核磁共振技术测试不同性别大鼠尿液代谢物的研究

采用核磁共振波谱技术测试不同性别大鼠尿液代谢物,分析性别因素对大鼠尿液代谢成分的影响.大鼠尿液核磁共振氢谱（1HNMR谱）结果采用主成分分析（principal component analysis,PCA）和正交偏最小二乘判别分析（orthogonal to partial least squares discriminant analysis,OPLS-DA）方法分析,得到不同性别大鼠尿液中的差异性代谢物.PCA分析结果显示2组尿液代谢成分有明显的差异,进一步进行OPLS-DA分析可以判别出2组尿液中具有差异性的代谢物.结果显示,雌性大鼠尿液中的丙氨酸、缬氨酸、鸟氨酸等氨基酸类以及乙酸、硫胺、氨基马尿酸、苯乙胺、氧氨嘧啶等代谢物含量高于雄性大鼠,差异有统计学意义（p〈0.05）.雄性大鼠尿液中的甲胺、二甲胺、三甲胺、肌酸酐、尿囊素、延胡索酸、甲酸等代谢物则明显高于雌性大鼠,差异有统计学意义（p〈0.05）.性别因素对大鼠尿液中的代谢成分有一定的影响.     

非靶向尿液代谢组学方法研究五味子治疗精尿病并发症作用机制

采用超高效液相色谱-串联四级杆飞行时间质谱联用技术(Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry,UPLC/Q-TOF-MS),结合主成分分析技术(Principal component analysis,PCA),进行了五味子治疗糖尿病并发症大鼠尿液代谢组学研究,对五味子治疗糖尿病并发症大鼠后尿液生物标志物变化进行了考察.采用UPLC/Q-TOF-MS方法分析了健康组、糖尿病并发症模型组和五味子给药组的大鼠尿液,采用偏最小二乘法-判别分析(Partial least squares discriminant analysis,PLS-DA)和正交偏最小二乘法-判别分析(Orthogonal partial least squares discriminant analysis,OPLS-DA)载荷图筛选,通过分析对各组分离贡献较大(VIP>1,P°0.05)化合物的串联质谱数据,再经Human Metabolome Data-base(HMDB)等数据库检索,进行质谱信息匹配,尿液中共鉴定出28种潜在生物标记物,其中正谱13种,负谱15种.这些生物标记物主要影响戊糖和葡糖醛酸相互转化通路、核黄素代谢、泛酸和CoA合成、精氨酸和脯氨酸代谢、肠内菌代谢、嘌吟代谢、Vc代谢胆酸合成、色氨酸代谢等通路,五味子从能量代谢、氨基酸代谢、肠内菌代谢、脂类代谢等各个角度发挥治疗糖尿病并发症的作用.从各个通路的相关生物功能分析,五味子治疗糖尿病肾病的作用较强,此外还具有降脂、抗氧化的功效.     

五味子治疗大鼠糖尿病肾病作用机制的血清代谢组学研究

采用基于超高效液相色谱与串联四级杆飞行时间质谱仪(Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry,UPLC/Q-TOF-MS)联用技术的代谢组学方法,通过分析大鼠血清内源性代谢物的变化,研究五味子治疗糖尿病肾病的作用机制。利用高脂高糖饲料喂养并腹腔注射链脲佐菌素(STZ)建立糖尿病大鼠模型。给药12周后,采用试剂盒方法测定尿蛋白、尿肌酐的含量,结果表明五味子水提取物可以显著降低模型动物的尿蛋白含量(p<0.05),对糖尿病大鼠肾病并发症具有一定的改善作用。采用UPLC/Q-TOF-MS方法分析了五味子对糖尿病肾病大鼠的血清代谢轮廓,分析了健康组、模型组和五味子给药组的大鼠血清,采用偏最小二乘法-判别分析(Partial least squares discriminant analysis,PLS-DA)进行数据分析。PLS-DA得分图显示健康组、模型组和五味子组的代谢轮廓有显著差别,根据正交偏最小二乘法-判别分析(Orthogonal partial least squares discriminant analysis,OPLS-DA)载荷图筛选,将对各组分离贡献大的化合物的串联质谱分析数据,经Human Metabolome Database(HMDB)等数据库检索,进行质谱信息匹配,鉴定出黄尿酸、油酰胺、棕榈酰胺、尿酸、5-羟基己酸、硫酸对甲酚、对甲酚葡萄糖苷酸7种内源性代谢物为生物标记物。研究结果表明五味子通过影响色氨酸代谢、嘌呤代谢、肠内菌代谢、脂肪酸代谢等通路对糖尿病肾病发挥治疗作用,其中嘌呤代谢、肠内菌代谢通路可能是五味子发挥治疗作用的重要途径。     

