PLS-近红外漫反射光谱法分析磺胺甲基异唑

偏最小二乘（ＰＬＳ）法同近红外漫反射光谱法结合，分析了粉末药品磺胺甲基异唑．讨论了波长对ＰＬＳ定量预测能力的影响．对照样品和试样的预测结果的ＲＳＤ分别为０．１１％和０．５６％，结果令人满意．     

PLS-近红外漫反射光谱法分析安体舒通

运用偏最小二乘（ＰＬＳ）法同近红外漫反射光谱法结合，非破坏分析了粉末药品安体舒通。讨论波长对ＰＬＳ定量预测能力的影响，校正样品和预测样品的预测结果的相对标准误差分别为０．３２０２％和１．３０９６％，结果令人满意     

正交函数-偏最小二乘算法及其在复方制剂分析中的应用

提出了一种由正交函数（ＯＦ） 与偏最小二乘法（ＰＬＳ） 相结合的正交函数 偏最小二乘算法（ＯＦ ＰＬＳ） ,并把它用于撒痛风注射液各组分的同时测定,与偏最小二乘法（ＰＬＳ） 所预测的结果进行比较,两者所测得安替比林、水杨酸钠、咖啡因的平均回收率和相对标准偏差分别为１００－２ ％ ,１－６ ％ ;１００－１ ％ ,０－３７％ ;１００－１ ％ ,０－９６ ％ 和９９－４ ％ ,２－０ ％ ;１００－９ ％ ,１－２ ％ ;９９－８ ％ ,１－５ ％ ．     

微量微生物法测定血清中司帕沙星浓度

目的 建立血清中司帕沙星（ＳＰＬＸ）浓度微生物测定。方法 采用微量微生物法。选用枯草杆菌、大肠杆菌为实验菌种测定ＳＰＬＸ血药浓度。结果 测量枯草杆菌的回收率：（９８．７５～１０５．５０）％,ＲＳＤ为（１．３～５．４）％;大肠杆菌的回收率为（（９５．８８～１０４．００％）,ＲＳＤ为（１．０～６．１）％。结论 用微量生物法测定ＳＰＬＸ血药浓度,操作简便,成本低廉,样品用量少,精密度高,适用于体内药物浓     

应用环丙沙星乳剂治疗烫伤大鼠铜绿假单胞菌感染

采用大鼠１５％深Ⅲ度烫伤铜绿假单胞菌感染模型,动态观察了１％磺胺嘧啶银（ＳＤ－Ａｇ）,０．５％环丙沙星（ＣＰＬＸ）及２％ＣＰＬＸ的治疗效果。伤口细菌量和体内白细胞量的检测结果显示,在抵抗铜绿假单胞菌和提高大鼠生存率方面,２％ＣＰＬＸ优于１％ＳＤ－Ａｇ和０．５％ＣＰＬＸ,与对照组比较有显著性差异（Ｐ＜０．００１）。     

褶合光谱－PLS法同时测定安痛定注射液3组分含量

通过褶合变换获得褶合光谱，以此为基础，结合应用偏最小二乘（ＰＬＳ）法，同时测定安痛定注射液中氨基比林、安替比林及巴比妥的含量，方法简便，结果满意。平均回收率和ＲＳＤ依次分别为：９９．８４％，０．１５％；９９．８７％，０．２１％及１００．２７％，０．３９％。     

诺氟沙星滴耳液的一阶导数分光光度测定

采用一阶导数分光光度法测定复方滴耳液中诺氟沙星的含量，样品不须分离，方法简便，结果满意。平均回收率１００．２４％，ＲＳＤ０．６３％，ｒ＝０．９９９９。     

双波长分光光度法测定新福林滴眼液中二组分的含量

目的 测定新福林滴眼液中二组分的含量。方法：采用双波长分光光度法。结果 实验中分别选择λＳＩ＝２４６ｎｍ λＲＩ＝２５６ｎｍ和λＳ２＝２６６ｎｍ λＲ２＝２８２ｎｍ为测定新福林和尼泊金乙酯的组合波长,其平均回收率分别为１０２．３３％和１００．５６％其ＲＳＤ分别为０．１５％和０．３４％。结论 回收率试验和样品测试结果满意,符合制剂快检要求。     

折光法测定木糖注射液含量

采用折光法测定木糖醇注射液的含量,因素法平均回收率为９９．８５％,ＲＳＤ为０．７６％,回归法平均回收率为９９．６９％,ＲＳＤ为０．８６％,样品测定结果与高碘盐法相近,但本法简易,快速,准确。适用于医院制剂分析。     

乘子罚函数分光光度法测定小儿安中磺胺二甲嘧啶和磺胺脒的含量

目的：建立同时测定小儿安中碘胺二甲嘧啶和磺胺含量的方法。方法：以乘子罚函数法处理多波长分光光度数据。结果：１０分模拟样品测定的平均回收率分别为１００．２１％和９８．３４％，ＲＳＤ分别为０．５１％和０．６２％，对三个实测样品的测定结果与标准方法一致。结论：准确度和精密度均符合要求。     

