Identification of an adverse outcome pathway (AOP) for chemical-induced craniofacial anomalies using the transgenic zebrafish model

Craniofacial anomalies are one of the most frequent birth defects worldwide and are often caused by genetic and environmental factors such as pharmaceuticals and chemical agents. Although identifying adverse outcome pathways (AOPs) is a central issue for evaluating the teratogenicity, the AOP causing craniofacial anomalies has not been identified. Recently, zebrafish has gained interest as an emerging model for predicting teratogenicity because of high throughput, cost-effectiveness and availability of various tools for examining teratogenic mechanisms. Here, we established zebrafish sox10-EGFP reporter lines to visualize cranial neural crest cells (CNCCs) and have identified the AOPs for craniofacial anomalies. When we exposed the transgenic embryos to teratogens that were reported to cause craniofacial anomalies in mammals, CNCC migration and subsequent morphogenesis of the first pharyngeal arch were impaired at 24 hours post-fertilization. We also found that cell proliferation and apoptosis of the migratory CNCCs were disturbed, which would be key events of the AOP. From these results, we propose that our sox10-EGFP reporter lines serve as a valuable model for detecting craniofacial skeletal abnormalities, from early to late developmental stages. Given that the developmental process of CNCCs around this stage is highly conserved between zebrafish and mammals, our findings can be extrapolated to mammalian craniofacial development and thus help in predicting craniofacial anomalies in human.

Investigating the uncertainty of prediction accuracy for the application of physiologically based pharmacokinetic models to animal-free risk assessment of cosmetic ingredients

Physiologically based pharmacokinetic (PBPK) models are considered useful tools in animal-free risk assessment. To utilize PBPK models for risk assessment, it is necessary to compare their reliability with in vivo data. However, obtaining in vivo pharmacokinetics data for cosmetic ingredients is difficult, complicating the utilization of PBPK models for risk assessment. In this study, to utilize PBPK models for risk assessment without accuracy evaluation, we proposed a novel concept-the modeling uncertainty factor (MUF). By calculating the prediction accuracy for 150 compounds, we established that using in vitro data for metabolism-related parameters and limiting the applicability domain increase the prediction accuracy of a PBPK model. Based on the 97.5th percentile of prediction accuracy, MUF was defined at 10 for the area under the plasma concentration curve and 6 for C_max. A case study on animal-free risk assessment was conducted for bisphenol A using these MUFs. As this study was conducted mainly on pharmaceuticals, further investigation using cosmetic ingredients is pivotal. However, since internal exposure is essential in realizing animal-free risk assessment, our concept will serve as a useful tool to predict plasma concentrations without using in vivo data.

RAID: Regression Analysis–Based Inductive DNA Microarray for Precise Read-Across

Chemical structure-based read-across represents a promising method for chemical toxicity evaluation without the need for animal testing; however, a chemical structure is not necessarily related to toxicity. Therefore, in vitro studies were often used for read-across reliability refinement; however, their external validity has been hindered by the gap between in vitro and in vivo conditions. Thus, we developed a virtual DNA microarray, regression analysis–based inductive DNA microarray (RAID), which quantitatively predicts in vivo gene expression profiles based on the chemical structure and/or in vitro transcriptome data. For each gene, elastic-net models were constructed using chemical descriptors and in vitro transcriptome data to predict in vivo data from in vitro data (in vitro to in vivo extrapolation; IVIVE). In feature selection, useful genes for assessing the quantitative structure–activity relationship (QSAR) and IVIVE were identified. Predicted transcriptome data derived from the RAID system reflected the in vivo gene expression profiles of characteristic hepatotoxic substances. Moreover, gene ontology and pathway analysis indicated that nuclear receptor-mediated xenobiotic response and metabolic activation are related to these gene expressions. The identified IVIVE-related genes were associated with fatty acid, xenobiotic, and drug metabolisms, indicating that in vitro studies were effective in evaluating these key events. Furthermore, validation studies revealed that chemical substances associated with these key events could be detected as hepatotoxic biosimilar substances. These results indicated that the RAID system could represent an alternative screening test for a repeated-dose toxicity test and toxicogenomics analyses. Our technology provides a critical solution for IVIVE-based read-across by considering the mode of action and chemical structures.