黄芩-栀子配伍治疗糖尿病肾病大鼠的尿液代谢组学研究

采用基于超高效液相色谱与串联四极杆飞行时间质谱仪(Ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry,UHPLC-Q-TOF MS)联用的代谢组学方法,通过分析大鼠尿液内源性代谢物的变化,研究黄芩-栀子药对治疗糖尿病肾病的作用机制。利用高脂高糖饲料喂养并腹腔注射链脲佐菌素(STZ)建立糖尿病大鼠模型。给药12周后,采用UHPLC-Q-TOF MS对正常对照组、模型组、黄芩-栀子药对治疗组的尿液样品进行代谢轮廓分析。利用正交偏最小二乘判别分析(Orthogonal partial least squares discriminant analysis,OPLS-DA)对实验数据进行分析,挑选出对各组分分离贡献较大(VIP>1,p<0.05)的化合物在Human Metabolome Database(HMDB)等数据库进行质谱信息匹配,共鉴定出糖尿病肾病潜在生物标记物31个,给药后回调生物标记物16个。研究结果表明,黄芩-栀子药对通过影响胆汁酸的合成与代谢、尿毒素代谢、能量代谢、色氨酸代谢、苯丙氨酸代谢、酪氨酸代谢等通路对糖尿病肾病起到治疗作用,其中胆汁酸的合成与代谢、尿毒素代谢和能量代谢可能是黄芩-栀子药对发挥治疗作用的主要途径。与单味药相比,配伍后的药对具有了新的药理作用。     

基于气相色谱-飞行时间质谱技术的佐剂性关节炎大鼠尿液代谢组学的研究

采用弗氏完全佐剂(FCA)诱导佐剂性关节炎(AA)大鼠模型,观察大鼠足趾肿胀度和踝关节组织的病理学形态变化。应用气相色谱-飞行时间质谱(GC-TOF MS)技术检测AA大鼠尿液代谢物谱,并对数据进行主成分分析(PCA)、偏最小二乘法-判别分析(PLS-DA)及正交偏最小二乘法-判别分析(OPLS-DA),探讨可能的发病机制。通过变量重要性投影值(VIP>1)和P值(<0.05),筛选出尿液中的差异代谢物。在模型组大鼠的尿液中共发现异柠檬酸、α-酮戊二酸、柠康酸、肌酸、3-羟基丁酸等20种差异代谢物。推断AA代谢组学的发病机制可能与能量代谢、氨基酸代谢、脂肪酸代谢途径有关。     

气相色谱-质谱联用结合化学计量学鉴别再生聚苯乙烯发泡餐盒

建立了气相色谱-质谱联用(Gas chromatography-mass spectrometer,GC-MS)结合化学计量学方法鉴别再生餐盒和新餐盒的方法。发泡餐盒试样经二氯甲烷溶解,加入甲醇沉淀大分子聚合物,采用GC-MS进行分析,并结合主成分分析(Principal component analysis,PCA)和正交偏最小二乘判别分析(Orthogonal par-tial least squares discriminantanalysis,OPLS-DA)等多变量统计分析方法筛选出再生餐盒和新餐盒的差异性物质,建立了再生餐盒和新餐盒的鉴别模型。结果表明,再生餐盒和新餐盒中的主要物质包括聚合残余(苯乙烯单体、二聚体和三聚体)、苯衍生物和添加剂等。OPLS-DA和t检验筛选出41种在含量上具有显著性差异的物质,基于差异性物质建立鉴别模型,初步建立了有效的鉴别再生聚苯乙烯发泡餐盒的方法。     

