Characterizing Chemical Exposure Trends from NHANES Urinary Biomonitoring Data.

BACKGROUND: Xenobiotic metabolites are widely present in human urine and can indicate recent exposure to environmental chemicals. Proper inference of which chemicals contribute to these metabolites can inform human exposure and risk. Furthermore, longitudinal biomonitoring studies provide insight into how chemical exposures change over time. OBJECTIVES: We constructed an exposure landscape for as many human-exposure relevant chemicals over as large a time span as possible to characterize exposure trends across demographic groups and chemical types. METHODS: We analyzed urine data of nine 2-y cohorts (1999-2016) from the National Health and Nutrition Examination Survey (NHANES). Chemical daily intake rates (in milligrams per kilogram bodyweight per day) were inferred, using the R package bayesmarker, from metabolite concentrations in each cohort individually to identify exposure trends. Trends for metabolites and parents were clustered to find chemicals with similar exposure patterns. Exposure variation by age, gender, and body mass index were also assessed. RESULTS: Intake rates for 179 parent chemicals were inferred from 151 metabolites (96 measured in five or more cohorts). Seventeen metabolites and 44 parent chemicals exhibited fold-changes ≥10 between any two cohorts (deltamethrin, di-n-octyl phthalate, and di-isononyl phthalate had the greatest exposure increases). Di-2-ethylhexyl phthalate intake began decreasing in 2007, whereas both di-isobutyl and di-isononyl phthalate began increasing shortly before. Intake for four parabens was markedly higher in females, especially reproductive-age females, compared with males and children. Cadmium and arsenobetaine exhibited higher exposure for individuals >65 years of age and lower for individuals <20 years of age. DISCUSSION: With appropriate analysis, NHANES indicates trends in chemical exposures over the past two decades. Decreases in exposure are observable as the result of regulatory action, with some being accompanied by increases in replacement chemicals. Age- and gender-specific variations in exposure were observed for multiple chemicals. Continued estimation of demographic-specific exposures is needed to both monitor and identify potential vulnerable populations. https://doi.org/10.1289/EHP12188.

SLIViT: a general AI framework for clinical-feature diagnosis from limited 3D biomedical-imaging data.

We present SLIViT, a deep-learning framework that accurately measures disease-related risk factors in volumetric biomedical imaging, such as magnetic resonance imaging (MRI) scans, optical coherence tomography (OCT) scans, and ultrasound videos. To evaluate SLIViT, we applied it to five different datasets of these three different data modalities tackling seven learning tasks (including both classification and regression) and found that it consistently and significantly outperforms domain-specific state-of-the-art models, typically improving performance (ROC AUC or correlation) by 0.1-0.4. Notably, compared to existing approaches, SLIViT can be applied even when only a small number of annotated training samples is available, which is often a constraint in medical applications. When trained on less than 700 annotated volumes, SLIViT obtained accuracy comparable to trained clinical specialists while reducing annotation time by a factor of 5,000 demonstrating its utility to automate and expedite ongoing research and other practical clinical scenarios.

Adopting duplex sequencing technology for genetic toxicity testing: A proof-of-concept mutagenesis experiment with N-ethyl-N-nitrosourea (ENU)-exposed rats.

Duplex sequencing (DS) is an error-corrected next-generation sequencing method in which molecular barcodes informatically link PCR-copies back to their source DNA strands, enabling computational removal of errors in consensus sequences. The resulting background of less than one artifactual mutation per 107 nucleotides allows for direct detection of somatic mutations. TwinStrand Biosciences, Inc. has developed a DS-based mutagenesis assay to sample the rat genome, which can be applied to genetic toxicity testing. To evaluate this assay for early detection of mutagenesis, a time-course study was conducted using male Hsd:Sprague Dawley SD rats (3 per group) administered a single dose of 40 mg/kg N-ethyl-N-nitrosourea (ENU) via gavage, with mutation frequency (MF) and spectrum analyzed in stomach, bone marrow, blood, and liver tissues at 3 h, 24 h, 7 d, and 28 d post-exposure. Significant increases in MF were observed in ENU-exposed rats as early as 24 h for stomach (site of contact) and bone marrow (a highly proliferative tissue) and at 7 d for liver and blood. The canonical, mutational signature of ENU was established by 7 d post-exposure in all four tissues. Interlaboratory analysis of a subset of samples from different tissues and time points demonstrated remarkable reproducibility for both MF and spectrum. These results demonstrate that MF and spectrum can be evaluated successfully by directly sequencing targeted regions of DNA obtained from various tissues⁠, a considerable advancement compared to currently used in vivo gene mutation assays.

