Ni Shiwei, Chen Fei, Chen Guolong, Yang Yufeng
Institute of Life Sciences, FuZhou University, FuZhou, Fujian, China.
School of Mathematics and Statistics, FuZhou University, FuZhou, Fujian, China.
Front Genet. 2022 Aug 10;13:956415. doi: 10.3389/fgene.2022.956415. eCollection 2022.
Biological pattern formation ensures that tissues and organs develop in the correct place and orientation within the body. A great deal has been learned about cell and tissue staining techniques, and today's microscopes can capture digital images. A light microscope is an essential tool in biology and medicine. Analyzing the generated images will involve the creation of unique analytical techniques. Digital images of the material before and after deformation can be compared to assess how much strain and displacement the material responds. Furthermore, this article proposes Development Biology Patterns using Digital Image Technology (DBP-DIT) to cell image data in 2D, 3D, and time sequences. Engineered materials with high stiffness may now be characterized digital image correlation. The proposed method of analyzing the mechanical characteristics of skin under various situations, such as one direction of stress and temperatures in the hundreds of degrees Celsius, is achievable using digital image correlation. A DBP-DIT approach to biological tissue modeling is based on digital image correlation (DIC) measurements to forecast the displacement field under unknown loading scenarios without presupposing a particular constitutive model form or owning knowledge of the material microstructure. A data-driven approach to modeling biological materials can be more successful than classical constitutive modeling if adequate data coverage and advice from partial physics constraints are available. The proposed procedures include a wide range of biological objectives, experimental designs, and laboratory preferences. The experimental results show that the proposed DBP-DIT achieves a high accuracy ratio of 99,3%, a sensitivity ratio of 98.7%, a specificity ratio of 98.6%, a probability index of 97.8%, a balanced classification ratio of 97.5%, and a low error rate of 38.6%.
生物模式形成确保组织和器官在体内正确的位置和方向发育。关于细胞和组织染色技术已经有了很多了解，并且如今的显微镜能够捕捉数字图像。光学显微镜是生物学和医学中的重要工具。对生成的图像进行分析将涉及创建独特的分析技术。可以比较材料变形前后的数字图像，以评估材料所响应的应变和位移量。此外，本文提出了利用数字图像技术的发育生物学模式（DBP - DIT）来处理二维、三维和时间序列中的细胞图像数据。具有高刚度的工程材料现在可以通过数字图像相关技术来表征。所提出的分析各种情况下皮肤力学特性的方法，例如在一个应力方向和数百摄氏度的温度下，使用数字图像相关技术是可行的。一种用于生物组织建模的DBP - DIT方法基于数字图像相关（DIC）测量，在不预先假定特定本构模型形式或不了解材料微观结构的情况下，预测未知加载场景下的位移场。如果有足够的数据覆盖范围以及来自部分物理约束的建议，那么一种数据驱动的生物材料建模方法可能比经典本构建模更成功。所提出的程序包括广泛的生物学目标、实验设计和实验室偏好。实验结果表明，所提出的DBP - DIT实现了99.3%的高精度率、98.7%的灵敏度率、98.6%的特异性率、97.8%的概率指数、97.5%的平衡分类率以及38.6%的低错误率。