4″-Sulfation Is the Major Metabolic Pathway of Epigallocatechin-3-gallate in Humans: Characterization of Metabolites, Enzymatic Analysis, and Pharmacokinetic Profiling

Epigallocatechin-3-gallate (EGCG), a major green tea polyphenol, has beneficial effects on human health. This study aimed to elucidate the detailed EGCG sulfation process to better understand its phase II metabolism, a process required to maximize its health benefits. Results show that kinetic activity of sulfation in the human liver and intestinal cytosol is 2-fold and 60- to 300-fold higher than that of methylation and glucuronidation, respectively, suggesting sulfation as the key metabolic pathway. Moreover, SULT1A1 and SULT1A3 are responsible for sulfation in the liver and intestine, respectively. Additionally, our human ingestion study revealed that the concentration of EGCG-4″-sulfate in human plasma (C_max: 177.9 nmol·L^-1, AUC: 715.2 nmol·h·L^-1) is equivalent to free EGCG (C_max: 233.5 nmol·L^-1, AUC: 664.1 nmol·h·L^-1), suggesting that EGCG-4″-sulfate is the key metabolite. These findings indicate that sulfation is a crucial factor for improving EGCG bioavailability, while also advancing the understanding of the bioactivity and toxicity of EGCG.

Persistent influence of precession on northern ice sheet variability since the early Pleistocene

Prior to ~1 million years ago (Ma), variations in global ice volume were dominated by changes in obliquity; however, the role of precession remains unresolved. Using a record of North Atlantic ice rafting spanning the past 1.7 million years, we find that the onset of ice rafting within a given glacial cycle (reflecting ice sheet expansion) consistently occurred during times of decreasing obliquity whereas mass ice wasting (ablation) events were consistently tied to minima in precession. Furthermore, our results suggest that the ubiquitous association between precession-driven mass wasting events and glacial termination is a distinct feature of the mid to late Pleistocene. Before then (increasing), obliquity alone was sufficient to end a glacial cycle, before losing its dominant grip on deglaciation with the southward extension of Northern Hemisphere ice sheets since ~1 Ma.

Comparison of toxicological effects and exposure levels between triclosan and its structurally similar chemicals using in vitro tests for read-across case study

Read-across based on structural and biological similarities is expected to be a promising alternative method for assessing systemic toxicity. A concrete strategy for quantitative chemical risk assessment would be to stack read-across case studies and extract key considerations from them. Thus, we developed a read-across case study by comparing the toxicological effects based on adverse outcome pathways and exposure levels of different structurally similar chemicals for a target organ. In this study, we selected the hepatotoxicity of triclosan and its structurally similar chemicals including diclosan and 1-chloro-3-(4-chlorophenoxy)benzene. The results of in vitro toxicogenomics showed that disorders of cholesterol synthesis were commonly detected with both triclosan and diclosan. The decrease in hepatocellular cholesterol levels was similar in the cells treated with triclosan and diclosan. Furthermore, the exposure levels of triclosan and diclosan for the liver were similar. Collectively, these results suggest that triclosan and diclosan show similar toxicological effects and severity of hepatotoxicity. Considering the existing repeated dose toxicity data, our prediction results are reasonable regarding the toxicological effect and its severity. Thus, the present study demonstrated the usability of comparing toxicological effects and exposure levels using read-across for quantitative chemical risk assessment.

