基于近红外光谱的人工神经网络研究STR基因座分型方法

以D16S539基因座的3种(9-9、9-11、11-11)基因型为例,设计引物扩增包含该多态性位点的1段DNA片段,获得了3种基因型建模样本各50个.基于近红外光谱(NIRS)结合误差反向传播人工神经网络(BPANN)建立了测定短串联重复序列(STR)基因型的判别模型,所建立的判别模型的校正均方根残差和预测集均方根误差分别为0.082 5、0.072 5,预测准确率均为100%.该方法不需任何前处理,只需一步PCR扩增和NIRS检测即可实现STR基因型判别,具有简单、快速、低成本等优点.     

基于紫外光谱-支持向量机对STR的基因分型

利用紫外光谱结合支持向量机(SVM)模式识别原理建立了短串联重复序列(STR)的分型方法.以D5S818基因座的10-10、11-13和13-13三个基因型为研究对象,优化了包含该多态性位点的DNA片段的聚合酶链反应(PCR)的扩增条件和紫外光谱检测条件,获得了优化条件下的待测样本紫外光谱.以该光谱为识别变量,建立了该...     

Massively parallel sequencing of STRs using a 29-plex panel reveals stutter sequence characteristics

Massively parallel sequencing of forensic STRs simultaneously provides length-based genotypes and core repeat sequences as well as flanking sequence variations. Here, we report primer sequences and concentrations of a next-generation sequencing (NGS)-based in-house panel covering 28 autosomal STR loci (CSF1PO, D1GATA113, D1S1627, D1S1656, D1S1677, D2S441, D2S1776, D3S3053, D5S818, D6S474, D6S1017, D6S1043, D8S1179, D9S2157, D10S1435, D11S4463, D13S317, D14S1434, D16S539, D18S51, D18S853, D20S482, D20S1082, D22S1045, FGA, TH01, TPOX, and vWA) and the sex determinant locus Amelogenin. Preliminary evaluation experiments showed that the panel yielded intralocus- and interlocus-balanced sequencing data with a sensitivity as low as 62.5 pg input DNA. A total of 203 individuals from Yunnan Bai population were sequenced with this panel. Comparative forensic genetic analyses showed that sequence-based matching probability of this 29-plex panel reached 2.37 × 10⁻²⁹, which was 23 times lower than the length-based data. Compound stutter sequences of eight STRs were compared with parental alleles. For seven loci, repeat motif insertions or deletions occurred in the longest uninterrupted repeat sequences (LUS). However, LUS and non-LUS stutters co-existed in the locus D6S474 with different sequencing depth ratios. These results supplemented our current knowledge of forensic STR stutters, and provided a sound basis for DNA mixture deconvolution.     

基于尺度不变特征变换筛选稳定特征波长的近红外光谱模型传递方法

该研究利用一维尺度不变特征变换(SIFT)算法寻找烟叶近红外光谱(Near infrared spectroscopy,NIRS)的稳定特征波长,根据样品精密度测试光谱筛选的波长计算重现率和重现度,采用L_9(3~3)正交表优化SIFT算法中的相关参数,使重现率和重现度尽可能高。基于优化的参数和主机上10个代表性样品的光谱,筛选出10个稳定特征波长集合,以这些波长集合并集的光谱响应为自变量,采用偏最小二乘(PLS)方法构建烟叶总植物碱NIRS模型(简称SIFT-PLS)。该模型直接传递到3台从机后,对3台从机样品总植物碱的平均相对预测误差(MRE)均满足小于6%的企业内控要求,而全光谱模型(WW-PLS)直接转移后仅1台从机的MRE满足要求,经分段直接校正(PDS)方法校正从机光谱后,WW-PLS模型也仅对1台从机的MRE小于6%。采用SIFT算法筛选稳定特征波长建立的NIRS模型可在3台从机直接共享,无需转移集,不需对从机光谱或光谱模型进行校正,实现了真正意义的无标样NIRS模型的直接转移。     