近红外漫反射光谱法测定阿奇霉素分散片的含量

目的应用近红外漫反射技术和化学计量学的方法对阿奇霉素分散片进行定量分析。方法通过偏最小二乘法建立数学模型,对预测集进行预测,并对实际样品的含量进行测定。结果40个样品经内部交叉验证建立预测模型,内部交叉验证确定系数R2=99.86,内部交叉验证的均方差RM SECV=0.504。用8个样品进行外部验证,预测值与真实值的相关系数达0.9994。预测值的平均回收率为100.2%(RSD=0.85%,n=8),方法精密度RSD=0.89%(n=7),方法稳定性RSD=0.90%(n=7)。结论本方法快速简便,结果准确,适用于对模型涉及企业的药品进行快速检查或质量控制。     

Simultaneous diffuse reflectance infrared determination of clavulanic acid and amoxicillin using multivariate calibration techniques

A method for simultaneous determination of clavulanic acid (CA) and amoxicillin (AMO) in commercial tablets was developed using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and multivariate calibration. Twenty-five samples (10 commercial and 15 synthetic) were used as a calibration set and 15 samples (10 commercial and 5 synthetic) were used for a prediction set. Calibration models were developed using partial least squares (PLS), interval PLS (iPLS), and synergy interval PLS (siPLS) algorithms. The best algorithm for CA determination was siPLS model with spectra divided in 30 intervals and combinations of 2 intervals. This model showed a root mean square error of prediction (RMSEP) of 5.1 mg g(-1). For AMO determination, the best siPLS model was obtained with spectra divided in 10 intervals and combinations of 4 intervals. This model showed a RMSEP of 22.3 mg g(-1). The proposed method was considered as a suitable for the simultaneous determination of CA and AMO in commercial pharmaceuticals products.     

注射用奥美拉唑钠水分含量的近红外漫反射光谱法测定

采用近红外漫反射光谱法对注射用奥美拉唑钠的水分含量进行定量分析.采集62份样品的近红外光谱,采用偏最小二乘法建立数学模型.50个样品经内部交叉验证建立预测模型,内部交叉验证均方差为0.136%;12个样品进行外部验证,外部验证预测均方差为0.074%,预测值与对照值的相关系数为0.9966.平均回收率为99.4%,RSD为3.2%.     

近红外漫反射光谱法结合CP-ANN和PLS高通量分析草麻黄药材

目的:建立草麻黄药材的近红外漫反射光谱高通量分析方法。方法:测量草麻黄样品的近红外漫反射光谱(near infra-red diffuse reflectance spectra,NIRDRS),应用化学计量学技术进行光谱处理和数据预处理,分别建立并验证草麻黄药材的产地和采摘时间判别对向传播人工神经网络(counter-propagation artificial neural network,CP-ANN)模型及麻黄碱和伪麻黄碱含量预测偏最小二乘(partial least square,PLS)模型。结果:草麻黄药材的产地和采摘时间判别CP-ANN模型的验证样品预测准确率分别为100.0%和80.0%;麻黄碱和伪麻黄碱含量预测PLS模型的验证样品预测均方根误差(root mean square errors ofprediction,RMSEPs)小,分别为1.12和0.236,预测值与参考值的相关系数(correlation coefficients)大,分别为0.9721和0.9309。结论:采用所建方法能同时对草麻黄药材的产地和采摘时间进行准确判别,对其麻黄碱和伪麻黄碱的含量进行准确预测。该方法准确、快速,无需特殊的样品处理,也不使用化学试剂。     

近红外漫反射光谱法测定红霉素肠溶片中红霉素A的含量

目的:应用近红外漫反射技术和化学计量学的方法对红霉素肠溶片中的红霉素 A 进行定量分析。方法:通过偏最小二乘法建立数学模型,对预测集进行预测,并对实际样品的含量进行测定。结果:40个校正集样品经内部交叉验证建立校正模型,内部交叉验证确定系数 R~2=99.86,内部交叉验证均方根误差(RMSECV)为0.50。对10个预测集样品进行外部验证,预测均方根误差(RMSEP)为0.493,预测值与真实值的相关系数达0.9995。预测值的平均回收率为100.11%(RSD=0.96%,n=10),方法精密度 RSD 为0.78%(n=8)。方法稳定性 RSD 为0.95%(n=7)。结论:本方法快速简便,结果准确,适用于药品快速检查和质量控制。     

近红外光谱法快速测定山橿药材中球松素含量

目的利用近红外光谱（NIR）技术建立一种山橿中球松素含量的快速分析方法。方法以HPLC分析值为参照,采用近红外漫反射光谱技术采集66份山橿样品的近红外漫反射光谱,结合偏最小二乘法（PLS）建立了球松素含量的定量分析模型。结果所建模型的相关系数（R2）、外部验证均方差（RMSEP）和内部交叉验证均方差（RMSECV）分别为0.992 31、0.076 5和0.450 0;验证集样品的NIR测得值与药典法测得值进行配对T检验,差异无统计学意义。结论本方法操作简便、无污染、结果准确可靠,可用于山橿中球松素含量的快速测定。     

