Targeted profiling: quantitative analysis of 1H NMR metabolomics data

Extracting meaningful information from complex spectroscopic data of metabolite mixtures is an area of active research in the emerging field of "metabolomics", which combines metabolism, spectroscopy, and multivariate statistical analysis (pattern recognition) methods. Chemometric analysis and comparison of 1H NMR1 spectra is commonly hampered by intersample peak position and line width variation due to matrix effects (pH, ionic strength, etc.). Here a novel method for mixture analysis is presented, defined as "targeted profiling". Individual NMR resonances of interest are mathematically modeled from pure compound spectra. This database is then interrogated to identify and quantify metabolites in complex spectra of mixtures, such as biofluids. The technique is validated against a traditional "spectral binning" analysis on the basis of sensitivity to water suppression (presaturation, NOESY-presaturation, WET, and CPMG), relaxation effects, and NMR spectral acquisition times (3, 4, 5, and 6 s/scan) using PCA pattern recognition analysis. In addition, a quantitative validation is performed against various metabolites at physiological concentrations (9 microM-8 mM). "Targeted profiling" is highly stable in PCA-based pattern recognition, insensitive to water suppression, relaxation times (within the ranges examined), and scaling factors; hence, direct comparison of data acquired under varying conditions is made possible. In particular, analysis of metabolites at low concentration and overlapping regions are well suited to this analysis. We discuss how targeted profiling can be applied for mixture analysis and examine the effect of various acquisition parameters on the accuracy of quantification.     

Metabolic profiling of liver from hypercholesterolemic pigs fed rye or wheat fiber and from normal pigs. High-resolution magic angle spinning 1H NMR spectroscopic study

This study presents the first application of a high-resolution magic angle spinning 1H NMR approach to elucidate the metabolic effects of a hypercholesterolemic condition and two high-fiber diets based on rye and wheat bread, respectively, in intact pig liver biopsy samples. Standard 1D and spin-echo 1H spectra were acquired on a total of 20 biopsy samples, and 2D total correlation spectroscopy experiments were carried out on selected samples for assignment of the observed resonances. Principal component analyses and partial least-squares regression discriminant analysis revealed differences in the hepatic lipid content and choline-containing compounds between normal and hypercholesterolemic pigs. In addition, the results demonstrated that the liver metabolite profile of hypercholesterolemic pigs fed a high-fiber rye bread differed from that of pigs fed high-fiber wheat bread with respect to both the lipoprotein fractions and the choline-containing compounds. These findings suggest that earlier reports on high-fiber rye diet-induced effects on plasma HDL/LDL content partially can be ascribed to effects on liver cholesterol metabolism and that the hepatic phospholipase pathways of phosphatidylcholine breakdown are affected by the high-fiber rye diet.     

Multivariate curve resolution applied to the analysis and resolution of two-dimensional [1H,15N] NMR reaction spectra

Multivariate curve resolution is proposed for the study of complex chemical reactions monitored by two-dimensional (2D) NMR spectroscopy. In particular, in this work, multivariate curve resolution is applied to the study of the reaction between (15)N-labeled cisplatin and the amino acid-nucleotide hybrid (Phac-Met-linker-p(5')dG). At several stages of the reaction, 2D [(1)H,(15)N] HSQC NMR spectra were acquired and stored in data matrices. In a first step, multivariate curve resolution was applied to analyze individually each one of these 2D spectra, allowing the resolution of the corresponding (1)H and (15)N one-dimensional correlation spectra. In a second step, the whole set of 2D spectra recorded along the reaction were simultaneously analyzed by multivariate curve resolution, allowing the resolution of the kinetic concentration profiles and of the pure 2D NMR spectra of each of the species detected along the reaction. Results finally obtained confirmed previously postulated reaction mechanisms involving the existence of two monofunctional adducts and of two bifunctional adducts, with the structure of one of them not completely resolved.     

双平行线阵的水下二维DOA估计算法

利用集群自主式水下航行器(Autonomous Underwater Vehicles,AUV)进行的水下协同作业的需求越来越多.对于水下集群作业来说,AUV的水下定位非常重要.目前,AUV通常采用声学定位的工作模式,利用长、短基线阵对水下目标的二维波达方向(Direction of Arrival,DOA)进行估计,...     

