药物分析英文文献15

From Exogenous to Endogenous:The Inevitable Imprint of Mass

Spectrometry in Metabolomics

Elizabeth J.Want,Anders Nordstro 1m,Hirotoshi Morita,and Gary Siuzdak*

Department of Molecular Biology,The Scripps Center for Mass Spectrometry,10550North Torrey Pines Road,

La Jolla,California 92037

Received September 27,2006

Mass spectrometry (MS)is an established technology in drug metabolite analysis and is now expanding into endogenous metabolite research.Its utility derives from its wide dynamic range,reproducible quantitative analysis,and the ability to analyze biofluids with extreme molecular complexity.The aims of developing mass spectrometry for metabolomics range from understanding basic biochemistry to biomarker discovery and the structural characterization of physiologically important metabolites.In this review,we will discuss the techniques involved in this exciting area and the current and future applications of this field.

Keywords:mass spectrometry ?liquid chromatography ?metabolomics ?biomarker characterization ?metabolite database

Introduction

The application of modern mass spectrometry technology to endogenous metabolite research derives from its success in drug metabolite studies,both quantitative and structural.1-11Interest also originates from the ability to perform more comprehensive metabolite analyses with new liquid chroma-tography/mass spectrometry (LC/MS)technologies,such as nanoESI-LC/MS,and the desire to unravel basic biochemical events of cells and tissues,or to identify disease or pharma-ceutical biomarkers.

One of the first metabolite profiling experiments was by Pauling and colleagues in 1971,who analyzed the metabolite content of human urine vapor and breath of subjects on a defined diet using gas chromatography (GC).12Approximately 250substances were detected in a breath sample and 280in a urine vapor sample.This group then went on to profile amino acids in urine,employing nonparametric statistical analysis for detecting profile differences related to gender and other variables.13This was the beginning of what we now call metabolomics,the aim of which is to provide a comprehensive profile of all the metabolites present in a biological sample.From the 1970s,gas chromatography mass spectrometry (GC/MS)became popular for metabolite profiling and is still used for the detection of many metabolic disorders.14Advan-tages of GC/MS include high resolution and reproducibility,as well as the availability of EI spectral libraries for structural identification.15In addition,since the 1990s,16nuclear magnetic resonance (NMR)has also been applied to areas such as plant metabolism,Duchenne Muscular Dystrophy,neurological dis-orders,and hepatotoxicity and nephrotoxicity in rodents,17-24with advantages in both speed and accuracy.However,because of the limitations of NMR in terms of sensitivity,LC/MS has emerged as a powerful alternative technology for metabolom-ics.In this review,the role of mass spectrometry in metabo-lomics will be discussed,encompassing data acquisition,data analysis,metabolite characterization,and many exciting ap-plications.

1.Data Acquisition

Due to the complex nature of biological samples,separation is often performed before mass spectrometric analysis to achieve the detection of as many metabolites as possible.Traditionally,GC was employed,as it is well-known for high resolution and reproducibility.However,disadvantages of GC include convoluted sample preparation (such as derivatization),lengthy analysis time,and the limitation on the size and type of molecule that can be analyzed (nonvolatile,polar macro-molecules are unsuitable).However,GC-MS is still widely used in plant metabolomics due in part to the nature of the metabolites being investigated.15,25-28

Liquid chromatography electrospray ionization mass spec-trometry (LC/ESI-MS)(Figure 1)is now a common metabolo-mics tool.Separation of the thousands of molecules present in biofluids using LC can reduce ion suppression 29-31by decreasing the number of competing analytes entering the mass spectrometer ion source at any one time.This results in a selective approach that allows for both quantitation and structural information,where sensitivities in the pg/mL range can be achieved readily.32LC/MS techniques have replaced some of the traditional specialized clinical laboratory meth-ods 33,34that used immunological,fluorometric,and biological techniques.35

An important factor in LC metabolite separation is the choice of column.Many biofluids,particularly urine,contain a vast array of highly polar molecules that are not retained well on the more traditional reverse phase (RP)LC columns.Normal phase techniques,which result in the elution of less polar molecules first and thus the retention of more polar molecules,

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require a different solvent system to that used by RP chroma-tography,typically containing no aqueous.A newer approach is hydrophilic interaction chromatography (HILIC),which can offer complementary information to that obtained using RP chromatography.36Here,water and acetonitrile can still be used,although starting from a high organic content and ending at high aqueous.HILIC approaches combined with ESI-MS techniques have already been applied to the analysis of dichloroacetic acid in rat blood and tissues,37plant metabolites such as oligosaccharides,glycosides,and sugar nucleotides,38and with APCI mass spectrometry for the determination of 5-fluorouracil in plasma and tissues.39

The ability of LC to separate complex mixtures prior to mass analysis comes at a cost of speed.An alternative to traditional reverse phase (RP)approaches is ultrahigh performance liquid chromatography (UPLC),40which utilizes columns with much smaller particle size packing material (1.4-1.7μm)than traditional columns,thus allowing for improved separation and higher resolution (Figure 2).This technology permits pumping and injection of liquids at pressures exceeding 10000psi.41Using this approach,sample analysis times can be reduced to as little as 1min,42resulting in much higher throughput.With UPLC,narrower chromatographic peaks can be achieved (peak widths at half-height <1s),resulting in increased peak capacity,lower ion suppression and improved signal-to-noise ratio,and thus increased sensitivity (Figure 2).Recent studies comparing UPLC and HPLC for their application to metabolomics studies showed that UPLC can detect more components than HPLC,32with a 20%increase reported over the same chromatographic length.43This study also showed UPLC to display superior retention time reproducibility and signal-to-noise ratios over HPLC.