黄芪口服液降低大鼠顺铂毒性作用机制的尿液代谢组学研究

采用基于液相色谱-飞行时间质谱联用(LC-TOF-MS)技术的代谢组学方法,分析大鼠尿液内源性代谢物的变化,研究黄芪口服液(HO)降低大鼠顺铂(CDDP)毒性的作用机制.采用低剂量多次腹腔注射CDDP的方法建立CDDP染毒大鼠模型,并连续给予16天HO.于第18天收集正常对照(Control)组、顺铂模型(CDDP)组和黄芪口服液(HO)组大鼠的24 h尿液, 进行LC-TOF-MS分析,以获取尿液代谢物组数据集,对所得数据进行主成分分析(PCA)和正交偏最小二乘法-判别分析(OPLS-DA)等多元统计分析,以筛选潜在生物标志物.于第20天采集大鼠血清测定肌酐和尿素氮水平.血清指标测定结果表明, HO可以显著降低CDDP染毒大鼠的肌酐和尿素氮水平(p<0.05).PCA得分图显示,3组可分别聚类,HO组位于Control组和CDDP组中间,表明HO可部分改善CDDP所致大鼠尿液代谢产物的异常变化.综合OPLS-DA分析、t检验和倍数变化分析结果,最终共筛选并初步鉴定出35个尿液代谢产物作为HO减毒相关的潜在生物标记物.代谢通路分析结果表明,HO可通过纠正体内氨基酸代谢、能量代谢和核苷酸代谢等通路的紊乱,降低CDDP所致机体毒性.     

血清代谢轮廓分析在评估乙肝肝硬化病程中的应用

采用高效液相色谱-质谱联用(HPLC-MS)作为代谢组学研究平台,分析不同Child-Pugh分级肝硬化病人和健康人群的血清标本,获取代谢轮廓.对数据进行主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA),用各组病例的80%作为训练数据构建疾病的OPLS-DA区分模型,以剩余的20%作为检测数据,观察模型对...     

肝细胞癌、肝硬化患者血清中代谢物组研究

采用核磁共振方法检测肝硬化、肝细胞癌(简称肝癌)患者和健康人血清中代谢物,研究3组血清代谢物组的差异.利用偏最小二乘法-判别式分析(partial least square-discriminant analysis, PLS-DA)对NMR谱数据进行模式识别分析,探讨利用基于1H NMR代谢组学技术诊断肝癌的可行性.结果表明,与健康人相比,肝硬化、肝癌患者血清中脂质(低密度脂蛋白和极低密度脂蛋白)、胆碱、乙酰乙酸等含量减少,谷氨酰胺、丙酮酸、苯丙氨酸、酪氨酸等含量增加.PLS-DA分析结果显示肝癌患者可与健康人、肝硬化患者鉴别开来,肝癌诊断灵敏度达921%,假阳性率为5.7%,优于血清甲胎蛋白(alpha-fetoprotein, AFP)检测.研究结果表明,基于1H NMR代谢组学技术结合PLS-DA的方法具有灵敏、准确、重复性好等优点,有助于肝癌早期诊断.     

高效液相色谱指纹图谱及随机森林应用于湖南安化黑茶水溶性成分的研究

建立了适用于湖南安化黑茶的高效液相色谱指纹图谱分析方法。样品用水在90℃恒温水浴中浸提20min,以C18色谱柱(250 mm×4.6 mm,5μm)分离,甲醇-0.1%磷酸溶液为流动相梯度洗脱,检测波长为270nm,流速为1.0 m L/min,黑茶的各种组分得到较好分离,共确定18个色谱峰作为安化黑茶的特征指纹峰,并通过对照品分析对其中12个峰进行确证。运用相似度评价、主成分分析、正交偏最小方差判别分析(Orthogonal partial least squares discriminant analysis,OPLS-DA)和随机森林法对78个黑茶样品指纹图谱进行了化学模式识别研究和变量重要性判定。结果表明联合指纹图谱分析法和随机森林法可有效区分湖南安化黑茶和其他产地的黑茶。该方法操作简单,精密度、稳定性和重现性良好,为安化黑茶的鉴别和质量控制提供了实验依据。     

