Vitexin and isovitexin delayed ageing and enhanced stress-resistance through the activation of the SKN-1/Nrf2 signaling pathway.

Vitexin and isovitexin, as potential SKN-1/Nrf2 (SKN-1 is a homologous protein of mammalian Nrf2) activators, extended lifespan and promoted healthspan in Caenorhabditis elegans. This study aims to elucidate the role of SKN-1/Nrf2 in vitexin and isovitexin-induced anti-aging and stress-resistance. Vitexin and isovitexin upregulated antioxidant gene and protein expressions, reduced ROS accumulation, and increased SKN-1 accumulation in the nucleus. They prolonged lifespan and clear ROS during stressful conditions in a skn-1-dependent manner. skn-1 was also found to be necessary for these compounds-induced longevity under normal conditions. They were also witnessed to retard cellular senescence and scavenge ROS in senescent cells by directly binding to the pocket of Keap1 to promote the dissociation and activation of Nrf2. This study showed that SKN-1/Nrf2 signaling was vital to delaying ageing and enhancing anti-stress capacity with vitexin and isovitexin. The findings provide new insights into apigenin C-glycosides activating the SKN-1/Nrf2 pathway and demonstrate their potential as candidates for innovative strategies in chemoprophylaxis against ageing and oxidative-related diseases.

Discriminating geographical origins and determining active substances of water caltrop shells through near-infrared spectroscopy and chemometrics.

Near-infrared spectroscopy (NIRS) combined with chemometric methods were used to discriminate the geographical origins of the water caltrop shells from different regions of China. Two active substances, the total phenolic content (TPC) and total flavonoid content (TFC) in the water caltrop shells were determined through the technique as well. Principal component analysis (PCA) combined with linear discriminant analysis (LDA) was adopted to build the geographical discriminant model. Quantitative analysis models of TPC and TFC were built using partial least squares (PLS) regression. 1st derivative and randomization test (RT) methods were used to optimize the quantitative analysis models. It was found that the geographical discriminant model can correctly recognize the water caltrop shells from different regions of China with a total accuracy of 93.33%. The values of TPC and TFC obtained by the optimized models and the standard method are close. The coefficient of determination (R2) and the ratio of prediction to deviation for the two substances were 0.91, 0.89 and 3.02, 3.02, respectively. The results demonstrated the feasibility of NIRS combined with chemometric methods for the geographical discrimination of water caltrop shells and the quantitative analysis of TPC and TFC in water caltrop shells.

Facile fabrication of naphthalene-functionalized magnetic nanoparticles for efficient extraction of polycyclic aromatic hydrocarbons from environmental water and fish samples.

In this study, naphthalene-modified magnetic nanoparticles (Fe3O4@Nap) were simply prepared based on specific chelation interaction between phosphate groups and metal ions on Fe3O4 surface. The resultant Fe3O4@Nap were characterized by FTIR, BET, SEM, TEM, NAM, TGA, and VSM techniques. With Fe3O4@Nap as adsorbent, the polycyclic aromatic hydrocarbons (PAHs) were efficiently extracted by magnetic solid-phase extraction (MSPE) from environmental water and fish samples through the π-π interaction between modified naphthalene groups and PAHs, followed by their determination by GC-MS/MS. The key parameters influencing the extraction efficiency were investigated. Under the optimized conditions, the Fe3O4@Nap-based MSPE/GC-MS/MS method proposed in this paper was evaluated and applied for analyzing PAHs in environmental water and fish samples. And the proposed MSPE/GC-MS/MS method exhibited good linearities for water samples (in the range of 0.1-10 ng/mL, R2 >0.9945) and for fish samples (in the range of 1-100 ng/g, R2 > 0.9905). The limits of detection (LODs) for water and fish samples were 0.004-0.031 ng/mL and 0.07-0.28 ng/g, respectively. Additionally, this method exhibited desirable accuracy and precision. The PAH recovery values from water and fish samples ranged from 81.5% to 109.6% with inter- and intra-day relative standard deviations (RSDs) of less than 12.8%. The MSPE/GC-MS/MS method was successfully applied to the analysis of real environmental water and fish samples. Overall, the newly synthesized Fe3O4@Nap exhibited high sensitivity, specificity, reusability, repeatability, and it could efficiently extract PAHs from environmental water and fish samples by MSPE.

