Serum metabolic profiling of human gastric cancer based on gas chromatography/mass spectrometry

Research on molecular mechanisms of carcinogenesis plays an important role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to non-invasively identify the potential biomarkers for the early diagnosis of human gastric cancer. The aims of this study were to explore the underlying metabolic mechanisms of gastric cancer and to identify biomarkers associated with morbidity. Gas chromatography/mass spectrometry (GC/MS) was used to analyze the serum metabolites of 30 Chinese gastric cancer patients and 30 healthy controls. Diagnostic models for gastric cancer were constructed using orthogonal partial least squares discriminant analysis (OPLS-DA). Acquired metabolomic data were analyzed by the nonparametric Wilcoxon test to find serum metabolic biomarkers for gastric cancer. The OPLS-DA model showed adequate discrimination between cancer and non-cancer cohorts while the model failed to discriminate different pathological stages (I-IV) of gastric cancer patients. A total of 44 endogenous metabolites such as amino acids, organic acids, carbohydrates, fatty acids, and steroids were detected, of which 18 differential metabolites were identified with significant differences. A total of 13 variables were obtained for their greatest contribution in the discriminating OPLS-DA model [variable importance in the projection (VIP) value >1.0], among which 11 metabolites were identified using both VIP values (VIP >1) and the Wilcoxon test. These metabolites potentially revealed perturbations of glycolysis and of amino acid, fatty acid, cholesterol, and nucleotide metabolism of gastric cancer patients. These results suggest that gastric cancer serum metabolic profiling has great potential in detecting this disease and helping to understand its metabolic mechanisms.

Influence of exercise modality on agreement between gas exchange and heart rate variability thresholds

The main purpose of this study was to investigate the level of agreement between the gas exchange threshold (GET) and heart rate variability threshold (HRVT) during maximal cardiopulmonary exercise testing (CPET) using three different exercise modalities. A further aim was to establish whether there was a 1:1 relationship between the percentage heart rate reserve (%HRR) and percentage oxygen uptake reserve (%V˙O2R) at intensities corresponding to GET and HRVT. Sixteen apparently healthy men 17 to 28 years of age performed three maximal CPETs (cycling, walking, and running). Mean heart rate and V˙O2 at GET and HRVT were 16 bpm (P<0.001) and 5.2 mL·kg-1·min-1 (P=0.001) higher in running than cycling, but no significant differences were observed between running and walking, or cycling and walking (P>0.05). There was a strong relationship between GET and HRVT, with R2 ranging from 0.69 to 0.90. A 1:1 relationship between %HRR and %V˙O2R was not observed at GET and HRVT. The %HRR was higher during cycling (GET mean difference=7%; HRVT mean difference=11%; both P<0.001), walking (GET mean difference=13%; HRVT mean difference=13%; both P<0.001), or running (GET mean difference=11%; HRVT mean difference=10%; both P<0.001). Therefore, using HRVT to prescribe aerobic exercise intensity appears to be valid. However, to assume a 1:1 relationship between %HRR and %V˙O2R at HRVT would probably result in overestimation of the energy expenditure during the bout of exercise.

Assessment of the diagnostic value of diffusion tensor imaging in patients with spinal cord compression: a meta-analysis

We investigated the diagnostic value of the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) of magnetic resonance diffusion tensor imaging (DTI) in patients with spinal cord compression (SCC) using a meta-analysis framework. Multiple scientific literature databases were exhaustively searched to identify articles relevant to this study. Mean values and standardized mean differences (SMDs) were calculated for the ADC and FA in normal and diseased tissues. The STATA version 12.0 software was used for statistical analysis. Of the 41 articles initially retrieved through database searches, 11 case-control studies were eligible for the meta-analysis and contained a combined total of 645 human subjects (394 patients with SCC and 251 healthy controls). All 11 studies reported data on FA, and 9 contained data related to the ADC. The combined SMDs of the ADC and FA showed that the ADC was significantly higher and the FA was lower in patients with SCC than in healthy controls. Subgroup analysis based on the b value showed higher ADCs in patients with SCC than in healthy controls at b values of both ≤500 and >500 s/mm2. In summary, the main findings of this meta-analysis revealed an increased ADC and decreased FA in patients with SCC, indicating that DTI is an important diagnostic imaging tool to assess patients suspected to have SCC.

Chemical characterization and antimicrobial activity of essential oils of salvia L. species

In this work, the essential oils of S. officinalis, S. sclarea, S. lavandulifolia and S. triloba were chemically analyzed by gas chromatography coupled to a mass spectrometry detector (GC/MSD), and their antimicrobial activity was tested against 10 microorganisms using the disk diffusion method and the Minimum Inhibitory Concentration (MIC) technique. The following major compounds were identified in the essential oils: α - and β-thujone, camphor and 1,8-cineole, except in S. sclarea, where linalool, linalyl acetate and α-terpineol were the major constituents. The antimicrobial activity showed significant differences (p < 0.05) only when obtained by the MIC method. Gram-positive microorganisms presented larger sensitivity for the essential oils. The lowest MIC was observed when Staphylococcus aureus was exposed to 2.31 mg.mL-1 of S. lavandulifolia essential oil, while the highest MIC value was obtained when Shigella flexneri was exposed to 9.25 mg.mL-1 of the same essential oil, thus demonstrating that this essential oil may be effective as a bacteriostatic agent against Gram-positive microorganisms.

