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益肺宣肺降浊方抗血管性痴呆的作用机制研究
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| 篇名： | 益肺宣肺降浊方抗血管性痴呆的作用机制研究 |
| TITLE： | Study on the mechanism of Yifei xuanfei jiangzhuo formula against vascular dementia |
| 摘要： | 目的 探讨益肺宣肺降浊方（YFXF）抗血管性痴呆（VD）的作用机制。方法通过网络药理学方法获取YFXF差异表达作用靶点（YDEGs）；利用列线图模型从YDEGs中筛选高风险基因；基于高风险基因从广义线性、支持向量机、极限梯度上升和随机森林模型中筛选最优机器学习模型。采用双侧颈总动脉闭塞术构建大鼠VD模型，并随机分为模型组、YFXF组（12.18g/kg，以生药总量计），另设假手术组，每组6只。评价YFXF对VD大鼠行为学（以逃避潜伏期和穿越平台次数为指标）、大脑皮层组织病理形态学变化以及分泌磷酸蛋白1（SPP1）/磷脂酰肌醇3激酶（PI3K）/蛋白激酶B（又名Akt）信号通路相关蛋白及SPP1mRNA表达的影响。结果共获得6个YDEGs，其中SPP1、CCL2、HMOX1、HSPB1可能是VD的高风险基因；基于高风险基因的广义线性模型预测准确性最高（曲线下面积为0.954）。与模型组比较，YFXF可显著缩短VD大鼠的逃避潜伏期，显著增加穿越平台次数（P＜0.05）；可改善大脑皮层组织神经元固缩和坏死等病理损伤，显著降低SPP1蛋白及mRNA的表达水平（P＜0.05），显著升高PI3K、Akt蛋白的磷酸化水平（P＜0.05）。结论VD高风险基因SPP1、CCL2、HMOX1和HSPB1可能是YFXF的重要作用靶点；YFXF可能通过下调SPP1蛋白及mRNA的表达、激活PI3K/Akt信号通路来发挥抗VD作用。 |
| ABSTRACT： | OBJECTIVE To investigate the mechanism of Yifei xuanfei jiangzhuo formula （YFXF） against vascular dementia （VD）. METHODS The differentially expressed genes of YFXF （YDEGs） were obtained by network pharmacology. High-risk genes were screened from YDEGs by using the nomogram model. The optimal machine learning models in generalized linear， support vector machine， extreme gradient boosting and random forest models were screened based on high-risk genes. VD model rats were established by bilateral common carotid artery occlusion， and were randomly divided into model group and YFXF group （12.18 g/kg， by the total amount of crude drugs）， and sham operation group was established additionally， with 6 rats in each group. The effects of YFXF on behavior （using escape latency and times of crossing platform as indexes）， histopathologic changes of cerebral cortex， and the expression of proteins related to the secreted phosphoprotein 1 （SPP1）/phosphoinositide 3-kinase （PI3K）/protein kinase B （aka Akt） signaling pathway and the mRNA expression of SPP1 in cerebral cortex of VD rats were evaluated. RESULTS A total of 6 YDEGs were obtained， among which SPP1， CCL2， HMOX1 and HSPB1 may be high-risk genes of VD. The generalized linear model based on high-risk genes had the highest prediction accuracy （area under the curve of 0.954）. Compared with the model group， YFXF could significantly shorten the escape latency of VD rats， significantly increase the times of crossing platform （P＜0.05）； improve the pathological damage of cerebral cortex， such as neuronal shrinkage and neuronal necrosis； significantly reduce the expressions of SPP1 protein and mRNA （P＜0.05）， while significantly increase the phosphorylation levels of PI3K and Akt （P＜0.05）. CONCLUSIONS VD high-risk genes SPP1， CCL2， HMOX1 and HSPB1 may be the important targets of YFXF. YFXF may play an anti-VD role by down-regulating the protein and mRNA expressions of SPP1 and activating PI3K/Akt signaling pathway. |
| 期刊： | 2024年第35卷第18期 |
| 作者： | 卓桂锋；陈炜；张金枝；黄德庆；袁炳茂；蒲珊珊；朱小敏；廖乃彬；苏明阳；陈湘怡；符钰岚；吴林 |
| AUTHORS： | ZHUO Guifeng，CHEN Wei，ZHANG Jinzhi，HUANG Deqing， YUAN Bingmao，PU Shanshan，ZHU Xiaomin，LIAO Naibin，SU Mingyang，CHEN Xiangyi，FU Yulan，WU Lin |
| 关键字： | 益肺宣肺降浊方；血管性痴呆；网络药理学；列线图模型；机器学习模型；SPP1/PI3K/Akt信号通路 |
| KEYWORDS： | Yifei xuanfei jiangzhuo formula； vascular dementia； network pharmacology； nomogram model； machine learning |
| 阅读数： | 1 次 |
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