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相关概念视频

Heart Failure Drugs: Inotropic Agents01:26

Heart Failure Drugs: Inotropic Agents

570
Positive inotropic agents are commonly used as the first line of treatment for heart failure. One such agent is digoxin, derived from the genus Digitalis, which has been known for centuries but effectively utilized since 1785. However, these cardiac glycosides can have potentially toxic effects due to their mechanism of action, which involves inhibiting Na+/K+-ATPase and increasing contractility. Digoxin is absorbed orally and distributed in various tissues, including the CNS. It has a long...
570

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相关实验视频

Updated: Jun 24, 2025

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
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针对药物诱导心脏毒性检测的二维深度学习框架

Zhijing Zhu1, Ruochen Wu2, Ma Luo3

  • 1Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou 310015, China.

ACS sensors
|June 6, 2024
PubMed
概括

新的深度学习模型STFT-CNN和SST-CNN使用人类相关的诱导多能干细胞衍生心肌细胞 (iPSC-CMs) 准确评估药物诱导的心脏毒性. 这些框架为可靠和高效的药物安全评估提供了重大进展.

关键词:
2D卷积神经网络是一个2D卷积神经网络.心脏毒性评估评估心脏毒性评估毒品分类 毒品分类 毒品分类短时间的里叶变换同步挤压转换变换

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Automated Contraction Analysis of Human Engineered Heart Tissue for Cardiac Drug Safety Screening
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科学领域:

  • 生物医学工程 生物医学工程
  • 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:

  • 药物诱导的心脏毒性带来了重大的临床和经济挑战.
  • 现有的体内和体外模型在准确识别心脏毒性物质方面存在局限性.
  • 准确的心脏毒性评估对于患者安全和有效的药物开发至关重要.

研究的目的:

  • 开发新的深度学习框架,以改善心脏毒性评估.
  • 为了利用诱导的多能干细胞衍生心肌细胞 (iPSC-CMs) 获得与人类相关的数据.
  • 提高药物安全评估的准确性和可靠性.

主要方法:

  • 利用诱导多能干细胞衍生的心肌细胞 (iPSC-CMs) 和阻抗测量来记录机械跳动信号.
  • 应用了短时间里叶变换 (STFT) 和同步挤压变换 (SST) 来将时间信号转换为2D表示.
  • 开发并实施STFT-CNN和SST-CNN深度学习框架用于数据分析.

主要成果:

  • 在药物类型分类方面,SST-CNN的准确度达到98.55%,在心脏毒性分类方面达到99%.
  • 这些框架在分类各种药物度时显示了98.5%的平均准确性.
  • 在准确性和可靠性方面,超过了传统模型,如反复神经网络 (RNN) 和1D-CNN.

结论:

  • 拟议的STFT-CNN和SST-CNN框架为心脏毒性评估提供了一个范式转变.
  • 这些深度学习模型为药物安全提供了更强大,更有效,更与人类相关的方法.
  • 这些框架的可扩展性承诺将彻底改变药物安全性评估,并减少对患者的伤害.