Effects of internal hydrophilic groups of a newly developed sustainable anionic surfactant on biodegradability and ecotoxicity

Recently, a new sustainable anionic surfactant called bio-based internal olefin sulfonate (Bio IOS) has been developed. This surfactant enables excellent water solubility and high surface activity. It has a unique structure of long hydrophobic alkyl chains (C16 to C18) with two types of hydrophilic groups in its midsection, which distinguish it from other conventional anionic surfactants. However, the effects of the specific structural features of the surfactant on its environmental properties and the consequent effects on the environment remain unclear. In this study, we investigated the environmental fate and ecotoxicity of Bio IOS and the effects of the types and positions of hydrophilic groups on biodegradability and ecotoxicity. Biodegradation studies demonstrated that Bio IOS was readily biodegradable with >99.5% removal in wastewater treatment activated sludge (test concentration: 1 mg/L) and a fast half-life of 5.8 h in river water (test concentration: 10 μg/L); the excellent biodegradability was likely due to the high water solubility attributed to the internal hydrophilic groups. Meanwhile, moderately toxic effects were observed, whereby the 50% lethal and effect concentrations of the three freshwater species were above 1 mg/L. Ecotoxicity studies with different types and positions of hydrophilic groups revealed that hydroxyalkane sulfonate was less toxic and that toxicity was reduced in the presence of more internally located hydrophilic groups. These findings suggest that the hydroxyl group and the internal positions of hydrophilic groups that constitute the molecular configuration resembling two separate shorter alkyl chains may reduce the adverse effects on organisms despite the long alkyl chains.

Risk factors for cefazolin-resistant febrile urinary tract infection in children

BACKGROUND

Febrile urinary tract infection (fUTI) is a common bacterial infection among children. This study investigated the risk factors for fUTI caused by cefazolin-resistant bacteria in children.

METHODS

The medical records of patients with fUTI hospitalized between April 2014 and March 2020 were retrospectively analyzed. The patients were divided into two groups based on the cefazolin susceptibility of the infection-causing bacteria: cefazolin-resistant and cefazolin-susceptible groups.

RESULTS

The records of 80 patients were evaluated. The median age was 5.0 months (range 0.5-119.4 months). Cefazolin-susceptible bacteria were detected in 60 patients (75.0%). Significant differences were noted between the cefazolin-resistant and cefazolin-susceptible groups regarding UTI-related antimicrobial prophylaxis and recurrence of UTI within 3 months (P = 0.0318 and P = 0.00876, respectively). However, no significant differences were observed between these two groups regarding renal anomalies, or UTI history. Logistic regression analysis revealed that the recurrence of UTI within 3 months was an independent, significant risk factor for cefazolin-resistant fUTI (odds ratio 3.81, 95% confidence interval: 1.07-13.5, P = 0.0388). Six patients who were empirically treated with antibiotics ineffective against the infection-causing bacteria recovered from fever before these antibiotics were switched to those effective against the infection-causing bacteria.

CONCLUSIONS

In children, a recurrence of UTI within 3 months is a risk factor for fUTI caused by cefazolin-resistant bacteria. Recognizing these risk factors before initiating fUTI treatment in children may support treatment with narrower-spectrum antibiotics, such as first-generation cephalosporins (e.g., cefazolin).

Single-strand specific nuclease enhances accuracy of error-corrected sequencing and improves rare mutation-detection sensitivity

