Bioinspired Fabrication of an Insensitive Ammonium Perchlorate Core-Shell Composite with Polydopamine Coating.

In this research, an ammonium perchlorate/polydopamine (AP/PDA) core-shell composite was prepared in a non-aqueous solution to reduce the mechanical sensitivity of ammonium perchlorate (AP). The result showed that the AP/PDA core-shell composite could be successfully constructed in ethyl acetate solution with an AP recovery rate that reached 86%. The mechanical sensitivity of the obtained AP/PDA core-shell composite was significantly reduced with a PDA content of only 0.76%. The DSC and TG also indicated that the coating of PDA showed catalytic activity in the thermal decomposition of AP with a lower decomposition temperature and a decreased Ea value of AP. Thus, this study proposed a simple strategy for achieving a good balanced between harnessing the energy and ensuring the safety of ammonium perchlorate by significantly reducing its mechanical sensitivity by using a very low polydopamine coating layer content, and this shows great potential for the design and fabrication of insensitive energetic composites for use in propellants.

Evaluation of Fourier deconvolution ion mobility spectrometer as high-performance gas chromatography detector for the analysis of plant extract flavors.

The Fourier deconvolution ion mobility spectrometer (FDIMS) offers multiplexing and improves the resolving power and signal-to-noise ratio. To evaluate the FDIMS as a detector for gas chromatography for the analysis of complex samples, we connected a drift tube ion mobility spectrometer to a commercial gas chromatograph and compared the performance including resolving power, sensitivity, and linear range using 2,6-di­tert-butylpyridine. Mixed standards were also injected into the tandem system to evaluate the performance under optimized conditions. A complex plant extract sample used as natural flavoring was investigated using the resulting system. The results show that the instrument implemented with the Fourier deconvolution multiplexing method demonstrated higher performance over the traditional signal averaging method including higher resolving power, better limit of detection, and wider linear range for a variety of compounds and natural plant extract flavorings.

Predicting minty compounds binary mixtures' pleasantness by odor intensity in aqueous solutions.

The aroma of mint is well-liked by the public, and key flavor odorants in mint aroma had been found, but how these molecules interact and form a satisfying odor remains a challenge. Quality, intensity, and pleasantness are our most basic perceptions of aromas; both intensity and pleasantness can be quantified. However, compared to intensity, research on pleasantness was lacking. Pleasantness was one of the most important indicators for formulating a satisfying mint flavor, and the study of binary mixtures was fundamental to our understanding of more complex mixtures. Therefore, the purpose of this study was to explore the characteristics of pleasantness as a function of concentration and, at the same time, to investigate the relationship between intensity and pleasantness in binary mixtures. Thirty sensory evaluation volunteers participated in the evaluation of the intensity and pleasantness of six key flavor odorants of mint and five binary mixtures. The results showed that the pleasantness increased first and then decreased or stabilized with the rising of concentration; even though the interactions in binary mixtures were not the same, their pleasantness could be predicted using the intensities of the components by Response Surface Design of Experiments, and the goodness of fit was greater than 0.92, indicating that the models had the great predictive ability. PRACTICAL APPLICATION: Whether blending flavors or evaluating them, a great deal of experience is required, yet the acquisition of this experience is a long process. Performing these tasks is difficult for the novice, and it helps to quantify the feeling for the flavor and build some mathematical models.

Fabrication of a High-Strength, Tough, Swelling-Resistant, Conductive Hydrogel via Ion Cross-Linking, Directional Freeze-Drying, and Rehydration.

Conductive hydrogels have been in huge demand in biomedical and wearable electronics. However, the application of traditional conductive hydrogels is largely limited due to their poor mechanical properties. Here, a conductive hydrogel with excellent mechanical strength and swelling resistance properties is prepared by ion cross-linking, directional freeze-drying, and rehydration. First, the acrylamide and acrylic acid are polymerized in the κ-carrageenan solution to form the hydrogel. Then, the obtained hydrogel is cross-linked with Fe3+ by soaking in ferric chloride solution. Finally, the ionic cross-linked hydrogels are reinforced by directional freeze-drying and rehydration. The resulting hydrogel has excellent tensile strength (5.67 MPa) and high toughness (7.63 MJ/m3). It is worth noting that the hydrogel also had excellent anti-swelling properties. Its mechanical strength and volume almost show no changes after soaking in deionized water for 40 days. In addition, the hydrogel exhibits good ionic conductivity (0.091 S/m), high sensitivity, and excellent stability when applied as a strain sensor. This work proposes a simple method to fabricate a conductive hydrogel with great mechanical properties and swelling resistance, which displays huge potential in varied fields.

