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A Simultaneous Quantification Method of Thalassemia Screening Multiple Indicators Using FTIR/ATR Spectroscopy

机译:使用FTIR / ATR光谱法同时定量筛选多种指标的筛选方法

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A simultaneous and rapid quantification method of the thalassemia screening indicators (MCV, MCH and HbA2) in the human blood was discussed by using Fourier transform infrared (FTIR) spectrometer and attenuated total reflection (ATR) techniques. Eight samples of the human blood were collected, MCV, MCH and HbA2 were measured by conventional chemical methods respectively, and it was as the reference chemical value of the calibration model for the spectrum. Each sample distilled water hemolysis, were diluted to 2 times, 3 times, 4 times, 5 times, 6 times hemolytic solution sample respectively, and the whole blood samples had been together a total of 6 groups of 48 samples for spectrometry. To each sample group and each screening indicator, based on the second derivatives of the spectra were calculated by using 11 points Savitzky-Goray smoothing, multiple linear regression (MLR) models were established by using the whole region (4000-600cm~(-1)) and the fingerprint region (1600-900cm~(-1)) respectively. The linear regression model corresponding to each wavenumber was also established, and the optimal single-point model was selected by the prediction effect. In the above calculation process, the predictive value of each sample was calculated by using the leave-one-out cross-validation. The results showed that the optimal single-point model corresponding to each sample group and each screening indicator had all good prediction effect. To the optimal single-point models for the whole blood sample group for the indicators of MCV, MCH and HbA2, which by direct determination, the adopting wavenumbers, root mean square error cross validations (RMSECV), relative root mean square error cross validations (RRMSECV), prediction correlation coefficients (R_P) were 1753cm~(-1), 2.52fl, 2.8%, 0.724; 951cm~(-1), 1.05pg, 3.2%, 0.864; 868cm~(-1), 0.1%, 3.1%, 0.941 respectively.
机译:在人血液中的地中海贫血筛选指标(MCV,MCH和的HbA2)同时和快速定量方法是通过使用傅里叶变换红外(FTIR)光谱仪和衰减全反射(ATR)技术的讨论。的人血液八个样品收集,MCV,MCH和的HbA2通过常规化学方法分别检测,并且它是作为频谱校准模型的参考化学值。每个样品蒸馏水溶血,稀释到2倍,3倍,4倍,5倍,分别为6倍溶血溶液样品,和全血样本已经在一起总共6组48个样品的光谱。向每个样品组,并且每个筛选的指标,基于所述光谱的二阶导数,通过使用11分Savitzky-Goray平滑,多元线性回归(MLR)模型建立通过使用整个区域(4000-600cm〜(计算值-1 ))和指纹区(1600-900cm〜(-1)分别地)。对应于每个波数的线性回归模型,还建立,并通过预测效果选择的最优单点模型。在上述计算过程中,各样品的预测值是通过使用留一法交叉验证计算。结果表明,对应于每个样品组的最佳单点模型,并且每个筛选指示器有所有良好的预测效果。到最佳的单点模型用于MCV,MCH和的HbA2,指标的全血样品基团,其通过直接确定,采用波数,根均方误差交叉验证(RMSECV),相对根均方误差交叉验证( RRMSECV),预测相关系数(R_P)为1753厘米〜(-1),2.52fl,2.8%,0.724; 951厘米〜(-1),1.05pg,3.2%,0.864; 868厘米〜(-1),0.1%,0.941分别3.1%。

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