When coupled to separation techniques,MS analysis of biofluids can offer high sensitivity and specificity.However,despite LC/MS being the foremost technique for the analysis of known compounds,44as well as the determination of unknowns using MS/MS,one limitation is the inability of LC/MS alone to unequivocally distinguish between some coeluting stereoisomers.45However,the application of ion-mobility mass spectrometry to metabolomics might be a powerful strategy for addressing the problem of resolving isomers.Indeed,an LC approach has been combined with ion mobility/time-of-flight (TOF)mass spectrometry for the characterization of a

combinatorial peptide library,enabling many peptide isomers with identical masses and retention times to be resolved.46

Furthermore,as LC-MS techniques for metabolomics can be affected by high noise levels,retention time shifts,and high variability in signal intensities,researchers are constantly investigating ways to reduce analysis time and sample prepara-tion in metabolomics studies.There have been some recent explorations of chip-based mass spectrometry approaches for the delivery of the biological sample to the mass spectrometer with the aim of improving metabolite detection.One recent study using protein precipitation of plasma combined with chip-based nanospray infusion reported high reproducibility,sample throughput,and the observation of over 1800different mass peaks up to 900Da.47Some of the samples were highly diluted to minimize ion suppression,and so although MS runs of 10min were used,for MS/MS studies,runtimes of 60-90min were needed to obtain meaningful data,offering no advantages over LC-MS/MS.In fact,using UPLC-MS/MS impressive fragmentation data can be collected in a run of 10min.48

Ionization Techniques.Once the components of a biological sample have been separated,ions must be produced.In GC,samples are vaporized and then ionized by electron-impact (EI)or chemical ionization (CI).Extensive libraries of EI spectra,such as the NIST database,which contains over 100000compounds,are available to aid in the identification of molecules (https://www.wendangku.net/doc/3110284665.html,/srd/nist1a.htm).EI has the advantages of good sensitivity and unique fragmentation.However,the molecular ion is often not detected due to the extensive fragmentation,which may prove hinder the identi-fication of unknown compounds.A disadvantage with EI is the limited mass range due to the thermal desorption requirement.As CI is much less energetic than electron ionization,it induces less fragmentation and in general,more stable ions,and so can be useful for identifying the molecular ion and thus determin-ing the molecular weight of a compound.However,CI still requires thermal desorption.Negative CI is particularly sensitive for perfluorinated derivatives and proves a limited but powerful approach for certain derivatized molecules such as steroids.However,for metabolomics studies,electrospray ionization (ESI)is most commonly used in conjunction with LC/MS.ESI offers soft ionization,excellent quantitative analysis and high sensitivity.With ESI,ions are generated directly from the liquid phase into the gas phase,establishing this technique as a convenient mass analysis platform for both liquid chromatog-raphy and automated sample analysis.In its simplest form,ESI can be quite effective even without separation,especially when combined with tandem mass spectrometry (MS/MS)where its direct application to metabolite screening is currently used for over 35diseases.49,50

Three alternative solution-based ionization strategies to ESI are also being used for LC/MS-based metabolomics,namely nanoESI,atmospheric pressure chemical ionization (APCI)and atmospheric pressure photoionization (APPI).NanoESI liquid chromatography,performed at low flow rates (～200nL/min),has already proved useful in proteomics studies 51,52where it significantly enhances sensitivity and dynamic range.53-55In nanoLC/nano-ESI-MS,ions are produced from small sub-micron sized droplets requiring less evaporation and a greater ability to focus the resulting ions into the analyzer,therefore increasing sensitivity and ultimately offering a greater dynamic range.APCI and APPI are widely used in the pharmaceutical industry 56-58yet have had limited exposure to metabolomics

Figure 1.Metabolomics aims to measure all the metabolites in a biofluid or https://www.wendangku.net/doc/3110284665.html,mon approaches include LC-MS and LC-MS/MS using electrospray ionization.Alterations in metabolite levels may reflect the activity of their corresponding enzymes.Additional factors affecting metabolite profiles include drug intake or the onset or progression of a disease.Metabolomics is complementary to proteomics and transcriptomics and the combination of data from all three approaches can provide important information regarding the status of a cell or organism.

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studies.Analogous to the ESI interface,APCI and APPI typically induce little or no fragmentation and are considered robust and relatively tolerant of high buffer concentrations.It is now recognized that these approaches can be valuable for the analysis of nonpolar and thermally stable compounds such as lipids 59,60with the apparent trend toward a “single”ionization source containing combinations of ESI and APCI or ESI and APPI.

There is a small but growing body of work using other ionization strategies for metabolomics.MALDI applications have been limited,due in part to matrix suppression issues for low molecular weight molecules.However,some research-ers believe that there could be advantages to using this https://www.wendangku.net/doc/3110284665.html,ing a novel sample deposition approach,semi-quantitation of amino acids from mammalian cells has been achieved using positive mode MALDI-TOF -MS.61Negative mode MALDI,rarely used due to the lack of suitable matrices,has been applied recently for the analysis of metabolites from Islets of Langerhans and E.Coli 62.In all,over 100metabolites were detected,although many could not be identified due to the lack of complete databases and the inability to distinguish isomers such as citrate and isocitrate.Recently,a matrix-suppressed laser desorption/ionization (MSLDI)strategy was evaluated.By decreasing the matrix/analyte ratio,less sup-pressed spectra were obtained,enabling the detection of lower abundance compounds.63However,it can be difficult to find a suitable matrix/analyte ratio without prior knowledge of metabolite concentrations.

Desorption ionization on porous silicon (DIOS)allows for the detection of small molecules in both positive and negative mode with little background interference 64and has recently been applied to metabolomics studies.65Here,26/30known metabolites in a mixture were detected rapidly in positive mode and in negative mode,showing the potential of DIOS as a metabolomics approach.

Recently,the combination of desorption electrospray ioniza-tion mass spectrometry (DESI-MS)and NMR was investigated for its application to metabolomics.66This group studied urine without any sample preparation to differentiate between diseased and healthy mice.DESI is an ambient ionization direct analysis technique,providing high sensitivity and specificity with minimal sample preparation.66There is no sample separa-tion and because the sample is placed on the surface rather than direct infusion,this affords a higher tolerance to salts.However,some compounds do not ionize well using any of the common ionization techniques and so will not be detected using MS alone.The coupling of NMR and MS has been used in combination with liquid chromatography (LC-NMR -MS)and applied to metabolite studies,such as in the pharmaceuti-cal drug discovery area.44,67This technique allows for the both MS and NMR data to be collected from a single LC run and the complementary information that can be provided makes this approach a powerful tool for the detection and identifica-tion of both known and unknown compounds.44Further,software is being developed to cope with the analysis of the complex data produced by these instruments,in particular,statistical heterospectroscopy (SHY),an approach to the inte-grated analysis of NMR and UPLC-MS data sets.68

