人工智能辅助的质谱成像与in situ图像细分用于亚细胞代谢学分析
Cong-Lin Zhao1, Han-Zhang Mou1, Jian-Bin Pan1
1State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University Nanjing 210023 China xl1992@nju.edu.cn binkang@nju.edu.cn xujj@nju.edu.cn.
Chemical science
|March 22, 2024
概括
本研究介绍了一种人工智能辅助的亚细胞质谱成像 (AI-SMSI) 策略,用于详细的细胞内分析. 该方法通过在特定细胞区内分析代谢物来区分药物作用,从而推进精密医学.
科学领域:
- 细胞和分子生物学 细胞和分子生物学
- 分析化学 分析化学
- 药理学 药理学是指药理学的学科.
背景情况:
- 亚细胞代谢学对于理解细胞功能和药物相互作用至关重要.
- 由于细胞大小和微环境的复杂性,分析细胞内异质性和药物效应具有挑战性.
研究的目的:
- 开发一种人工智能辅助的亚细胞质谱成像 (AI-SMSI) 战略,用于高分辨率的代谢学.
- 在亚细胞水平上区分异构药物 doxorubicin (DOX) 和 epirubicin (EPI) 的作用机制.
主要方法:
- 开发了一个AI-SMSI战略,利用纳米分辨率质谱成像.
- 采用关氨酸和氨酸离子作为核和细胞质的in situ图像分割的标记物.
- 应用先进的人工智能模型用于在不同的亚细胞区域内的代谢物概况.
主要成果:
- 成功细分亚细胞区和配置代谢物.
- 根据立体化学差异解密了DOX和EPI的独特药物作用机制.
- 在细胞质中确定了15种代谢物生物标志物,区分DOX和EPI效应.
- 在酸盐-酸盐穿通道中的谷氨酸和酸盐的降低调节与DOX更高的偏毒性有关.
结论:
- 人工智能-SMSI方法可以进行详细的亚细胞代谢分析.
- 这一战略为探索药物细胞相互作用和推进精准医学提供了新的途径.
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