超高效液相色谱/飞行时间质谱法分析尿液中的代谢物用于区分人类性别的研究

尿中的代谢产物可以反映生命个体的生理状态。为了考察在非严格控制条件下(即对志愿者的饮食、生活方式以及样品采集时间等诸多条件不加以控制)基于尿中代谢物的指纹图谱对男女性别进行区分的可行性,采用超高效液相色谱/飞行时间质谱(UPLC/TOF-MS)联用技术分析了31个随机尿样,并用主成分分析法（PCA）和偏最小二乘法判别分析（PLS-DA）两种数据处理方法对数据进行处理,与PCA法比较,PLS-DA法能提高分类效果,并筛选出4种可能的与性别相关的生物标记物。研究结果表明,UPLC/MS联用技术通量高,数据量丰富;模式识别数据处理方法适合于从大量数据中提取信息,两者的结合有利于代谢组学的研究。     

基于近红外光谱和OPLS-DA的不同牌号卷烟分类识别方法研究

为了对卷烟牌号进行准确分类鉴别,提出了一种基于近红外光谱(NIRS)分析技术结合有监督的模式识别快速鉴别卷烟牌号的新方法。利用标准正态变量变换(SNV)、多元散射校正(MSC)、一阶导数(FD)、二阶导数(SD)和Savitzky-Golay平滑(SG)及其相结合的光谱预处理方法对烟丝光谱进行预处理,通过近红外光谱结合主成分分析(PCA)、偏最小二乘判别分析(PLS-DA)和正交偏最小二乘判别分析(OPLS-DA) 3种模式识别方法对不同牌号烟丝进行分类识别研究,并采用分类识别正确率作为评价指标。实验结果表明：(1)烟丝近红外光谱主成分得分图交叉重叠,区分不明显,PCA无法识别出5种牌号的成品烟丝;(2)烟丝光谱经MSC+FD预处理后的PLS-DA模型可得到较好的识别效果,校正集和测试集的分类识别正确率分别为100%和98.3%;(3)烟丝光谱经MSC+SD预处理后的OPLS-DA模型的模式识别效果最好,模型对自变量拟合指数(R2X）,因变量的拟合指数(R2Y)和模型预测指数(Q2)分别为0.485、0.907 和0.748,近红外光谱校正集和测试集的分类识别正确率均为100%。说明近红外光谱技术结合有监督模式识别方法OPLS-DA建立的烟丝牌号分类模型具有高效快速、准确无损的优点,为卷烟烟丝分类提供了一种新的快速鉴别方法。     

A Comparative Study of Elution Gradients in UPLC-TOF-MS-Based Metabonomics Research

Serum and urine samples from patients with type 2 diabetes mellitus and control samples were analyzed by UPLC-TOF-MS; fast and slow separation gradients were compared using both positive and negative ionization modes. The resulting data were analyzed using partial least squares discriminant analysis (PLS-DA), and models were developed to differentiate between patient and control samples. The models were evaluated using external test sets to classify their predictive ability. Under both fast and slow gradient conditions, the PLS-DA models generated using serum samples were more robust than those generated using urine samples, and the positive ionization mode produced better differentiation and higher classification rates than negative ionization mode. In addition, fast gradient conditions were found to have a comparable ability for differentiation to slow gradient conditions.     

基于超高效液相色谱-四极杆飞行时间质谱联用技术的血瘀模型大鼠血浆代谢组学分析

采用盐酸肾上腺素加冰水浴建立急性血瘀大鼠模型，使用超高效液相色谱-四极杆飞行时间质谱（UPLC-Q-TOF/MS）检测空白对照组与血瘀模型组中血浆代谢物，用主成分分析（PCA）、有监督偏最小二乘法判别分析（PLS-DA）及正交偏最小二乘法判别分析（OPLS-DA）对代谢组学数据进行多维统计分析，筛选潜在生物标志物。与对照组相比，在血瘀模型组大鼠血浆中检测出46个差异代谢物，血瘀模型组中乙酰胆碱、N6，N6，N6-三甲基-L-赖氨酸、胞嘧啶、乙酰肉碱等21个代谢物显著上调，吲哚丙酸、LysoPC（14：0）等25个代谢物显著下调，可能与脂质代谢、半乳糖代谢、亚油酸代谢、不饱和脂肪酸生物合成、糖酵解、花生四烯酸代谢等通路有关。代谢产物可作为血瘀证研究中的重要标记物，该研究结果有助于揭示血瘀证的发病机制，可为临床血瘀疾病的诊断及选用药物治疗提供思路，为后续治疗手段提供参考依据。     

