Genotoxic and oxidative stress effects of 2-amino-9H-pyrido[2,3-b]indole in human hepatoma G2 (HepG2) and human lung alveolar epithelial (A549) cells.

2-Amino-9H-pyrido[2,3-b]indole (AαC), which is present in high quantities in cigarette smoke and also in fried food, has been reported to be a probable human carcinogen. However, few studies have reported on the genotoxicity and oxidative stress induced by AαC. This study investigated the genotoxic effects of AαC in human hepatoma G2 (HepG2) and human lung alveolar epithelial (A549) cells using the comet assay. Significant increases in DNA fragment migration indicated that AαC causes serious DNA damage in HepG2 and A549 cells. The role of oxidative stress in the mechanism of AαC-induced genotoxicity was clarified by measuring the level of intracellular reactive oxygen species (ROS), the GSH/GSSG ratio and the formation of 8-hydroxydeoxyguanosine (8-OHdG), a marker of oxidative DNA damage. The results showed that the levels of ROS and 8-OHdG increased, whereas the GSH/GSSG ratio decreased. The concentration of 8-OHdG was positively related to DNA damage. Taken together, these results indicate that AαC can induce genotoxicity and oxidative stress and that AαC likely exerts genotoxicity in HepG2 and A549 cells through ROS-induced oxidative DNA damage. This is the first report to describe AαC-induced genotoxic and oxidative stress in HepG2 and A549 cells.

Determination of volatile organic acids in oriental tobacco by needle-based derivatization headspace liquid-phase microextraction coupled to gas chromatography/mass spectrometry.

A method coupling needle-based derivatization headspace liquid-phase microextraction with gas chromatography-mass spectrometry (HS-LPME/GC-MS) was developed to determine volatile organic acids in tobacco. The mixture of N,O-bis(trimethylsilyl)trifluoroacetamide and decane was utilized as the solvent for HS-LPME, resulting that extraction and derivatization were simultaneously completed in one step. The solvent served two purposes. First, it pre-concentrated volatile organic acids in the headspace of tobacco sample. Second, the volatile organic acids extracted were derivatized to form silyl derivatives in the drop. The main parameters affecting needle-based derivatization HS-LPME procedure such as extraction and derivatization reagent, microdrop volume, extraction and derivatization time, and preheating temperature and preheating time were optimized. The standard addition approach was essential to obtain accurate measurements by minimizing matrix effects. Good linearity (R(2)> or =0.9804) and good repeatability (RSDs< or =15.3%, n=5) for 16 analytes in spiked standard analytes sample were achieved. The method has the additional advantages that at the same time it is simple, fast, effective, sensitive, selective, and provides an overall profile of volatile organic acids in the oriental tobacco. This paper does offer an alternative approach to determine volatile organic acids in tobacco.

Microfluidic liquid-air dual-gradient chip for synergic effect bio-evaluation of air pollutant.

In this paper, a novel prototype liquid-air dual gradient chip is introduced, which has paved the way for effective synergic effect bio-evaluation of air pollutant. The chip is composed of an array of the agarose liquid-air interfaces, top air gradient layer and bottom liquid gradient layer. The novel agarose liquid-air interface allows for non-biased exposure of cells to all the substances in the air and diffusive interactions with the liquid phase; while the dual liquid-air gradient provides powerful screening abilities, which well reduced errors, saved time and cost from repeated experiment. Coupling the two functions, the chip subsequently facilitates synergic effect evaluation of both liquid and air factors on cells. Here cigarette smoke was taken as the model air pollutant, and its strong synergic effects with inflammatory level of A549 lung cancer cells on their fate were successfully quantified for the first time. These results well testified that the proposed dual-gradient chip is powerful and indispensable for bio-evaluation of air pollutant.

A microfluidic cigarette smoke collecting platform for simultaneous sample extraction and multiplex analysis.

In this work, we report a novel microfluidic gas collecting platform aiming at simultaneous sample extraction and multiplex mass spectrometry (MS) analysis. An alveolar-mimicking elastic polydimethylsiloxane (PDMS) structures was designed to move dynamically driven by external pressure. The movement was well tuned both by its amplitude and rhythm following the natural process of human respiration. By integrating the alveolar units into arrays and assembling them to gas channels, a cyclic contraction/expansion system for gas inhale and exhale was successfully constructed. Upon equipping this system with a droplet array on the alveolar array surface, we were able to get information of inhaled smoke in a new strategy. Here, with cigarette smoke as an example, analysis of accumulation for target molecules during passive smoking is taken. Relationships between the breathing times, distances away from smokers and inhaled content of nicotine are clarified. Further, by applying different types of extraction solvent droplets on different locations of the droplet array, simultaneous extraction of nicotine, formaldehyde and caproic acid in sidestream smoke (SS) are realized. Since the extract droplets are spatially separated, they can be directly analyzed by MS which is fast and can rid us of all complex sample separation and purification steps. Combining all these merits, this small, cheap and portable platform might find wide application in inhaled air pollutant analysis both in and outdoors.

A chemometric-assisted method based on gas chromatography-mass spectrometry for metabolic profiling analysis.

An automatic and efficient data analysis method for comprehensive metabolic profiling analysis is urgently required. In this study, a new chemometric-assisted method for metabolic profiling analysis (CAMMPA) was developed to discover potentially valuable metabolites automatically and efficiently. The proposed method mainly consists of three stages. First, automatic chromatographic peak detection is performed based on the total ion chromatograms of samples to extract chromatographic peaks that can be accurately quantified. Second, a novel peak-shift alignment technique based on peak detection results is implemented to resolve time-shift problems across samples. Consequently, aligned results, including aligned chromatograms, and peak area tables, among others, can be successfully obtained. Third, statistical analysis using results from unsupervised and supervised classification results, together with ANOVA and partial least square-discriminate analysis, is performed to extract potential metabolites. To demonstrate the proposed technique, a complex GC-MS metabolic profiling dataset was measured to identify potential metabolites in tobacco plants of different growth stages as well as different plant tissues after maturation. Results indicated that the efficiency of the routine metabolic profiling analysis procedure can be significantly improved and potential metabolites can be accurately identified with the aid of CAMMPA.

Chemometric strategy for automatic chromatographic peak detection and background drift correction in chromatographic data.

Peak detection and background drift correction (BDC) are the key stages in using chemometric methods to analyze chromatographic fingerprints of complex samples. This study developed a novel chemometric strategy for simultaneous automatic chromatographic peak detection and BDC. A robust statistical method was used for intelligent estimation of instrumental noise level coupled with first-order derivative of chromatographic signal to automatically extract chromatographic peaks in the data. A local curve-fitting strategy was then employed for BDC. Simulated and real liquid chromatographic data were designed with various kinds of background drift and degree of overlapped chromatographic peaks to verify the performance of the proposed strategy. The underlying chromatographic peaks can be automatically detected and reasonably integrated by this strategy. Meanwhile, chromatograms with BDC can be precisely obtained. The proposed method was used to analyze a complex gas chromatography dataset that monitored quality changes in plant extracts during storage procedure.