Improved Decision Making for Water Lead Testing in U.S. Child Care Facilities Using Machine-Learned Bayesian Networks.

Tap water lead testing programs in the U.S. need improved methods for identifying high-risk facilities to optimize limited resources. In this study, machine-learned Bayesian network (BN) models were used to predict building-wide water lead risk in over 4,000 child care facilities in North Carolina according to maximum and 90th percentile lead levels from water lead concentrations at 22,943 taps. The performance of the BN models was compared to common alternative risk factors, or heuristics, used to inform water lead testing programs among child care facilities including building age, water source, and Head Start program status. The BN models identified a range of variables associated with building-wide water lead, with facilities that serve low-income families, rely on groundwater, and have more taps exhibiting greater risk. Models predicting the probability of a single tap exceeding each target concentration performed better than models predicting facilities with clustered high-risk taps. The BN models' Fß-scores outperformed each of the alternative heuristics by 118-213%. This represents up to a 60% increase in the number of high-risk facilities that could be identified and up to a 49% decrease in the number of samples that would need to be collected by using BN model-informed sampling compared to using simple heuristics. Overall, this study demonstrates the value of machine-learning approaches for identifying high water lead risk that could improve lead testing programs nationwide.

Lead Levels in Tap Water at Licensed North Carolina Child Care Facilities, 2020-2021.

Objectives. To evaluate lead levels in tap water at licensed North Carolina child care facilities. Methods. Between July 2020 and October 2021, we enrolled 4005 facilities in a grant-funded, participatory science testing program. We identified risk factors associated with elevated first-draw lead levels using multiple logistic regression analysis. Results. By sample (n = 22 943), 3% of tap water sources exceeded the 10 parts per billion (ppb) North Carolina hazard level, whereas 25% of tap water sources exceeded 1 ppb, the American Academy of Pediatrics' reference level. By facility, at least 1 tap water source exceeded 1 ppb and 10 ppb at 56% and 12% of facilities, respectively. Well water reliance was the largest risk factor, followed by participation in Head Start programs and building age. We observed large variability between tap water sources within the same facility. Conclusions. Tap water in child care facilities is a potential lead exposure source for children. Given variability among tap water sources, it is imperative to test every source used for drinking and cooking so appropriate action can be taken to protect children's health. (Am J Public Health. 2022;112(S7):S695-S705. https://doi.org/10.2105/AJPH.2022.307003).

IL-25 blockade augments antiviral immunity during respiratory virus infection.

IL-25 is implicated in the pathogenesis of viral asthma exacerbations. However, the effect of IL-25 on antiviral immunity has yet to be elucidated. We observed abundant expression and colocalization of IL-25 and IL-25 receptor at the apical surface of uninfected airway epithelial cells and rhinovirus infection increased IL-25 expression. Analysis of immune transcriptome of rhinovirus-infected differentiated asthmatic bronchial epithelial cells (BECs) treated with an anti-IL-25 monoclonal antibody (LNR125) revealed a re-calibrated response defined by increased type I/III IFN and reduced expression of type-2 immune genes CCL26, IL1RL1 and IL-25 receptor. LNR125 treatment also increased type I/III IFN expression by coronavirus infected BECs. Exogenous IL-25 treatment increased viral load with suppressed innate immunity. In vivo LNR125 treatment reduced IL-25/type 2 cytokine expression and increased IFN-ß expression and reduced lung viral load. We define a new immune-regulatory role for IL-25 that directly inhibits virus induced airway epithelial cell innate anti-viral immunity.

Disparities in well water outreach and assistance offered by local health departments: A North Carolina case study.

Drinking water supplied by private wells is a national concern that would benefit from improved outreach and support to ensure safe drinking water quality. In North Carolina (NC), local health departments (LHDs) have private well programs that enforce statewide well construction standards, offer water testing services, and provide well water outreach and assistance. Programs were evaluated to determine their capacity and capability for well water outreach and assistance and identify differences among programs. All LHDs reported overseeing the construction of new wells as required by law. However, services provided to existing well users were offered infrequently and/or inconsistently offered. Lack of uniformity was observed in the number of LHD staff and their assigned responsibilities; the costs and availability of well water testing; and the comfort of LHD staff communicating with well owners. While the total number of staff was lower in LHDs in rural counties, the number of outreach activities and services offered was typically not related to the number of well users served. Variations in structure and capacity of well programs at LHDs have created unequal access to services and information for well users in NC. This research underscores the need to examine infrastructure that supports the well water community on a national scale.

