UPLC法测定藿香正气软胶囊中橙皮苷、和厚朴酚、厚朴酚和苍术素的含量

目的 建立同时测定藿香正气软胶囊中橙皮苷、和厚朴酚、厚朴酚和苍术素的UPLC方法。方法 色谱柱:Acquity UPLC BEH C18柱（100 mm×2.1 mm,1.7 μm）,流动相:乙腈-0.2%甲酸水,梯度洗脱,流速为0.4 mL/min,柱温30 ℃,检测波长284 nm测定橙皮苷,290 nm测定和厚朴酚、厚朴酚,336 nm测定苍术素。结果 橙皮苷、和厚朴酚、厚朴酚和苍术素质量浓度分别在0.025 3~1.012 0、0.021 4~0.854 0、0.024 4~0.976 0、0.0032 5~0.130 0 mg/mL范围内与峰面积呈良好线性关系（r≥0.999 4）,平均加样回收率在97.7%~100.3%（RSD≤1.9%,n=6)。结论 该方法准确、灵敏、专属性强,可用于藿香正气软胶囊的质量控制。      

基于超高效液相色谱-四级杆串联飞行时间质谱联用法的牛奶质量控制和掺假鉴别

目的 建立基于超高效液相色谱-四级杆串联飞行时间质谱联用结合模式识别分析法对牛奶进行质量控制和掺假物质鉴别。方法 样品经高速离心除脂肪,乙腈除蛋白后,取上清,经ACQUITY UPLCTM BEH C18柱分离,Q-TOF MS/MS检测,PCA和PLS-DA对所获数据进行分类分析。结果 牛奶和掺入不同物质的掺假牛奶在BPC图谱和PCA与PLS-DA得分图上可以有很好的区分,能准确筛检出差异物质或掺假物质。结论 UPLC/Q-TOF-MS/MS结合模式识别分析法可用于牛奶的质量控制和掺假鉴别。     

多指标综合加权评分法优选补骨脂-肉豆蔻药对水提工艺研究

目的：采用超高效液相（UPLC）指纹图谱结合多指标综合加权评分法优选补骨脂、肉豆蔻药对水提工艺。方法：采用L₉（3⁴）进行正交试验,选择浸润时间、纯化水用量、提取时间、提取次数为考察因素,以补骨脂素、异补骨脂素、补骨脂乙素、去氢二异丁香酚及补骨脂酚的转移率及超高效液相（UPLC）指纹图谱各特征峰总面积为综合考察指标,采用综合加权评分法进行数据分析,优选出补骨脂-肉豆蔻药对最佳水提工艺。结果：优选出补骨脂-肉豆蔻药对最佳水提工艺为浸润40 min,8倍量水提取3次,每次1 h。结论：优化的工艺合理、可行,有效成分转移率较高,为补骨脂-肉豆蔻药对水提工艺的确定提供了确切依据。     

Development and validation of a rapid UPLC/MS method for the simultaneous determination of I3C,DIM, and related metabolites and its application to pharmacokinetics studies

Indole-3-carbinol (I3C) and diindolylmethane (DIM) are naturally derived dietary phytochemicals with promising anti-cancer properties that have been demonstrated both in vitro and in vivo. Using reversed-phase ultra-performance liquid chromatography(UPLC) coupled with mass spectrometry (MS), a rapid, specific, and high throughput method was developed and validated for the quantification and identification of I3C, DIM, and other I3C metabolites in plasma. Samples containing I3C or DIM and the internal standard 4-methoxy indole (IS) were extracted using a liquid-liquid extraction technique. The mean recovery was 96.21% for I3C and 108.5% for DIM. Separation was achieved using a Waters Acquity UPLC HSS T3, 1.8 µm, 2.1 mm×150 mm column and acetonitrile–water gradient elution. The flow rate was 0.3 mL/min and the run time was 9 min. The limits of detection and quantification for I3C and DIM were 15 ng/mL and 25 ng/mL, respectively. Calibration curves for I3C and DIM were linear (r²>0.99) over a concentration range of 0.025–20 µg/mL. Precision, accuracy, and stability analysis fulfilled the CDER guidelines criteria. The method was successfully applied to the determination of the pharmacokinetic parameters of I3C or DIM after oral, intravenous, or intraperitoneal administration to Sprague Dawley rats. The method described here is superior over existing analytical methods for I3C and its metabolites in terms of sensitivity, speed, and separation.     