Convolutional neural network-based portable computer vision system for freshness assessment of crayfish (Prokaryophyllus clarkii).

Developing novel techniques for freshness assessment are of the utmost importance in yield and trade of aquatic products. The crayfish (Prokaryophyllus clarkii) is one of the most popular freshwater products in China, and its food safety should be a serious concern. In this study, a convolutional neural network (CNN)-based portable computer vision system for freshness assessment of crayfish method was proposed. A portable microscope was utilized to collect the microscopic images of crayfish with different freshness levels. The convolutional neural network was constructed and then optimized to extract features from the microscopic images. For the pictures from the portable microscope, the prediction accuracies of freshness could be 86.5% and 83.3% when the optimized networks were applied. The results indicate that the convolutional neural network-based portable computer vision system may provide an alternative way for the freshness assessment in the crayfish industrial chain. PRACTICAL APPLICATION: Portable computer vision system was constructed by a portable microscope connected to a mobile phone. The freshness of crayfish could be rapidly assessed by analyzing the pictures of crayfish using the system. The convolutional neural network-based portable computer vision system may provide an alternative way for the freshness assessment in the crayfish industrial chain.

Flowerlike Ni-NiO composite as magnetic solid-phase extraction sorbent for analysis of carbendazim and thiabendazole in edible vegetable oils by liquid chromatography-mass spectrometry.

A rapid, selective, and sensitive method was developed for the detection of carbendazim and thiabendazole in edible vegetable oil. Two benzimidazole analytes were pre-concentrated by magnetic solid phase extraction (MSPE) using flowerlike Ni-NiO composite as sorbents and followed by LC-MS/MS analysis. The flowerlike Ni-NiO composite sorbent displayed a high affinity towards benzimidazole analytes due to the reversible coordination interaction between the Ni(Ⅱ) ion and the electron-donating imidazole group. In comparison to the previous methods, this procedure is less time-consuming and simpler during sample preparation. The parameters affecting the extraction efficiency were optimized in detail. The method was validated according to SANTE/12682/2019. The limits of detection were in the range of 0.001-0.003 mg•kg-1. The recoveries ranged from 89.3% to 110.7% with inter-day and inter-day precision less than 10.9%. The results indicate that flowerlike Ni-NiO composite might be a promising alternative for MSPE of benzimidazole compounds in foods.

[Determination of bongkrekic acid in tremella and auricularia auricular by improved QuEChERS method combined with ultra-high performance liquid chromatography-triple quadrupole mass spectrometry].

An improved QuEChERS (quick, easy, cheap, effective, rugged, safe) method, combined with ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), was used to determine bongkrekic acid (BA) in tremella and auricularia auricular. BA is a fat-soluble, fatal bacterial toxin produced by the aerobic gram-negative bacteria Burkholderia gladioli pathovar cocovenenans. Tremella and auricularia auricular, which have rich nutritional values, are traditional edible fungi in China that are very popular among Chinese consumers. However, tremella and auricularia auricular are easily contaminated by BA during storage and foaming, and this poses a great threat to food safety and human health. Therefore, establishing a rapid and efficient analysis method for detecting BA in tremella and auricularia auricular is of considerable significance. However, the BA concentration in the actual sample is very low, and the matrices of tremella fuciformis and auricularia auricular are very complex. Thus, it is necessary to employ appropriate sample pretreatment technology to extract and purify BA from tremella and auricularia auricular samples prior to instrumental analysis. In this study, the QuEChERS method, combined with UHPLC-MS/MS, was used to detect BA in tremella and auricularia auricular. The key parameters, such as extraction solvent, extraction method, and adsorbent used for cleanup, were optimized to obtain high extraction efficiency. The content of acetic acid in the extraction solution strongly influenced the extraction efficiency of BA, and acetonitrile with 5%(v/v) acetic acid was determined to be the optimum extraction solvent. After salting out, the acetonitrile extract was purified by dispersive solid phase extraction using 200 mg C18 as a cleanup adsorbent. The sample was then separated on a Waters HSS T3 column (100 mm×2.1 mm, 1.8 µm), using a water solution containing 0.01% (v/v) formic acid and 0.05% (v/v) ammonia and methanol as mobile phases. MS analysis was performed using an electrospray ionization source in the negative and multiple reaction monitoring (MRM) modes. Under the optimized conditions, the matrix effects of UHPLC-MS/MS in tremella and auricularia auricular were -6.3% and -11.5%, respectively; this indicated that the method had a significant purification effect, and the sample matrix did not affect the MS detection of BA. Further study showed that in the concentration range of 1-200 µg/L, the square of the regression coefficient of the linear equation (R2) was greater than 0.999. The limit of detection (LOD) and limit of quantitation (LOQ) were 0.15 µg/kg and 0.5 µg/kg, respectively. The average recoveries in samples spiked with 0.5, 10, and 50 µg/kg BA in tremella ranged from 92.4% to 102.6%, and the intra-day and inter-day relative standard deviations (RSDs) were 4.3%-4.9% and 3.2%-3.5%, respectively. For auricularia auricular, the average recoveries ranged from 89.6% to 102.3%, and the intra-day and inter-day RSDs were 2.4%-9.5% and 3.6%-4.1%, respectively. These results indicate that the proposed method has satisfactory sensitivity, accuracy, and precision. Finally, the method showed good performance when applied to the analysis of real samples. Compared with other reported methods, the LOD and LOQ of our proposed method were lower, with satisfactory recovery and precision. Taken together, this study provides an effective detection technology for the monitoring and risk control of BA in tremella and auricularia auricular.