Supporting the Student's Graduated Independence in Diabetes Care.

The gradual progression to self-management is a critical milestone for children/adolescents with diabetes. This article provides recommendations to facilitate collaboration between the student's family, diabetes healthcare provider, and school nurse to support and implement a plan that enables the child/adolescent to acquire the skills and knowledge necessary to successfully transition to independent management of diabetes.

Subsets of Visceral Adipose Tissue Nuclei with Distinct Levels of 5-Hydroxymethylcytosine.

The reprogramming of cellular memory in specific cell types, and in visceral adipocytes in particular, appears to be a fundamental aspect of obesity and its related negative health outcomes. We explored the hypothesis that adipose tissue contains epigenetically distinct subpopulations of adipocytes that are differentially potentiated to record cellular memories of their environment. Adipocytes are large, fragile, and technically difficult to efficiently isolate and fractionate. We developed fluorescence nuclear cytometry (FNC) and fluorescence activated nuclear sorting (FANS) of cellular nuclei from visceral adipose tissue (VAT) using the levels of the pan-adipocyte protein, peroxisome proliferator-activated receptor gamma-2 (PPARg2), to distinguish classes of PPARg2-Positive (PPARg2-Pos) adipocyte nuclei from PPARg2-Negative (PPARg2-Neg) leukocyte and endothelial cell nuclei. PPARg2-Pos nuclei were 10-fold enriched for most adipocyte marker transcripts relative to PPARg2-Neg nuclei. PPARg2-Pos nuclei showed 2- to 50-fold higher levels of transcripts encoding most of the chromatin-remodeling factors assayed, which regulate the methylation of histones and DNA cytosine (e.g., DNMT1, TET1, TET2, KDM4A, KMT2C, SETDB1, PAXIP1, ARID1A, JMJD6, CARM1, and PRMT5). PPARg2-Pos nuclei were large with decondensed chromatin. TAB-seq demonstrated 5-hydroxymethylcytosine (5hmC) levels were remarkably dynamic in gene bodies of various classes of VAT nuclei, dropping 3.8-fold from the highest quintile of expressed genes to the lowest. In short, VAT-derived adipocytes appear to be more actively remodeling their chromatin than non-adipocytes.

Are children with type 1 diabetes safe at school? Examining parent perceptions.

OBJECTIVE: To describe parent perceptions of children's diabetes care at school including: availability of licensed health professionals; staff training; logistics of provision of care; and occurrence and treatment of hypo- and hyperglycemia; and to examine parents' perceptions of their children's safety and satisfaction in the school environment. RESEARCH DESIGN AND METHODS: A survey was completed by parents of children with type 1 diabetes from permissive (trained, non-medical school personnel permitted to provide diabetes care; N = 237) and non-permissive (only licensed health care professionals permitted to provide diabetes care; N = 198) states. RESULTS: Most parents reported that schools had nurses available for the school day; teachers and coaches should be trained; nurses, children, and parents frequently provided diabetes care; and hypo- and hyperglycemia occurred often. Parents in permissive states perceived children to be as safe and were as satisfied with care as parents in non-permissive states. CONCLUSIONS: Training non-medical staff will probably maximize safety of children with diabetes when a school nurse is not available.

Developmental toxicity of Louisiana crude oil-spiked sediment to zebrafish.

