KOBAYASHI Pharmaceutical, Co. Ltd., Ibaraki, Japan.
Department of Science and Technology, NARA Institute of Science and Technology, Ikoma, Japan.
Skin Res Technol. 2022 May;28(3):391-401. doi: 10.1111/srt.13109. Epub 2021 Nov 9.
Intercellular lipids contain a lamellar structure that glows in polarized images. It could be expected that the intercellular lipid content be estimated from the luminance values calculated from polarized images of stratum corneum strips. Therefore, we attempted to develop a method for simple and rapid evaluation of the intercellular lipid content through a procedure. Herein, we demonstrated a relationship between the luminance value and the amount of ceramides, one of the main components of intercellular lipids.
The stratum corneum was collected from the forearm using slides with a pure rubber-based adhesive, which did not produce unnecessary luminescence under polarizing conditions. Images were analyzed using luminance indices. The positive secondary ion peak images were obtained using the time of flight-secondary ion mass spectrometry; the polarized and brightfield images were obtained using a polarized microscope. The ceramide and protein amount was measured by high-performance liquid chromatography and bicinchoninic acid protein assay after microscope imaging. Images and quantitative values were used to construct evaluation models based on a convolutional neural network (CNN).
There was a correlation between the highlighted areas of the polarized image to overlap with the area where ceramide-derived peak was detected. Evaluation of the CNN-based model of the polarized images predicted the amount of ceramides per unit of stratum corneum.
The method proposed in the study enabled a large number of specimens to provide a simple, rapid, and efficient evaluation of the intercellular lipid content.
细胞间脂质含有层状结构,在偏光图像中会发光。因此,可以预期从角质层条带的偏光图像中计算出的亮度值来估计细胞间脂质的含量。因此,我们试图通过一种程序开发一种简单快速评估细胞间脂质含量的方法。在此,我们展示了亮度值与细胞间脂质主要成分之一神经酰胺含量之间的关系。
使用纯橡胶基粘合剂的载玻片从前臂收集角质层,该载玻片在偏光条件下不会产生不必要的发光。使用亮度指数分析图像。使用飞行时间二次离子质谱法获得正二次离子峰图像;使用偏光显微镜获得偏光和明场图像。显微镜成像后,通过高效液相色谱法和双缩脲蛋白测定法测量神经酰胺和蛋白质的量。使用图像和定量值构建基于卷积神经网络(CNN)的评价模型。
偏光图像中突出显示的区域与检测到神经酰胺衍生峰的区域重叠。基于偏光图像的 CNN 模型评估预测了单位角质层中神经酰胺的含量。
该研究提出的方法能够对大量标本进行简单、快速、高效的细胞间脂质含量评估。