Antrodia cinnamomea exerts an anti-hepatoma effect by targeting PI3K/AKT-mediated cell cycle progression in vitro and in vivo

Antrodia cinnamomea is extensively used as a traditional medicine to prevention and treatment of liver cancer. However, its comprehensive chemical fingerprint is uncertain, and the mechanisms, especially the potential therapeutic target for anti-hepatocellular carcinoma (HCC) are still unclear. Using UPLC?Q-TOF/MS, 139 chemical components were identified in A. cinnamomea dropping pills (ACDPs). Based on these chemical components, network pharmacology demonstrated that the targets of active components were significantly enriched in the pathways in cancer, which were closely related with cell proliferation regulation. Next, HCC data was downloaded from Gene Expression Omnibus database (GEO). The Cancer Genome Atlas (TCGA) and DisGeNET were analyzed by bioinformatics, and 79 biomarkers were obtained. Furtherly, nine targets of ACDP active components were revealed, and they were significantly enriched in PI3K/AKT and cell cycle signaling pathways. The affinity between these targets and their corresponding active ingredients was predicted by molecular docking. Finally, in vivo and in vitro experiments showed that ACDPs could reduce the activity of PI3K/AKT signaling pathway and downregulate the expression of cell cycle-related proteins, contributing to the decreased growth of liver cancer. Altogether, PI3K/AKT-cell cycle appears as the significant central node in anti-liver cancer of A. Cinnamomea.     

疏血通注射液UPLC指纹图谱及5种核苷类成分含量测定研究

[目的] 建立疏血通注射液超高液相色谱（UPLC）指纹图谱及尿嘧啶、次黄嘌呤、黄嘌呤、肌苷和鸟嘌呤核苷含量测定的方法。[方法] 采用ACQUITY UPLC®BEH Amide色谱柱（2.1 mm×100 mm，1.7 μm），以0.1%甲酸水-乙腈为流动相进行梯度洗脱，柱温25 ℃，流速0.3 mL/min，检测波长254 nm。建立33批疏血通注射液的UPLC指纹图谱，采用中药色谱指纹图谱相似度评价软件进行相似度分析，同时测定其中5种核苷类成分的含量。[结果] 疏血通注射液指纹图谱及5种核苷类成分含量测定方法的各项方法学考察结果均良好。不同批次疏血通注射液相似度均在0.998以上。33批样品标定了10个共有峰，其中有5个已知峰，分别为尿嘧啶、次黄嘌呤、黄嘌呤、肌苷、鸟嘌呤核苷。该5种核苷类成分的平均含量分别为34.57、153.50、52.76、53.23和14.46 μg/mL。[结论] 建立的疏血通注射液UPLC指纹图谱及含量测定方法稳定可靠、操作简便，可以为疏血通注射液的质量评价提供参考。     

基于UPLC指纹图谱和网络药理学的当归炮制前后差异质量标志物研究

目的 筛选当归Angelicae Sinensis Radix炮制前后差异特征成分，建立当归炮制前后差异质量标志物（quality markers,Q-Marker）的定量分析方法，为当归和当归炭Angelicae Sinensis Radix Carbonisata的质量评价提供依据。方法 采用UPLC法分别构建当归和当归炭的指纹图谱，运用化学模式识别技术筛选当归炭炮制前后的主要差异成分，结合中药Q-Marker“五原则”和网络药理学分析筛选潜在的差异Q-Marker，并进行定量分析。结果 15批当归UPLC指纹图谱共标定19个共有峰，当归炭UPLC指纹图谱共标定10个共有峰，指认7个成分。采用主成分分析（principal component analysis,PCA）可明显区分当归和当归炭；偏最小二乘法-判别分析（partial least squares method-discriminant analysis,PLS-DA）辨识出影响当归与当归炭差异的10个主要色谱峰，按VIP值大小排序依次为峰23、22、10、16、7、3、2、1、4、11。结合中药Q-Marker“五原则...     