Embryonic exposures to the components of petroleum, including polycyclic aromatic hydrocarbons (PAHs), cause a characteristic suite of developmental defects and cardiotoxicity in a variety of fish species. We exposed zebrafish embryos to reference sediment mixed with laboratory weathered South Louisiana crude oil and to sediment collected from an oiled site in Barataria Bay, Louisiana in December 2010. Laboratory oiled sediment exposures caused a reproducible set of developmental malformations in zebrafish embryos including yolk sac and pericardial edema, craniofacial and spinal defects, and tissue degeneration. Dose-response studies with spiked sediment showed that total polycyclic aromatic hydrocarbons (tPAH) concentrations of 27mg tPAH/kg (dry weight normalized to 1 percent organic carbon [1 percent OC]) caused a significant increase in defects, and concentrations above 78mg tPAH/kg 1 percent OC caused nearly complete embryo mortality. No toxicity was observed in Barataria sediment with 2mg tPAH/kg 1 percent OC. Laboratory aging of spiked sediment at 4°C resulted in a nearly 10-fold decrease in sensitivity over a 40-day period. This study demonstrates oiled sediment as an exposure pathway to fish with dose-dependent effects on embryogenesis that are consistent with PAH mechanisms of developmental toxicity. The results have implications for effects on estuarine fish from oiled coastal areas during the Deepwater Horizon spill.

Augmenting aquatic species sensitivity distributions with interspecies toxicity estimation models.

Species sensitivity distributions (SSDs) are cumulative distribution functions of species toxicity values. The SSD approach is being used increasingly in ecological risk assessment but is often limited by available toxicity data needed for diverse species representation. In the present study, the authors evaluate augmenting aquatic species databases limited to standard test species using toxicity values extrapolated from interspecies correlation estimation (ICE) models for SSD development. The authors compared hazard concentrations at the 5th centile (HC5) of SSDs developed using limited measured data augmented with ICE toxicity values (augmented SSDs) with those estimated using larger measured toxicity datasets of diverse species (reference SSDs). When SSDs had similar species composition to the reference SSDs, 0.76 of the HC5 estimates were closer to the reference HC5; however, the proportion of augmented HC5s that were within 5-fold of the reference HC5s was 0.94, compared with 0.96 when predicted SSDs had random species assemblages. The range of toxicity values among represented species in all SSDs also depended on a chemical's mode of action. Predicted HC5 estimations for acetylcholinesterase inhibitors showed the greatest discrepancies from the reference HC5 when SSDs were limited to commonly tested species. The results of the present study indicate that ICE models used to augment datasets for SSDs do not greatly affect HC5 uncertainty. Uncertainty analysis of risk assessments using SSD hazard concentrations should address species composition, especially for chemicals with known taxa-specific differences in toxicological effects. This article is a US Government work and is in the public domain in the USA.

Prediction of aquatic toxicity mode of action using linear discriminant and random forest models.

The ability to determine the mode of action (MOA) for a diverse group of chemicals is a critical part of ecological risk assessment and chemical regulation. However, existing MOA assignment approaches in ecotoxicology have been limited to a relatively few MOAs, have high uncertainty, or rely on professional judgment. In this study, machine based learning algorithms (linear discriminant analysis and random forest) were used to develop models for assigning aquatic toxicity MOA. These methods were selected since they have been shown to be able to correlate diverse data sets and provide an indication of the most important descriptors. A data set of MOA assignments for 924 chemicals was developed using a combination of high confidence assignments, international consensus classifications, ASTER (ASessment Tools for the Evaluation of Risk) predictions, and weight of evidence professional judgment based an assessment of structure and literature information. The overall data set was randomly divided into a training set (75%) and a validation set (25%) and then used to develop linear discriminant analysis (LDA) and random forest (RF) MOA assignment models. The LDA and RF models had high internal concordance and specificity and were able to produce overall prediction accuracies ranging from 84.5 to 87.7% for the validation set. These results demonstrate that computational chemistry approaches can be used to determine the acute toxicity MOAs across a large range of structures and mechanisms.

Development of aquatic toxicity benchmarks for oil products using species sensitivity distributions.

Determining the sensitivity of a diversity of species to spilled oil and chemically dispersed oil continues to be a significant challenge in spill response and impact assessment. We used standardized tests from the literature to develop species sensitivity distributions (SSDs) of acute aquatic toxicity values for several petroleum products and 2 Corexit oil dispersants. Fifth percentile hazard concentrations (HC5s) were computed from the SSDs and used to assess relative oil product toxicity and in evaluating the feasibility of establishing toxicity benchmarks for a community of species. The sensitivity of mysids (Americamysis bahia) and silversides (Menidia beryllina) were evaluated within the SSDs to determine if these common test species were appropriate surrogates for a broader range of species. In general, SSD development was limited by the availability of acute toxicity values that met standardization criteria for a diversity of species. Pooled SSDs were also developed for crude oil and Corexit dispersants because there was only small variability in the HC5s among the individual oil or dispersant products. The sensitivity of mysids and silversides varied across the oil and dispersant products, with the majority of toxicity values greater than the HC5. Application of SSDs appears to be a reasonable approach to developing oil product toxicity benchmarks, but additional toxicity data are needed for a larger range of species conducted under standardized test conditions.