Mass Analyzers.Along with advances in ionization sources,mass analyzers have improved with respect to speed,accuracy,and resolution.The most common mass analyzers are the quadrupole and time-of-flight (TOF)based analyzers.Other analyzers that can be used for metabolomics studies include ion traps,Fourier transform mass spectrometers (FTMS),and orbitraps,some of which will be discussed in this section.Quadrupole mass analyzers can be coupled to many different ionization sources,with advantages including comparatively high pressure tolerance,good dynamic range,and excellent stability,all at a relatively low cost.To perform tandem mass analysis with a quadrupole instrument,three quadrupoles are placed in series.Each quadrupole has a separate function:the first quadrupole (Q1)scans across a preset m /z range to select an ion of interest,which is then fragmented in the second quadrupole (Q2),the collision cell,using argon or helium as the collision gas.The third quadrupole (Q3)analyzes the fragment ions generated in the collision cell (Q2).

The linear time-of-flight (TOF)mass analyzer is the simplest mass analyzer,with virtually unlimited mass range,whereas the TOF reflectron has mass range up to m /z ～10000.The TOF reflectron is now widely used with ESI and MALDI,and more recently for electron ionization in GC/MS applications.TOF instruments offer high resolution,fast scanning capabilities (ms),and accuracy on the order of 5part per million (ppm).Quadrupole-TOF (Q-TOF)mass analyzers combine the stability of a quadrupole analyzer with the high efficiency,sensitivity,and accuracy of a time-of-flight reflectron mass analyzer,and are typically coupled to ESI sources.Q-TOF mass analyzers are an obvious choice for obtaining metabolite fragmentation data.

Figure 2.Ultrahigh performance liquid chromatography (UPLC)utilizes columns with smaller particle size packing material (1.4-1.7μm)than traditional columns and can enhance several aspects of chromatography in a metabolomics context.(1)Separation of metabolites is improved,decreasing ion suppression and in turn improving data interpretability (2)Signal to Noise (S/N)is improved due to narrower peak widths allowing for increased peak capacity and improved accuracy and sensitivity.(3)Sample run time is decreased dramatically allowing for faster sample throughput.

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The quadrupole can act as any simple quadrupole analyzer to scan across a specified m /z range,but can also be used to selectively isolate a precursor ion and direct that ion into the collision cell.The resultant fragment ions are analyzed by the TOF reflectron mass analyzer.Q-TOF analyzers offer signifi-cantly higher sensitivity and accuracy over tandem quadrupole instruments when acquiring full fragment mass spectra.The ion trap mass analyzer can be used for both MS scanning and MS/MS studies.It allows the isolation of one ion species by ejecting all others from the trap,whereby the isolated ions can subsequently be fragmented.However,a major limitation of the ion trap is its inability to perform high sensitivity triple quadrupole-type precursor ion scanning and neutral loss scanning experiments.Furthermore,the upper limit on the ratio between precursor m /z and the lowest trapped fragment ion is ～0.3(the “one-third rule”).The dynamic range is also limited due to space charge effects when too many ions are in the trap,which diminish the performance of the ion trap.Here,the linear ion trap has an advantage over the 3D trap,with a larger analyzer volume which lends itself to a greater dynamic range and an improved range of quantitative analysis.Quad-rupole ion traps have MS n capabilities,allowing for multiple MS/MS experiments to be performed quickly without having multiple analyzers,such that real time LC-MS/MS is now routine.Other important advantages of quadrupole ion traps include their compact size,and their ability to trap and accumulate ions to provide a better ion signal.

Fourier transform mass spectrometry (FTMS)offers high resolution and the ability to perform multiple collision experi-ments (MSn).FTMS is capable of ejecting all but the ion of interest,fragmenting the selected ion and yielding high-accuracy fragment masses.Ultrahigh resolution FTMS can be coupled to MALDI,ESI,APCI,and EI,although the new quadrupole-FTMS and quadrupole linear ion trap-FTMS mass analyzers are typically coupled to electrospray ionization sources.Newer hybrid instrument designs are preferable over coupling FTMS/MS to separation techniques such as LC,as MS/MS experiments can be performed outside the magnet.69This presents some advantages because high resolution in FTMS is dependent on the presence of high vacuum.Perform-ing MS/MS experiments outside the cell is thus faster because the ICR cell is not exposed to a pulse of gas to initiate dissociation and thus can be maintained at ultrahigh vacuum.Instruments,such as the LTQ-FT,combine the excellent performance and capabilities of the FT mass spectrometers with the well-established,tested,and validated features of quadrupoles and ion traps.Due to the robust,externally calibrated accurate mass determination for both parent and product ions,the LTQ-FT could be a very powerful analytical

tool for metabolomics studies,allowing for the confirmation of known metabolites or to elucidate the structures of unknown metabolites.

2.Data Analysis

LC/MS based metabolomics studies generate large,complex datasets which require sophisticated software to enable inter-pretation.A current challenge is achieving the high-throughput conversion of these datasets into organized data matrices necessary for further statistical processing,as well as visualiza-tion.As two or more sample sets are often compared for changes in metabolite levels,metabolites must first be detected in all samples,matched between the samples and then their levels compared (Figure 3).Multiple adducts (such as sodium and potassium)can be formed using LC-ESI/MS,thus com-plicating the data produced by increasing the number of peaks detected.It is imperative that the same metabolites are identified correctly in all samples to enable this comparison.To this end,software has been produced in order to allow peak picking and evaluation.Many instrument manufacturers have produced their own software,which often works solely with data generated from a particular instrument.These include MarkerLynx (Waters),MassHunter (Agilent)and MarkerView (Applied Biosystems/MDS SCIEX).However,some researchers desire the freedom to modify many parameters and also to compare data from different instruments and so have devel-oped their own software.Examples of these include MZmine,70,71XCMS,72and MET-IDEA 73and are generally freely available for download and in some cases,user modification.

