人工智能辅助的初级和二级代谢标记的识别,用于术后 Delirium
Vladimir A Ivanisenko1,2,3,4, Artem D Rogachev2,5, Aelita-Luiza A Makarova1
1Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences (SB RAS), Novosibirsk 630090, Russia.
International journal of molecular sciences
|November 9, 2024
概括
这项研究使用先进的人工智能识别了手术后痴呆症 (POD) 的关键代谢标志物. 乳酸,伊诺西托和甲基半氨酸能够以99%的准确度预测POD,揭示系统代谢中断.
科学领域:
- 生物化学 生物化学
- 计算生物学 计算生物学
- 神经科学是一个神经科学.
背景情况:
- 术后妄想 (POD) 背后的分子机制尚未完全理解.
- 确定POD可靠的生物标志物对于早期检测和干预至关重要.
研究的目的:
- 用先进的生物信息学方法识别POD的主要和次要的代谢标志物.
- 探索这些标记物在POD分子遗传机制中的作用.
主要方法:
- 使用遗传算法和人工神经网络分析了血清代谢概况.
- 用基因网络重建来研究分子遗传途径.
- 代谢物被分为主要 (预测性) 或次要 (相关性) 标记物.
主要成果:
- 确定L-乳酸,内醇和甲基半氨酸是主要的POD标记物,达到99%的预测精度 (AUC).
- 54个二级标记物,包括GABA和血清素,表明POD患者的代谢模式受到干扰.
- 产生了假设,将基因组POD标志物与通过已识别的代谢物通过代谢失调联系起来.
结论:
- POD涉及代谢过程的系统性干扰,通过特定的初级和二级代谢物概况来表明.
- 该研究引入了一种新的生物信息技术,用于代谢数据分析.
- 这些发现有助于我们更好地了解POD病原体,并为生物标志物发现提供了潜在的机会.
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