A database of human predictive patch test data for skin sensitization.

Critical to the evaluation of non-animal tests are reference data with which to assess their relevance. Animal data are typically used because they are generally standardized and available. However, when regulatory agencies aim to protect human health, human reference data provide the benefit of not having to account for possible interspecies variability. To support the evaluation of non-animal approaches for skin sensitization assessment, we collected data from 2277 human predictive patch tests (HPPTs), i.e., human repeat insult patch tests and human maximization tests, for skin sensitization from 1555 publications. We recorded protocol elements and positive or negative outcomes, developed a scoring system to evaluate each test for reliability, and calculated traditional and non-traditional dose metrics. We also traced each test result back to its original report to remove duplicates. The resulting database, which contains information for 1366 unique substances, was characterized for physicochemical properties, chemical structure categories, and protein binding mechanisms. This database is publicly available on the National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods website and in the Integrated Chemical Environment to serve as a resource for additional evaluation of alternative methods and development of new approach methodologies for skin sensitization assessments.

Adopting Duplex Sequencing™ Technology for Genetic Toxicity Testing: A Proof-of-Concept Mutagenesis Experiment with N-Ethyl-N-Nitrosourea (ENU)-Exposed Rats.

Duplex sequencing (DuplexSeq) is an error-corrected next-generation sequencing (ecNGS) method in which molecular barcodes informatically link PCR-copies back to their source DNA strands, enabling computational removal of errors by comparing grouped strand sequencing reads. The resulting background of less than one artifactual mutation per 10 7 nucleotides allows for direct detection of somatic mutations. TwinStrand Biosciences, Inc. has developed a DuplexSeq-based mutagenesis assay to sample the rat genome, which can be applied to genetic toxicity testing. To evaluate this assay for early detection of mutagenesis, a time-course study was conducted using male Hsd:Sprague Dawley SD rats (3 per group) administered a single dose of 40 mg/kg N-ethyl-N-nitrosourea (ENU) via gavage, with mutation frequency (MF) and spectrum analyzed in stomach, bone marrow, blood, and liver tissues at 3 h, 24 h, 7 d, and 28 d post-exposure. Significant increases in MF were observed in ENU-exposed rats as early as 24 h for stomach (site of contact) and bone marrow (a highly proliferative tissue) and at 7 d for liver and blood. The canonical, mutational signature of ENU was established by 7 d post-exposure in all four tissues. Interlaboratory analysis of a subset of samples from different tissues and time points demonstrated remarkable reproducibility for both MF and spectrum. These results demonstrate that MF and spectrum can be evaluated successfully by directly sequencing targeted regions of DNA obtained from various tissues, a considerable advancement compared to currently used in vivo gene mutation assays. HIGHLIGHTS: DuplexSeq is an ultra-accurate NGS technology that directly quantifies mutationsENU-dependent mutagenesis was detected 24 h post-exposure in proliferative tissuesMultiple tissues exhibited the canonical ENU mutation spectrum 7 d after exposureResults obtained with DuplexSeq were highly concordant between laboratoriesThe Rat-50 Mutagenesis Assay is promising for applications in genetic toxicology.

Bayesian inference of chemical exposures from NHANES urine biomonitoring data.

