Shinozaki Atsumi, Matsuda Kazuhiro, Aoyagi Satoka
Faculty of Science and Technology, Seikei University, 3-3-1 Kichijoji-Kitamachi, Musashino, Tokyo, 180-8633, Japan.
Surface Science Laboratories, Toray Research Center, Inc., 3-2-11, Sonoyama, Otsu, Shiga, 520-8567, Japan.
Anal Bioanal Chem. 2025 Mar;417(6):1049-1054. doi: 10.1007/s00216-024-05711-0. Epub 2024 Dec 27.
Methods that facilitate molecular identification and imaging are required to evaluate drug penetration into tissues. Time-of-flight secondary ion mass spectrometry (ToF-SIMS), which has high spatial resolution and allows 3D distribution imaging of organic materials, is suitable for this purpose. However, the complexity of ToF-SIMS data, which includes nonlinear factors, makes interpretation challenging. Therefore, in this study, ToF-SIMS data of a stratum corneum treated with diclofenac were analyzed using machine learning to enable the evaluation of drug distribution. Diclofenac-related mass peaks were identified using autoencoder results, and the degree of penetration was evaluated across 2-20 stripped tapes. In addition, the permeation pathway was clarified by comparing the secondary ion images of phosphatidylethanolamine (PhEA; a marker of the inside of the cell); cholesterol, which is abundant in cell membranes; and diclofenac. Based on the biomolecule-related ion images showing the penetration pathway of diclofenac applied to the skin, diclofenac penetrates both the extracellular space and inside cells.
需要有助于分子识别和成像的方法来评估药物渗透到组织中的情况。飞行时间二次离子质谱（ToF-SIMS）具有高空间分辨率，能够对有机材料进行三维分布成像，适用于此目的。然而，ToF-SIMS数据的复杂性（包括非线性因素）使得解释具有挑战性。因此，在本研究中，使用机器学习分析了用双氯芬酸处理的角质层的ToF-SIMS数据，以评估药物分布。利用自动编码器的结果识别与双氯芬酸相关的质量峰，并评估了2至20条剥离胶带的渗透程度。此外，通过比较磷脂酰乙醇胺（PhEA；细胞内部的标志物）、细胞膜中丰富的胆固醇和双氯芬酸的二次离子图像，阐明了渗透途径。基于显示双氯芬酸应用于皮肤后的渗透途径的生物分子相关离子图像，双氯芬酸可穿透细胞外空间和细胞内部。
