Mass Spectrogram Research Articles

Analysis of pattern recognition and dimensionality reduction techniques for odor biometrics

In this paper, we analyze the performance of several well-known pattern recognition and dimensionality reduction techniques when applied to mass-spectrometry data for odor biometric identification. Motivated by the successful results of previous works capturing the odor from other parts of the body, this work attempts to evaluate the feasibility of identifying people by the odor emanated from the hands. By formulating this task according to a machine learning scheme, the problem is identified with a small-sample-size supervised classification problem in which the input data is formed by mass spectrograms from the hand odor of 13 subjects captured in different sessions. The high dimensionality of the data makes it necessary to apply feature selection and extraction techniques together with a simple classifier in order to improve the generalization capabilities of the model. Our experimental results achieve recognition rates over 85% which reveals that there exists discriminatory information in the hand odor and points at body odor as a promising biometric identifier.

Components analysis of volatile matter in simethicone by gas chromatography-mass spectrometry

The aims of the present study were to analyze the chemical compositions of volatile matter in simethicone crude drug qualitatively and quantitatively. Gas chromatography-mass spectrum (GC-MS) method was used for the separation and determination of the volatile matter in simethicone. The qualitative analysis of volatile matter components in simethicone with the viscosity of 500-centistokes (cs) was studied by GC-MS, through the interpretation of the mass spectrogram and investigation of the law of peaks. Area normalization method was used for preliminary quantitative analysis according to the GC spectrogram. The total content of volatile matter in simethicone was determined by loss on heating method. 42 components in the sample were identified in our study, which accounted for 99.21% of the total volatile matter content, including two sets of homologous compounds: 20 species of linear methylpolysiloxane (MDmM, MM to MD21M) and 22 species of cyclic methylpolysiloxane (Dn, D3 to D24). Our study offered scientific evidence for improving the production condition and controlling the quality of simethicone. Key words: Simethicone, volatile matter, gas chromatography-mass spectrometry (GC-MS).

Water-soluble non-alkaloid chemical constituents contained in Corydalis yanhusuo by trimethylsilyl derivatization GC-MS

To study the water-soluble non-alkaloid chemical constituents of Corydalis yanhusuo. The 80% alcohol extracts of C. yanhusuo passed through DA201 macroporous resin. Eluted fractions were collected and passed though 732 # cation exchange resin. Water eluate was collected, dried and derived with trimethylsilane. Gas Chromatography/Mass Spectrometry and NIST 2005 library were adopted for MS/MS mass spectrogram to infer the compound structure. Sixteen compounds were tentatively identified from about fifty peaks detected by GC-MS and identified as hydroxyl and carboxyl polar compounds. These sixteen compounds were found for the first time in C. yanhusuo. The results provide scientific basis for in-depth development of C. yanhusuo.

SIMS studies of titanium biomaterial hydrogenation after magnetoelectropolishing

Hydrogenation of the commercial purity (99%) CP Titanium Grade 2 biomaterial was investigated using the secondary ion mass spectrometry (SIMS) after two finishing electrochemical operations: standard electropolishing (EP), and magnetoelectropolishing (MEP). The SIMS depth profile analyses were carried out right after electropolishing, and again one month later. The mass spectrograms of secondary positive and negative ions were recorded. SIMS spectra reveal higher emission of positive O+, Ti+ and TiO+ secondary ions which corresponds to higher oxidation of MEP sample. Negative spectra show higher concentration of compounds containing carbon on MEP sample than those of EP sample. Lower content of hydrogen in the near-surface layers in the MEP sample right after the process was revealed. It was found that the concentrations of oxygen and hydrogen alter in time. One month of storage in air causes the contents of hydrogen in EP and MEP samples to be equalized. The SIMS studies performed after a one month period show that the differences in hydrogen contents between EP and MEP samples are not significant.

