Search Results - "Simpson, Kayla"

Cellular response of keratinocytes to the entry and accumulation of nanoplastic particles by Martin, Leisha, Simpson, Kayla, Brzezinski, Molly, Watt, John, Xu, Wei

“…Plastic accumulation in the environment is rapidly increasing, and nanoplastics (NP), byproducts of environmental weathering of bulk plastic waste, pose a…”
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Understanding Nanoplastic Particle Intracellular Accumulation and Cell Response in Human Skin Cells by Simpson, Kayla

“…Environmental nanoplastic particles (NPs) are considered hazardous materials that can potentially enter human bodies through various entry pathways due to…”
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Photodegradation enhances the toxic effect of anthracene on skin by Brzezinski, Molly, Martin, Leisha, Simpson, Kayla, Lu, Kaijun, Gan, Nin, Huang, Chi, Garcia, Kaitlin, Liu, Zhanfei, Xu, Wei

“…Anthracene, a polycyclic aromatic hydrocarbon (PAH), is a widespread environmental pollutant that poses potential risks to human health. Exposure to anthracene…”
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The influence of somatic maturity on the relationship between the Triglyceride/HDL ratio and vascular health in children and adolescents with dyslipidemia by Talluri, Rachna, Sherman, Ashley K., Goth, Natalie, Simpson, Kayla, Kuzava, Laura, Raghuveer, Geetha, White, David A.

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The influence of somatic maturity on the relationship between the triglyceride/high‐density lipoprotein ratio and vascular health in children and adolescents with dyslipidemia by Talluri, Rachna, Sherman, Ashley K., Goth, Natalie, Simpson, Kayla, Kuzava, Laura, Raghuveer, Geetha, White, David A.

“…Introduction Both the triglyceride to HDL cholesterol (TG/HDL) ratio and timing of pubertal maturation have been identified as independent contributors to the…”
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Systematically Analyzing Prompt Injection Vulnerabilities in Diverse LLM Architectures by Benjamin, Victoria, Braca, Emily, Carter, Israel, Kanchwala, Hafsa, Khojasteh, Nava, Landow, Charly, Luo, Yi, Ma, Caroline, Magarelli, Anna, Mirin, Rachel, Moyer, Avery, Simpson, Kayla, Skawinski, Amelia, Heverin, Thomas

“…This study systematically analyzes the vulnerability of 36 large language models (LLMs) to various prompt injection attacks, a technique that leverages…”
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