A huge challenge with metabolomic data analysis can often be the classification of data,either with or without prior knowledge that such classes exist.The development of new data analysis approaches 74,75including multivariate statistical analy-sis for biomarker discovery 5,28,76,77has facilitated the discovery of hidden structure in data.Therefore,with many of these software programs,data (as peak lists or similar)can be output in a suitable format to then be analyzed using multivariate statistics (Figure 4).These multivariate techniques can help to discern peaks with high discriminating power between the sample groups being analyzed,i.e.,potential biomarkers.78Most companies and research groups involved in metabolite research supplement these available data mining techniques with in-house software to further enable compound identification and quantification.

A variety of multivariate statistics and pattern recognition methods are currently in use for metabolomics studies,which can be divided into two categories,unsupervised and super-vised methods.In unsupervised methods,such as principal component analysis and hierarchical cluster analysis,the algorithm is not given a training set and so input data is

Figure 3.LC/MS metabolomics studies generate large,complex datasets,and there is the possibility of retention time drift between samples over the course of the study.Alignment of chromatographic data is fundamental for the production of comparable data sets.A data extraction tool like XCMS allows for nonlinear correction of retention time drift in the time domain.Other freely available data processing software includes MZmine and MET-IDEA.

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classified in an “unsupervised”manner.Conversely,with supervised methods,a classification system is given some input data together with the answers,known as the “training set”,which can be used to build a model and estimate necessary parameters.These include discriminant analysis,such as projection to latent structures (also called partial least-squares)(PLS)and orthogonal projection to latent structures (O-PLS),artificial neural networks (ANNs),and evolutionary-based computational algorithms.

Principal component analysis (PCA)79is often used for metabolomics.80,81PCA can be used in the reduction of data dimensionality,to investigate clustering tendency,such as with gene expression data,82to detect outliers,and to visualize data structure.83,84However,PCA gives a simplified representation of the information contained in the spectra and cannot generally use additional information about the data,such as class information.Therefore,PCA is often followed by a supervised analysis technique such as PLS-DA or O-PLS-DA.In fact,Lutz and colleagues showed by comparison of PCA with PLS-DA that there was a clear advantage in using a supervised model where class details are known.78

Hierarchical cluster analysis organizes information about variables in a data set,forming “clusters”,where the degree of association is strong between samples within the same cluster and weak between those in different clusters.This approach may reveal associations and structure in data that were not previously evident.Hierarchical clustering can be represented as a tree,or dendrogram,where each step in the clustering process is illustrated by a join of the tree.The combination of proteomics and cluster analysis has been applied successfully to the classification of normal breast,benign breast and breast cancer tissues using just the protein expression profiles.85

Projection to latent structures,also called partial least-squares discriminant analysis (PLS-DA)is performed in order to enhance the separation between groups of observations,often by rotating PCA components to achieve maximum separation between classes,and to understand which variables are responsible for separating the classes.Orthogonal projec-tion on latent structure discriminant analysis (O-PLS-DA),developed by Trygg and Wold,can be a powerful tool for the analysis of metabolomics data.86,87Like PLS-DA,O-PLS-DA is a supervised pattern recognition technique,but has improved predictive quality because the structured noise is modeled separately.O-PLS-DA has been used in conjunction with STOCSY (statistical total correlation spectroscopy)in the analysis of NMR metabolomics data.88

ANNs are powerful data modeling tools,capable of learning patterns and relations from input data,making good pattern recognition engines and robust classifiers.ANNs are being used effectively for problems including building nonlinear classifica-tion and regression models.Currently,ANNs are being devel-

oped which can predict patient responses to drugs,which would enable ideal dosing regimes to be established.89

A newer approach to the mining of highly complex metabo-lomics data is to apply evolutionary computational-based methods.90These are explanatory supervised learning tech-niques,including genetic algorithms,genetic programming,evolutionary programming and genomic computing,which could be ideal strategies for mining such high-dimensional data as that obtained from metabolomic studies.90

However,there appears to be no consensus on which multivariate statistics approach is truly superior,and so at present it seems that individual companies and research groups are employing their own combination of data analysis software and multivariate statistics to address their individual metabo-lomics challenges.

Databases.The collection of LC/MS data and subsequent comparative analysis is becoming more straightforward,yet a major challenge lies in characterizing the metabolites that have interesting biological properties and whose mass is initially identified.In contrast to the well-annotated gene and protein databases that can be searched easily,at present,no such comprehensive tools exist for metabolite researchers.However,current metabolite databases,although incomplete,offer a starting point for characterization.Among the databases cur-rently available,the most widely used are the NIST database,which includes mass spectral data for some known metabolites (https://www.wendangku.net/doc/3110284665.html,/srd/nist1.htm),as well as the KEGG,HumanCyc,ARM,and METLIN databases.The KEGG database is a valuable resource for metabolomics researchers (http://www.genome.jp/kegg/ligand.html).HumanCyc (https://www.wendangku.net/doc/3110284665.html,)includes known metabolites as well as those predicted by algorithms which project metabolic pathways from a genomic sequence.A database constructed as part of the Atomic Reconstruction of Metabolism (ARM)project,compiles metabolite structures together with molecular weight and MS fragmentation data (http://www.metabolome.jp).In addition,the University of Alberta hosts a mini-library of full mass spectra of newer drugs,metabolites and some breakdown products,(http://www.ualberta.ca/～gjones/mslib.htm).Other databases include the human metabolite database (http://www.hmdb.ca/),which acts as an electronic repository for identification of small molecule metabolites.The Spectral Database for Organic Compounds SDBS provides access to a wealth of spectra of organic compounds (NMR,MS,IR).Another metabolite database is the “tumor metabolome”database,established at the Justus-Liebig University Giessen in Germany (https://www.wendangku.net/doc/3110284665.html,).

LIPID MAPS (https://www.wendangku.net/doc/3110284665.html,/tools/index.html)and Lipid Search (http://lipidsearch.jp/LipidNavigator.htm)are useful databases to search lipid metabolites.Although phos-pholipids and some other lipids are important metabolites,numbers of the registered secondary metabolites are still limited.