基于近红外光谱分析技术的食品包装塑料的定性分析

该文基于近红外漫反射光谱分析技术对食品包装材料聚乙烯、聚丙烯进行定性判别试验研究,选取不同波段范围、采用不同光谱预处理方法,使用主成分分析法(Principal component analysis,PCA)结合SIMCA、贝叶斯判别、K-近邻3种模式识别方法建立定性预测模型,并根据正确识别率比较了各模型预测性能。结果表明：使用SIMCA方法、贝叶斯判别、K-近邻3种方法建立的定性校正模型均在1 050~1 550 nm波长范围内效果较好;采用矢量归一化、标准正态变量变换、中心化、滑动均值滤波、多项式平滑滤波、一阶微分6种光谱预处理方法和上述3种模式识别方法对塑料样品近红外光谱进行了数据处理,其中在1 050~1 550 nm范围内,主成分因子数为3,采用原始光谱建立的K-近邻定性校正模型较优,对样品校正集和预测集的正确识别率均为100%。可为食品包装材料聚乙烯、聚丙烯的快速鉴别研究提供参考。     

废旧涤/棉混纺织物近红外定量分析模型的建立及预测

将中红外光谱筛选出的598个纯涤、纯棉及涤/棉混纺样本采用GB/T 2910.11-2009法测定其涤、棉准确含量,其中校正集样本252个,验证集样本346个。使用便携式近红外光谱仪获取样本的原始近红外光谱(NIRS)。校正集样本依据回归系数的分布趋势和范围选取最佳建模谱区,并采用差分一阶导、S-G平滑和均值中心化相结合的方法对原始光谱进行预处理,利用偏最小二乘法(PLS)建立涤/棉混纺织物中涤含量的近红外(NIR)定量分析模型。同时分析了样本颜色对NIRS的影响,探讨了斜线光谱样本、奇异样本和不同组织结构织物对模型预测效果的影响。结果表明:利用PLS法建立的涤/棉混纺织物定量分析模型最优组合包含1个光谱区间和9个主成分因子,校正集相关系数(RC)为0.998,标准偏差(SEC)为0.908。为验证所建模型的有效性和实用性,对346个未参与建模的涤棉样本进行了预测,并将预测结果与国标法测定值进行方差分析,两种方法结果无显著差异,预测正确率达97%以上。模型的建立为废旧涤/棉混纺织物快速、无损分拣提供了基础数据库。     

Developmental validation of the Microreader™ 20A ID system

The Microreader? 20A ID system is designed for forensic applications such as personal identification, parentage testing, and research. It includes 13 combined DNA index system (CODIS) short tandem repeat (STR) loci (CSF1PO, FGA, TH01, TPOX, vWA, D3S1358, D5S818, D7S820, D8S1179, D13S317, D16S539, D18S51, and D21S11), three expanded CODIS STR loci (D12S391, D19S433, and D2S1338), three non‐CODIS STR loci (D6S1043, Penta D, and Penta E), and the amelogenin locus in one reaction with a six‐dye fluorescent (FAM, HEX, TAMAR, ROX, PUR, and QD550) analysis system. In this study, the Microreader? 20A ID system was validated according to the Scientific Working Group on DNA Analysis Methods validation guidelines for forensic DNA Analysis methods and Chinese national standard, including PCR‐based studies, sensitivity study, precision, and accuracy evaluation, stutter calculation, inhibitor tests, species specificity, and DNA mixture studies. Our results suggest that the Microreader? 20A ID system is a useful tool for personal identification and parentage testing.     