Evaluation of noni (Morinda citrifolia) volatile profile by dynamic headspace and gas chromatography-mass spectrometry

Noni is a fruit that has interested the scientific community due to its medicinal and functional activities. Different products that contain noni are already in the market, but their consumption could be impaired by their distinctive unpleasant aroma and flavor. The aim of this work was to evaluate the noni pulp volatile profile by dynamic headspace and gas chromatography-mass spectrometry. Thirty seven volatile compounds were detected, mainly alcohols (63.3%), esters (26.9%), cetones (7.4%), and acids (1.2%).

Multicomponent diffusion during Prato cheese ripening: mathematical modeling using the finite element method

The partial replacement of NaCl by KCl is a promising alternative to produce a cheese with lower sodium content since KCl does not change the final quality of the cheese product. In order to assure proper salt proportions, mathematical models are employed to control the product process and simulate the multicomponent diffusion during the reduced salt cheese ripening period. The generalized Fick's Second Law is widely accepted as the primary mass transfer model within solid foods. The Finite Element Method (FEM) was used to solve the system of differential equations formed. Therefore, a NaCl and KCl multicomponent diffusion was simulated using a 20% (w/w) static brine with 70% NaCl and 30% KCl during Prato cheese (a Brazilian semi-hard cheese) salting and ripening. The theoretical results were compared with experimental data, and indicated that the deviation was 4.43% for NaCl and 4.72% for KCl validating the proposed model for the production of good quality, reduced-sodium cheeses.

(E)-2-Nonenal determination in brazilian beers using headspace solid-phase microextraction and gas chromatographic coupled mass spectrometry (HS-SPME-GC-MS)

(E)-2-nonenal is considered an important off-flavor of beer, related to the flavor of beer staling. In this study, a new method for determination of (E)-2-nonenal in beer using headspace solid-phase microextraction and gas chromatographic coupled mass spectrometry (HS-SPME-GC-MS) was developed and applied in Brazilian beer samples. The extractions were carried out in CAR-PDMS (carboxen-polydimethylsiloxane) fiber and the best results were found with 15 minutes of equilibrium and 90 minutes of extraction at 50 °C. The method was linear in the range from 0.02 to 4.0 μg.L-1 with correlation coefficient of 0.9994. The limits of detection and quantification were 0.01 and 0.02 μg.L-1, respectively. 96.5% of recovery and 4% precision (RSD) were obtained in the fortification of beer samples with 2.0 μg.L-1 of (E)-2-nonenal. The developed method proved to be simple, efficient and highly sensitive to the determination of this analyte being easily applied in the quality control of the brewery. (E)-2-nonenal was found in all beer samples analyzed with levels between 0.17 and 0.42 μg.L-1.

Dynamics of gas levels inside packages containing minimally processed Pera orange

The purpose of this study was to evaluate the changes in concentrations of O2 and CO2 inside packages of minimally processed Pera orange. Previously selected oranges that were washed, sanitized, and chilled were peeled using hydrothermal treatment (immersion of fruits in water at 50 °C for 8 minutes). The peeled oranges were then packed in five different plastic packages under passive and active modified atmosphere (5% O2 + 10% CO2 + 85% N2). The fruits were stored at 6 °C and 12 °C. The package headspace gas composition was evaluated for twelve days at 6 °C and nine days at 12 °C. The polypropylene film (32 µm) promoted modified atmosphere similar to that initially injected (5% O2 + 10% CO2 + 85% N2) at 6 °C and 12 °C. With regard to the atmosphere modification system, the injection of a gas mixture anticipated achieving an equilibrium atmosphere inside the packages at 12 °C. At 6 °C, the gas composition inside the packages was kept close to that of the injection, but the equilibrium was not verified.

Characterization and classification of pequi trees (Caryocar brasiliense Camb.) based on the profile of volatile constituents using headspace solid-phase microextraction - gas chromatography - mass spectrometry and multivariate analysis

In order to determine the variability of pequi tree (Caryocar brasiliense Camb.) populations, volatile compounds from fruits of eighteen trees representing five populations were extracted by headspace solid-phase microextraction and analyzed by gas chromatography-mass spectrometry. Seventy-seven compounds were identified, including esters, hydrocarbons, terpenoids, ketones, lactones, and alcohols. Several compounds had not been previously reported in the pequi fruit. The amount of total volatile compounds and the individual compound contents varied between plants. The volatile profile enabled the differentiation of all of the eighteen plants, indicating that there is a characteristic profile in terms of their origin. The use of Principal Component Analysis and Cluster Analysis enabled the establishment of markers (dendrolasin, ethyl octanoate, ethyl 2-octenoate and β-cis-ocimene) that discriminated among the pequi trees. According to the Cluster Analysis, the plants were classified into three main clusters, and four other plants showed a tendency to isolation. The results from multivariate analysis did not always group plants from the same population together, indicating that there is greater variability within the populations than between pequi tree populations.