The KNApSAcK database (http://kanaya.aist-nara.ac.jp/KNApSAcK/Manual/KNApSAcKManual.html)can also be used to pick up metabolites not registered in the above databases.This database is specific for secondary metabolites and MS-based data searches can also be performed.Some databases focus purely on electron impact mass spectrometry data,such as the Wiley Registry of Mass Spectral Data (https://www.wendangku.net/doc/3110284665.html,),the largest commercially available reference library of mass spectra.The GOLM open access database at the Max-Planck Institute of Molecular Plant

Figure 4.Once data has been aligned,the output can be manually inspected before data are further processed using multivariate statistics.These multivariate techniques can help to discern potential biomarkers,which then undergo targeted analysis to further validate their significance as biomarkers.

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Physiology also focuses on electron ionization mass spectrom-etry data and is intended as a repository for experiments performed at this institute,as well as for data from collabora-tors.91

To support the identification of metabolites we have devel-oped METLIN,a web-based data repository (https://www.wendangku.net/doc/3110284665.html,/)on endogenous and exogenous metabolites.METLIN provides mass,elemental composition,CAS#,KEGG#,some MS/MS data,and a diverse collection of LC/MS and high-resolution Fourier transform mass spectrometry (FTMS)spec-tra,primarily from human biofluids and also some model organisms.The purpose of this data is to aid in metabolite identification through accurate mass measurement and isotopic pattern evaluation.METLIN also includes an annotated list of known metabolite structural information,both endogenous and drug metabolites can be easily cross-correlated with the LC/MS and FTMS data.Further,METLIN provides a number of data visualization tools including color 3D LC-MS plots and histograms.

A long-term aim in metabolomics is the establishment of data standards,to standardize experiment descriptions,par-ticularly within publications.ArMet 92(https://www.wendangku.net/doc/3110284665.html,),is a data model to describe plant metabolomics experiments and their results.93Other groups have produced reporting requirements for metabolomics experiments,15to form a checklist of the information necessary for the publication of metabolomics data.A standard metabolic reporting structure policy document (SMRS Group,2004)has been developed by a group from industry and academia.

Metabolite Identification.Once potential biomarkers have been selected,identification is required.Some metabolites observed in metabolomics studies may be well-known and characterized.Databases such as KEGG,human metabolite database,and METLIN can be used to search candidate molecules.If samples are analyzed using high-resolution mass spectrometry,then many candidates can be excluded.Once candidate molecules are obtained,co-chromatography and comparison of MS/MS data are necessary to confirm the identification of the molecule.

If the molecule is not known then the next task is identifica-tion,a significant challenge given the often limited sample amount and trace quantities of some metabolites.The overall procedure can be summarized in Figure 5with the initial LC isolation of molecule of interest followed by tandem mass measurements on a Q-TOF for structural characterization and FTMS analysis for accurate mass measurements.Typical methods for obtaining elemental composition involve high-resolution ESI-FTMS and FTMS/MS technology for accurate mass determination,as well as the newer LTQ-FT technology.Orthogonal acceleration Q-TOF mass spectrometry 94is also being used to obtain high accurate mass measurements.

Furthermore,UPLC/MS E ,performed on a Q-TOF,has been presented recently as an approach for obtaining fragmentation data from LC/MS metabolomics studies.95This technique was applied to small molecules in complex mixtures and was achieved using simultaneous acquisition of exact mass at high and low collision energy,without reported loss of quality in the chromatographic data,offering an alternative approach to structural elucidation in complex mixture analysis problems.However,despite the usefulness of this mass spectrometry data,the lack of comprehensive mass spectral libraries often precludes identification of molecules based on this data alone.Ultimately,the combination of many technologies will be required to identify unknown metabolites in biofluids including high sensitivity capillary NMR,which can provide metabolite structure characterization down to low microgram level,96,97chemical modification for functional group identification,and finally independent synthesis for verification.

An example of the isolation and characterization of com-pletely novel metabolites was recently shown with the discovery of a family of taurine-conjugated fatty acids.11The challenge in identifying these metabolites was addressed in a three-step approach,(1)ultrahigh accuracy FTMS mass measurements,(2)high accuracy tandem mass analysis using a Q-TOF,and (3)chemical synthesis of potential candidates using the results and structural information gained from experiments (1)and (2).

3.Applications of Mass Spectrometry in Metabolomics

As metabolomics techniques become more robust and sophisticated,their applications become more widespread (Table 1).Combined with proteomics and genomics,metabo-lomics can help gain insight into systems biology,by studying the metabolite alterations and their relationships to changes in gene expression,protein expression and enzyme activity.98-100Despite the obvious challenges facing mass spectrometry in metabolomics,including the confirmation of known metabo-lites and the identification of unknown metabolites,many studies are underway employing these techniques.One par-ticularly successful application of metabolomics has been in understanding gene function in model organisms such as yeast,plants and mice.25,101-103Notably,metabolomics has been applied to mouse models of Huntingtons Disease,104cardiac disease,103and Duchenne muscular dystrophy.20

However,despite a great need and potential,there are currently very few metabolomic studies in cancer therapeutics.Metabolomics can be applied to the study of cancer by monitoring tumor growth and regression,and has already been used to study the function of hypoxia-inducible factor 1 in tumors.105By combining functional genomics with metabolo-mics,features of neuroendocrine cancers associated with a poor outcome have been identified.99

Figure 5.Identification of an unknown metabolite or confirmation of a known metabolite can be performed using mass spectrometry.The compound can be isolated using chromatography and characterization facilitated through accurate mass measurements to provide an elemental composition and tandem mass spectral data for structural information.Ultimately,synthetic standards are generated to validate (with perhaps other spectroscopic data),a structural hypothesis.