Construction of Indoline-Fused Tetrahydroisoquinolines through a Domino Coupling Reaction Catalyzed by CuCoFe Layered Double Hydroxide.

A convenient catalytic protocol for efficiently constructing indoline-fused tetrahydroisoquinolines based on CuCoFe layered double hydroxide (LDH) has been described. Preliminary mechanistic studies show that indoline-fused tetrahydroisoquinolines are produced via domino coupling/cyclization reactions between tetrahydroisoquinolines and active methylene compounds, including malononitrile, malonates, and analogues. CuCoFe-LDH can accelerate the Csp3-Csp3 and Csp3-Csp2 formation reactions in a single step. The research thus presents a unique opportunity to develop a synthetic methodology for N-containing polycyclic compounds.

Functional analysis of the ocnE gene involved in nicotine-degradation pathways in Ochrobactrum intermedium SCUEC4 and its enzymatic properties.

The SCUEC4 strain of Ochrobactrum intermedium is a newly isolated bacterium that degrades nicotine can use nicotine as the sole carbon source via a series of enzymatic catalytic processes. The mechanisms underlying nicotine degradation in this bacterium and the corresponding functional genes remain unclear. Here, we analyzed the function and biological properties of the ocnE gene involved in the nicotine-degradation pathways in strain SCUEC4. The ocnE gene was cloned by PCR with total DNA of strain SCUEC4 and used to construct the recombinant plasmid pET28a-ocnE. The overexpression of the OcnE protein was detected by SDS-PAGE analysis, and study of the function of this protein was spectrophotometrically carried out by monitoring the changes of 2,5-dihydroxypyridine. Moreover, the effects of temperature, pH, and metal ions on the biological activities of the OcnE protein were analyzed. The optimal conditions for the biological activities of OcnE, a protein of approximately 37.6 kDa, were determined to be 25 °C, pH 7.0, and 25 µmol/L Fe2+, and the suitable storage conditions for the OcnE protein were 0 °C and pH 7.0. In conclusion, the ocnE gene is responsible for the ability of 2,5-dihydroxypyridine dioxygenase. These findings will be beneficial in clarifying the mechanisms of nicotine degradation in O. intermedium SCUEC4.

Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs).

Geographical discrimination and adulteration analysis play significant roles in edible oil analysis. A novel method for discrimination and adulteration analysis of edible oils were proposed in this study. The two-dimensional correlation spectra of edible oils were obtained by solvents perturbation and the convolutional neural networks (CNNs) were constructed to analyze the synchronous and asynchronous correlation spectra of the edible oils. The differences for geographical origins of oils or oil types could be amplificated through the networks. For different networks, the layer sequences and the filter number of convolutional layers may affect the analysis results. A group of sesame oils from different geographical origins and a group of olive oils adulterated by other vegetable oils were adopted to evaluate the proposed method. The results show that the proposed method may provide an alternative method for edible oil discrimination and adulteration analysis in practical applications. For the two datasets, the prediction accuracy could be 97.3% and 88.5%, respectively.

Simultaneous and rapid determination of sesamin and sesamolin in sesame oils using excitation-emission matrix fluorescence coupled with self-weighted alternating trilinear decomposition.