超滤和核磁技术定性分析聚羧酸减水剂的大单体

采用超滤和核磁技术,建立分析未知聚羧酸减水剂中大单体的方法。结果表明,未知聚羧酸减水剂样品依次经过30,10,3 k D(道而顿)超滤膜后,大分子量的组分被逐级滤去;超滤滤液再经过500D的透析袋预处理去除杂质,得到相对较纯的大单体。应用核磁共振氢谱技术对常见的已知大单体进行鉴别分析,进而解析出未知聚羧酸样品使用的大单体为异戊烯醇聚乙二醇醚(TPEG)。该法为聚羧酸高分子样品的剖析提供重要的分析手段,对聚合物的分析具有一定的借鉴作用。     

Automated resolution of nontarget analyte signals in GC x GC-TOFMS data using parallel factor analysis

We previously reported a method for the automated (objective) selection of a PARAFAC model having an appropriate number of factors for mathematical resolution of signal from a target analyte in GC x GC-TOFMS data (i.e., for an analysis in which the identity of the analyte is known a priori). While the previous target method has been successfully applied in several studies, the target method requires that the identity of the analyte be known. Also, multiple applications of the target method are required in cases where several analytes of interest are present in a single subsection of the chromatogram. Thus, having to know the analyte identity a priori restricts the applicability of the automated implementation of PARAFAC. The method presented in this report generalizes the previous method to allow analysis of one or more nontarget analyte signals in a subsection of a GC x GC-TOFMS chromatogram (i.e., for analyses when identities of analyte and interferences are not known a priori), thereby addressing and overcoming the limitations of the target method. Herein, we put the nontarget analyte PARAFAC method into theoretical context and illustrate the mechanics of the method using simulated data. We use real experimental GC x GC-TOFMS data to demonstrate the broad applicability of the method, with various analysis situations selected to illustrate challenging chemical analysis scenarios.     

Determination of the primary structures of heparin- and heparan sulfate-derived oligosaccharides using band-selective homonuclear-decoupled two-dimensional 1H NMR experiments

Band-selective homonuclear-decoupled (BASHD) two-dimensional NMR experiments are applied to the assignment of 1H NMR spectra of oligosaccharides, using as an example a heparin-derived hexasaccharide. The anomeric (H1) region of the 1H NMR spectrum is band-selected in the F1 dimension. With the increased resolution that results from less truncation of interferograms in the t1 dimension, finer digital resolution in the F1 dimension, and collapse of multiplets to singlets in the F1 dimension, cross-peaks to the anomeric protons of the two iduronic acid residues, which overlap in normal two-dimensional total correlation spectroscopy (TOCSY) and rotating frame Overhauser enhancement spectroscopy (ROESY) spectra of the hexasaccharide, are resolved in BASHD-TOCSY and BASHD-ROESY spectra, leading to an unequivocal assignment of the 1H NMR spectrum of the hexasaccharide. Incorporation of the water attenuation by transverse relaxation method for the complete and selective elimination of the water resonance into two-dimensional BASHD experiments makes it possible to observe oligosaccharide resonances at the frequency of the water resonance, as demonstrated with the observation of cross-peaks to resonances at the frequency of the water resonance in BASHD-TOCSY spectra of a second heparin-derived hexasaccharide.     

Class modeling analysis of heparin 1H NMR spectral data using the soft independent modeling of class analogy and unequal class modeling techniques

To differentiate heparin samples with varying amounts of dermatan sulfate (DS) impurities and oversulfated chondroitin sulfate (OSCS) contaminants, proton NMR spectral data for heparin sodium active pharmaceutical ingredient samples from different manufacturers were analyzed using multivariate chemometric techniques. A total of 168 samples were divided into three groups: (a) Heparin, [DS] ≤ 1.0% and [OSCS] = 0%; (b) DS, [DS] > 1.0% and [OSCS] = 0%; (c) OSCS, [OSCS] > 0% with any content of DS. The chemometric models were constructed and validated using two well-established methods: soft independent modeling of class analogy (SIMCA) and unequal class modeling (UNEQ). While SIMCA modeling was conducted using the entire set of variables extracted from the NMR spectral data, UNEQ modeling was combined with variable reduction using stepwise linear discriminant analysis to comply with the requirement that the number of samples per class exceed the number of variables in the model by at least 3-fold. Comparison of the results from these two modeling approaches revealed that UNEQ had greater sensitivity (fewer false positives) while SIMCA had greater specificity (fewer false negatives). For Heparin, DS, and OSCS, respectively, the sensitivity was 78% (56/72), 74% (37/50), and 85% (39/46) from SIMCA modeling and 88% (63/72), 90% (45/50), and 91% (42/46) from UNEQ modeling. Importantly, the specificity of both the SIMCA and UNEQ models was 100% (46/46) for Heparin with respect to OSCS; no OSCS-containing sample was misclassified as Heparin. The specificity of the SIMCA model (45/50, or 90%) was superior to that of the UNEQ model (27/50, or 54%) for Heparin with respect to DS samples. However, the overall prediction ability of the UNEQ model (85%) was notably better than that of the SIMCA model (76%) for the Heparin vs DS vs OSCS classes. The models were challenged with blends of heparin spiked with nonsulfated, partially sulfated, or fully oversulfated chondroitin sulfate A, dermatan sulfate, or heparan sulfate at the 1.0, 5.0, and 10.0 wt % levels. The results from the present study indicate that the combination of (1)H NMR spectral data and class modeling techniques (viz., SIMCA and UNEQ) represents a promising strategy for assessing the quality of commercial heparin samples with respect to impurities and contaminants. The methodologies show utility for applications beyond heparin to other complex products.     