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Another important application of metabolomics is in the pharmaceutical arena,where it can be used to investigate drug efficacy and toxicity,to diagnose or predict disease states,or to classify patient groups based on their specific metabolism. By measuring alterations in biofluid metabolite concentrations after administration of a therapeutic agent,and applying multivariate statistical analysis techniques to highlight any differences between dosed and control samples,the effect of a potential drug can be studied.106Alterations in specific me-tabolites,such as succinate,glycine,and dimethylamine in the blood indicate kidney damage.17In addition,the nephrotoxin gentamicin,when administered to male Wistar-derived rats, has been shown to increase N-acetyl-beta-D-glucosaminidase (NAG)activity significantly,accompanied by kidney damage. Using a combination of NMR and HPLC-TOF-MS/MS,raised glucose and reduced trimethylamine N-oxide(TMAO),as well as reduced xanthurenic acid and kynurenic acid were observed in the urine of treated animals.23Furthermore,bromobenzene treatment to rats induces the formation of the novel biomarker, 5-oxoproline,in liver tissue,blood plasma,and urine.107These studies could be eventually expanded to humans,where metabolomics techniques may be able to highlight the re-sponses of different groups of patients to a given drug.In this way,metabolomics may dramatically reduce the costs of drug development,by eliminating the progression of compounds destined to fail due to toxicity.Additionally,in the drug development phase,metabolomics could also aid in the discovery of new preclinical and clinical safety and efficacy biomarkers.The timing of the appearance of small molecule markers in the particular biofluids may also be of importance.

The value of metabolomics in plant biotechnology has increased significantly,and despite the convoluted nature of plant metabolism,the interpretation of metabolomics data is becoming easier,in part due to more sophisticated data analysis approaches.Metabolomics can be used for the phe-notyping of plants,and has been used in part to assess the natural variance in metabolite profiles between plants,with the potential to improve compositional quality.26Already,metabo-lomic techniques have been applied to a vast array of plant species,such as potato,27tomato,108,109wheat,110rice,111Arabi-dopsis,25aspen,112cucumber,113strawberry,114and lettuce.115 Over1000small molecules have been quantitated in a single leaf extract,as well as more than500compounds from potato tubers.25,27

Summary and Outlook.The area of metabolomics is ex-panding rapidly and applications for this science range from basic biochemistry to clinical biomarker discovery.The primary challenge in metabolomics is in the generation of compre-hensive,quantitative profiles of the thousands of components present in biofluids,an issue that is largely being addressed with LC/MS technology.Data analysis is becoming more mature,due to the development of sophisticated bioinformatics software packages that will ultimately drive the discovery process.However,probably the greatest challenge in metabo-lomics is in structurally characterizing physiologically important molecules.The application of high-accuracy instruments and advancements in the generation of fragmentation data,along with the growing numbers of databases available,are gradually making this task possible.As these challenges are being met, it is encouraging that new potential biomarkers for diseases such as myocardial ischemia,116atherosclerosis,117muscular dystrophy,118influenza-associated encephalopathy,119and vari-ous cancers66,99,120are being identified.As metabolomics data is complementary to transcriptomics and proteomics,the data from all three approaches can be meshed to provide a more complete picture of cells and even whole organisms.Ultimately it is the discovery of novel metabolites10,11as well as correlating the changes of multiple metabolites with physiological events that make this area alluring and challenging. Acknowledgment.This work was supported by NIH Grant MH062261and DOE Grant DE-AC02-05CH11231.A.N. is supported by a postdoctoral fellowship from the Swedish Research Council(V.R.).

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英语论文题目中英文表达

"英语论文题目","英语论文选题方向" "Application of the communicative Approach to Reading Comprehension","英语教学法" "The Use of Body Language in Middle School English Teaching ","英语教学法" "Teaching Vocabulary Within a Communicative Frame Work用交际法教词汇","英语教学法" "Develop Students' Reading Skills in English Teaching","英语教学法" "A Brief Analysis of Improving Senior Middle School Students' Reading Ability浅谈高中生英语阅读能力的提高","英语教学法" "The Characteristics of Athletic English and Its Translation 体育英语的特点及翻译","翻译" "The Semantic Contrast of Color Words between English and Chinese and their Translation 中英颜色词的语义对比及翻译","翻译" "Chinese Reduplicated Words and their Translation into English 汉语叠词及其英译","翻译" "Brand Translation 商标翻译","翻译" "On Translating Methods of Numerals between Chinese and English中英数字的翻译方法","翻译" "Literal and Free Translation in the Translation of Advertisement Headlines and Slogans 广告用语的直译和意译","翻译" "On the Translation of Chinese Trade Mark into English 中文商标的英译","翻译" "The Analysis of the Chinese Topic Structure and Its Translation 汉语话题结构的分析及其翻译","语言学" "English Euphemism: Classification and Application","语言学" "Differences Between Chinese And English Culture Reflected in Connotation of Dragon 从龙一词的文化内涵看汉英文化的差异","文化" " English Vocabulary Teaching T actics in Junior Middle School初中英语词汇教学策略","英语教学法" "A Brief Presentation of Body Language in Intercultural Communication 跨文化交际身势语简述","文化" "English Euphemism: Classification and Application 英语委婉语的分类及其应用","语言学" "A General Study of Women's Culture对女性文化的初步探索","文化" "Criticism on American Southern Womanhood in the Sound and the Fury 浅谈《喧哗与骚动》中对于美国南方妇道观的批判","文化" "Reproduction of African Myth--on Colonialism in \"Heart of Darkness\" 非洲神话的再现-"黑暗之心"中的殖民主义","文学" "The Unification of T.S.Elict's Artistic Theory and Practice As Seen in the Waste Land 论"荒原"中T.S.艾略特的艺术理论与实践的统一","文学" "The Application of Gothic Theme"呼啸山庄"中哥特主题的应用","文学" "The Family Tragedy and Behavior Analysis of Teresa Degarge对特丽莎家庭悲剧和行为表现的研究","文学" "HAMLET APPRECIATION --SHAKESPEAKE'SSUCCESS IN CHARACTERS'S DEPIET"哈姆雷特"赏析--莎士比亚成功的人物描写","文学" "An Analsis of the Artistic Features of Lord of the Flies对小说《蝇王》的艺术特色的研究","文学" "A Exploration of Fagin Characters and His Function in Oliver Twist 对费金这个角色在《雾都孤儿》中作用的研究","文学" "THE ANALYSIS OF LISTENING APPROACH IN ENGLISH TEACHING 英语教学中关于听力教学方法的分析","英语教学法"