Evaluation of in silico development of aquatic toxicity species sensitivity distributions.

Determining the sensitivity of a diversity of species to environmental contaminants continues to be a significant challenge in ecological risk assessment because toxicity data are generally limited to a few standard test species. This study assessed whether species sensitivity distributions (SSDs) could be generated with reasonable accuracy using only in silico modeling of toxicity to aquatic organisms. Ten chemicals were selected for evaluation that spanned several modes of actions and chemical classes. Median lethal concentrations (LC50s) were estimated using three internet-based quantitative structure activity relationship (QSAR) tools that employ different computational approaches: ECOSAR (Ecological Structure Activity Relationships), ASTER (Assessment Tools for the Evaluation of Risk), and TEST (Toxicity Estimation Software Tool). Each QSAR estimate was then used as input into the SSD module of the internet-based toxicity estimation program Web-ICE to generate an in silico estimated fifth percentile hazard concentration (HC5) for each of the ten chemicals. The accuracy of the estimated HC5s was determined by comparison to measured HC5s developed from an independent dataset of experimental acute toxicity values for a diversity of aquatic species. Estimated HC5s showed generally poor agreement with measured HC5s determined for all available aquatic species, but showed better agreement when species composition of the chemical specific SSDs were identical. These results indicated that LC50 variability and species composition were large sources of error in estimated HC5s. Additional research is needed to reduce uncertainty in HC5s using only in silico approaches and to develop computational approaches for predicting species sensitivity.

Anti-human embryonic stem cell monoclonal antibody Hesca-2 binds to a glycan epitope commonly found on carcinomas.

Hesca-2, a monoclonal antibody (mAb) IgM raised to the human embryonic stem cell (hESC) line BG-01v, binds with high affinity (nM) to the disaccharide epitope (Galß1-3GlcNAc) on a glycan microarray. This epitope was expressed on pluripotent progenitor hESCs in culture, but not in various differentiated cells derived from hESC based on immunofluorescence microscopy. Hesca-2 stains a limited subset of cells in adult human tissues (eg, esophagus and breast). This mAb also crossreacts in immunofluorescence microscopy studies with several human ovarian cancer cell lines and is cytotoxic to them based on the release of cytosolic enzyme lactate dehydrogenase into the media. Hesca-2 immunohistochemically stained tissue from a number of human tumors, including ovary, breast, colon, and esophageal cancer. These data suggest that Hesca-2 recognizes a surface marker found both in stem cells and certain cancer cells.

Influence of taxonomic relatedness and chemical mode of action in acute interspecies estimation models for aquatic species.

Ecological risks to aquatic organisms are typically assessed using acute toxicity data for relatively few species and with limited understanding of relative species sensitivity. We developed a comprehensive set of interspecies correlation estimation (ICE) models based on acute toxicity data for aquatic organisms and evaluated three key sources of model uncertainty: taxonomic relatedness, chemical mode of action (MOA), and model parameters. Models are least-squares regressions of acute toxicity of surrogate and predicted species. A total of 780 models were derived from acute values for 77 species of aquatic organisms and over 550 chemicals. Cross-validation of models showed that accurate model prediction was greatest for models with surrogate and predicted taxa within the same family (91% of predictions within 5-fold of measured values). Recursive partitioning provided user guidance for selection of robust models using model mean square error and taxonomic relatedness. Models built with a single MOA were more robust than models built using toxicity values with multiple MOAs, and improve predictions among species pairs with large taxonomic distance (e.g., within phylum). These results indicate that between-species toxicity extrapolation can be improved using MOA-based models for less related taxa pairs and for those specific MOAs.