Field reliability modeling based on two-dimensional warranty data with censoring times

ABSTRACT

Warranty data can be used for estimating product reliability, identifying causes of failure and designing warranty policy. Based on two-dimensional warranty data, we utilize an accelerated failure time model to investigate the effect of usage rate on product degradation. The stochastic expectation-maximization algorithm is proposed to estimate parameters of the reliability model considering both censored data and field data. Extensive simulation studies are used to validate the proposed method and to compare it with the maximum likelihood method. The utilities of the results have been demonstrated through real warranty data collected from an automobile manufacturer in China.     

High-resolution two-dimensional angle measurement technique based on fringe analysis

A novel angle-measurement technique based on fringe analysis for phase-measuring profilometry is proposed. A two-dimensional (2-D) angle between two mirror surfaces is determined by least-squares fitting of a plane to the 2-D distribution of the phase difference introduced by the 2-D tilt angle. To evaluate the performance of the proposed technique, numerical simulations that use the Fourier-transform technique and the phase-shift technique for fringe analysis were performed, and the results are compared. A 2-D angle-measurement interferometer based on a Mirau interference microscope was developed that demonstrated the validity of the proposed principle. It is shown by simulation and experiment that the proposed 2-D angle-measurement technique can achieve both a wide measurement range and a high angular resolution simultaneously.     

Interference-free analysis using three-way fluorescence data and the parallel factor model. Determination of fluoroquinolone antibiotics in human serum

Three-way fluorescence data and multivariate calibration based on parallel factor analysis (PARAFAC) are combined for the simultaneous quantitation of three fluoroquinolone anitibiotics (norfloxacin, enoxacin, and ofloxacin) in human serum samples. The three analytes can be adequately determined with limits of detection of 0.2, 3.0, and 0.5 microg L(-1), respectively, with minimum experimental effort. The selected analytical methodology fully exploits the so-called second-order advantage of the employed three-way data, allowing obtaining individual concentrations of calibrated analytes in the presence of any number of uncalibrated (serum) components. In contrast to PARAFAC, less satisfactory results were obtained with a multidimensional partial least-squares (nPLS) model trained with the same calibration set.     

Sample classification based on Bayesian spectral decomposition of metabonomic NMR data sets

1H NMR spectra of biofluids provides a wealth of biochemical information on the metabolic status of an organism. Through the application of pattern recognition and classification algorithms, the data have been shown to provide information on disease diagnosis and the beneficial and adverse effects of potential therapeutics. Here, a novel approach is described for identifying subsets of spectral patterns in databases of NMR spectra, and it is shown that the intensities of these spectral patterns can be related to the onset and recovery from a toxic lesion in both a time-related and dose-related fashion. These patterns form a new type of combination biomarker for the biological effect under study. The approach is illustrated with a study of liver toxicity in rats using NMR spectra of urine following administration of a model hepatotoxin hydrazine.     

Analysis of condensation and imidization of norbornene derivatives by 1H NMR analysis effect of processing conditions

The condensation and imidization reactions of norbornene derivatives have been analysed and the intermediates formed during the course of these reactions are identified. The mechanisms involved and the effect of the processing conditions are discussed.     

基于模态展开法的二维消声器传递损失分析

运用模态展开法通过求解矩形和圆柱形二维消声器的压力响应函数以及其相应的四极参数，推导了这些消声器模型的传递损失计算模型。采用此模型计算了二维圆柱形消声器的传递损失，并建立了三维有限元模型验证了该模型的正确性。通过与格林函数法比较传递损失能量计算结果，表明在面源尺寸相对较大时，采用该模型具有更高的计算精度。     

Adaptive optics based on analog parallel stochastic optimization: analysis and experimental demonstration

Wave-front distortion compensation using direct system performance metric optimization is studied both theoretically and experimentally. It is shown how different requirements for wave-front control can be incorporated, and how information from different wave-front sensor types can be fused, within a generalized gradient descent optimization paradigm. In our experiments a very-large-scale integration (VLSI) system implementing a simultaneous perturbation stochastic approximation optimization algorithm was applied for real-time adaptive control of multielement wave-front correctors. The custom-chip controller is used in two adaptive laser beam focusing systems, one with a 127-element liquid-crystal phase modulator and the other with beam steering and 37-control channel micromachined deformable mirrors. The submillisecond response time of the micromachined deformable mirror and the parallel nature of the analog VLSI control architecture provide for high-speed adaptive compensation of dynamical phase aberrations of a laser beam under conditions of strong intensity scintillations. Experimental results demonstrate improvement of laser beam quality at the receiver plane in the spectral band up to 60 Hz.     