药物分析论文

阿司匹林对抗血栓的分析研究方法 姓名：陈曦 班级：制药132 学号：2013013085

阿司匹林对抗血栓的分析研究方法 【摘要】心血管疾病是危害人类健康的严重疾病，而抗血栓治疗是此类疾病抢救措施及预防策略的核心。抗血栓药按作用机制主要分为抗血小板药、抗凝血药和溶栓药三类。 【关键词】心血管疾病；抗血栓治疗；抗血小板药；抗凝血药。 心血管疾病是危害人类健康的严重疾病，是造成死亡的主要原因之一。心血管疾病是指由于心脏及血管病变而引起的一系列疾病，包括心脏病、高血压、高脂血症等。抗血栓治疗一直是心血管疾病抢救措施及预防策略的核心。抗血栓药按作用机制主要分为抗血小板药、抗凝血药和溶栓药三类。前两类主要用于预防血栓形成，是抗血栓治疗的重要方法，后一类主要用于急性心肌梗死、脑梗死后，溶解已形成的血栓。 1.抗凝血药 抗凝血药是通过影响凝血过程中的某些凝血因子阻止凝血过程的药物。正常人由于有完整的血液凝固系统和抗凝及纤溶系统，所以血液在血管内既不凝固也不出血，始终自由流动完成其功能，但当机体处于高凝状态或抗凝及纤溶减弱时，则发生血栓栓塞性疾病。目前常用的抗凝血药根据化学结构主要有以下两类： 1.1肝素类 肝素是一种由D-葡糖醛酸和N-乙酰-D葡糖胺残基交替排列，并经脱乙酰和硫酸化，D-葡糖醛酸转化为L-艾杜糖醛酸等一系列修饰而成的直链粘多糖。肝素是最早使用的抗凝药，在体内外均有很强的抗凝

作用，这是通过抗凝血酶Ⅲ来实现的，可有效地防止深静脉血栓和肺栓塞的形成，临床上常用于治疗急性心肌梗死和不稳定型心绞痛。该制剂只能静脉给药，当用量过多引起出血时，可用等量鱼精蛋白中和，长期使用肝素有引起出血的危险，副作用较大。与普通肝素相比，低分子量肝素类物质具有较强的抗Xa因子活性和促纤溶作用，其抑制凝血酶及血小板的作用较弱，且不增加血管通透性，故血小板减少及出血发生率明显减少。低分子量肝素类物质血浆蛋白非特异性结合力低，其生物利用度可达98%，量效关系明确，预期浓度和疗效准确，加之其本身对APTT影响不明显．故无需药物监测。低分子量肝素类物质血浆半衰期长，达200~300分钟，为未分馏肝素类物质的2~4倍。因此用药简单，一般经皮下注射给药，每日注射1次即可。 在1993年以前，深度静脉血栓和肺栓塞的治疗几乎完全依赖于肝素（heparin）。然而时至今日，由于低分子量肝素类产品更易给药且副反应发生率低，尤其是出血风险大为降低及用药后不需密集监测，故它们已经成为用来预防和治疗深度静脉血栓的主要临床选择。 1.2香豆素类 香豆素是一类含有4-羟基香豆素基本结构的物质，口服参与体内代谢才能发挥抗凝作用，称为口服抗凝药，这是唯一在临床广泛应用的口服抗凝血药，如双香豆素、华法林(苄丙酮香豆素)和醋硝香豆素，它们的化学结构与维生素K类似，故亦称为维生素K拮抗剂，它们的药理作用相同。 华法林与维生素K竞争羧化酶，使凝血因子Ⅱ、Ⅶ、Ⅸ、Ⅹ合成

100篇英文经典文献

share with 各位会计、财务专业的同学... （P.S.读英文期刊绝对是体力活...开读前一定要吃好睡好...） 这些是会计学的基础文献，是所有其他文献的参考文献~~~ 经典文献（The 100 articles with the highest citation index-until 1996） 参考：Lawrence D. Brown, 1996, “Influential Accounting Articles, Individuals, Ph. D Granting Institutions and Faculties; A Citational Analysis”, Accounting, Organizations and Society, Vol.21, NO.7/8, P726-728 1. Ball, R. and Brown, P., 1968, “An Empirical Evaluation of Accounting Income Numbers”, journal of Accounting Research, Autumn, pp. 159-178 1. 2.Watts R.L., Zimmerman J., 1978, “Towards a Positive Theory of the Determination of Accounting Standards”, The Ac counting Review, pp. 112-134 2. 3.Healy P.M, 1985, “The Effect of Bonus Schemes on Accounting Decisions”, Journal of Accounting and Economics, April, 85-107 3.Hopwood A. G., “Towards an Organizational Perspective for the Study of Accounting and Information S ystems”, Accounting, Organizations and Society (No. 1, 1978) pp. 3-14 4.Collins, D. W., Kothari, S. P., 1989, “An Analysis of Intertemporal and Cross-Sectional Determinants of Earnings Response Coefficients”, journal of Accounting & Economics, pp. 143-181 5.EastonP.D, Zmijewski M.E, 1989, “Cross-Sectional Variation in the Stock Market Response to Accounting Earnings Announcements”, Journal of Accounting and Economics, 117-141 6.Beaver, W. H., 1968, “The Information Content of Annual Earnings Announcements”, jo urnal of Accounting Research, pp. 67-92 7.Holthausen R.W., Leftwich R.W., 1983, “The Economic Consequences of Accounting Choice: Implications of Costly Contracting and Monitoring”, journal of Accounting & Economics, August, pp77-117 8.Patell J.M, 1976, “Corp orate Forecasts of Earnings Per Share and Stock Price Behavior: Empirical Tests. Journal of Accounting Research, Autumn, 246-276 9.Brown L.D., Griffin P.A., Hagerman R.L., Zmijewski M.E, 1987, “An Evaluation of Alternative Proxies for the Market’s Assessment of Unexpected Earnings”, Journal of Accounting and Economics, 61-87 10.Ou J.A., Penman S.H., 1989, “Financial Statement Analysis and the Prediction of Stock Returns”, Journal of Ac counting and Economics, Nov., 295-329 11.William H. Beaver, Roger Clarke, William F. Wright, 1979, “The Association between Unsystematic Security Returns and the Magnitude of Earnings Forecast Errors,” Journal of Accounting Research, 17, 316-340.

