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人工智能辅助的 lubiprostone 的重新用途缓解了管间纤维化
Anupama Samantasinghar1, Faheem Ahmed1, Chethikkattuveli Salih Abdul Rahim1
1Department of Mechatronics Engineering, Jeju National University, Republic of Korea.
重用药物 lubiprostone 通过抑制关键信号通路,有效地治疗管间纤维化 (TIF). 一种新型近道管在芯片上的模型在验证慢性病的抗纤维菌疗法方面被证明是优越的.
科学领域:
- 腎臟病學 (nephrology) 是一種醫學.
- 生物医学工程 生物医学工程
- 药理学 药理学是指药理学的学科.
背景情况:
- 管间纤维化 (TIF) 是慢性病 (CKD) 进展的主要驱动因素,缺乏有效的治疗方法.
- 目前的临床前模型往往无法准确预测纤维化的药物疗效.
研究的目的:
- 为了研究机器学习识别的重用药物皮质的抗纤维素潜力.
- 为了验证 lubiprostone 的有效性,使用先进的近接管在芯片系统和体内小鼠模型.
主要方法:
- 采用了近端管道在芯片上的模型和单边尿道阻塞 (UUO) 的小鼠模型.
- 评估的TIF生物标志物,包括CTGF,细胞外基质沉积,TGF-β,MMPs,PAI-1,EMT和JAK/STAT信号.
- 结果与传统的二维细胞培养相比较.
主要成果:
- 在芯片模型和UUO小鼠中,比显著降低了TIF生物标志物.
- 靠近管状芯片模型的生理学相关性比2D培养更高.
- 卢比素抑制了TGF-β/Smad,JAK/STAT以及上皮-介质细胞转换 (EMT) 途径.
结论:
- 靠近管状芯片系统是一种高通量,体内类似的模型,用于脏纤维化药物查.
- 重新利用的 lubiprostone 通过向主要的 profibrotic 途径,显示出强大的抗纤维素作用.
- 卢比普罗在治疗TIF和恢复功能方面表现有前途.
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