BACKGROUND: Sesamin and sesamolin are two typical and important lignans isolated from sesame oil. Various studies have shown the bioactivity, physiological activity, and potential health benefits of the two components. In this study, a rapid method for the simultaneous determination of sesamin and sesamolin in sesame oils was proposed. The excitation-emission fluorescence spectra of the oils were obtained after a simple pretreatment, then self-weighted alternating trilinear decomposition was used to extract the quantitative information from the very overlapping spectra. RESULTS: It was found that reasonable quantification results could be obtained with the limits of detection for the two lignans. These limits were 0.05 mg/g and 0.24 mg/g, and the limits of quantitation were 0.14 mg/g and 0.74 mg/g, respectively. The average recoveries for sesamin and sesamolin were 99.05% and 94.97%. CONCLUSION: The results indicate that, with simple sample pretreatment, the application for combining excitation-emission fluorescence spectra and self-weighted alternating trilinear decomposition can be a useful and sensitive tool for the determination of lignans in sesame oil. © 2020 Society of Chemical Industry.

Associations between household renovation and rhinitis among preschool children in China: A cross-sectional study.

During 2010-2012, we surveyed 40,010 3- to 6-year-old children in seven Chinese cities (Beijing, Taiyuan, Urumqi, Shanghai, Nanjing, Changsha, and Chongqing). Their parents reported information on household renovation, including the timing of renovation and the choice of materials for walls and floors in the child's room, and the incidence of their child's rhinitis. Multivariate and two-level (city-child) logistic regression analyses yielding adjusted odds ratios (AOR) with 95% confidence intervals were performed. Sensitivity analyses stratifying data for location and economic level were also performed. About 48.0% of the children had ever had allergic rhinitis, 41.2% had current allergic rhinitis, and 9.0% had had doctor-diagnosed rhinitis. Exposure to household renovation during early lifetime (birth to 1-year-old) had an AOR of 1.43 (1.04-1.9) for allergic rhinitis. The incidence of allergic rhinitis was significantly different in children exposed to different floor and wall covering materials. Floor or wall covering material composed of organic materials significantly increased the risk of childhood allergic rhinitis compared with tile flooring or lime wall covering. Oil paint had an AOR of 1.66 (1.28-2.14) for diagnosed rhinitis compared with lime wall covering. Adding new furniture the year before pregnancy was associated with an AOR of 1.18 (1.10-1.27) and 1.18 (1.11-1.25) for lifetime and current rhinitis. Solid wood or tiles/ceramic as floor materials, and using wallpaper, oil paint, or emulsion panels as wall materials were risk factors for doctor-diagnosed rhinitis. Sensitivity analyses showed that children living in southern or higher economic level China cities were more likely to have allergic rhinitis with household renovation.

Functional analysis of the agnH gene involved in nicotine-degradation pathways in Agrobacterium tumefaciens strain SCUEC1.

Agrobacterium tumefaciens strain SCUEC1 is a nicotine-degrading bacterium, which has been recently isolated from the tobacco waste-contaminated field soil. However, the mechanism for nicotine degradation in this strain remains unclear. Here, we analyze the function and biological properties of the agnH gene in the strain SCUEC1. The overexpression of the AgnH protein was detected by SDS-PAGE analysis, and functional insight of the AgnH protein was carried out with monitoring the changes of maleic acid into fumaric acid by high performance liquid chromatography (HPLC). Moreover, the effects of temperature, pH and metal ions on the enzymatic activities of the AgnH protein were also analyzed. The results demonstrated that the agnH gene was successfully ligated to the plasmid pET28a. The optimal condition for the enzymatic activities for the AgnH, approximately 28.0 kDa, was determined as 37 °C, pH 8.0 and 25 µM Mg2+. Conclusively, the agnH gene fulfils an important role in the conversion of maleic acid into fumaric acid involved in nicotine-degradation pathways in Agrobacterium tumefaciens strain SCUEC1.

Optimizing Rice Near-Infrared Models Using Fractional Order Savitzky-Golay Derivation (FOSGD) Combined with Competitive Adaptive Reweighted Sampling (CARS).

