基于与生物学相关的化学指标预测模型的宜根的质量评级评估
Ke Liu1, Chun-Lu Liu1, Long Wang1
1State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, China.
Phytochemical analysis : PCA
|March 4, 2025
概括
一个新的模型使用与免疫活动相关的化学指标预测了宜 (CR) 的质量等级. 这种综合方法改善了传统中医 (TCM) 的质量评估,以提高临床疗效.
科学领域:
- 药理学 药理学是指药理学的学科.
- 植物化学 植物化学
- 传统中国医学 (TCM) 是一种
背景情况:
- 传统中医 (TCM) 的质量对于临床疗效至关重要.
- 目前用于查雷迪克斯 (CR) 的质量评估方法与疗效没有很好的相关性.
- 现有的方法无法充分反映CR的质量级别.
研究的目的:
- 利用与生物学相关的化学指标开发CR质量分级的预测模型.
- 为评估CR质量制定化学-生物学综合战略.
- 提高TCM质量评估的可靠性.
主要方法:
- 根据免疫活性,CR样品被预先分为三种等级.
- 统计分析 (ANOVA,灰色相关性,皮尔森相关性) 确定了与免疫活性相关的关键化学指标.
- 为了预测质量等级,开发了后勤回归和质量综合评估指数 (QCEI).
主要成果:
- 27批CR成功被分为三个质量等级 (I,II,III).
- 水溶性提取物,多糖和氨基酸与免疫活性有很强的相关性 (灰色相关性> 0.8,皮尔森相关性> 0.4,p < 0.05).
- 后勤回归和QCEI模型都有效地预测了CR质量等级,后勤回归显示出卓越的性能.
结论:
- 本研究提出了第一个化学-生物学综合策略,用于评估CR质量等级.
- 开发的模型为TCM质量评估提供了一种新的方法.
- 这些发现为CR分级提供了更准确的方法,有可能改善其临床应用.
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