蟾酥急性毒性的代谢组学研究

本文中,我们运用代谢组学方法结合心电图分析对蟾酥导致的大鼠急性毒性进行了研究,通过超高效液相色谱-飞行时间质谱建立了大鼠血清的代谢指纹谱,采用主成分分析和正交偏最小二乘法判别分析法分析了对照组和各给药组之间的代谢物谱差异,通过变量重要性投影和T检验选取潜在的生物标志物,结合质谱同位素分析、数据库检索以及标准品对潜在生物标志物进行了鉴定。结果表明,蟾酥可导致心脏心率减慢、心律失常、甚至出现心肌梗塞现象,其导致心脏损伤的原因可能是通过阻碍自由脂肪酸再酰化或激活蛋白激酶通路干扰了脂质代谢,这对于阐述蟾酥毒性作用机理提供了新思路。     

Fecal metabolome profiling of liver cirrhosis and hepatocellular carcinoma patients by ultra performance liquid chromatography-mass spectrometry

Fecal metabolome of healthy humans and patients suffering from liver cirrhosis and hepatocellular carcinoma (HCC) were studied using ultra performance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF MS). Metabolic features detected by the method were then statistically treated using partial least squares to latent structure-discriminant analysis (PLS-DA) models to discriminate between healthy and diseased states. PLS-DA was also used to discriminate between cirrhosis and HCC stressed fecal metabolomes and to identify potential biomarkers for cirrhosis and HCC that are expressed at significantly different amounts in fecal metabolomes. Score plots of pattern recognition analysis distinguished liver cirrhosis and HCC patients from healthy humans. Based on the variable of importance in the project (VIP) values and S-plots, six metabolites were considered as potential biomarkers with a strong increase in lysophosphatidylcholines and a dramatic decrease in bile acids and bile pigments in patients with liver cirrhosis and HCC in comparison with healthy humans. Results demonstrate the potential of UPLC-MS as an efficient and convenient method that can be applied to screen fecal samples and aid in the early diagnosis of cirrhosis and hepatocellular carcinoma.     

Characterization of Gasoline by Raman Spectroscopy with Chemometric Analysis

A rapid Raman spectroscopy protocol is reported to classify gasoline according to its distributor and to identify and quantify common adulterants. Gasoline from three distributors was collected from 19 stations in São Paulo, Brazil. Principal component analysis (PCA) showed specific clusters for each distributor, and partial least squares discriminant analysis (PLS-DA) correctly identified the origin of the samples. To evaluate the technique for the identification and quantification of the adulterants, authentic samples from each distributor were fortified at levels from 2.5 up to 25.0% (v/v) using ethanol, methanol, toluene, and turpentine to obtain 120 altered samples. PCA showed clear separation among the samples with the adulterants and PLS-DA precisely identified the adulterants (478 in 480 predictions by cross-validation), irrespective of the distributor and the concentration. One classification model was used to characterize all distributors. To quantify the adulterants, 36 multivariate calibration models were constructed using partial least squares (PLS), interval PLS, and PLS genetic algorithm for each distributor and for each adulterant. Cross-validation errors of less than 5.0% were obtained for all adulterants regardless of the distributor. Raman spectroscopy and multivariate analysis were shown to be powerful for rapid and inexpensive for the characterization of gasoline origin and the identification and quantification of common adulterants.     

Multivariate analysis of laser-induced breakdown spectroscopy chemical signatures for geomaterial classification

A large suite of natural carbonate, fluorite and silicate geological materials was studied using laser-induced breakdown spectroscopy (LIBS). Both single- and double-pulse LIBS spectra were acquired using close-contact benchtop and standoff (25 m) LIBS systems. Principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to identify the distinguishing characteristics of the geological samples and to classify the materials. Excellent discrimination was achieved with all sample types using PLS-DA and several techniques for improving sample classification were identified. The laboratory double-pulse LIBS system did not provide any advantage for sample classification over the single-pulse LIBS system, except in the case of the soil samples. The standoff LIBS system provided comparable results to the laboratory systems. This work also demonstrates how PCA can be used to identify spectral differences between similar sample types based on minor impurities.