Detection of Murine Toxoplasmosis Using Magnetic Bead-Based Serum Peptide Profiling by MALDI-TOF MS

Establishment of a rapid, highly specific, and accurate method for diagnosis of Toxoplasma gondii infection is essential to control and prevent zoonotic toxoplasmosis. In this study, a novel diagnostic strategy using magnetic bead-based serum peptide profiling by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was developed. The serum peptides (samples I, II, and III) from T. gondii RH strain-infected mice at days 3, 6, and 9 post-infection (p.i.), and healthy mice were enriched by the optimized magnetic bead-based hydrophobic interaction (MB-HIC8). The mass spectrograms were acquired by MALDI-TOF MS, and analyzed by ClinProTools bioinformatics software from Bruker Daltonics. The diagnostic models from T. gondii RH-infected serum peptide profiling of samples I, II, and III were produced by genetic algorithms, and verified by cross-validation. The sample II model could correctly recognize T. gondii RH strain infection in mice at days 3, 6, and 9 p.i. with a sensitivity of 91.1% and a specificity of 96.7%., and also detect T. gondii ME49 strain-infected serum samples at days 3, 6, 9, and 12 p.i. with a sensitivity of 91.7%. The results of the present study suggest that serum peptide profiling by MALDI-TOF MS is a novel potential tool for the clinical diagnosis of acute T. gondii infection.

Application of PCA-RBF Method to QSRR Studies on Hydrocarbon in FCC Gasoline with PCA-RBF

A novel Artificial Neutral Network (ANN) algorithm based on Principle component analysis(PCA) is proposed and applied to predicted the retention index of a series of hydrocarbons in FCC gasoline. The PCA technology is utilized to preprocess the mass spectrogram of FCC gasoline for parameter selection and to reduce the input of prediction model, which thus improve the input factors and eliminates the correlation among the inputs. Then new sample data are input into radial basis function-artificial neutral network(RBF-ANN) to construct the prediction model.156 compounds were divided into two subsets. RSM of training set and testing set is 0.9958 and 0.9991, respectively. The satisfactory results were obtained.

Detection of Leishmania donovani infection using magnetic beads-based serum peptide profiling by MALDI-TOF MS in mice model

Leishmaniasis is an important parasitic disease, and definite diagnosis using a specific and sensitive method is the first step to cure the disease. Here, we present a novel diagnostic strategy based on serum peptide profiling by magnetic beads and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The serum peptides from the Leishmani donovani-infected and healthy mice were enriched by the optimized magnetic beads. The mass spectrograms were acquired by MALDI-TOF MS and analyzed by the ClinProTools bioinformatics software from Bruker Daltonics. The diagnostic model of serum peptide profiling produced by the ClinProTools software could correctly detect L. donovani infection in mice from the third day post-infection, with the accuracy of 94.1%, sensitivity of 92.4%, and specificity of 97.1%, respectively. The results of the present study suggested that the serum peptide profiling by MALDI-TOF MS is a novel potential tool for the clinical diagnosis of leishmaniasis.

Classification algorithms for predicting sleepiness and sleep apnea severity

Identifying predictors of subjective sleepiness and severity of sleep apnea are important yet challenging goals in sleep medicine. Classification algorithms may provide insights, especially when large data sets are available. We analyzed polysomnography and clinical features available from the Sleep Heart Health Study. The Epworth Sleepiness Scale and the apnea-hypopnea index were the targets of three classifiers: k-nearest neighbor, naive Bayes and support vector machine algorithms. Classification was based on up to 26 features including demographics, polysomnogram, and electrocardiogram (spectrogram). Naive Bayes was best for predicting abnormal Epworth class (0-10 versus 11-24), although prediction was weak: polysomnogram features had 16.7% sensitivity and 88.8% specificity; spectrogram features had 5.3% sensitivity and 96.5% specificity. The support vector machine performed similarly to naive Bayes for predicting sleep apnea class (0-5 versus >5): 59.0% sensitivity and 74.5% specificity using clinical features and 43.4% sensitivity and 83.5% specificity using spectrographic features compared with the naive Bayes classifier, which had 57.5% sensitivity and 73.7% specificity (clinical), and 39.0% sensitivity and 82.7% specificity (spectrogram). Mutual information analysis confirmed the minimal dependency of the Epworth score on any feature, while the apnea-hypopnea index showed modest dependency on body mass index, arousal index, oxygenation and spectrogram features. Apnea classification was modestly accurate, using either clinical or spectrogram features, and showed lower sensitivity and higher specificity than common sleep apnea screening tools. Thus, clinical prediction of sleep apnea may be feasible with easily obtained demographic and electrocardiographic analysis, but the utility of the Epworth is questioned by its minimal relation to clinical, electrocardiographic, or polysomnographic features.

