Chemical composition, antioxidant, anti-inflammatory and antiproliferative activities of the essential oil of Cymbopogon nardus, a plant used in traditional medicine.

Objectives Natural products commonly used in traditional medicine, such as essential oils (EOs), are attractive sources for the development of molecules with anti-proliferative activities for future treatment of human cancers, e.g., prostate and cervical cancer. In this study, the chemical composition of the EO from Cymbopogon nardus was characterized, as well as its antioxidativeproperties and anti-inflammatory and antiproliferative activities on LNCaP cells derived from prostate cancer. Methods The chemical composition of the EO was determined by GC/FID and GC/MS analyses. The antioxidative properties were assessed using DPPH radical scavenging assay and ABTS+• radical cation decolorization assay, and the anti-inflammatory capacity was determined by the inhibition of the lipoxygenase activity. Antiproliferative activity was evaluated by MTT assay. Results Collectively, our data show that the major constituents of C. nardus EO are citronellal (33.06 %), geraniol (28.40 %), nerol (10.94 %), elemol (5.25 %) and delta-elemene (4.09 %). C. nardus EO shows modest antioxidant and anti-inflammatory activity compared to the standard galic acid. C. nardus EO exhibits the best antiproliferative activity on the prostate cancer cell line LNCaP with an IC50 of 58.0 ± 7.9 µg/mL, acting through the induction of the cell cycle arrest. Conclusions This study has determined that C. nardus EO efficiently triggers cytotoxicity and pens a new field of investigation regarding the putative use of this EO in vivo.

Quantitative Analysis of Metabolites at the Single-Cell Level by Hydrogen Flame Desorption Ionization Mass Spectrometry.

To date, direct quantitation of cellular metabolites at the picoliter level or in a single cell is still a challenge due to tiny sampling materials, the accuracy of the sampling volume, and the ubiquitous matrix effect. Herein, picoliter magnitude quantitative analysis was performed using a pressure-assisted microsampling probe coupled to the hydrogen flame desorption ionization mass spectrometer (HFDI-MS). The sampling was accurately controlled with a picoliter pump, and the analytes were rapidly vaporized and quantitatively transferred to the gas phase by adequate heat. The vapor-phase analytes reacted with protonated water cluster ions by the proton-transfer reaction (PTR). The accurate sampling, flash thermal desorption, and proton-transfer ionization processes were conducted spatiotemporally, which could greatly reduce matrix effects to facilitate the quantitation of analytes without the internal standard. Furthermore, this workflow enabled the quantitation of cellular metabolites at the picoliter/single-cell level.

Green chromatography determination of fatty acid methyl esters in biodiesel.

This work proposes a green, simple and rapid chromatographic methodology for separation and determination of a group of 13 fatty acids methyl esters (FAMEs) by using a capillary gas chromatography with a flame ionization detector. The method was successfully applied for the determination of FAMEs in biodiesel samples from commercial and waste cooking oils, synthesized by homogeneous catalysis. Detection and quantification limits were in the µg L(-1) level. Direct injection of sample solution was compared with solid-phase extraction and solid-phase microextraction procedures, giving similar results. The lower analysis time represent considerable improvement compared with other papers. The described methodology is especially suitable for process control applications. The samples analysed showed total contents of FAMEs higher than 96.5%, which verifies the European regulations.

Metabolic fingerprinting of hard and semi-hard natural cheeses using gas chromatography with flame ionization detector for practical sensory prediction modeling.

Metabolic fingerprinting using gas chromatography with flame ionization detector (GC/FID) was used to generate a practical metabolomics-based tool for quality evaluation of natural cheese. Hydrophilic low molecular weight components, relating to sensory characteristics, including amino acids, fatty acids, amines, organic acids, and saccharides, were extracted and derivatized prior to the analysis. Data on 12 cheeses, six Cheddar cheeses and six Gouda cheeses, were analyzed by multivariate analysis. Prediction models for two sensory attributes relating to maturation, "Rich flavor" and "Sour flavor", were constructed with 4199 data points from GC/FID, and excellent predictability was validated. Chromatograms from GC/FID and gas chromatography/time-of-flight-mass spectrometry (GC/TOF-MS) were comparable when the same column was used. Although GC/FID alone cannot identify peaks, the mutually complementary relationship between GC/FID and GC/MS does allow peak identification. Compounds contributing significantly to the sensory predictive models included lactose, succinic acid, L-lactic acid, and aspartic acid for "Rich flavor", and lactose, L-lactic acid, and succinic acid for "Sour flavor". Since similar model precision was obtained using GC/FID and GC/TOF-MS, metabolic fingerprinting using GC/FID, which is a relatively inexpensive instrument compared with GC/MS, is easy to maintain and operate, and is a valid alternative when metabolomics (especially using GC/MS) is to be used in a practical setting as a novel quality evaluation tool for manufacturing processes or final products.

