目的 综合分析丹参SalviaeMiltiorrhizae Radix et Rhizoma-红花Carthami Flos药对不同配比的特征化学成分含量与其抗血栓作用变化规律，优化丹参-红花药对活血化瘀配伍比例。方法 建立丹参-红花药对不同配比（1∶1、1∶2、1∶3、1∶4、1∶5、2∶1、3∶1、4∶1、5∶1）的指纹图谱及特征成分定量测定方法；采用HPLC法结合综合评分法对丹参-红花药对的提取工艺进行考察，确定最佳提取工艺；以斑马鱼模式生物测定不同配比丹参-红花提取物的抗血栓活性；采用主成分分析（principal component analysis，PCA）法整合特征成分含量与抗血栓活性强度，从成分和药效2个层面综合评价丹参-红花药对的最佳配比。结果 9种配比的丹参-红花药对指纹图谱共确定了17个共有峰，其中指认了9种特征成分，分别为羟基红花黄色素A（2号峰）、木犀草苷（3号峰）、山柰酚-3-O-芸香糖苷（4号峰）、槲皮苷（5号峰）、丹酚酸B（8号峰）、二氢丹参酮I（12号峰）、隐丹参酮（14号峰）、丹参酮I（15号峰）、丹参酮II_A（17号峰）；最佳提取工艺为10倍量70%乙醇，回流提取1 h。含量测定结果显示，丹参-红花配伍后相比单味药材，特征成分含量发生明显变化，配伍比例为1∶5时丹参中特有的丹酚酸和丹参酮类成分含量较高，配伍比例为3∶1、4∶1、5∶1时红花中指标性成分羟基红花黄色素A、木犀草苷、山柰酚-3-O-芸香糖苷的含量相对较高，提示丹参-红花共煎会促进有效成分的溶出；抗血栓效应显示，丹参-红花配比为3∶1时具有最好的抗血栓活性，预防血栓率达43.7%。PCA结果显示，丹参-红花配伍“成分-效应”综合评价指标（F值）排序为3∶1＞4∶1＞5∶1＞2∶1＞1∶1＞1∶5＞1∶4＞1∶2＞1∶3，表明3∶1为丹参-红花的最佳配伍比例。结论 通过化学成分分析和体内活性评价，揭示了不同配比丹参-红花药对的特征成分含量变化与抗血栓作用的相关性，通过“成分-效应”综合评价解释最佳配伍比例，为进一步开展该药对的量-效关联性分析奠定了基础，也为临床遣方时确定适宜用量提供参考。

Objective To analyze the correlation between the content changes of characteristic components and its antithrombotic effect in different proportions of the Danshen (Salviae Miltiorrhizae Radix et Rhizoma, SMRR)-Honghua (Carthami Flos, CF) herb pair, and optimize the compatibility ratio of SMRR and CF for promoting blood circulation and removing blood stasis. Methods Fingerprint profiles and quantitative determination methods for characteristic components were established for SMRR-CF herb pair at different ratios (1:1, 1:2, 1:3, 1:4, 1:5, 2:1, 3:1, 4:1, 5:1). The HPLC combined with a comprehensive scoring method was used to determine the optimal extraction process of the SMRR-CF herb pair. The anti-thrombotic activity of the SMRR-CF extracts at different ratios was measured using zebrafish as a model organism. The principal component analysis (PCA) method was used to integrate the content of characteristic components and the intensity of antithrombotic activity, and the optimal ratio of SMRR and CF was comprehensively evaluated from two aspects of composition and efficacy. Results The fingerprint profiles of the SMRR-CF herb pair in nine different ratios collectively identified 17 common peaks, among which nine characteristic components were characterized. These include hydroxysafflor yellow A (peak 2), luteoloside (peak 3), kaempferol-3-O-rutinoside (peak 4), quercitrin (peak 5), salvianolic acid B (peak 8), dihydrotanshinone I (peak 12), cryptotanshinone (peak 14), tanshinone I (peak 15), and tanshinone II_A (peak 17). The optimal extraction process was determined to be maceration with 10 times the amount of 70% ethanol for 1 h by reflux. The content determination showed that the characteristic components changed significantly after the compatibility of SMRR and CF compared with the single herb. When the SMRR-CF ratio was 1:5, decoction yielded the highest concentrations of salvianolic acids and tanshinones derived from SMRR. Conversely, ratios of 3:1, 4:1 and 5:1 produced the greatest amounts of hydroxysafflor yellow A, luteoloside and kaempferol-3-O-rutinoside from CF, indicating that co-decoction facilitates the extraction of bioactive constituents from both herbs. Pharmacodynamic evaluation revealed that the 3:1 ratio exhibited the strongest antithrombotic activity, achieving a thrombosis inhibition rate of 43.7%. Principal-component analysis of the “composition-effect” dataset ranked the comprehensive indices (F-values) as 3:1 > 4:1 > 5:1 > 2:1 > 1:1 > 1:5 > 1:4 > 1:2 > 1:3, confirming that the 3:1 ratio represents the optimal compatibility of the SMRR-CF pair. Conclusion In this study, chemical profiling and in vivo pharmacodynamic evaluation were integrated to elucidate the quantitative relationship between the dynamic changes of characteristic constituents and the antithrombotic efficacy of the SMRR-CF herb pair across different compatibility ratios. An optimal ratio was identified through a “composition-effect”-based comprehensive assessment. These findings not only establish a foundation for subsequent dose-effect investigations of this classic combination, but also offer a rational reference for determining prescription design in latent prescriptions.

R283.6

国家自然科学基金资助项目（82204597）;南京中医药大学自然科学基金项目（XPT82204597）;江苏省研究生科研与实践创新计划项目（KYCX25_2373）