UPLC-MS analysis of constituents of Dachuanxiong Fang active parts absorbed into blood

To study the constituents absorbed into blood following the intragstric administration of Dachuanxiong Fang active parts(DCXF) to the experimental migrainous model rats induced by nitroglycerin. The UPLC-MS was used as the analytic method. The DCXF, Chuanxiong active parts, Tianma active parts, gastrodin, ferulic acid and senkyunolide I were used as the control samples. The information on the total ion chromatogram, mass chromatogram and the mass spectrogram were synthetically analyzed to confirm the constituents absorbed into blood. Ten of the DCXF constituents were detected in the rats plasma post the intragastric administration of DCXF, in whitch four including gastrodin came from Tianma active parts and six including ferulic acid and senkyunolide I from Chuanxiong active parts. The findings abtained from the study can provide the useful information for the determination of bioactive substances of the DCXF.

Optimum ion implantation and annealing conditions for stimulating secondary negative ion emission

The type, energy, ion dose, and heating temperature required to ensure a stable minimum work function of a surface in one experimental cycle (at least 2–3 min) are determined. Secondary ion mass spectrograms are recorded using Cs+, Ba+, and Ar+ ions. Cu, Al, and Mo samples are studied. The optimum ion implantation conditions and the activation temperature that provide a stable minimum work function of the sample surfaces are found. The samples implanted by Ba+ ions withstand higher temperature and current loads than the samples implanted by Cs+ ions. However, the work function in the case of Cs+ ions decreases stronger (to 1.9 eV). It is shown that neutral sputtered particles do not leave the surface at eφ ≤ 1.85–1.90 eV.

Efficient separation of homologous α-lactalbumin from transgenic bovine milk using optimized hydrophobic interaction chromatography

Transgenic bovine milk could be a rich source of recombinant human proteins. However, the co-presence of bovine and human homologous proteins can be a challenge for product purification. In this study, the average surface hydrophobicity and electric potential of human α-lactalbumin (HLA) and bovine α-lactalbumin (BLA) were analyzed and compared through the exposure area calculation of different amino acids. Based on the analysis, calcium independent hydrophobic interaction chromatography was selected for separation of recombinant human α-lactalbumin (rHLA) from BLA in transgenic bovine milk. The operating conditions for the best separation of two proteins were predicted by fluorescence data. Three commercially available HIC resins (Butyl Sepharose 4 FF, Octyl Sepharose 4 FF, Phenyl Sepharose 6 FF) were compared. The transgenic milk was skimmed and treated by pH adjustment to remove a large quantity of casein protein. The supernatant was loaded on the hydrophobic interaction chromatographic matrix. The correct elution fraction was further treated with gel filtration chromatography. The overall recovery of rHLA was up to 67.1% with the purity greater than 95%. Circular dichroism spectroscopy (CD) and mass spectrogram (MS) confirmed the native state and glycosylated form of the purified rHLA.

Structure–biodegradability relationship of nonylphenol isomers during biological wastewater treatment process

The relationship between nonylphenol (NP) isomer structure and its biodegradability within the wastewater treatment process of sequencing batch reactor (SBR) was investigated. The GC–MS method was used for detecting the NP isomers existing in the SBR influent, activated sludge and effluent. Fifteen NP isomers were detected in the influent, with significant biodegradability variations being observed among these isomers. It was found that the NP isomers associated with retention time of 10.553, 10.646, 10.774, and 10.906 min in the GC–MS analysis showed higher biodegradability, while the isomers with retention time of 10.475, 10.800, and 10.857 min illustrated lower biodegradability. Through analyzing the mass spectrograms, the chemical structures of four selected NP isomers in the wastewater were further deduced. The higher correlation coefficients of 0.9421 and 0.9085 were observed between the NP isomer biodegradation rates and the molecular connectivity indexes with the order of two and four, respectively. Such correlation analysis indicated that a more complex side branch structure (such as a larger side carbon-chain branch or more branches in the nonyl) of NP isomer would lead to lower biodegradability, and a longer nonyl chain of the isomer would result in a higher biodegradability.

