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The National Center for Environmental Health (NCEH), part of the Centers for Disease Control and Prevention (CDC), and the Agency for Toxic Substances and Disease Registry (ATSDR) support and conduct research advancing national, state, and local public health response to per- and polyfluoroalkyl substances (PFAS). PFAS are a group of manufactured chemicals used in industry and consumer products that persist in the environment. Given the growing evidence linking PFAS with adverse health effects in humans, NCEH and ATSDR developed a public health research framework to capture the broad range of PFAS research activities being conducted and supported by the agency to determine future research priorities and identify opportunities for interagency collaboration. The framework was conceptualized via a multidisciplinary visioning process designed to identify compelling questions and research activities that span five scientific domains: toxicology, exposure, human health, public health action, and cross-cutting priorities. This paper presents a framework, compelling questions and research activities to help NCEH and ATSDR advance scientific discovery in partnership with federal, state, and local stakeholders as part of a comprehensive public health response to PFAS contamination.

Per- and polyfluoroalkyl substances (PFAS) are environmental contaminants that have received significant public attention. PFAS are a large group of human-made chemicals that have been used in industry and consumer products worldwide since the 1950s. Human exposure to PFAS is a growing public health concern. Studies suggest that exposure to PFAS may increase the risk of some cancers and have negative health impacts on the endocrine, metabolic, and immune systems. Federal and state health partners are investigating the exposure to and possible health effects associated with PFAS. Government agencies can observe social media discourse on PFAS to better understand public concerns and develop targeted communication and outreach efforts. The primary objective of this study is to understand how social media is used to share, disseminate, and engage in public discussions of PFAS-related information in the United States. We investigated PFAS-related content across 2 social media platforms between May 1, 2017, and April 30, 2019, to identify how social media is used in the United States to seek and disseminate PFAS-related information. Our key variable of interest was posts that mentioned \"PFAS,\" \"PFOA,\" \"PFOS,\" and their hashtag variations across social media platforms. Additional variables included post type, time, PFAS event, and geographic location. We examined term use and post type differences across platforms. We used descriptive statistics and regression analysis to assess the incidence of PFAS discussions and to identify the date, event, and geographic patterns. We qualitatively analyzed social media content to determine the most prevalent themes discussed on social media platforms. Our analysis revealed that Twitter had a significantly greater volume of PFAS-related posts compared with Reddit (98,264 vs 3126 posts). PFAS-related social media posts increased by 670% over 2 years, indicating a marked increase in social media users' interest in and awareness of PFAS. Active engagement varied across platforms, with Reddit posts demonstrating more in-depth discussions compared with passive likes and reposts among Twitter users. Spikes in PFAS discussions were evident and connected to the discovery of contamination events, media coverage, and scientific publications. Thematic analysis revealed that social media users see PFAS as a significant public health concern and seek a trusted source of information about PFAS-related public health efforts. The analysis identified a prevalent theme-on social media, PFAS are perceived as an immediate public health concern, which demonstrates a growing sense of urgency to understand this emerging contaminant and its potential health impacts. Government agencies can continue using social media research to better understand the changing community sentiment on PFAS and disseminate targeted information and then use social media as a forum for dispelling misinformation, communicating scientific findings, and providing resources for relevant public health services.

Individuals across their lifespan may experience hearing loss from medications or chemicals, prompting concern about ototoxic environmental exposures. This study applies computational modeling as a screening-level hazard identification and chemical prioritization approach and is not intended to constitute a human health risk assessment or to estimate exposure- or dose-dependent ototoxic risk. We evaluated in silico drug-induced ototoxicity models on 80 environmental chemicals, excluding 4 with known ototoxicity, and analyzed 76 chemicals using fingerprinting, similarity assessment, and machine learning classification. We compared predicted environmental ototoxicants with ototoxic drugs, paired select polychlorinated biphenyls with the antineoplastic drug mitotane, and used PCB 177 as a case study to construct an ototoxicity pathway. A systems biology framework predicted and compared molecular targets of mitotane and PCB 177 to generate a network-level mechanism. The consensus model (accuracy 0.95 test; 0.90 validation) identified 18 of 76 chemicals as potential ototoxicants within acceptable confidence ranges. Mitotane and PCB 177 were both predicted to disrupt thyroid-stimulating hormone receptor signaling, suggesting thyroid-mediated pathways may contribute to auditory harm; additional targets included AhR, transthyretin, and PXR. Findings indicate overlapping mechanisms involving metabolic, cellular, and inflammatory processes. This work shows that integrated computational modeling can support virtual screening and prioritization for chemical and drug ototoxicity risk assessment.

