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人参提取物对心肌损伤保护作用的靶细胞提取及与 BP 神经网络分类相结合的谱效关系筛选潜在生物活性成分。

Target Cell Extraction and Spectrum-Effect Relationship Coupled with BP Neural Network Classification for Screening Potential Bioactive Components in Ginseng Extract with a Protective Effect against Myocardial Damage.

机构信息

Research Center for Traceability and Standardization of TCMs, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, China.

Jiangsu Key Laboratory of TCM Evaluation and Translational Research, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, China.

出版信息

Molecules. 2024 Apr 28;29(9):2028. doi: 10.3390/molecules29092028.

DOI:10.3390/molecules29092028
PMID:38731522
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11085743/
Abstract

Cardiovascular disease has become a common ailment that endangers human health, having garnered widespread attention due to its high prevalence, recurrence rate, and sudden death risk. Ginseng possesses functions such as invigorating vital energy, enhancing vein recovery, promoting body fluid and blood nourishment, calming the nerves, and improving cognitive function. It is widely utilized in the treatment of various heart conditions, including palpitations, chest pain, heart failure, and other ailments. Although numerous research reports have investigated the cardiovascular activity of single ginsenoside, there remains a lack of systematic research on the specific components group that predominantly contribute to cardiovascular efficacy in ginseng medicinal materials. In this research, the spectrum-effect relationship, target cell extraction, and BP neural network classification were used to establish a rapid screening system for potential active substances. The results show that red ginseng extract (RGE) can improve the decrease in cell viability and ATP content and inhibit the increase in ROS production and LDH release in OGD-induced H9c2 cells. A total of 70 ginsenosides were identified in RGE using HPLC-Q-TOF-MS/MS analysis. Chromatographic fingerprints were established for 12 batches of RGE by high-performance liquid chromatography (HPLC). A total of 36 common ingredients were found in 12 batches of RGE. The cell viability, ATP, ROS, and LDH of 12 batches RGE were tested to establish gray relationship analysis (GRA) and partial least squares discrimination analysis (PLS-DA). BP neural network classification and target cell extraction were used to narrow down the scope of Spectral efficiency analysis and screen the potential active components. According to the cell experiments, RGE can improve the cell viability and ATP content and reduce the oxidative damage. Then, seven active ingredients, namely, Ginsenoside Rg1, Rg2, Rg3, Rb1, Rd, Re, and Ro, were screened out, and their cardiovascular activity was confirmed in the OGD model. The seven ginsenosides were the main active substances of red ginseng in treating myocardial injury. This study offers a reference for quality control in red ginseng and preparations containing red ginseng for the management of cardiovascular diseases. It also provides ideas for screening active ingredients of the same type of multi-pharmacologically active traditional Chinese medicines.

摘要

心血管疾病已成为危害人类健康的常见疾病,由于其高发病率、复发率和猝死风险,已引起广泛关注。人参具有补气、养血、生津、安神、益智等功能,广泛应用于各种心脏病的治疗,如心悸、胸痛、心力衰竭等。虽然有大量研究报告探讨了单一人参皂苷的心血管活性,但对于人参药材中主要发挥心血管功效的特定成分群,仍缺乏系统研究。本研究采用谱效关系、靶细胞提取和 BP 神经网络分类,建立了一种快速筛选潜在活性物质的方法。结果表明,红参提取物(RGE)可改善 OGD 诱导的 H9c2 细胞活力下降和 ATP 含量减少,抑制 ROS 生成和 LDH 释放增加。采用 HPLC-Q-TOF-MS/MS 分析鉴定 RGE 中共有 70 种人参皂苷。采用高效液相色谱法(HPLC)建立了 12 批 RGE 的色谱指纹图谱。在 12 批 RGE 中发现共有 36 种成分。对 12 批 RGE 的细胞活力、ATP、ROS 和 LDH 进行测试,建立灰色关联分析(GRA)和偏最小二乘判别分析(PLS-DA)。采用 BP 神经网络分类和靶细胞提取对谱效分析范围进行缩小,筛选潜在的活性成分。根据细胞实验,RGE 可提高细胞活力和 ATP 含量,减少氧化损伤。然后,筛选出 7 种活性成分,即人参皂苷 Rg1、Rg2、Rg3、Rb1、Rd、Re 和 Ro,并在 OGD 模型中证实了它们对心血管的活性。这 7 个人参皂苷是红参治疗心肌损伤的主要活性物质。本研究为红参及其制剂的质量控制以及心血管疾病的管理提供了参考,也为同类型多药效活性的中药的活性成分筛选提供了思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/0eb8c8a8ba35/molecules-29-02028-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/2137d06c7aa8/molecules-29-02028-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/94f39a1a9c59/molecules-29-02028-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/9a6b08e2feae/molecules-29-02028-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/9357e749f5d9/molecules-29-02028-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/e0b8a1690298/molecules-29-02028-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/05069ec38571/molecules-29-02028-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/0eb8c8a8ba35/molecules-29-02028-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/2137d06c7aa8/molecules-29-02028-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/94f39a1a9c59/molecules-29-02028-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/9a6b08e2feae/molecules-29-02028-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/9357e749f5d9/molecules-29-02028-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/e0b8a1690298/molecules-29-02028-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/05069ec38571/molecules-29-02028-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87a0/11085743/0eb8c8a8ba35/molecules-29-02028-g007.jpg

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