Comparison of MTBSTFA and BSTFA in derivatization reactions of polar compounds prior to GC/MS analysis

In this study, MTBSTFA and BSTFA, which are among the preferred derivatization reagents for silylation were both tested on derivatization of six different groups of polar chemicals to get information about usefulness in terms of sensitivity and specificity of both reagents. Tested compound groups were nitrophenols and methoxyphenols, sterols and sugars, dicarboxylic acids and hydroxylated polycyclic aromatic hydrocarbons. It was found that MTBSTFA-derivates produce characteristic fragmentation patterns presenting mainly the fragments [M] +, [M−57] + and [M−131] +, of which [M−57] + is generally dominant on the mass spectrogram. BSTFA-derivates mainly show the fragments [M] +, [M−15] + and [M−89] + whereof the molecular ion [M] + is generally dominant. It was also found that steric hindrance and molecular mass play a very important role in the choice of the best suited derivatization reagent: compounds with sterically hindered sites derivatized with MTBSTFA produce very small analytical responses or no signal at all, and compounds with high molecular mass produce no characteristic fragmentation pattern when derivatization is performed with BSTFA. It was also found that MTBSTFA-derivatization facilitates separation of isomer analytes, suggesting its choice in combination to semi-polar columns, whilst BSTFA seems better for sterically hindered compounds. Findings were confirmed with applications of both reagents to biological and environmental matrices (urine and atmospheric aerosols).

Optimization of Bioinformatics Analysis Conditions by Peptide Mass Fingerprint Identify Proteins

The bioinformatics analysis conditions (databases and major parameters) in the process of Peptide Mass Fingerprint (PMF) identify target proteins were optimized in this study. In this process of experiment design and analysis, the Bovine Carbonic anhydrase-2 (CAH2_BOVIN) and human Hsp70s protein (Heat shock protein 70) were separated by two-dimension electrophoresis(2-DE), proteolysis by Trypsin Gold, and then the lysed peptides were gathered and analyzed using MALDI-TOF-MS, and the peptides mass data and mass spectrogram were obtained. In this study, the Swissprot, MSDB, NCBInr, Random databases, MASCOT, and MS-Fit were selected as search engines, and the standard CAH2_BOVIN was used as model to set up protein search standard conditions. Results show that Swissprot is the better database for protein PMF study, the better missed cleavage is one site, the better peptide tolerance is ±1 Da, and average peptide mass type is better than monoisotopic type to get target proteins. Then human Hsp70s protein mass data was used as sample to check the accuracy of MS search standard conditions. Results show that the optimized databases and parameters are reliable.

Detection and Significance of Serum Protein Marker of Hirschsprung Disease

The objective of this study was to identify a specific fingerprint chromatogram model of serum proteins for early screening and diagnosis of Hirschsprung disease. To detect the protein mass spectrograms of 78 serum specimens (42 specimens of Hirschsprung disease, 16 specimens of adhesive ileus including appendicitis and Meckel diverticulum after operation and inflammatory bowel disease, and 20 specimens of normal control subjects), we used surface-enhanced laser desorption/ionization time of flight mass spectrometry technology, combined with bioinformatics methods (support vector machine) to develop and compare protein mass spectrograms from serum samples. We identified 3 protein markers, the mass-to-charge ratio of which is positioned at 3221.7, 5639.2, and 6884.2 from the fingerprint chromatogram model of serum protein for early screening and diagnosis of Hirschsprung disease. The markers had 100% sensitivity and specificity. The fingerprint chromatogram model of serum protein using surface-enhanced laser desorption/ionization time of flight mass spectrometry technology combining support vector machine is a new method of early screening and diagnosis of Hirschsprung disease that is worthy of additional research and application.