Genetic polymorphisms of 20 short tandem repeat loci from the Han population in Henan,China

The aim of this study was to investigate the genetic polymorphism of 20 short tandem repeat (STR) loci including D1S1656, D2S1338, D3S1358, D5S818, D6S1043, D7S820, D8S1179, D12S391, D13S317, D16S539, D18S51, D19S433, D21S11, CSF1PO, FGA, Penta D, Penta E, TH01, TPOX, and vWA in Han population of Henan, China and to assess its value in forensic science. Genomic DNA was extracted from 274 blood samples of unrelated healthy individuals in the Henan Han population. Alleles were amplified with PowerPlex® 21 system kit and PCR products were detected with ABI3130 genetic analyzer (Applied Biosystems) and the data were analyzed with modified PowerStats v1.2. A total of 229 alleles were observed in this Han population and the allelic frequencies ranged from 0.0020 to 0.5090 in the present study. Observed genotype distributions for each locus do not show deviations from Hardy–Weinberg equilibrium expectations (p < 0.05). The combined power of discrimination, combined power of exclusion, and combined matching probability of this 20 STR loci were 0.999999999, 0.999999994603, and 4.0433 × 10^?24, respectively. The 20 STR loci are highly polymorphic in the Han population of Henan, China and they may be of great value in forensic science and human population genetics.     

近红外光谱法同时测定废水中化学需氧量和生化需氧量

采用120个废水样品的近红外透射光谱结合偏最小二乘法,分别建立了废水中化学需氧量和生化需氧量的预测模型,并对光谱数据预处理方法和异常值诊断进行了讨论。所建的废水中化学需氧量和生化需氧量的预测模型相关系数分别为0.9542和0.9652;模型的预测相对偏差分别为25.24mg·mL-1和12.13mg·mL-1;预测范围分别为28.4～528.0mg·mL-1和16.0～305.2mg·mL-1。通过对模型进行t-检验,在显著性水平大于0.05的条件下,其测定结果与标准方法的测定结果对比,两者无显著性差异。     

Constraints on supramolecular structure in amyloid fibrils from two-dimensional solid-state NMR spectroscopy with uniform isotopic labeling

We show that strong constraints on supramolecular structure in amyloid fibrils can be obtained from solid-state nuclear magnetic resonance measurements on samples with uniformly 13C-labeled segments. The measurements exploit two-dimensional (2D) 13C-13C exchange spectroscopy in conjunction with high-speed magic angle spinning, with proton-mediated exchange of 13C nuclear spin magnetization as recently demonstrated by Baldus and co-workers (J. Am. Chem. Soc. 2002, 124, 9704-9705). Proton-mediated 2D exchange spectra of fibrils formed by residues 16-22 of the 40-residue Alzheimer's beta-amyloid peptide show strong nonsequential, intermolecular cross-peaks between alpha-carbons that dictate an antiparallel beta-sheet structure in which residue 16+k aligns with residue 22-k. The strong alpha/alpha cross-peaks are absent from conventional, direct 2D exchange spectra. Proton-mediated 2D exchange spectra of fibrils formed by residues 11-25 indicate an antiparallel beta-sheet structure with a pH-dependent intermolecular alignment. In contrast, proton-mediated 2D exchange spectra of fibrils formed by the full-length beta-amyloid peptide are consistent with a parallel beta-sheet structure. These data show that the supramolecular structure of amyloid fibrils is not determined by the amino acid sequence at the level of 7-residue or 15-residue segments. The proton-mediated 2D exchange spectra additionally demonstrate that the intermolecular alignment in the beta-sheets of these amyloid fibrils is highly ordered, with no detectable evidence for "misalignment" defects.     

Development of a univariate calibration model for pharmaceutical analysis based on NIR spectra

Near-infrared spectroscopy (NIRS) has been widely used in the pharmaceutical field because of its ability to provide quality information about drugs in near-real time. In practice, however, the NIRS technique requires construction of multivariate models in order to correct collinearity and the typically poor selectivity of NIR spectra. In this work, a new methodology for constructing simple NIR calibration models has been developed, based on the spectrum for the target analyte (usually the active principle ingredient, API), which is compared with that of the sample in order to calculate a correlation coefficient. To this end, calibration samples are prepared spanning an adequate concentration range for the API and their spectra are recorded. The model thus obtained by relating the correlation coefficient to the sample concentration is subjected to least-squares regression. The API concentration in validation samples is predicted by interpolating their correlation coefficients in the straight calibration line previously obtained. The proposed method affords quantitation of API in pharmaceuticals undergoing physical changes during their production process (e.g. granulates, and coated and non-coated tablets). The results obtained with the proposed methodology, based on correlation coefficients, were compared with the predictions of PLS1 calibration models, with which a different model is required for each type of sample. Error values lower than 1-2% were obtained in the analysis of three types of sample using the same model; these errors are similar to those obtained by applying three PLS models for granules, and non-coated and coated samples. Based on the outcome, our methodology is a straightforward choice for constructing calibration models affording expeditious prediction of new samples with varying physical properties. This makes it an effective alternative to multivariate calibration, which requires use of a different model for each type of sample, depending on its physical presentation.     

