Historic animal-based toxicity testing methods cannot keep pace with the need for prioritizing new and existing chemicals for comprehensive risk assessment. New approach methodologies such as high-throughput in vitro transcriptomics screening have emerged to address this challenge. However, most in vitro methods were developed using mammalian cell lines, including human, and may not adequately represent environmental species, potentially limiting the utility of this methodology for supporting environmental risk assessment. The objective of this study was to evaluate whether zebrafish cell lines can generate biologically meaningful chemical effects data in a high-throughput transcriptomics pipeline that is protective of toxicologically relevant aquatic apical endpoints. Forty-two test chemicals were screened in two commercially available zebrafish cell lines (ZFL liver and ZEM2S embryonic fibroblast) using the TempO-Seq zS1500+ platform. Transcriptomic points of departure (tPODs) were derived using two methods: Gene-level analysis (tPODgenes) with BMDExpress software and biological pathway altering concentrations (BPACs/tPODsignatures) from signature-based dose-response analysis. When converted to predicted external water concentrations using quantitative in vitro-in vivo extrapolation models, tPODs were generally protective of aquatic in vivo endpoints from the ECOTOX Knowledgebase. Differential gene expression and biological pathway analysis revealed potential cell-type specific effects for several chemicals, highlighting the value of using multiple cell types for capturing tissue-specific responses. Lastly, the biological pathway information was used to extrapolate the chemical effects data across species through an integration of protein-protein interaction network analysis and the Sequence Alignment to Predict Across Species Susceptibility tool, which has significant implications for improving the ecological relevance of these methods.

Chronic ocular surface pain (COSP) is defined as ocular pain that is perceived to originate from the ocular surface and persists for more than 3 months. Clear epidemiological data on COSP prevalence are lacking. In 2025, a total of 100 eye care providers were surveyed, including 50 optometrists and 50 ophthalmologists. The survey aimed to assess the percentage of their weekly patient volume diagnosed with COSP, the diagnostic methods used, contributing etiologies, and current management strategies. Additionally, practitioners identified key indicators of successful treatment and attributes they believed would have the greatest impact on patient outcomes. Lastly, they rated their satisfaction with current therapeutic options. An estimated 33% of optometrists' patients and 29% of ophthalmologists' patients had COSP. Of those diagnosed with dry eye disease (DED), 63% also had COSP. Providers managed COSP with over-the-counter (OTC) artificial tears (97% of respondents), OTC gels and ointments (90%), hot compresses (86%), and prescription therapies indicated for DED (30-88%), while a minority routinely used amniotic membranes (37%), serum tears (26%), intense pulsed light (18%), and LipiFlow (16%). The proportions of providers who were satisfied or very satisfied with these therapies were as follows: 64% for amniotic membranes and serum tears, 63% for device-based therapies, 40% for prescription medications, and 21% for OTC drops, ointments, and hot compresses. This survey provides initial insight into the prevalence of COSP among patients in US eye care clinics, along with perspectives on managing this condition from both optometrists and ophthalmologists. The most common therapeutic strategies for COSP (OTC artificial tears, gels, and ointments) were associated with the lowest levels of provider satisfaction. COSP and dry eye disease are distinct but closely linked conditions. These results demonstrate an unmet need for new treatment options to address COSP.

Huntington’s disease (HD) is an autosomal dominant neurodegenerative disease caused by an abnormal expansion of cytosine-adenine-guanosine (CAG) trinucleotidein the huntingtin gene. Mutant huntingtin (mHTT) expression in neurons and glial cells affects neuron and astrocyte functions and leads to the loss of medium spiny neurons of the striatum. Brain cholesterol pathway is severely affected by HTT mutation in neurons and astrocytes, contributing to HD pathogenesis. Decreased cholesterol production and transport by astrocytes impair synapse maturation and neurotransmission. Brain cholesterol metabolism is maintained by cholesterol hydroxylation into 24-hydroxycholesterol by the neuronal enzyme cholesterol 24-hydroxylase (CYP46A1). CYP46A1 is decreased in affected brain regions in HD patients and mice. AAV-CYP46A1 striatal delivery was shown to restore cholesterol metabolism with neuroprotective effects in two mouse models of HD, characterized by mHTT aggregates’ reduction, improved transcriptomic profile, and Brain-Derived Neurotrophic Factor (BDNF) signaling, and preservation of striatal neurons. From a therapeutic perspective, we intended to clarify the detailed mechanisms and the specific role of neurons and astrocytes in the therapeutic effects of AAV-CYP46A1 delivery. We first evaluated CYP46A1 expression in astrocytes in HD post-mortem putamen at a late stage of disease progression. To determine the specific contribution of CYP46A1 expression in astrocytes compared to neurons on the HD phenotype, we assessed the effects of AAV-CYP46A1 striatal injection under the control of astrocytic (GFA2) or neuronal (hSYN) promoters in R6/2 mice. Overall, equivalent transgenic CYP46A1 protein levels, both astrocytic and neuronal targeting, mitigate medium ppiny neuron (MSN) atrophy and improve spine density in R6/2 mice. Reduction of mHTT aggregates in neurons is similar when CYP46A1 is overexpressed in neurons or in astrocytes. However, astrocyte targeting reduces mHTT aggregates in neurons and astrocytes, while restricted neuronal targeting reduces mHTT aggregates in neurons only. Altogether, astrocytic targeting of CYP46A1 expression in CYP46A1-tested animals combines cell-autonomous and non-cell-autonomous mechanisms of action, with improved phenotypic correction compared to neuronal-restricted targeting. Allowing expression in both cell types with higher expression levels of CYP46A1 showed overall better efficacy. We demonstrate that astrocyte-neuron combined targeting with AAV-CAG-CYP46A1 delivery increases therapeutic efficacy. This study brings new evidence that CAG-mediated CYP46A1 striatal overexpression significantly modifies the transcriptome in R6/2 mice for pathways involved in synaptogenesis and inflammation, suggesting targeting both astrocytes and neurons provides benefits for HD phenotypic correction.Supplementary InformationThe online version contains supplementary material available at 10.1186/s40478-025-02054-4.