Serum biomarkers for Alzheimer's disease: Proteomic discovery

For Alzheimer's disease (AD), the most common neurodegenerative disease, there is no simple, cost-effective biomarker for disease identification. Using novel mass spectrometry (MS)-based techniques, and analysis of the albumin-enriched low molecular weight proteome, minute amounts of human serum were analyzed for the measurement of thousands of peptides and proteins in parallel. The mass spectrograms were then evaluated with a novel computer algorithm to identify spectral peaks that discriminate between samples from patients with and without AD. There are four peaks that distinguish AD from control subjects and AD subjects from those with Parkinson's disease (PD). Additionally, after analyzing data from a recently published study of AD and control subjects, we found three discriminating peaks in common with the four from our patient serum samples. The identification of these peptides/proteins, and their direct measurement in patient serum, may allow the development of a simple, cost-effective test for AD.

Speciation Distribution of Polycyclic Aromatic Sulfur Heterocycles in Crude Oil

A method for speciation analysis of polycyclic aromatic sulfur heterocycles (PASHs) in crude oil was established. The PASHs were separated from the oil sample by ligand exchange chromatography using SiO 2 with PdCl 2. The sulfur compounds were then determined by gas chromatography using a mass spectrogram detector (GC/MS), gas chromatography with a sulfur chemiluminescence detector (GC-SCD), and chromatography retention index of the compounds. More than 100 PASHs (including alkyl benzothiophene, dibenzothiophene, and alkyl dibenzothiophene) were identified. The dibenzothiophene and alkyl dibenzothiophene represent about 91 % of the total PASHs in crude oil. The method can be applied for speciation analysis of PASHs in crude oils from different sources.

Optimally matched wavelets

AbstractSeveral applications require to retrieve a certain pattern from a signal where the actual scaling of the pattern is not known before. We consider applications like evaluation of mass spectrograms, detection of component wearout by observing the current of an engine, detection of pollutions of rotor spinning machines, decomposition of (audio) signals into time‐frequency atoms.We try to solve this problem with discrete wavelet transforms where the wavelet function is constructed to match the given pattern. An approach for a biorthogonal basis constructed by the lifting scheme is presented. This method is rather simple and fast and allows the choice of the smoothness at least of the primal wavelet in a very natural way. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Identification of major active constituents in the fingerprint of Salvia miltiorrhiza Bunge developed by high-speed counter-current chromatography

High-speed counter-current chromatography was applied as a method to develop fingerprinting of Salvia miltiorrhiza Bunge, a popular traditional Chinese medicine, in our previous study. Important active constituents that were directly related to the therapy effect should be identified. Each effluent fraction and standard samples (cryptotanshinone, tanshinoneI and tanshinoneIIA) were analyzed by ultraviolet spectroscopy and liquid chromatography–mass spectroscopy. It was concluded from the UV-Vis spectrograms, retention times in LC analysis and mass spectrograms, that fractions 7, 8 and 11 were respectively cryptotanshinone (M r 296), tanshinone I (M r 276) and tanshinone IIA (M r 294).

Identification of major active constituents in the fingerprint of Salvia miltiorrhiza Bunge developed by high-speed counter-current chromatography

High-speed counter-current chromatography was applied as a method to develop fingerprinting of Salvia miltiorrhiza Bunge , a popular traditional Chinese medicine, in our previous study. Important active constituents that were directly related to the therapy effect should be identified. Each effluent fraction and standard samples (cryptotanshinone, tanshinoneI and tanshinoneIIA) were analyzed by ultraviolet spectroscopy and liquid chromatography–mass spectroscopy. It was concluded from the UV-Vis spectrograms, retention times in LC analysis and mass spectrograms, that fractions 7, 8 and 11 were respectively cryptotanshinone (M r 296), tanshinone I (M r 276) and tanshinone IIA (M r 294).