Developing a rapid and stable method for analyzing the quality parameters of rice is important. Near-infrared (NIR) spectroscopy combined with chemometric techniques have been used to predict the critical contents of rice and shown its accuracy and stability. To further improve the predictive ability, we combine the derivative method of fractional order Savitzky-Golay derivation (FOSGD) with the wavelength selection method of competitive adaptive reweighted sampling (CARS). Compared with the traditional integer order Savitzky-Golay derivation (IOSGD), the FOSGD could improve the resolution ratio of the raw spectra more effectively. The wavelength selection method, CARS, could further extract the informative variables from the processed spectra. Four key contents of rice samples, including moisture, amylose, chalkiness degree, and gel consistency, were utilized to validate this method. The prediction results indicated that partial least squares (PLS) models optimized with FOSGD-CARS own higher accuracy and stability with smaller the root mean squared error of cross validations (RMSECVs) and root mean squared error of predictions (RMSEPs). The proposed method is convenient and provides a practical alternative for rice analysis.

Rapid and nondestructive determination of sesamin and sesamolin in Chinese sesames by near-infrared spectroscopy coupling with chemometric method.

Sesame was one of the most important crops in Africa and east Asia. The sesamin and sesamolin in sesames have shown various pharmacological, biological and physiologic activities. In this study, a rapid and nondestructive method for determination of sesamin and sesamolin in Chinese sesames by near-infrared spectroscopy coupled with chemometric method was proposed. The near infrared spectra of sesame samples from three different Chinese areas were collected and the partial least squares (PLS) was used to construct the quantitative models. The spectral preprocessing and variable selection methods were adopted to improve the predictability and stability of the model. Reasonable quantitative results can be obtained when the samples used for model construction and prediction were harvested in same years. For sesamin and sesamolin, the correlation coefficient (R) and root mean square error prediction (RMSEP) were 0.9754, 0.9636 and 151.2951, 39.7720, respectively. The optimized models seem less effective when they were used to predict the samples harvested in other years or countries. However, acceptable results can still be obtained.

Rapid determination of phytosterols by NIRS and chemometric methods.

Phytosterols have been extensively studied because it plays essential roles in the physiology of plants and can be used as nutritional supplement to promote human health. We use a rapid method by coupling near-infrared spectroscopy (NIRS) and chemometric techniques to quickly and efficiently determine three essential phytosterols (ß-sitosterol, campesterol and stigmasterol) in vegetable oils. Continuous wavelet transform (CWT) method was adopted to remove the baseline shift in the spectra. The quantitative analysis models were constructed by partial least squares (PLS) regression and randomization test (RT) method was used to further improve the models. The optimized models were used to calculate the phytosterol contents in prediction set in order to evaluate their predictability. We have found that the phytosterol contents obtained by the optimized models and Gas Chromatography/Mass Spectrometry (GC/MS) analysis are almost consistent. The root mean square error of prediction (RMSEP) and ratio of prediction to deviation (RPD) for the three phytosterols are 525.7590, 212.2245, 65.1611 and 4.0060, 4.7195 and 3.5441, respectively. The results have proved the feasibility of the proposed method for rapid and non-destructive analysis of phytosterols in edible oils.

Multi-spectrometer calibration transfer based on independent component analysis.

Calibration transfer is indispensable for practical applications of near infrared (NIR) spectroscopy due to the need for precise and consistent measurements across different spectrometers. In this work, a method for multi-spectrometer calibration transfer is described based on independent component analysis (ICA). A spectral matrix is first obtained by aligning the spectra measured on different spectrometers. Then, by using independent component analysis, the aligned spectral matrix is decomposed into the mixing matrix and the independent components of different spectrometers. These differing measurements between spectrometers can then be standardized by correcting the coefficients within the independent components. Two NIR datasets of corn and edible oil samples measured with three and four spectrometers, respectively, were used to test the reliability of this method. The results of both datasets reveal that spectra measurements across different spectrometers can be transferred simultaneously and that the partial least squares (PLS) models built with the measurements on one spectrometer can predict that the spectra can be transferred correctly on another.

Neuroprotective effects and UPLC-Q-TOF/MS-based active components identification of external applied a novel Wen-Luo-Tong microemulsion.