Rice planthoppers are the most destructive pests of rice production and the vectors of rice viruses. Fenmezoditiaz as a novel mesoionic insecticide is used for rice planthopper management by targeting the insect's neural nicotinic acetylcholine receptor. This study aimed to evaluate the effects of fenmezoditiaz on the acquisition, propagation, and transmission of southern rice black-streaked dwarf virus (SRBSDV) by the white-backed planthopper, Sogatella furcifera (Hemiptera: Delphacida). The results revealed that sublethal concentrations of fenmezoditiaz significantly impaired SRBSDV acquisition and viral replication in S. furcifera. Fenmezoditiaz-treated viruliferous S. furcifera exhibited a lower transmission efficiency of SRBSDV to un-infected rice seedlings. Electrical penetration graph (EPG) recordings revealed prolonged non-probing (NP), salivary secretion (N2/N3), and xylem feeding (N5) durations, alongside shortened phloem contact behavior (N4a/N4b), of fenmezoditiaz-treated individuals, indicating disrupted feeding behaviors, which are critical for reducing viral infection. By reducing viral titers and interfering with phloem ingestion, fenmezoditiaz significantly suppresses SRBSDV transmission. These findings revealed fenmezoditiaz's dual role in pest control and viral transmission blockage, providing a foundation for incorporation into integrated management of vector-borne plant viruses.

BackgroundMortality is a critical variable in health care research, especially for evaluating medical product safety and effectiveness. However, inconsistencies in the availability and timeliness of death date and cause of death (CoD) information present significant challenges. Conventional sources such as the National Death Index and electronic health records often experience data lags, missing fields, or incomplete coverage, limiting their utility in time-sensitive or large-scale studies. With the growing use of social media, crowdfunding platforms, and web-based memorials, publicly available digital content has emerged as a potential supplementary source for mortality surveillance. Despite this potential, accurate tools for extracting mortality information from such unstructured data sources remain underdeveloped.ObjectiveThe aim of the study is to develop scalable approaches using natural language processing (NLP) and large language models (LLMs) for the extraction of mortality information from publicly available web-based data sources, including social media platforms, crowdfunding websites, and web-based obituaries, and to evaluate their performance across various sources.MethodsData were collected from public posts on X (formerly known as Twitter), GoFundMe campaigns, memorial websites (EverLoved and TributeArchive), and web-based obituaries from 2015 to 2022, focusing on US-based content relevant to mortality. We developed an NLP pipeline using transformer-based models to extract key mortality information such as decedent names, dates of birth, and dates of death. We then used a few-shot learning (FSL) approach with LLMs to identify primary and secondary CoDs. Model performance was assessed using precision, recall, F1-score, and accuracy metrics, with human-annotated labels serving as the reference standard for the transformer-based model and a human adjudicator blinded to the labeling source for the FSL model reference standard.ResultsThe best-performing model obtained a microaveraged F1-score of 0.88 (95% CI 0.86‐0.90) in extracting mortality information. The FSL-LLM approach demonstrated high accuracy in identifying primary CoD across various web-based sources. For GoFundMe, the FSL-LLM achieved 95.9% accuracy for primary cause identification compared to 97.9% for human annotators. In obituaries, FSL-LLM accuracy was 96.5% for primary causes, while human accuracy was 99%. For memorial websites, FSL-LLM achieved 98% accuracy for primary causes, with human accuracy at 99.5%.ConclusionsThis study demonstrates the feasibility of using advanced NLP and LLM techniques to extract mortality data from publicly available web-based sources. These methods can significantly enhance the timeliness, completeness, and granularity of mortality surveillance, offering a valuable complement to traditional data systems. By enabling earlier detection of mortality signals and improving CoD classification across large populations, this approach may support more responsive public health monitoring and medical product safety assessments. Further work is needed to validate these findings in real-world health care settings and facilitate the integration of digital data sources into national public health surveillance systems.

ABSTRACT Exposures to pollutants rarely occur in isolation, often coexisting with other environmental stressors such as diet and may be particularly insidious in early life. The aim of this study was to examine effects of maternal exposure to cadmium (Cd) and consumption of a high-fructose diet (HFrD) on development of mouse offspring. Female CD-1 mice were administered either 0.5 or 5 ppm Cd in drinking water with or without an approximate 60% fructose diet for 3 weeks prior to mating. Dams were maintained on the same treatment until postnatal day (PND) 16. Cadmium concentrations in maternal, fetal, and neonatal liver increased in a concentration-dependent manner irrespective of diet. Endpoints known to be associated with Cd or HFrD adverse effects were assessed longitudinally in offspring from birth to young adulthood, including growth trajectory, pubertal development, body composition, glycemic tolerance and hepatic lipid accumulation. Maternal exposure to either Cd or HFrD alone significantly advanced onset of puberty, hypoglycemia, and reduced adiposity in adulthood. HFrD rarely exacerbated metal-initiated effects in most of the endpoints examined outside of pubertal timing. Because of chronic effects attributed to Cd or HFrD on metabolic function (e.g. glucose tolerance), transcriptomics and gene methylation analyses were performed on livers from neonatal and adult offspring. Data were largely consistent with phenotypic findings. In summary, maternal exposure to Cd or HFrD alone perturbed growth and development, producing long-lasting changes in metabolic function in adult offspring. HFrD did not appear to significantly exaggerate adverse outcomes attributed to metal exposure in the endpoints examined.