Tissue distribution of lignans in rats in response to diet, dose−response, and competition with isoflavones

This paper investigates the occurrence and distribution of the lignan metabolites enterodiol (END) and enterolactone (ENL) and the isoflavone daidzein (DAID) in rat tissues by use of liquid chromatography−electrospray ionization mass spectrometry (LC−ESI/MSn) following a variety of dietary regimes. Furthermore, we examined the dose−response and distribution of END and ENL in liver, testes, prostate, and lung, and we investigated the effects of competition between lignans and isoflavones on metabolite distribution. In liver, testes, prostate, and lung tissue, dose-related increases in END concentration were observed. In the testes, coadministration of 60 mg/kg secoisolariciresinol diglycoside (SDG) with 60 mg/kg isoflavones produced alterations in the resulting metabolite profile, causing increased END concentration and decreased DAID concentration. Results indicate lignan accumulation in tissues occurs, and coadministration of lignans with isoflavones affects the metabolite profile, with effects dependent on tissue type.

Comprehensive profiling and quantitation of amine group containing metabolites

Primary and secondary amines, including amino acids, biogenic amines, hormones, neurotransmitters, and plant siderophores, are readily derivatized with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate using easily performed experimental methodology. Complex mixtures of these amine derivatives can be fractionated and quantified using liquid chromatography–electrospray ionization-mass spectrometry (LC–ESI-MS). Upon collision induced dissociation (CID) in a quadrupole collision cell, all derivatized compounds lose the aminoquinoline tag. With the use of untargeted fragmentation scan functions, such as precursor ion scanning, the loss of the aminoquinoline tag (Amq) can be monitored to identify derivatized species; and the use of targeted fragmentation scans, such as multiple reaction monitoring, can be exploited to quantitate amine-containing molecules. Further, with the use of accurate mass, charge state, and retention time, identification of unknown amines is facilitated. The stability of derivatized amines was found to be variable with oxidatively labile derivatives rapidly degrading. With the inclusion of antioxidant and reducing agents, tris(2-carboxyethyl)-phosphine (TCEP) and ascorbic acid, into both extraction solvents and reaction buffers, degradation was significantly decreased, allowing reproducible identification and quantification of amine compounds in large sample sets.

Analysis of residues of prometryne and acetochlor in soil-water system by solid-phase extraction and gas chromatography/mass spectrometry

A highly sensitive and simple analytical method was developed for analyzing the binary mixed pesticides of prometryne and acetochlor in soil–water system by gas chromatography/mass spectrometry (GC/MS). The sample solution was first purified by C18 solid-phase extraction column, which was leached by acetone. The leachate was enriched to 1.0 mL by pressure blowing concentrator and then analyzed by GC/MS. The linear calibration curves were showed in the range of 1–15 μg/mL with a correlation coefficient of 0.9991. The average recoveries (n = 5) were between 95.3 and 115.7%, with relative standard deviations ranged from 1.71 and 7.95%. The limits of detection of Prometryne/Acetochlor were up to 0.06 and 0.17 μg/mL, respectively. This method provides a reliable approach to examine and evaluate the residues of prometryne and acetochlor in the soil–water system.

Different complexation behavior of P-functionalized ferrocene derivatives towards SnCl2 , SnCl4 and SnPh2 Cl2 : auto-ionization and redox-type reactions

The novel phosphonyl-substituted ferrocene derivatives [Fe(η(5) -Cp)(η(5) -C5 H3 {P(O)(O-iPr)2 }2 -1,2)] (Fc(1,2) ) and [Fe{η(5) -C5 H4 P(O)(O-iPr)2 }2 ] (Fc(1,1') ) react with SnCl2 , SnCl4 , and SnPh2 Cl2 , giving the corresponding complexes [(Fc(1,2) )2 SnCl][SnCl3 ] (1), [{(Fc(1,1') )SnCl2 }n ] (2), [(Fc(1,1') )SnCl4 ] (3), [{(Fc(1,1') )SnPh2 Cl2 }n ] (4), and [(Fc(1,2) )SnCl4 ] (5), respectively. The compounds are characterized by elemental analyses, (1) H, (13) C, (31) P, (119) Sn NMR and IR spectroscopy, (31) P and (119) Sn CP-MAS NMR spectroscopy, cyclovoltammetry, electrospray ionization mass spectrometry, and single-crystal as well as powder X-ray diffraction analyses. The experimental work is accompanied by DFT calculations, which help to shed light on the origin for the different reaction behavior of Fc(1,1') and Fc(1,2) towards tin(II) chloride.

Phytochemical analysis of Hibiscus caesius using high performance liquid chromatography coupled with mass spectrometry

Various species in genus Hibiscus are traditionally known for their therapeutic attributes. The present study focused on the phytochemical analysis of a rather unexplored species Hibiscus caesius (H. caesius), using high-pressure liquid chromatography coupled with mass spectrometry (HPLC-MS). The analysis revealed five major compounds in the aqueous extract, viz. vanillic acid, protocatechoic acid, quercetin, quercetin glucoside and apigenin, being reported for the first time in H. caesius. Literature suggests that these compounds have important pharmacological traits such as anti-cancer, anti-inflammatory, anti-bacterial and hepatoprotective etc. however, this requires further pharmacological investigations at in vitro and in vivo scale. The above study concluded the medicinal potential of H. caesius.