近红外光谱法快速测定右旋糖酐40葡萄糖注射液的含量

目的运用近红外透反射光谱分析技术和化学计量学方法对右旋糖酐40葡萄糖注射液进行无损、快速定量分析。方法以在全国范围内不同企业生产的右旋糖酐40葡萄糖注射液及实验室自制不同质量浓度的样品为分析对象,用光纤探头和液体测样附件测定近红外光谱,用偏最小二乘法(PLS)建立右旋糖酐40和葡萄糖定量模型。结果所建模型具有良好的预测能力,测定验证集中样品的含量,葡萄糖外部验证均方差(RMSEP)为0.749,右旋糖酐40外部验证均方差(RMSEP)为0.74;与药典标准方法相比,NIR法测定葡萄糖平均预测偏差为0.62,平均相对偏差为1.87%,右旋糖酐40平均预测偏差为0.59,平均相对偏差为1.53%。结论该方法快速无损,结果准确,可用于该制剂快速同时检测分析。     

Determination of copolymer ratios of poly(lactide-co-glycolide) using near-infrared spectroscopy

The near infrared (NIR) spectroscopic technique was used to determine copolymer ratios of polylactide-co-glycolide samples. Appropriate quantities of DL-polylactic acid and lactic-co-glycolic acid polymers with 86:14, 75:25, 64:36 and 52:48 lactide to glycolide ratios were dissolved in methylene chloride to obtain 5% (w/w) solutions. NIR spectra of the samples were obtained from the solutions using a Polyol Analyzer operated in the transmittance mode. Linear regression calibration models were generated at 2130 and 2288 nm from the second derivative spectral data obtained from the NIR technique. The lowest and highest standard errors of calibration (SEC) at 2130 nm were 1.29 and 1.63%, whereas those obtained from the calibration models generated at 2288 nm were 2.00 and 2.03%, respectively. Partial least squares (PLS) calibration models were also generated from the second derivative spectral data from 1100 to 2500 nm. The lowest and the highest SEC for the models were 1.46 and 1.53%, respectively. The calibration models were then used to predict the lactide contents of the unknown (test) samples. The highest percent error of prediction was 2.56% for samples with 86% lactide content when the linear regression calibration at 2130 nm was used, whereas the highest percent error of prediction was 1.56% for samples with 64% lactide content when the linear regression calibration at 2288 nm was used. The highest percent error of prediction was 1.73% for samples with 75% lactide content when the two-factor PLS calibration model was used.     

Correlation between chromatographic fingerprint and antioxidant activity of Turnera diffusa (Damiana)

In the present contribution, the partial least squares (PLS) method was used to establish a correlation between the antioxidant activity (obtained by DPPH assay) and chromatographic profiles of TURNERA DIFFUSA extracts. Chromatograms were obtained using HPLC-DAD. A model was constructed using 40 samples with 2550 X variables corresponding to the responses obtained at different times; the Y variables consisted of experimental values of antioxidant activity of each extract (measured as EC??). Prior to this analysis, alignment of chromatograms was performed based on consideration of seven high-intensity signals present in all samples. The PLS1 model was validated by cross-validations; its capacity was evaluated using correlation parameters R2, root mean square error of calibration (RMSEC), and root mean square error of prediction (RMSEP). The best results were achieved with zero order chromatograms using five-point smoothing (R2?=?0.96, RMSEC?=?3.31, and RMSEP?=?7.86). Under these conditions, the optimal number of components was five. The model was applied to the prediction of antioxidant activity of commercial products; no significant differences were found between the experimental and predicted antioxidant activities for 83?% of them.     

Rapid quantification of phenolic acids in Radix Salvia Miltrorrhiza extract solutions by FT-NIR spectroscopy in transflective mode

A rapid method for simultaneous determination of main phenolic acids in Radix Salvia Miltrorrhiza extract solutions was developed using Fourier transform near infrared spectroscopy in transflective mode and multivariate calibration and HPLC-UV as the reference method. Partial least squares (PLS) algorithm was conducted on the calibration of regression models. The multiplicative scatter correction, Norris derivative and second derivative were adopted for the spectral pre-processing, and the number of PLS factors were optimized by leave-one-out cross-validation. The performance of the final model was evaluated according to root mean square error of prediction (RMSEP) and correlation coefficient (R). The R values achieved in the prediction set were above 0.93. The developed models were used for analysis of unknown samples and routine monitoring with satisfactory results. This work demonstrated that NIR spectroscopy combined with PLS algorithm could be used for the rapid determination of the main phenolic acids of Salvia Miltrorrhiza extract solutions.