Error-corrected sequences (ECSs) that utilize double-stranded DNA sequences are useful in detecting mutagen-induced mutations. However, relatively higher frequencies of G:C > T:A (1 × 10⁻⁷ bp) and G:C > C:G (2 × 10⁻⁷ bp) errors decrease the accuracy of detection of rare G:C mutations (approximately 10⁻⁷ bp). Oxidized guanines in single-strand (SS) overhangs generated after shearing could serve as the source of these errors. To remove these errors, we first computationally discarded up to 20 read bases corresponding to the ends of the DNA fragments. Error frequencies decreased proportionately with trimming length; however, the results indicated that they were not sufficiently removed. To efficiently remove SS overhangs, we evaluated three mechanistically distinct SS-specific nucleases (S1 Nuclease, mung bean nuclease, and RecJf exonuclease) and found that they were more efficient than computational trimming. Consequently, we established Jade-Seq™, an ECS protocol with S1 Nuclease treatment, which reduced G:C > T:A and G:C > C:G errors to 0.50 × 10⁻⁷ bp and 0.12 × 10⁻⁷ bp, respectively. This was probably because S1 Nuclease removed SS regions, such as gaps and nicks, depending on its wide substrate specificity. Subsequently, we evaluated the mutation-detection sensitivity of Jade-Seq™ using DNA samples from TA100 cells exposed to 3-methylcholanthrene and 7,12-dimethylbenz[a]anthracene, which contained the rare G:C > T:A mutation (i.e., 2 × 10⁻⁷ bp). Fold changes of G:C > T:A compared to the vehicle control were 1.2- and 1.3-times higher than those of samples without S1 Nuclease treatment, respectively. These findings indicate the potential of Jade-Seq™ for detecting rare mutations and determining the mutagenicity of environmental mutagens.

In silico systems for predicting chemical-induced side effects using known and potential chemical protein interactions, enabling mechanism estimation

In silico models for predicting chemical-induced side effects have become increasingly important for the development of pharmaceuticals and functional food products. However, existing predictive models have difficulty in estimating the mechanisms of side effects in terms of molecular targets or they do not cover the wide range of pharmacological targets. In the present study, we constructed novel in silico models to predict chemical-induced side effects and estimate the underlying mechanisms with high general versatility by integrating the comprehensive prediction of potential chemical-protein interactions (CPIs) with machine learning. First, the potential CPIs were comprehensively estimated by chemometrics based on the known CPI data (1,179,848 interactions involving 3,905 proteins and 824,143 chemicals). Second, the predictive models for 61 side effects in the cardiovascular system (CVS), gastrointestinal system (GIS), and central nervous system (CNS) were constructed by sparsity-induced classifiers based on the known and potential CPI data. The cross validation experiments showed that the proposed CPI-based models had a higher or comparable performance than the traditional chemical structure-based models. Moreover, our enrichment analysis indicated that the highly weighted proteins derived from predictive models could be involved in the corresponding functions of the side effects. For example, in CVS, the carcinogenesis-related pathways (e.g., prostate cancer, PI3K-Akt signal pathway), which were recently reported to be involved in cardiovascular side effects, were enriched. Therefore, our predictive models are biologically valid and would be useful for predicting side effects and novel potential underlying mechanisms of chemical-induced side effects.

P5750Manipulation strategy for crossing coronary chronic total occlusion: an update from the Japanese CTO-PCI expert registry

Background

The percutaneous coronary intervention (PCI) strategy for chronic total occlusion (CTO) based on the guidewire manipulation time remains infrequent.

Purpose

We aimed to assess CTO-PCI strategy on the basis of guidewire manipulation time.

Methods

A total of 5843 patients undergoing CTO PCI between January 2014 and December 2017 and enrolled in the Japanese CTO-PCI expert registry were assessed. Their CTO-PCI strategies, procedural outcomes, and guidewire manipulation time were analysed.

Results

The primary retrograde approach was performed on 1562 patients (26.7%). The overall guidewire and technical success rates were 92.8% and 90.6%, respectively. Median guidewire manipulation time of guidewire success and failure were 56 (interquatile range [IQR]: 22 to 111) min and 176 (IQR: 130 to 229) min, respectively. The average Japanese CTO score of the primary antegrade approach with the antegrade alone, the primary antegrade approach with the retrograde approach, and the primary retrograde approach were 1.7±1.1, 2.1±1.2, and 2.3±1.1, respectively (p<0.001). Median successful guidewire crossing time of single wiring in the antegrade alone was 23 (IQR: 11 to 44) min, and that of the primary retrograde approach was significantly shorter than that of the primary antegrade approach with the retrograde approach (107 [IQR: 70 to 161] min vs. 126 [IQR: 87 to 174] min; p<0.001). Reattempt, CTO length ≥20 mm, and proximal cap ambiguity were the predictors of guidewire failure in the primary antegrade approach with antegrade alone, but were not those in the primary retrograde approach.

