用人工智能方法系统地揭示植物的定量多目标整合效应.
Jiang Qi-Yu1, Ren Tian-Ai2, Fan Xin-Yu1
1Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.
Plant biotechnology journal
|August 18, 2025
概括
这项研究引入了一种人工智能方法来分析棘如何生长.
科学领域:
- 生物医学科学 生物医学科学
- 计算生物学 计算生物学
- 药理学 药理学是指药理学的学科.
背景情况:
- 植物拥有多种化学成分,针对各种疾病途径.
- 了解植物对疾病的综合多目标效应是复杂的.
- 动脉样硬化涉及周围血管脂肪组织 (PVAT) 微环境中的复杂的细胞和分子相互作用.
研究的目的:
- 开发一种基于人工智能 (AI) 的新方法,以评估植物在单细胞水平上对疾病的综合多目标影响.
- 研究棘对动脉样硬化PVAT微环境的影响的潜在机制和景观.
主要方法:
- 利用深度自编码神经网络编码单细胞转录组数据.
- 使用多目标综合评分 (MTIS) 量化了棘对动脉样硬化的综合多目标效应.
- 进行单细胞水平分析,包括MTIS比较,伪时间分析,细胞通信和免疫透.
主要成果:
- 开发并应用了一种新的AI方法,在单细胞水平上映射黄杉对动脉样硬化PVAT的综合作用.
- 通过多目标分析揭示了黑对PVAT微环境的影响的潜在机制.
- 证明了MTIS在量化评估植物衍生多目标效应方面的能力.
结论:
- 开发的AI方法使植物药物的综合多目标效应能够进行系统的单细胞水平分析.
- 棘表现出影响动脉样硬化PVAT微环境的潜在机制.
- 这种新的方法在研究各种疾病的多组分,多目标植物性疗法方面具有广泛的适用性.
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