Hollow fiber liquid-phase microextraction coupled with gas chromatography-flame ionization detection for the profiling of fatty acids in vegetable oils.

The development of a two phase hollow fiber liquid-phase microextraction technique, followed by gas-chromatography-flame ionization detection (GC-FID) for the profiling of the fatty acids (FAs) (lauric, myristic, palmitic, stearic, palmitoleic, oleic, linoleic, linolenic and arachidic) in vegetable oils is described. Heptadecanoic acid methyl ester was used as the internal standard. The FAs were transesterified to their corresponding methyl esters prior to the extraction. Extraction parameters such as type of extracting solvent, temperature, extraction time, stirring speed and salt addition were studied and optimized. Recommended conditions were extraction solvent, n-tridecane; extraction time, 35 min; extraction temperature, ambient; without addition of salt. Enrichment factors varying from 37 to 115 were achieved. Calibration curves for the nine FAs were well correlated (r(2)>0.994) within the range of 10-5000 µg L(-1). The limit of detection (signal:noise, 3) was 4.73-13.21 ng L(-1). The method was successfully applied to the profiling of the FAs in palm oils (crude, olein, kernel, and carotino cooking oil) and other vegetable oils (soybean, olive, coconut, rice bran and pumpkin). The encouraging enrichments achieved offer an interesting option for the profiling of the minor and major FAs in palm and other vegetable oils.

Analysis of the chemical composition of the essential oil of Polygonum minus Huds. using two-dimensional gas chromatography-time-of-flight mass spectrometry (GC-TOF MS).

The essential oil in leaves of Polygonum minus Huds., a local aromatic plant, were identified by a pipeline of gas chromatography (GC) techniques coupled with mass-spectrometry (MS), flame ionization detector (FID) and two dimensional gas chromatography time of flight mass spectrometry (GC x GC-TOF MS). A total of 48 compounds with a good match and high probability values were identified using this technique. Meanwhile, 42 compounds were successfully identified in this study using GC-MS, a significantly larger number than in previous studies. GC-FID was used in determining the retention indices of chemical components in P. minus essential oil. The result also showed the efficiency and reliability were greatly improved when chemometric methods and retention indices were used in identification and quantification of chemical components in plant essential oil.

Fast GC-FID based metabolic fingerprinting of Japanese green tea leaf for its quality ranking prediction.

There is a need of reliable, rapid, and cost-effective analysis technique to evaluate food and crop compositions, which are important to improve their qualities and quantities. Prior to fast GC-FID development, metabolic fingerprints, and predictive models obtained from a conventional GC-FID were evaluated by comparison to those derived from GC-TOF-MS. A similar chromatographic pattern with higher sensitivity of polyphenol compounds including epicatechin gallate (ECg) and epigallocatechin gallate (EGCg) had been achieved by using conventional GC-FID. Fast gas chromatograph coupled with flame ionization detector (GC-FID) has been carried out with 10 m x 0.18 mm id x 0.20 microm df capillary column. The analysis time per sample was reduced to less than 14 min compared to those of a conventional GC-FID (38 min) and GC-TOF-MS (28 min). The fast GC-FID also offered reliable retention time reproducibility without significant loss of peak resolution. Projections to latent structures by means of partial least squares (PLS) with orthogonal signal correction filtering (OSC) was applied to the fast GC-FID data. The predictive model showed good model fit and predictability with RMSEP of 3.464, suggesting that fast GC-FID based metabolic fingerprinting could be an alternative method for the prediction of Japanese green tea quality.

Determination of radix ginseng volatile oils at different ages by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry.

Comprehensive 2-D GC (GC x GC) coupled with TOF MS or flame ionization detector (FID) was employed to characterize and quantify the chemical composition of volatile oil in the radixes of Panax ginseng C. A. Mey. (ginseng) at different ages. Thirty-six terpenoids were tentatively identified based on the MS library search and retention index in a ginseng sample at the age of 3 years. An obvious group-type separation was obtained in the GC x GC-TOF MS chromatogram. The data collected by GC x GC-FID were processed using a principal component analysis (PCA) method to classify the samples at different ages. The compounds responsible for the significant differentiation among samples were defined. It was found that the relative abundances of alpha-cadinol, alpha-bisabolol, thujopsene, and n-hexadecanoic acid significantly rise with the increase in age.