中药材三七中皂苷类成分的近红外光谱快速无损分析新方法

提出了用近红外漫反射光谱快速无损测定三七中皂苷类成分的新方法采用 HPLC分析了中药材三七固皂昔R_1,人参皂苷Hg_1,Rb_1和Rd的含量,用吸附树脂 比色法测定了三七总皂苷（PNS）的含量,共获得R_1,Bg_1,Rb_1,Rd,PNS的含 量范围分别为1,58-5．08,21,68-46.13,11.46-40.41粉．在3500-1100cm~(-1) 扫描样品,以交叉验证误差均方根（RMsECV）为指标,通过筛选,近红外波段和光 谱预处理方法．采用偏最小二乘算法建立了近红外光谱与5个组分PHLC分析值之间 的校正模型,预测了8个未知样本．R_1,Rg_1,Rb_1,Rd及PNS校正模型的RMSECV 分别为0．40,1.47,1.94,0RMSEP分别为0．53,3．15,2．14,0．70,9．03． 该方法快速无损,结果可靠,为中药材复杂体系中化学组分的测定提供了新的绿色 分析手段．     

Development and validation of a novel SiFaSTRTM 23‐plex system

Human identification and paternity testing are usually based on the study of STRs depending on their particular characteristics in the forensic investigation. In this paper, we developed a sensitive genotyping system, SiFaSTR^? 23‐plex, which is able to characterize 18 expanded Combined DNA Index System STRs (D3S1358, D5S818, D2S1338, TPOX, CSF1PO, TH01, vWA, D7S820, D21S11, D10S1248, D8S1179, D1S1656, D18S51, D12S391, D19S433, D16S539, D13S317, and FGA), three highly polymorphic STRs among Chinese people (Penta D, Penta E, and D6S1043), one Y‐chromosome Indel and amelogenin using a multiplex PCR; the PCR amplified products were analyzed using the Applied Biosystems 3500 Genetic Analyzer. Full genotyping profiles were obtained using only 31.25 pg of control DNA; various case‐type specimens, as well as ten‐year‐old samples were also successfully genotyped. Additionally, in the validation studies, this multiplex was demonstrated to be human‐specific and compatible with the interference of multiple PCR inhibitors. The system also enabled the detection of mixtures, and complete profiles could be obtained at the mixed ratios of 1:1, 1:3, and 3:1. The development and validation study here illustrated that the SiFaSTR^? 23‐plex system is accurate, powerful, and more sensitive than many other systems. What's more, the population data in our study not only illustrated that this 23‐plex typing system was straightforward and efficient but also expanded the Chinese STR database, which could facilitate the appropriate application of the 23 genetic markers in forensic genetics, especially in the Chinese population.     

UV–化学模式识别不同产地的丹参

建立由UV–化学模式识别法评价丹参质量的方法。分别用正己烷、乙酸乙酯、水、乙醇提取不同产地的丹参,并测绘其紫外光谱。取紫外光谱各波长的吸光度为特征数据,进行主成分分析、聚类分析,对不同产地丹参质量的差异进行了评价。不同溶剂提取液的光谱聚类结果有所差异,可将不同产地丹参聚为3类。UV–化学模式识别技术可以从整体上反应丹参所含成分的差异,可为丹参质量控制与评价提供依据。     