Endocrine-Disrupting Chemicals (EDCs) disrupt thyroid hormone (TH) synthesis, transport, metabolism, and action, thereby perturbing systemic endocrine homeostasis. Transthyretin (TTR) is a key TH transport protein that regulates circulating hormone distribution and tissue availability, particularly during critical developmental windows. Chemical interference with TTR-binding may alter TH bioavailability and represent a transport-mediated molecular initiating event within thyroid-axis perturbation. Despite widespread exposure, many thyroidal EDCs remain unidentified, and their health effects are difficult to assess due to multiple simultaneous exposures. To support endocrine hazard identification and chemical prioritization within risk assessment frameworks, we developed machine learning-based QSAR models during the Tox24 challenge, using a dataset of 1512 chemicals to predict TTR-binding affinity. Of these, 67% were used for training, 13% for testing, and 20% for validation. Molecular descriptors were selected by first removing highly correlated features and then ranking the remaining descriptors using mutual information regression. The leverage approach was applied to define the models’ applicability domain (AD). Five machine learning algorithms, including gradient boosting regressor (GBR), Random Forest, Lasso Regression, Support Vector Machine (SVM), and regularized SVM models, were developed. The GBR model demonstrated the best overall performance. This model achieved an R2 of 0.89 on the training set, 0.58 on the test set, and 0.55 on the validation set. The molecular descriptor analysis highlights hydrophobicity, steric effects, branching, connectivity, and ionization/electronic effects as the mechanistic basis for TTR disruption and stabilization, providing structural insight into features associated with thyroid hormone displacement. The AD analysis indicated that 97.5% of the test set and 96.0% of the validation set fell within the reliable descriptor space. Importantly, these predictions extend beyond model benchmarking by informing weight-of-evidence evaluations of thyroid-axis perturbation and supporting the prioritization of chemicals for targeted testing within non-animal new approach methodologies. Overall, this work highlights the application of in silico approaches for screening EDCs, supporting the prioritization and identification of potentially harmful chemicals.

The prevalence of plastics in the environment raises concerns about their complex and poorly understood effects on human health. Research continues to uncover more sources of exposure and wider ranges of plastics within the body. Adverse health effects have been observed in animals, but their relevance to humans remains unclear. To address the growing need for reliable toxicity assessment resources and tools to aid in the synthesis of findings and the identification of data gaps and needs, we have developed a data visualization tool to provide streamlined access to the evaluated data on the chemical impacts of plastics on human health. The Plastics-Related Toxicology Profiles Tool uses Tableau Public to organize the extracted chemical-specific information from ATSDR Toxicological Profiles, the United Nations Environmental Program’s 2023 Chemicals in Plastics Technical Report, and a literature review of relevant research in Google Scholar and PubMed. The tool organizes extracted data from 98 ATSDR Toxicological Profiles representing over 476 substances related to plastics production in 16 tabulated health outcome categories associated with plastics exposure. The chemicals are organized into four categories based on their role in plastics manufacturing. The top four health endpoints impacted by all listed substance profiles are respiratory, neurologic, hepatic, and developmental effects. More than 30% of the substance profiles affected these systems as well as other non-cancer endpoints involving the immunological, renal, and reproductive systems, as well as increased cancer risk in respiratory and hepatic systems. Most monomers negatively impact development and the respiratory system, and most metal additives affect the respiratory system. We explain how this data visualization tool combined with ATSDR’s framework for assessing health impacts from multiple chemicals could be applied to identify the target organs impacted by components of the common plastic polyvinyl chloride. Hazard quotients and index show low toxicity and health risk of components in the cured product. This data provide a valuable resource for prioritizing health risk assessments. Use of this interactive tool can enhance the ability of public health professionals to navigate the expanding literature, synthesize findings, and identify future health risk assessment and research priorities.

