoff). The detailed analysis of the metabolic pathway for the major metabolite (M11) formation showed that hydroxylation follows the E1 mechanism, leading to dehydration and the formation of a tetrahydropyrazine derivative. The olaparib piperazine ring C approaches the heme-Fe within activating distance (6 ± 2 Å) in most docked poses and during 200 ns MD simulations. The C10 leading to hydroxylated metabolite (M6) remains at >10 Å, making the reactive M12 formation less likely. Furthermore, the MM-GBSA-based per-residue calculations showed that 13 active-site residues, including Arg105, contribute significantly to the binding energy (avg: −1.24 kcal/mol). DFT-based global and local reactivity (electrophilicity: ω) analysis showed that the 4-acetylphthalazin-1(2H)-one group in the M12 metabolite (formed from M6) is highly electrophilic and might explain the idiosyncratic toxicities. These findings may offer valuable insights into the mechanisms of toxicity and for the design of novel and less toxic olaparib analogs.

Tetrahydrocannabinol (THC), the primary psychoactive compound of cannabis, is the most widely abused substance worldwide, with an annual prevalence of 4.3% of adults and 5.3% of the 15–16 year-old population estimated as of 2022. THC has both acute and chronic effects through the dopaminergic and endocannabinoid systems. This study was conducted to better understand the metabolites and metabolic pathways in biological systems affected by cannabis, which may help find practical diagnostic and treatment approaches for people with cannabis dependence in the future. Metabolomic analysis of urine samples was performed using gas chromatography–mass spectrometry (GC–MS). MetaboAnalyst software was used to determine sample metabolite profiles, which were then subjected to multivariate statistical analysis. From data of over 200 metabolites in each sample of cannabis users, 92 metabolites with a p-value of less than 0.05 were selected for further analyses, of which 38 showed a decrease and 54 showed an increase compared to the nonuser group. Based on 43 metabolites (VIP > 1), subjected to MetaboAnalyst and CPDB, amino acid metabolism (especially arginine, methionine, and cysteine), vitamin metabolism (particularly biotin), and the urea cycle were the primarily affected metabolic pathways. The AUC values of the four metabolites (salsoline, 6-thiourate, procollagen 5-hydroxy-l-lysine, and biotin) with the highest VIP scores were between 0.93 and 0.98, with no significant difference. Metabolites with high VIP scores hold promise as biomarker candidates for identifying cannabis users, and the prominent pathways provide new insights into the understanding of the metabolic effects of cannabis.

Advancement of therapeutic modalities using carbon-based nanomaterials (CBNMs) has mounted in the last few decades. The concept of therapeutic advancement consists of a possible application by understanding the toxicity issues and their fate in the living biological system. Carbon based nanomaterials are recently exploited for their unique properties, and their utilization toward biomedical application such as drug delivery system (DDS), tissue regeneration, nonviral immunotherapy, biosensing, bioimaging, etc. is well reported. Despite such a report, it is very much required to understand their toxicity assessment with fate within the human body. The present review assesses the toxic behavior of various carbonaceous materials and the therapeutic advancement in spite of their toxicity issues. Carbon nanostructures (carbon quantum dot, carbon nanotube, fullerene, graphene, carbon nanohorn, carbon nanodiamond, etc.) impart various cellular toxicities, which are based on their geometric structure as well as chemical composition and physicochemical parameters (size, morphology, surface passivation). Moreover, this review also includes an additional section describing various sources of carbon with their preparation and their properties. Regardless of the toxicity barrier, carbon based materials are still ameliorating the therapeutic advancement with respect to various biomedical applications, which are also highlighted in this review along with their use by suppressing their toxic behavior.

Recent studies have shown that certain peptides and small molecules can induce pseudoanaphylaxis reactions by triggering mast cell degranulation (MCD), resulting in the release of vasoactive and proinflammatory mediators. This mechanism can result in severe adverse drug reactions with potentially life-threatening consequences in humans or loss of tolerability in animal studies, representing a considerable challenge in the development of peptide and small-molecule therapeutics. Therefore, early identification of drug candidates with MCD potential is crucial for an efficient Design–Make–Test–Analyze (DMTA) cycle while promoting the 3Rs principle (replacement, reduction, refinement) in animal research. In the present work, we introduce a proactive risk mitigation strategy aimed at evaluating and minimizing the MCD activity of peptide drug candidates. We developed an ex vivo rat peritoneal mast cell degranulation (rMCD) assay to screen and prioritize candidates that do not exhibit rMCD activity during the lead optimization phase. Importantly, structure–activity relationships (SAR) were established by leveraging rMCD data sets which included ∼3000 diverse peptides across 28 internal programs targeting multiple therapeutic areas. Critical physicochemical properties were identified as predictive calculated parameters for rMCD outcomes. Additionally, we developed a directed message passing neural network (D-MPNN) model that combines structural features with calculated and predicted physicochemical properties, demonstrating strong predictive performance for rMCD outcomes. This model facilitates the early prioritization of peptide drug candidates for rMCD assays during the candidate selection phase and accelerates hit-to-lead and lead optimization by identifying peptides within a series that exhibit minimal rMCD liabilities. Notably, the D-MPNN model outperformed traditional in silico property-based calculators in our prospective validation study. Furthermore, to address species-specific SAR, we also established a human MCD (hMCD) assay, revealing an 80% concordance in MCD outcomes between species. This hMCD assay identifies the MCD liabilities of compounds that differ from those in rats, indicating potential risks in humans. This comprehensive in silico and in vitro approach enables drug discovery teams to advance drug candidates that are free from MCD liability in a resource-efficient manner, thereby increasing the likelihood of success in both nonclinical and clinical studies.