BACKGROUND: Knowing which environmental chemicals contribute to metabolites observed in humans is necessary for meaningful estimates of exposure and risk from biomonitoring data. OBJECTIVE: Employ a modeling approach that combines biomonitoring data with chemical metabolism information to produce chemical exposure intake rate estimates with well-quantified uncertainty. METHODS: Bayesian methodology was used to infer ranges of exposure for parent chemicals of biomarkers measured in urine samples from the U.S population by the National Health and Nutrition Examination Survey (NHANES). Metabolites were probabilistically linked to parent chemicals using the NHANES reports and text mining of PubMed abstracts. RESULTS: Chemical exposures were estimated for various population groups and translated to risk-based prioritization using toxicokinetic (TK) modeling and experimental data. Exposure estimates were investigated more closely for children aged 3 to 5 years, a population group that debuted with the 2015-2016 NHANES cohort. SIGNIFICANCE: The methods described here have been compiled into an R package, bayesmarker, and made publicly available on GitHub. These inferred exposures, when coupled with predicted toxic doses via high throughput TK, can help aid in the identification of public health priority chemicals via risk-based bioactivity-to-exposure ratios.

Goal Achievement and Goal-Related Cognitions in Behavioral Activation Treatment for Depression.

This study investigates the extent to which achieving goals during behavioral activation (BA) treatment predicts depressive symptom improvement, and whether goal-related cognitions predict goal achievement or treatment response. Patients (n = 110, mean age 37.6, 54% female) received low-intensity cognitive behavioral therapy for depression, which included setting up to three behavioral goals in each of three BA-focused sessions (i.e., 9 goals per patient). Patients completed items from the Self-Regulation Skills Battery to assess goal-related cognitions and goal achievement for these goals, and depressive symptoms were assessed weekly with the PHQ-9. Multilevel models investigated the relationships between goal-related cognitions, goal achievement and depressive symptoms. Depressive symptoms improved curve-linearly during treatment (B = 0.12, p < .001), but were not predicted by contemporaneous or time-lagged goal achievement. While cumulative goal achievement predicted end-of-treatment depressive symptoms (r = -.23; p < .01), this relationship became nonsignificant after controlling for depressive symptoms at baseline. Readiness, planning and action control predicted greater goal achievement, whereas greater goal ownership predicted less goal achievement (all p < .05). Motivation and outcome expectancy were related to subsequent, but not contemporaneous, improvements in depressive symptoms (all p < .05). This study indicates the importance of goal-related cognitions in BA treatments, and future research should investigate potential moderators of the relationships between goal-related cognitions, goal achievement, and improvements in depressive symptoms.

Expression and purification of a single-chain Type IV restriction enzyme Eco94GmrSD and determination of its substrate preference.

The first reported Type IV restriction endonuclease (REase) GmrSD consists of GmrS and GmrD subunits. In most bacteria, however, the gmrS and gmrD genes are fused together to encode a single-chain protein. The fused coding sequence for ECSTEC94C_1402 from E. coli strain STEC_94C was expressed in T7 Express. The protein designated as Eco94GmrSD displays modification-dependent ATP-stimulated REase activity on T4 DNA with glucosyl-5-hydroxymethyl-cytosines (glc-5hmC) and T4gt DNA with 5-hydroxymethyl-cytosines (5hmC). A C-terminal 6xHis-tagged protein was purified by two-column chromatography. The enzyme is active in Mg(2+) and Mn(2+) buffer. It prefers to cleave large glc-5hmC- or 5hmC-modified DNA. In phage restriction assays, Eco94GmrSD weakly restricted T4 and T4gt, whereas T4 IPI*-deficient phage (Δip1) were restricted more than 10(6)-fold, consistent with IPI* protection of E. coli DH10B from lethal expression of the closely homologous E. coli CT596 GmrSD. Eco94GmrSD is proposed to belong to the His-Asn-His (HNH)-nuclease family by the identification of a putative C-terminal REase catalytic site D507-H508-N522. Supporting this, GmrSD variants D507A, H508A, and N522A displayed no endonuclease activity. The presence of a large number of fused GmrSD homologs suggests that GmrSD is an effective phage exclusion protein that provides a mechanism to thwart T-even phage infection.