UPLC同时测定不同产地白术中3种白术内酯成分的含量

目的:建立UPLC同时测定白术中3种白术内酯成分含量分析方法。方法:样品以甲醇超声提取30 min进行处理。采用超高效液相色谱，以Agilent Poroshell 120 EC-C₁₈(3.0 mm×150 mm, 2.7μm)为色谱柱，流动相水(A)-甲醇(B)梯度洗脱，流速0.5 mL·min^-1,柱温30℃,检测波长分别为220和276 nm,进样量3μL。采用IBM SPSS 27.0软件对24批白术进行聚类分析和主成分分析。结果:3个成分在考察的浓度范围内，浓度与峰面积之间呈良好的线性关系(r>0.999),回收率均在103.05%～106.35%,RSD 2.0%～3.3%。经聚类分析发现，24批白术药材可聚为四大类；经主成分分析发现，2个主成分因子的累计方差贡献率为98.975%(第一主成分、第二主成分的贡献率分别为92.124%、6.601%)。结论:该方法简便、快捷、准确且灵敏度高，对评控白术药材的质量提供参考。     

基于谱效关系的藏药材全缘叶绿绒蒿全草（非花入药部位）抗氧化质量标志物初步研究

目的建立基于谱效关系的藏药材全缘叶绿绒蒿Meconopsis integrifolia全草(非花入药部位)(HMI)的质量标志物研究方法,为其质量控制提供依据。方法测定10批次HMI提取物的UPLC指纹图谱、UPLC-ESI-Q-TOF-MS/MS法对化学成分进行指认,测定10批样品的总抗氧化能力、ABTS自由基清除能力、DPPH自由基清除能力、超氧阴离子自由基抑制能力,采用主成分分析法筛选能更大程度反映HMI提取物的抗氧化能力指标,采用灰色关联度法关联抗氧化能力指标与指纹图谱共有峰的相关性,综合分析筛选质量标志物,HSCCC法分离鉴定所筛选化学成分的结构。结果从HMI提取物指纹图谱确定了29个共有峰,UPLC-ESI-Q-TOF-MS/MS法指认了样品中的18种化学成分,包括16种黄酮类成分和2种生物碱类成分;主成分分析法筛选出DPPH清除能力能更大程度反映HMI提取物的抗氧化能力;灰色关联度分析表明29个共有峰与DPPH清除能力的关联度均大于0.5,综合分析确认槲皮素-3-O-β-D-葡萄糖基-(1→6)-β-D-葡萄糖苷和槲皮素-3-O-[2′′′-O-乙酰基-β-D-半乳糖基-(1→6)-β-D-葡萄糖苷]作为HMI的质量标志物,其中槲皮素-3-O-[2′′′-O-乙酰基-β-D-半乳糖基-(1→6)-β-D-葡萄糖苷]为新化合物。结论基于谱效关系的HMI质量标志物的研究,对阐明药效物质基础、筛选与药效相关的核心质量标志物,保证药材质量的可控性和合理应用有重要意义。     

基于网络药理学和指纹图谱的安宫牛黄丸质量标志物预测与分析

目的 通过网络药理学与指纹图谱预测安宫牛黄丸中的潜在质量标志物（Q-Marker）。方法 应用网络药理学筛选和分析安宫牛黄丸活性成分及临床适应证（卒中、高热昏迷、脑炎、脑出血及癫痫）的作用靶点和通路，并寻找关键活性成分；应用超高效液相色谱（UPLC）构建安宫牛黄丸的指纹图谱，结合网络药理学预测其潜在的Q-Marker，并使用AutoDock Vina软件对潜在的Q-Marker与关键靶点进行分子对接验证。结果 收集得到安宫牛黄丸活性成分128个，经过筛选得到10个核心靶点（STAT3、AKT1、MAPK1等）和7个关键活性成分（小檗碱、槲皮素、汉黄芩素、黄芩素、熊果酸、黄芩苷及麝香酮），涉及炎症反应、细胞免疫、脂质代谢等相关机制。安宫牛黄丸的UPLC指纹图谱，标定22个共有峰，并指认出15个色谱峰，结合网络药理学筛选出的关键活性成分初步预测4个成分为其潜在的Q-Marker，分别是小檗碱、黄芩苷、黄芩素、汉黄芩素，涉及的关键生物通路包括AGEs-RAGE通路、PI3K-Akt通路以及MAPK通路等。结论 借助网络药理学结合UPLC指纹图谱分析预测得到安宫牛黄丸潜在的Q-Marker分别为小檗碱、黄芩苷、黄芩素、汉黄芩素，为其全面质量控制提供依据。