Analysis of self-assembled monolayer interfaces by electrospray mass spectrometry : a gentle approach

A general mass spectrometry technique for the characterization of alkanethiol-modified surfaces is presented. Alkanethiol self-assembled onto a gold surface (in this case, peptides were attached to the gold surface via a thiolate bond) was reductively desorbed in 0.05 M KOH in the presence of octadecyl-derivatized silica gel. The peptide adsorbed onto the silica gel, whereupon it could be filtered, washed to remove any salts, and then eluted using a mixture of 4:1 v/v methanol/water. The eluant containing the peptide was injected into a Fourier transform ion-cyclotron resonance mass spectrometer (FTICR/MS) via electrospray ionization. The spectrum showed no fragmentation of the peptide, demonstrating the gentleness of the technique. This simple procedure is not limited to FTICR/MS and could be adapted to other mass spectrometers.

Gas chromatography-chemical ionization-mass spectrometric fatty acid analysis of a commercial supercritical carbon dioxide lipid extract from New Zealand green-lipped mussel (Perna canaliculus)

Supercritical fluid extracts of New Zealand green-lipped mussels (NZGLM) have been suggested to have therapeutic properties related to their oil components. The large number of minor FA in NZGLM extract was characterized by a GC-CIMS/MS method that excels at identification of double-bond positions in FAME. The extract contained five major lipid classes: sterol esters, TAG, FFA, sterols, and polar lipids. The total FA content of the lipid extract was 0.664 g/mL. Fifty-three unsaturated FA (UFA) were fully identified, of which 37 were PUFA, and a further 21 UFA were detected for which concentrations were too low for assignment of double-bond positions. There were 17 saturated FA, with 14∶0, 16∶0, and 18∶0 present in the greatest concentration. The 10 n−3 PUFA detected included 20∶5n−3 and 22∶6n−3, the two main n−3 FA; n−3 PUFA at low concentrations were 18∶3, 18∶4, 20∶3, 20∶4, 21∶5, 22∶5, 24∶6, and 28∶8. There were 43 UFA from the n−4, n−5, n−6, n−7, n−8, n−9, n−10, n−11 families, with 16∶2n−4, 16∶1n−5, 18∶1n−5, 18∶2n−6, 20∶4n−6, 16∶1n−7, 20∶1n−7, 16∶1n−9, 18∶1n−9, and 20∶1n−9 being the most abundant. In general, we estimated that FAME concentrations greater than 0.05% (w/w) were sufficient to assign double-bond positions. In total, 91 FA were detected in an extract of the NZGLM, whereas previous studies of fresh flesh from the NZGLM had reported identification of 42 FA. These data demonstrate a remarkable diversity of NZGLM FA.

A clustering based hybrid system for mass spectrometry data analysis

Recently, much attention has been given to the mass spectrometry (MS) technology based disease classification, diagnosis, and protein-based biomarker identification. Similar to microarray based investigation, proteomic data generated by such kind of high-throughput experiments are often with high feature-to-sample ratio. Moreover, biological information and pattern are compounded with data noise, redundancy and outliers. Thus, the development of algorithms and procedures for the analysis and interpretation of such kind of data is of paramount importance. In this paper, we propose a hybrid system for analyzing such high dimensional data. The proposed method uses the k-mean clustering algorithm based feature extraction and selection procedure to bridge the filter selection and wrapper selection methods. The potential informative mass/charge (m/z) markers selected by filters are subject to the k-mean clustering algorithm for correlation and redundancy reduction, and a multi-objective Genetic Algorithm selector is then employed to identify discriminative m/z markers generated by k-mean clustering algorithm. Experimental results obtained by using the proposed method indicate that it is suitable for m/z biomarker selection and MS based sample classification.

Dimensionality reduction of protein mass spectrometry data using random projection

Protein mass spectrometry (MS) pattern recognition has recently emerged as a new method for cancer diagnosis. Unfortunately, classification performance may degrade owing to the enormously high dimensionality of the data. This paper investigates the use of Random Projection in protein MS data dimensionality reduction. The effectiveness of Random Projection (RP) is analyzed and compared against Principal Component Analysis (PCA) by using three classification algorithms, namely Support Vector Machine, Feed-forward Neural Networks and K-Nearest Neighbour. Three real-world cancer data sets are employed to evaluate the performances of RP and PCA. Through the investigations, RP method demonstrated better or at least comparable classification performance as PCA if the dimensionality of the projection matrix is sufficiently large. This paper also explores the use of RP as a pre-processing step prior to PCA. The results show that without sacrificing classification accuracy, performing RP prior to PCA significantly improves the computational time.

Mass spectrometry cancer data classification using wavelets and genetic algorithm

This paper introduces a hybrid feature extraction method applied to mass spectrometry (MS) data for cancer classification. Haar wavelets are employed to transform MS data into orthogonal wavelet coefficients. The most prominent discriminant wavelets are then selected by genetic algorithm (GA) to form feature sets. The combination of wavelets and GA yields highly distinct feature sets that serve as inputs to classification algorithms. Experimental results show the robustness and significant dominance of the wavelet-GA against competitive methods. The proposed method therefore can be applied to cancer classification models that are useful as real clinical decision support systems for medical practitioners.