用稀疏的自编码器分析用迪克洛菲纳克治疗的人类皮肤的飞行时间二次离子质谱数据
Atsumi Shinozaki1, Kazuhiro Matsuda2, Satoka Aoyagi3
1Faculty of Science and Technology, Seikei University, 3-3-1 Kichijoji-Kitamachi, Musashino, Tokyo, 180-8633, Japan.
Analytical and bioanalytical chemistry
|December 27, 2024
概括
对飞行时间二次离子质谱学 (ToF-SIMS) 数据的机器学习分析揭示了狄克洛菲纳克如何穿透皮肤. 发现该药物可以通过细胞外空间和直接进入细胞.
科学领域:
- 材料科学 材料科学 材料科学
- 生物医学工程 生物医学工程
- 分析化学 分析化学
背景情况:
- 评估药物透到组织对于制药开发至关重要.
- 飞行时间二次离子质谱 (ToF-SIMS) 为有机材料的3D成像提供了高空间分辨率.
- 由于非线性因素,ToF-SIMS数据的复杂性在解释方面存在挑战.
研究的目的:
- 使用机器学习分析用二二治疗角层的ToF-SIMS数据.
- 为了能够评估毒品的分销和透途径.
- 为了克服复杂的ToF-SIMS数据的解释性挑战.
主要方法:
- 应用机器学习,特别是自动编码器,用于分析ToF-SIMS数据.
- 使用自编码器输出识别了与迪克洛芬雅克相关的质量峰值.
- 通过分析剥带样本 (第2至20号) 评估药物透率.
- 将二甲的二次离子图像与生物分子 (酸乙醇胺和胆固醇) 进行比较,以绘制透通路图.
主要成果:
- 在ToF-SIMS数据中成功识别了与狄克洛菲纳克相关的质量峰值.
- 量化了迪克洛芬雅克在角层多层透的程度.
- 通过将其分布与细胞和膜标记器相关联,可视化了药物的透途径.
- 确定狄克洛菲纳克通过细胞外路径和细胞内路径透到皮肤.
结论:
- 机器学习有效地帮助解释复杂的ToF-SIMS数据用于药物分布分析.
- 迪克洛菲纳克利用双重通路穿透皮肤,进入细胞外空间和细胞.
- 这项研究为了解分子水平上药物与组织相互作用提供了一种新的方法.
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