药物分析论文

药物化学论文 题目：苯佐卡因的合成 作者陈媛学号 系别化学化工系专业11师范班完成时间二0一四年六月十日

摘要：本文主要介绍了苯左卡因以硝基苯甲酸为原料的制备方法，以及苯左卡因的实验制备过程。通过对本文的学习，我们能够了解苯左卡因的化学 性质和发展状况以及他在医药方面的相关用途。 关键词：苯左卡因；硝基甲酸；合成 Abstract: This article mainly introduced benzene left Kain take the nitryl benzoic acid as raw material preparation method, as well as the benzene left Kain's experiment prepares the process.Through to this article study, we can understand the benzene left Kain's chemical property and the development condition as well as he in the medicine aspect related use. Key word: Benzene left Kain; Nitryl formic acid; Synthesis

1 苯佐卡因概况 1.1苯佐卡因的基本性质 苯佐卡因，英文名BenLzocaine，化学名为对氨基苯甲酸乙酷(Ethylp一aminobenzoate)或4一氨基苯甲酸乙酷(p~Aminobenzoieacidethylester)，化学分子式为CgHllNOZ，相对分子量为165.19。苯佐卡因为白色针状晶体，无臭，味苦。熔点91~92e，沸点183~184e(1.87kPa)。微溶于水，溶于乙醇!氯仿，乙醚。它是重要的医药中间体，可作为奥索仿!奥索卡因!普鲁卡因等前体原料。 1.2国内外制剂开发现状 国外使用苯佐卡因的制剂很多，美国药物索引1984年收载苯佐卡因制剂即达一百多种，其中片剂27种，软膏17种，霜剂6种，胶囊剂3种，还有凝胶剂!栓剂!洗剂!气雾剂等。苯佐卡因作用的特点适用于口腔科，如美国Beutllch生产的/Hurrieaine0是以水溶性聚乙二醇为基质，含20%苯佐卡因的软膏，主要用于口腔科注射前局部麻醉和牙结石!牙酿手术前的麻醉止痛;Armour生产的/AAA0气雾剂，含苯佐卡因1.5%，氯化节基十六烷基二甲基胺0.0413%，用于治疗由寒冷!滴鼻后和其他刺激所引起的咽喉痛，口腔溃疡及口腔咽喉的轻度感染;英国ICI的/复方洗必泰片0(HibitaneantisePtie)含盐酸洗必泰smg，苯佐卡因Zmg，治疗口腔和咽喉感染，缓解咽喉痛和喉炎，防止扁桃体切除术和牙科手术后的继发性感染。 美国药典(第24版)!英国药典(1998年版)!中国药典(2000年版)等对苯佐卡因制剂均有收载l6]。国内有制成散剂!5%软膏!栓剂，国外制剂品种较多，用于口腔杀菌!溃疡!咽喉止疼止痒，并且含片!喷雾剂!以及耳用制剂品种较多。与国外相比，苯佐卡因在我国的使用范围是非常狭窄的，仅仅在一些外用软膏中作为止痒成份，因此它的作用特点没有得到充分的发挥。美国药典(24版)还收载有单复方凝胶!软膏!霜剂!表面溶液剂等，我国这方面品种还没有。仅见盐酸丁卡因片(1997年新药品种汇编)适用于消化道内镜检查前麻醉咽喉粘膜。苯佐卡因疗效确切，安全有效，5中国药品6把它列为我国第一批非处方药(OTC)。其制剂的开发需要进一步加强。 2苯佐卡因合成研究现状 苯佐卡因的制备，有从甲基苯胺出发，有从对硝基苯甲酸出发，亦有从甲苯出发。当前国内厂家生产的苯佐卡因大部分都以对硝基苯甲酸和乙醇为原料，经酷

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药物分析文献综述

2016-20 17学年第1 学期 文献综述 名称高效液相色谱法手性固定相分手性药物研究进展专业2016级药物化学 学号161320217 姓名李松子 导师柯美荣 指导老师林子俺 时间2016年12月19日

高效液相色谱法手性固定相分手性药物研究进展 摘要 手性（chirality)是指化合物的分子式和结构式相同，因分子空间排列不同导致两个分子互为镜像和实物的现象。手性药物（chiral drug)是指药物分子结构中引人手性中心后得到的一对互为实物与镜像的对映异构体（enantiomer) 这些对映构体的理化性质基本相似，仅旋光性质有所差别。目前在约2000种常用药物中有近500种药物以外消旋体的形式存在。外消旋体药物中可能只有一种对映异构体有药效，其镜像分子却有毒副作用或药效相反或无药效：如左旋巴比妥酸盐抑制神经活动而右旋巴比妥酸盐却兴奋神经；右旋甲状腺素钠可降低血脂而左旋甲状腺素钠对心脏有毒副作用；抗菌药左旋氧氣沙星的药效高于其右旋体数倍对映异构体也对香料化学和农业化学方面有重要作用：如S-型的香芹酮有香菜味,而R-型却具有荷兰薄荷香味；农药溴氰菊酯的8个异构体中，（3R,1R,S）异构体的杀虫活性是（3S, lS，R)的70多倍。手性药物的分离分析在生物和化学领域一直是研究热点。 色谱法利用固定相与外消旋体之间的作用力不同使流动相洗脱时各组分保 留时间不同而实现分离的目的。色谱法以其优良的识别能力成为目前应用最广泛的手性拆分方法，尤其在性药物的分离分析和纯度检测等方面。常用的手性色谱分离技术包括高效液相色谱法（HPLC)、气相色谱法（GC)、毛细管电色谱法（CEC)等根据侍分离化合物的分子结构选择合适的手性色谱非常重要。 在用HPLC法分离手性物质时，可以通过改变色谱柱的流动相和固定相来改变改善HPLC的分离效果。根据手性固定相的不同来源，可分为天然、半合成和全合成三大类。本文介绍国内外近几年手性固定相拆分手性药物的研究进展，包括几种经典类型及一些新型手性固定相。固定相可分为几种经典的固定相：环糊精类手性固定相、多糖类手性固定相、Pirkle 型手性固定相、蛋白质类手性固定相。根据添加剂的性质可将手性流动相添加剂(CMPA)分为4类：配基交换型手性添加剂、手性离子型配合剂、环型葡聚糖添加剂以及基于其他作用的手性流动相添加剂。 1.几种经典手性固定相的手性药物拆分