Conclusions

Although successful guidewire crossing time of the primary antegrade approach with the antegrade alone is short, that of the primary retrograde approach can be shorter than that of the primary antegrade approach with the retrograde approach. Choosing an appropriate CTO-PCI strategy leads to shortening of successful guidewire crossing time.

Validation of AIST-SHANEL Model Based on Spatiotemporally Extensive Monitoring Data of Linear Alkylbenzene Sulfonate in Japan: Toward a Better Strategy on Deriving Predicted Environmental Concentrations

Strategies for deriving predicted environmental concentrations (PECs) using environmental exposure models have become increasingly important in the environmental risk assessment of chemical substances. However, many strategies are not fully developed owing to uncertainties in the derivation of PECs across spatially extensive areas. Here, we used 3-year environmental monitoring data (river: 11 702 points; lake: 1867 points; sea: 12 points) on linear alkylbenzene sulfonate (LAS) in Japan to evaluate the ability of the National Institute of Advanced Industrial Science and Technology (AIST)-Standardized Hydrology-Based Assessment Tool for the Chemical Exposure Load (SHANEL) model developed to predict chemical concentrations in major Japanese rivers. The results indicate that the estimation ability of the AIST-SHANEL model conforms more closely to the actual measured values in rivers than it does for lakes and seas (correlation coefficient: 0.46; proportion within the 10× factor range: 82%). In addition, the 95th percentile, 90th percentile, 50th percentile, and mean values of the distributions of the measured values (14 µg/L, 8.2 µg/L, 0.88 µg/L, and 3.4 µg/L, respectively) and estimated values (19 µg/L, 13 µg/L, 1.4 µg/L, and 4.2 µg/L, respectively) showed high concordance. The results suggest that AIST-SHANEL may be useful in estimating summary statistics (e.g., 95th and 90th percentiles) of chemical concentrations in major rivers throughout Japan. Given its practical use and high accuracy, these environmental risk assessments are suitable for a wide range of regions and can be conducted using representative estimated values, such as the 95th percentile. Integr Environ Assess Manag 2019;15:750-759. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

A decision tree-based integrated testing strategy for tailor-made carcinogenicity evaluation of test substances using genotoxicity test results and chemical spaces

Genotoxicity evaluation has been widely used to estimate the carcinogenicity of test substances during safety evaluation. However, the latest strategies using genotoxicity tests give more weight to sensitivity; therefore, their accuracy has been very low. For precise carcinogenicity evaluation, we attempted to establish an integrated testing strategy for the tailor-made carcinogenicity evaluation of test materials, considering the relationships among genotoxicity test results (Ames, in vitro mammalian genotoxicity and in vivo micronucleus), carcinogenicity test results and chemical properties (molecular weight, logKow and 179 organic functional groups). By analyzing the toxicological information and chemical properties of 230 chemicals, including 184 carcinogens in the Carcinogenicity Genotoxicity eXperience database, a decision tree for carcinogenicity evaluation was optimised statistically. A decision forest model was generated using a machine-learning method-random forest-which comprises thousands of decision trees. As a result, balanced accuracies in cross-validation of the optimised decision tree and decision forest model, considering chemical space (71.5% and 75.5%, respectively), were higher than balanced accuracy of an example regulatory decision tree (54.1%). Moreover, the statistical optimisation of tree-based models revealed significant organic functional groups that would cause false prediction in standard genotoxicity tests and non-genotoxic carcinogenicity (e.g., organic amide and thioamide, saturated heterocyclic fragment and aryl halide). In vitro genotoxicity tests were the most important parameters in all models, even when in silico parameters were integrated. Although external validation is required, the findings of the integrated testing strategies established herein will contribute to precise carcinogenicity evaluation and to determine new mechanistic hypotheses of carcinogenicity.