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深度学习驱动的识别从多能干细胞中分化早期中皮细胞的识别

Sakib Mohammad¹, Arpan Roy², Andreas Karatzas¹

¹School of Electrical, Computer, and Biomedical Engineering, Southern Illinois University Carbondale, Carbondale, IL 62901, USA.

|March 27, 2024

概括

深度学习模型使用细胞和核形态学准确地预测了来自多能干细胞的早期中皮细胞. 这一进步有助于用于再生医学应用的高通量查.

科学领域:

干细胞生物学干细胞生物学
发育生物学是发展生物学.
计算生物学是一种计算生物学.

背景情况:

多能干细胞分化成三个生殖层:外皮,内皮和中皮.
在分化过程中早期识别和表征细菌层具有挑战性,限制了高通量查.
准确的血统规范对于再生医学至关重要.

研究的目的:

开发深度学习 (DL) 方法来预测和分类早期中皮细胞.
利用细胞和核形态来分类从胚胎体 (EBs) 区分出的中皮细胞.
建立一个快速和高通量方法来评估谱系规范效率.

主要方法:

使用了一种转基因的小鼠胚胎干细胞 (mESC) 谱系 (OGTR1) 与中皮基因 (Brachyury (T):DsRed) 验证.
训练了一个卷积神经网络 (CNN) 模型 (InceptionV3) 用相对比和核图像进行细胞分类.
雇佣了一个注意力U-Net CNN用于相对比和核图像的图像细分.

主要成果:

在InceptionV3 CNN实现了相位图像97%,核图像90%的准确性,用于分类介质皮细胞与非介质皮细胞.
注意U-Net CNN实现了相对比图像的61%,核图像的69%的联合分数的平均交叉.
在分化细胞中验证了中皮基因上调 (Brachyury (T):DsRed).

结论:

深度学习模型可以根据形态学准确预测中皮细胞分化.
细胞培养,成像和DL的整合加速了血统特征识别.
这种方法有很大的潜力,可以通过高效的查来推进再生医学.

关键词:

细胞和核的形态.深度学习是一种深度学习.胚胎体是一个胚胎体.胚胎干细胞是一种胚胎干细胞.这里是 mesoderm 和 mesoderm 的区别.

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