IIT Seminar Series: Christie Sayes
Tue, September 29, 2026 11:00 AM - Tue, September 29, 2026 1:00 PM at 162 Food Safety & Toxicology Building
*The Institute for Integrative Toxicology presents Dr. Christie Sayes, Baylor University, to speak on, “The 'Breakdown' on Microplastics: A Review of Human Health Risks and Knowledge Gaps Associated with Micro- and Nano-Plastics in Food & Packaging,” on Tuesday, September 29, 2026, at 11:00 a.m. in 162 Food Safety and Toxicology Building.
*Fulfills seminar requirements for the Environmental and Integrative Toxicological Sciences Graduate Programs. Seminars that fulfill this requirement are archived at: https://iit.msu.edu/training/eits/recent-seminar-list.html.
Talk Abstract:
This talk presents research on micro- and nanoplastics (MNPs) in food processing. MNPs are widespread in the environment, detected in air, water, and soil, and can enter plants and animals, posing risks to humans through ingestion. They migrate from plastic packaging to processed and organic foods, with factors like storage, acidity, fat content, temperature, and packaging materials influencing their presence. Studies show MNPs can disrupt the gut microbiome and affect various systems, with toxicity potentially increased by chemical additives. This talk discusses the relationship between MNPs, food production, analytical techniques, and the need for further research on MNP processing.
Speaker Bio:
Dr. Christie M. Sayes is an expert in materials chemistry, exposure science, environmental health, and risk characterization. Her work involves collaborating on safety-by-design studies for engineered substances and emerging contaminants in pharmaceuticals, agriculture, and consumer products. Sayes’ research interests include chemical transformations in complex environments. She has expertise in laboratory science and U.S. regulatory frameworks. Her routine work includes developing new alternative methodologies (NAMs), validating animal models, conducting biochemical activity, studying toxicological mechanisms, using mass spectrometry and electron microscopy, and establishing predictive statistical methods.