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   https://doi.org/10.3390/nano11010111  

   Stine, Jared S.; Harper, Bryan J.; Conner, Cathryn G.; Velev, Orlin D.; Harper, Stacey L. (January 2021, Nanomaterials)

   null (Ed.)

   Lignin is the second most abundant biopolymer on Earth after cellulose. Since lignin breaks down in the environment naturally, lignin nanoparticles may serve as biodegradable carriers of biocidal actives with minimal environmental footprint compared to conventional antimicrobial formulations. Here, a lignin nanoparticle (LNP) coated with chitosan was engineered. Previous studies show both lignin and chitosan to exhibit antimicrobial properties. Another study showed that adding a chitosan coating can improve the adsorption of LNPs to biological samples by electrostatic adherence to oppositely charged surfaces. Our objective was to determine if these engineered particles would elicit toxicological responses, utilizing embryonic zebrafish toxicity assays. Zebrafish were exposed to nanoparticles with an intact chorionic membrane and with the chorion enzymatically removed to allow for direct contact of particles with the developing embryo. Both mortality and sublethal endpoints were analyzed. Mortality rates were significantly greater for chitosan-coated LNPs (Ch-LNPs) compared to plain LNPs and control groups. Significant sublethal endpoints were observed in groups exposed to Ch-LNPs with chorionic membranes intact. Our study indicated that engineered Ch-LNP formulations at high concentrations were more toxic than plain LNPs. Further study is warranted to fully understand the mechanisms of Ch-LNP toxicity. 

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   https://doi.org/10.1093/toxsci/kfaf069  

   Schwartz, Ashley_V; Sant, Karilyn_E; George, Uduak_Z (May 2025, Toxicological Sciences)

   Abstract Zebrafish (Danio rerio) are a popular vertebrate model for high-throughput toxicity testing, serving as a model for embryonic development and disease etiology. However, standardized protocols using zebrafish tend to explore pathologies and behaviors at the organism level rather than at the organ-specific level. This study investigates the effects of chemical exposures on pancreatic function in whole-embryo zebrafish by integrating network analysis and machine learning, leveraging widely available datasets to probe an organ-specific effect. We compiled transcriptomics data for zebrafish exposed to 53 exposures from 25 unique chemicals, including halogenated organic compounds, pesticides/herbicides, endocrine-disrupting chemicals, pharmaceuticals, parabens, and solvents. All raw sequencing data were processed through a uniform bioinformatics pipeline for re-analysis and quality control, identifying differentially expressed genes and altered pathways related to pancreatic function and development. Clustering analysis revealed 5 distinct clusters of chemical exposures with similar impacts on pancreatic pathways, with gene co-expression network analysis identifying key driver genes within these clusters, providing insights into potential biomarkers of chemical-induced pancreatic toxicity. Machine learning was utilized to identify chemical properties that influence pancreatic pathway response, including average mass and biodegradation half-life. The random forest model achieved robust performance (4-fold cross-validation accuracy: 74%) over eXtreme Gradient Boosting, support vector machine, and multiclass logistic regression. This integrative approach enhances our understanding of the relationships between chemical properties and biological responses in a target organ, supporting the use of zebrafish whole embryos as a high-throughput vertebrate model. This computational workflow can be leveraged to investigate the complex effects of other exposures on organ-specific development. 

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3. Microbial Biotransformation Products and Pathways of Dichloroacetamide Herbicide Safeners

   https://doi.org/10.1021/acs.estlett.2c00862  

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   https://doi.org/10.1016/j.jinorgbio.2022.112110  

   Sun, Yifei; Das, Sanjit; Brown, Spenser R.; Blevins, Emily R.; Qu, Fengrui; Ward, Nicholas A.; Gregory, Shawn Aiden; Boudreaux, Chance M.; Kim, Yonghyun; Papish, Elizabeth T. (March 2023, Journal of Inorganic Biochemistry)