目的 系统分析经典名方开心散在正常与抑郁模型大鼠体内的入血及入脑成分，初步揭示其抗抑郁作用的药效物质基础。方法 采用慢性不可预知温和应激（chronic unpredicted mild stress，CUMS）法构建抑郁模型大鼠，并通过旷场实验、新物体识别实验、糖水偏好实验和强迫游泳实验进行行为学验证；随后，运用UPLC-Q-Exactive Orbitrap MS/MS技术，对正常组与模型组大鼠ig开心散后血清及脑组织样本进行系统检测与分析。结果 在正常组大鼠血清和脑组织中分别鉴定出143个（47个原型＋96个代谢物）和11个成分；而在抑郁模型组中整体数量显著减少，仅分别鉴定出83个（28个原型＋55个代谢物）和4个成分。其中，在CUMS模型组血清和脑组织样本中均检测到β-细辛醚、人参皂苷Rg₁、人参皂苷Rb₁和远志𠮿酮Ⅲ能直接透过血脑屏障的原型成分。结论 初步明确了开心散在正常和抑郁模型大鼠体内的入血及入脑成分，鉴定出4个关键活性成分，为后续开心散的质量标志物筛选和深入抗抑郁作用机制解析提供了科学实验基础。

Objective To systematically analyze the blood-absorbed and brain-absorbed components of the classical formula Kaixin San (KXS) in normal and depression model rats, and preliminarily elucidate the pharmacological material basis of its antidepressant effect. Methods A depression model rat was established using the chronic unpredictable mild stress (CUMS) method, and behavioral verification was performed through open field test, novel object recognition test, sucrose preference test, and forced swimming test. The components in the serum and brain tissue from normal and model rats after intragastric administration of KXS were comprehensively analyzed by UPLC-Q-Exactive Orbitrap MS/MS. Results In the control rats, 143 (including 47 prototypes and 96 metabolites) and 11 components were identified in serum and brain tissue, respectively. In contrast, the overall number in the depression model rats significantly decreased, with only 83 (including 28 prototypes and 55 metabolites) and 4 components detected in serum and brain tissue, respectively. Among them, four prototype components were confirmed to cross the brain in serum and brain tissue samples of the CUMS model rats, including β-asarone, ginsenoside Rg₁, ginsenoside Rb₁, and polygalaxanthone III. Conclusion This study identified four key active components from the blood-absorbed and brain-absorbed components of KXS in normal and depression model rats, providing experimental evidence for screening quality markers of KXS and in-depth analysis its antidepressant mechanism.

R284.1

合肥综合性国家科学中心大健康研究院新安医学与中医药现代化研究所“揭榜挂帅”项目（2023CXMMTCM014）；安徽省科技厅自然基金项目（2408085MH229）；安徽省科技重大专项项目（202203a07020031）