Optimization of LPS-Induced Inflammation Model and Its Feasibility as a Fast Screening Model for Cosmetics

Abstract

Objectives: The existing inflammatory models are concentrated in relatively complex medical fields, and most of them use a single type of cell, and the induction conditions are not uniform, so t he current LPS-induced inflammation model is less conducive to the study of skin inflammation. The aim of this research is to enhance the existing LPS-induced inflammation model and establish a skin inflammation model that is suitable for the swift screening of anti-inflammatory agents in the cosmetics industry. Methods: LPS was used to induce inflammatory responses in KC and THP-1 cells. Enzyme-linked immunosorbent assay (ELISA) was employed to assess the levels of IL-1 α , IL-8, and TNF- α in the two cell types, while the DCFH-DA probe was utilized to label the levels of reactive oxygen species (ROS) in both cell types. Results: In KC cells, 10 μg/mL of LPS induced a significant upregulation of IL-8 but did not result in elevated expression of IL-1 α . However, at 100 μg/mL of LPS, both IL-8 and IL-1 α were highly expressed in KC cells. LPS concentrations ranging from 0.01 to 100 μg/mL failed to stimulate TNF- α production in KC cells but induced a gradient increase in ROS levels. In THP-1 cells, LPS concentrations from 0.01 to 100 μg/mL did not induce IL-1 α production but significantly elevated IL-8 and led to a gradient increase in TNF- α and ROS. After treatment with 100 μg/mL of LPS, the cosmetic ingredient Rucika KGM mitigated the elevated levels of IL-1 α , IL-8, and ROS in LPS-induced KC cells and IL-8 and ROS in THP-1 cells. Conclusion: This study has successfully developed an application-oriented model suitable for investigating skin inflammation, enabling the rapid and comprehensive screening of cosmetic ingredients with anti-inflammatory activity.