纹党参与白条党参红外光谱的SIMCA聚类鉴别方法研究

以纹党参和白条党参的红外光谱为聚类分析的对象,研究了红外光谱结合SIMCA聚类分析法对纹党参和白条党参进行识别与分类的可行性.选取400 ～2 000 cm~(-1)范围内的光谱,通过基线补偿(Offset)和散射校正(MSC)等预处理后,采用SIMCA聚类分析法建立识别模型.结果表明,所建模型对纹党参和白条党参的识别率分别达92%和96%,拒绝率均为100%.用盲样对所建模型进行了测试,测试结果全部正确.该法可实现对纹党参和白条党参的快速鉴别.     

近红外光谱法快速测定附子中6个生物碱的含量

应用近红外光谱(NIRS)技术结合偏最小二乘(PLS)和最小二乘支持向量机(LS-SVM)建立了附子中多指标成分的快速无损检测方法。选取38批样品建立了同时测定附子样品中6种成分含量的高效液相色谱(HPLC)方法;通过采集附子样品的NIRS图,分别采用PLS和LS-SVM建立了各个成分HPLC测定值与NIRS图的定量校正模型。所建立的苯甲酰新乌头原碱、苯甲酰乌头原碱、苯甲酰次乌头原碱、新乌头碱、次乌头碱、乌头碱、单酯型生物碱总量和双酯型生物碱总量LS-SVM模型的相对预测偏差(RPD)分别为3.3、3.2、4.1、7.7、8.8、7.6、4.0和8.6;验证集相关系数(rpre)分别为0.9486、0.9475、0.9668、0.9909、0.9946、0.9969、0.9669和0.9927,且LS-SVM模型优于PLS模型,说明NIRS模型验证集与HPLC测定值具有良好的非线性关系,模型预测效果良好。采用NIRS技术结合LS-SVM模型可以快速对附子中的上述6个生物碱含量以及单酯型生物碱总量和双酯型生物碱总量进行检测,方法操作简便,对控制附子中的生物碱含量具有一定的指导作用。     

Analysis of berberine and total alkaloid content in cortex phellodendri by near infrared spectroscopy (NIRS) compared with high-performance liquid chromatography coupled with ultra-visible spectrometric detection

This paper developed a rapid method using near infrared spectroscopy (NIRS) to differentiate two species of Cortex Phellodendri (CP), Cortex Phellodendri Chinensis (PCS) and Cortex Phellodendri Amurensis (PAR), and to predict quantitatively the content of berberine and total alkaloid content in all Cortex Phellodendri samples. Three alkaloids, berberine, jatrorrhizine and palmatine were analyzed simultaneously with a Thermo ODS Hypersil column by gradient elution with a new mobile phase under high-performance liquid chromatography-diode array detection (HPLC-DAD). Berberine content determined by HPLC-DAD was exploited as a critical parameter for successful discrimination between them. Multiplicative scatter correction (MSC), second derivative and Savitsky-Golay (S.G.) were utilized together to correct the scattering effect and eliminate the baseline shift in all near infrared diffuse reflectance spectra as well as to enhance spectral features in order to give a better correlation with the results obtained by HPLC-DAD. With the use of principal component analysis (PCA), samples datasets were separated successfully into two different clusters corresponding to two species. Furthermore, a partial least squares (PLS) regression method was built on the correlation model. The results showed that the correlation coefficients of the prediction models were R = 0.996 for the berberine and R = 0.994 for total alkaloid content. The influences of water absorption bands present in the NIR spectra on the models were also investigated in order to explore the practicability of NIRS in routine use. The outcome showed that NIRS possibly acts as routine screening in the quality control of Chinese herbal medicine.     