Mammalian Hedgehog (HH) signalling pathway plays an essential role in tissue homeostasis and its deregulation is linked to rheumatological disorders. UBR5 is the mammalian homologue of the E3 ubiquitin-protein ligase Hyd, a negative regulator of the Hh-pathway in Drosophila . To investigate a possible role of UBR5 in regulation of the musculoskeletal system through modulation of mammalian HH signaling, we created a mouse model for specific loss of Ubr5 function in limb bud mesenchyme. Our findings revealed a role for UBR5 in maintaining cartilage homeostasis and suppressing metaplasia. Ubr5 loss of function resulted in progressive and dramatic articular cartilage degradation, enlarged, abnormally shaped sesamoid bones and extensive heterotopic tissue metaplasia linked to calcification of tendons and ossification of synovium. Genetic suppression of smoothened ( Smo ), a key mediator of HH signalling, dramatically enhanced the Ubr5 mutant phenotype. Analysis of HH signalling in both mouse and cell model systems revealed that loss of Ubr5 stimulated canonical HH-signalling while also increasing PKA activity. In addition, human osteoarthritic samples revealed similar correlations between UBR5 expression, canonical HH signalling and PKA activity markers. Our studies identified a crucial function for the Ubr5 gene in the maintenance of skeletal tissue homeostasis and an unexpected mode of regulation of the HH signalling pathway.

Type 1 diabetes mellitus (T1D) is a chronic disease caused by an unremitting autoimmune attack on pancreatic [beta] cells. This autoimmune chronicity is mediated by stem-like progenitor [CD8.sup.+] T cells that continually repopulate the pool of [beta] cell-specific cytolytic effectors. Factors governing the conversion of progenitors to effectors, however, remain unclear. T1D has been linked to a chromosomal region (Xp13-p11) that contains the epigenetic regulator UTX, which suggests a key role for UTX in T1D pathogenesis. Here, we show that T cell-specific UTX deletion in NOD mice protects against T1D development. In T cells of NOD mice and patients with T1D, UTX ablation resulted in the accumulation of [CD8.sup.+] progenitor cells with a concomitant decrease of effector cells, suggesting a key role for UTX in poising progenitors for transition to effectors. Mechanistically, UTX's role in T1D was independent of its inherent histone demethylase activity but instead relied on binding with transcription factors (TCF1 and STAT3) to coregulate genes important in the maintenance and differentiation of progenitor [CD8.sup.+] T cells. Together, these findings identify a critical role for UTX in T1D and the UTX:TCF1:STAT3 complex as a therapeutic target for terminating the long-lived autoimmune response.

Type 1 diabetes mellitus (T1D) is a chronic disease caused by an unremitting autoimmune attack on pancreatic β cells. This autoimmune chronicity is mediated by stem-like progenitor CD8 + T cells that continually repopulate the pool of β cell–specific cytolytic effectors. Factors governing the conversion of progenitors to effectors, however, remain unclear. T1D has been linked to a chromosomal region (Xp13-p11) that contains the epigenetic regulator UTX, which suggests a key role for UTX in T1D pathogenesis. Here, we show that T cell–specific UTX deletion in NOD mice protects against T1D development. In T cells of NOD mice and patients with T1D, UTX ablation resulted in the accumulation of CD8 + progenitor cells with a concomitant decrease of effector cells, suggesting a key role for UTX in poising progenitors for transition to effectors. Mechanistically, UTX’s role in T1D was independent of its inherent histone demethylase activity but instead relied on binding with transcription factors (TCF1 and STAT3) to coregulate genes important in the maintenance and differentiation of progenitor CD8 + T cells. Together, these findings identify a critical role for UTX in T1D and the UTX:TCF1:STAT3 complex as a therapeutic target for terminating the long-lived autoimmune response.

From toxic waste in Love Canal, New York, to lead in Flint, Michigan, environmental contamination can cause chronically elevated psychosocial stress in individuals and across families and communities. Stress is a normal reaction to environmental contamination, not a mental health disorder. Still, stress can affect people's health and quality of life. In addition, lengthy environmental and health investigations, loss of trust in institutions, financial strains, and other concerns associated with environmental contamination are sources of stress. Conversely, individual and community resilience can promote physical and psychological health and enhance well-being. Community resilience is the ability of a community to adapt to changing conditions and prepare for, withstand, and rapidly recover from disruption. Currently, ATSDR is taking a fresh look at psychosocial stress related to environmental contamination, with a focus on per- and polyfluoroalkyl substances (PFAS) in drinking water. This community-engaged project might enhance knowledge and understanding of PFAS contamination-related stressors, informing new tools, resources, and strategies to reduce stress and build resilience in affected communities.

Bayesian analysis results require a choice of prior distribution. In long-baseline neutrino oscillation physics, the usual parameterisation of the mixing matrix induces a prior that privileges certain neutrino mass and flavour state symmetries. Here we study the effect of privileging alternate symmetries on the results of the T2K experiment. We find that constraints on the level of CP violation (as given by the Jarlskog invariant) are robust under the choices of prior considered in the analysis. On the other hand, the degree of octant preference for the atmospheric angle depends on which symmetry has been privileged.