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Raspberry pi: Assessments of emerging organic chemicals by the predictive in silico methods
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Researchers used computer modeling to assess the toxicity of phthalate and bisphenol plasticizer chemicals, which leach from plastics into food and the environment. These computational tools can help predict which plastic additives pose the greatest risks to human health without extensive animal testing.
Abstract Phthalic acid esters (PAEs) and bisphenols are used as plasticizers worldwide. During plastic production, use, deposition, and recycling these compounds contaminate the environment and affect environmental health. In this study, we investigated the toxicity of plasticizers by using in silico tools. None of the test compounds were found to be hERG blockers in multiclass predictions as evaluated by the Pred-hERG 4.1 tool. Among all tested compounds in Pred-Skin 2.0, only BBP, BCP, DBP, diethyl phthalate (DEP), DMP, DNHP, DNPP, DPP, DTDP, DUP, and ODP were non-skin sensitizers. Our results demonstrate that in silico tools provide a reliable, fast, and economic way to explore the toxicological effects of EOCs.
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Integrating structure and experimental data annotations with computational modeling framework for predicting micro-nanoplastics toxicities
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Scientists have created a computer-based method to predict how toxic tiny plastic particles (microplastics and nanoplastics) might be to our cells, without needing to run slow, expensive lab experiments for every single type of plastic. By teaching computer models to recognize patterns based on a plastic particle's shape and size, researchers can now screen many more plastic types for potential health risks than traditional testing allows. This matters because it could speed up our understanding of which plastics pose the greatest danger as they build up in our environment and bodies.
Rapid assessment of the intrinsic hazard potential of different types of plastic additives using machine learning (RF-MLP)
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Researchers built a computer model combining two machine learning methods to predict how hazardous plastic additives might be, since lab testing all of them is too costly. Tested on 7,267 plastic additives, the model performed better than other common prediction methods when checked against existing toxicity data for 60 additives.
In silico insights into microplastic additive toxicity: Risks of pulmonary fibrosis and endocrine disruption
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Researchers used computational modeling to investigate how five common microplastic additives, including phthalates and flame retardants, interact with proteins involved in lung fibrosis and endocrine function. Molecular docking revealed that these additives bind strongly to fibrotic markers like TGF-beta and to hormone receptors, suggesting potential mechanisms for tissue damage and hormonal disruption. The study highlights the need for further investigation into the health risks posed by chemical additives leaching from microplastics.
Environmental and health hazards of chemicals in plastic polymers and products
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Researchers reviewed the environmental and health hazards of chemicals in plastic polymers and products, examining the toxicological profiles of monomers, additives, and degradation products that can leach from plastics into food, water, and the environment. The study identifies numerous plastic-associated chemicals with endocrine-disrupting, carcinogenic, or developmental toxicity potential and calls for more comprehensive safety testing of plastic formulations.
Computational prediction of potential aggravating mechanisms of polyethylene terephthalate microplastics in diabetic foot ulcers: An integrated in silico approach combining network toxicology, bioinformatics, machine learning, and molecular dynamics simulations
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Using computer modeling (not actual patient testing), researchers found clues that tiny plastic particles from PET plastic (commonly used in water bottles and food packaging) might make diabetic foot ulcers worse by interfering with genes that help repair cell damage and regulate blood sugar processing. While these findings are just a starting point—based on computer simulations rather than lab or human studies—they add to growing concerns that microplastics in our environment could impact chronic health conditions like diabetes complications, making this an area worth watching as research continues.
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When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.