Measurement of lactate in whole human blood with near-infrared transmission spectroscopy

We have evaluated the potential of near-infrared spectroscopy (NIRS) as a technique for rapid analysis of lactate in whole blood. To test the NIRS technique, a comparison was made with a standard clinical method using whole blood samples taken from five exercising human subjects at three different stage of exercise. To expand lactate concentration within the physiological range, standard additions method was used to generate 45 unique data points. Spectra were collected over the 2050-2400 nm spectral range with a 1 mm optical path length quartz cell. Reference lactate concentrations in the samples were determined by enzymatic measurements. Estimates and calibration of the lactate concentration with NIRS was made using partial least squares (PLS) regression analysis and leave-N-out cross validation on second derivative spectra. Separate calibrations were determined from each of the subject samples and cumulative PRESS was used to determine the number of PLS factors in the final model. The results from the PLS model presented are generated from the five individual calibration coefficient vectors and provided a correlation coefficient of 0.978 and a standard error of cross validation of 0.65 mmol l⁻¹ between the enzymatic assay and the NIRS technique. To study the parameters that impact the spectra baseline and the correlation between the calculated model and the data, referenced measurements of lactate against baseline spectrum were made for each individual. A correlation coefficient of 0.992 and a standard error of cross validation of 0.21 mmol l⁻¹ were found. The results suggest that NIRS may provide a valuable tool to assess physiological status for both research and clinical needs.     

Rapid recognition of Chinese herbal pieces of Areca catechu by different concocted processes using Fourier transform mid-infrared and near-infrared spectroscopy combined with partial least-squares discriminant analysis

Rapid and sensitive recognition of herbal pieces according to different concocted processing is crucial to quality control and pharmaceutical effect.Near-infrared(NIR) and mid-infrared(MIR) technology combined with supervised pattern recognition based on partial least-squares discriminant analysis (PLSDA) was attempted to classify and recognize six different concocted processing pieces of 600 Areca catechu L.samples and the influence of fingerprint information preprocessing methods on recognition performance was also investigated in this work.Recognition rates of 99.24%,100%and 99.49%for original fingerprint,multiple scatter correct(MSC) fingerprint and second derivative(2nd derivative) fingerprint of NIR spectra were achieved by PLSDA models,respectively.Meanwhile,a perfect recognition rate of 100%was obtained for the above three fingerprint models of MIR spectra.In conclusion.PLSDA can rapidly and effectively extract otherness of fingerprint information from NIR and MIR spectra to identify different concocted herbal pieces of A.catechu.     

High-frequency and -field electron paramagnetic resonance of high-spin manganese(III) in tetrapyrrole complexes

High-field and -frequency electron paramagnetic resonance (HFEPR) spectroscopy has been used to study three complexes of high spin Manganese(III), 3d4, S = 2. The complexes studied were tetraphenylporphyrinatomanganese(III) chloride (MnTPPCI), phthalocyanatomanganese(III) chloride (MnPcCl), and (8,12-diethyl-2,3,7,13,17,18-hexamethylcorrolato)manganese(III) (MnCor). We demonstrate the ability to obtain both field-oriented (single-crystal like) spectra and true powder pattern HFEPR spectra of solid samples. The latter are obtained by immobilizing the powder, either in an n-eicosane mull or KBr pellet. We can also obtain frozen solution HFEPR spectra with good signal-to-noise, and yielding the expected true powder pattern. Frozen solution spectra are described for MnTPPCl in 2:3 (v/v) toluene/CH2Cl2 solution and for MnCor in neat pyridine (py) solution. All of the HFEPR spectra have been fully analyzed using spectral simulation software and a complete set of spin Hamiltonian parameters has been determined for each complex in each medium. Both porphyrinic complexes (MnTPPCl and MnPcCl) are rigorously axial systems, with similar axial zero-field splitting (zfs): D approximately -2.3 cm(-1), and g values quite close to 2.00. In contrast, the corrole complex, MnCor, exhibits slightly larger magnitude, rhombic zfs: D approximtely -2.6 cm(-1), absolute value(E) approximately 0.015 cm(-1), also with g values quite close to 2.00. These results are discussed in terms of the molecular structures of these complexes and their electronic structure. We propose that there is a significant mixing of the triplet (S = 1) excited state with the quintet (S= 2) ground state in Mn(III) complexes with porphyrinic ligands, which is even more pronounced for corroles.