Chemotherapy induced neuropathy causes excruciating pain to cancer patients. Wen-Luo-Tong (WLT), a traditional Chinese medicinal compound, has been used to alleviate anti-cancer drug such as oxaliplatin-induced neuropathic pain for many years. However, the current route of administration of WLT is inconvenient and the active ingredients and mechanism of action of WLT are still unclear. To address these issues, we developed a novel formulation of WLT (W/O microemulsion) for the ease of application. New ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) methods were employed for analysis of the ingredients. We identified seven ingredients that penetrated through the skin into the Franz cell receptor solution and four of those ingredients were retained in skin tissue when WLT microemulsion was applied. We tested the microemulsion formulation on an oxaliplatin-induced neuropathy rat model and showed that this formulation significantly decreased oxaliplatin-induced mechanical hyperalgesia responses. Schwann cells (SCs) viability experiment in vitro was studied to test the protective effect of the identified seven ingredients. The result showed that Hydroxysafflor Yellow A, icariin, epimedin B and 4-dihydroxybenzoic acid significantly increased the viability of SCs after injured by Oxaliplatin. Our report presents the first novel formulation of WLT with neuroprotective effect and ease of use, which has potential for clinical applications.

Transdermal Delivery of Compounds with Different Lipophilicity and Molecular Weight from W/O Microemulsions Analyzed by UPLC-QTOF/ MS and LC-MS/MS.

OBJECTIVE: The aim of this study was to develop a novel W/O microemulsion for a natural extract of Wen-Luo-Tong (WLT) containing mainly icariin, hydroxysafflor yellow A (HSYA) and gallic acid to be applied to skin as a potential treatment for peripheral neuropathy. METHODS: The oil phase was selected on the basis of affinity with the surfactant and co-surfactant. Pseudo-ternary diagrams were constructed to optimize microemulsions and finally stability studies were performed on the selected formulations. Droplet sizes were analyzed by using a zetasizer and were found to be within the desired range. Selected microemulsions with acceptable viscosities, containing 5%, 8% and 10% of water extract solution, were used for in vitro skin penetration studies using Franz diffusion cells and excised rat skin. New LC-MS/MS and UPLC-Q-TOF/MS methods were employed for quantitative and qualitative analysis. RESULTS: The optimized formulation (ME-4) consisting of 10% (w/w) water extract solution, 60% isopropyl myristate, 30%(w/w) Smix: Propylene glycol (5:2) significantly increased the cumulative permeated amounts of HSYA, icariin and gallic acid compared with the water extract solution controls. CONCLUSION: This novel formulation also increased the number of components penetrating rat skin. Ten components were detected in the Franz cell receptor solution using a UPLC-Q-TOF/MS system after the application of formulation ME-4 for 24h on the skin in vitro. However, only one component was detected after applying the control. Therefore, the microemulsion ME-4 was selected for future in vivo pharmacodynamic studies.

Band target entropy minimization for retrieving the information of individual components from overlapping chromatographic data.

Band target entropy minimization (BTEM) is a self-modeling curve resolution (SMCR) approach relying on non-negative criterion and minimization of Shannon entropy. In this study, BTEM algorithm was applied to retrieving the information of individual components from overlapping gas chromatography-mass spectrometry (GC-MS) data. The algorithm starts with dividing the whole data into bands along the retention time. In each band, singular value decomposition (SVD) is used to decompose the data into scores and loadings. Because the pure chromatographic signal possesses the lowest Shannon entropy, the chromatographic signal of each component can be constructed by optimizing the combination of the loadings with minimal Shannon entropy under non-negative criterion. To show the efficiency of the algorithm, a simulated four-component overlapping GC-MS data and an experimental GC-MS data of 18 organophosphorus pesticide mixture are investigated. The results show that both the chromatographic profiles and mass spectra of the components can be successfully extracted from the overlapping signals.

Rapid discrimination of slimming capsules based on illegal additives by electronic nose and flash gas chromatography.

The discrimination of counterfeit and/or illegally manufactured medicines is an important task in the pharmaceutical industry for pharmaceutical safety. In this study, 22 slimming capsule samples with illegally added sibutramine and phenolphthalein were analyzed by electronic nose and flash gas chromatography. To reveal the difference among the different classes of samples, principal component analysis and linear discriminant analysis were employed to analyze the data acquired from electronic nose and flash gas chromatography, respectively. The samples without illegal additives can be discriminated from the ones with illegal additives by using electronic nose or flash gas chromatography data individually. To improve the performance of classification, a data fusion strategy was applied to integrate the data from electronic nose and flash gas chromatography data into a single model. The results show that the samples with phenolphthalein, sibutramine and both can be classified well by using fused data.