基于有限和瞬时旋量理论的Exechon并联机器人运动学分析

运动学分析是并联机构性能分析、建模和优化设计的基础。传统的运动学分析方法中并联机构的拓扑模型与速度模型只能单独构建,无法揭示其内在联系,导致运动学模型的构建不够全面和准确;另外,以现有运动学性能指标作为运动学优化目标时,存在平转耦合机构运动学评价指标的物理意义不明确等问题。为此,以一平动两转动(1T2R)的Exechon并联机器人为研究对象,利用有限和瞬时旋量(finite and instantaneous screw, FIS)理论对其拓扑、运动学建模进行研究。根据FIS理论中的微分映射关系,在统一的数学框架下建立Exechon并联机器人的拓扑模型和速度模型,得到其速度和力雅克比矩阵。在此基础上,以可解析分析机构运动奇异性的虚功率传递率作为运动学性能指标,来有效评价Exechon并联机器人的运动/力传递性能。给定一组Exechon并联机器人模型的尺寸参数,借助MATLAB分析该机器人的局部虚功率传递率分布情况。研究结果为并联机构的性能分析与建模提供了参考,为Exechon并联机器人的优化设计奠定了理论基础。     

Characterization and matching of oil samples using fluorescence spectroscopy and parallel factor analysis

A novel approach for matching oil samples by fluorescence spectroscopy combined with three-way decomposition of spectra is presented. It offers an objective fingerprinting based on the relative composition of polycyclic aromatic compounds (PACs) in oils. The method is complementary to GC-FID for initial screening of oil samples but can also be used for prescreening in the field, onboard ships, using a portable fluorescence spectrometer. Parallel factor analysis (PARAFAC) was applied to fluorescence excitation-emission matrixes (EEMs) of heavy fuel oils (HFOs), light fuel oils, lubricating oils, crude oils, unknown oils, and a sample collected in the spill area two weeks after the Baltic Carrier oil spill (Denmark, 2001). A total of 112 EEMs were decomposed into a five-factor PARAFAC model using excitation wavelengths from 245 to 400 nm and emission wavelengths from 280 to 550 nm. The PARAFAC factors were compared to EEMs of PAC standards with two to five rings, and the comparisons indicate that each of the factors can be related to a mixture of PACs with similar fluorescence characteristics: a mixture of naphthalenes and dibenzothiophenes, fluorenes, phenanthrenes, chrysenes, and five-ring PACs, respectively. Oils were grouped in score plots according to oil type. Except for HFOs and crude oils, the method easily discriminated between the four oil types. Minor overlaps of HFOs and crude oils were observed along all five PARAFAC factors, and the variability of crude oils was large along factor 2 due to a varying content of five-ring PACs. The spill sample was correctly assigned as a HFO with similar PAC pattern as oil from the cargo tank of the Baltic Carrier by comparing the correlation coefficient of scores for the oil spill sample and possible source oils (i.e., oils in the database).     

Metabolic assessment of human liver transplants from biopsy samples at the donor and recipient stages using high-resolution magic angle spinning 1H NMR spectroscopy

This work presents the first application of high-resolution magic angle spinning (HR-MAS) 1H NMR spectroscopy to human liver biopsy samples, allowing a determination of their metabolic profiles before removal from donors, during cold perfusion, and after implantation into recipients. The assignment of peaks observed in the 1H HR-MAS NMR spectra was aided by the use of two-dimensional J-resolved, TOCSY and 1H-13C HMQC spectra. The spectra were dominated by resonances from triglycerides, phospholipids, and glycogen and from a variety of small molecules including glycerophosphocholine (GPC), glucose, lactate, creatine, acetate, amino acids, and nucleoside-related compounds such as uridine and adenosine. In agreement with histological data obtained on the same biopsies, two of the six livers were found to contain high amounts of triglycerides by NMR spectroscopy, which also indicated that these tissues contained a higher degree of unsaturated lipids and a lower proportion of phospholipids and low molecular weight compounds. Additionally, proton T2 relaxation times indicated two populations of lipids, a higher mobility triglyceride fraction and a lower mobility phospholipid fraction, the proportions of which changed according to the degree of fat content. GPC was found to decrease from the pretransplant to the posttransplant biopsy of all livers except for one with a histologically confirmed high lipid content, and this might represent a biomarker of liver function posttransplantation. NMR signals produced by the liver preservation solution were clearly detected in the cold perfusion stage biopsies of all livers but remained in the posttransplant spectra of only the two livers with a high lipid content and were prominent mainly in the graft that later developed primary graft dysfunction. This study has shown biochemical differences between livers used for transplants that can be related to the degree and type of lipid composition. This technology might therefore provide a novel screening approach for donor organ quality and a means to assess function in the recipient after transplantation.