[Gas chromatography-mass spectrometry data analysis algorithm based on sparse model and its application in resolving severely overlapped peaks].

A Gas chromatography-mass spectrometry (GC-MS) data analysis algorithm is proposed. The mass spectrum at the top of the chromatographic peak is the spectrum to be solved. A certain amount of related reference spectra is retrieved from the spectral library, then, the equation of the chromatographic response value of each pure component is solved. A step by step strategy is used for the mass spectra retrieval. Firstly, an efficient indexing technology is used for rough selection, then, the "strong peak out with high probability" and the "extrusion" rules are used to exclude more unrelated mass spectra. A regression algorithm based on a sparse model is proposed to solve the equation of the chromatographic response value. Compared with the traditional algorithm, this algorithm can extract the main structure of the spectrum to be solved, and avoid over-fitting. The experimental results show that the proposed algorithm has a higher accuracy and smaller residual reference spectrum set, and the sparse model achieves satisfactory experimental results in the analysis of severely overlapped peaks. The proposed method provides an effective solution for resolving overlapped peaks, especially severely overlapped peaks, in GC-MS data.

Desorption corona beam ionisation (DCBI) mass spectrometry for in-situ analysis of adsorbed phenol in cigarette acetate fiber filter.

The study of spatial distribution characteristics of the adsorbed compounds for absorbent materials has significant importance in understanding the behaviors of aerosols while they migrating in the absorbent materials. Herein, for the first time, desorption corona beam ionization-mass spectrometry (DCBI-MS) has proposed for direct in-situ analysis of adsorbed aerosol for absorbent materials. DCBI is a novel atmospheric pressure chemical ionization (APCI)-related technique developed by our group in recent years. It can facilitate accurately localizing sampling by forming a visible thin corona beam and avoid the risk of sample contamination and matrix interference compared with other similar techniques. The advantages of DCBI-MS allow rapid screening of the spatial distribution characteristics of the adsorbed compounds for absorbent materials. The distribution characteristic of phenol in cigarette filter tip filled with cellulose acetate fiber was studied as a model case for demonstrating the feasibility of the developed method. As a comparison, conventional HPLC was also used for the study of the distribution characteristic of phenol. The results revealed DCBI-MS had highly improved assay simplicity in spatial distribution characteristic analysis of phenol for the acetate fiber tip, therefore, exhibiting a great potential for convenient, rapid and cost-efficient analysis of the spatial distribution characteristic investigation of adsorbed compounds for adsorbent materials.

Adaptive variable-weighted support vector machine as optimized by particle swarm optimization algorithm with application of QSAR studies.

Representing a compound by a numerous structural descriptors becomes common in quantitative structure-activity relationship (QSAR) studies. As every descriptor carries molecular structure information more or less, it seems more advisable to investigate all the possible descriptor vectors rather than traditional variable selection when building a QSAR model. Based on particle swarm optimization (PSO) algorithm, a more flexible descriptor selection and model construction method variable-weighted support vector machine (VW-SVM) is proposed. The new strategy adopted in this paper is to weight all structural descriptors with continuous non-negative values rather than removing or reserving any ones arbitrarily. The manner of invoking PSO to seek non-negative weights of variables can be regarded as a process of searching optimized rescaling for every molecular structural descriptor. Moreover, PSO is employed to search the optimal parameters of VW-SVM model besides variable weights, enables the construction of a rational and adaptive parameter-free QSAR model according to the performance of the total model. Results obtained by investigating glycogen synthase kinase-3α inhibitors and carbonic anhydrase II inhibitors indicate VW-SVM can hold more useful structure information of compounds than other methods as optimally weighting all the descriptors, consequently leading to precisely QSAR models coupled with developed performance both in training and in prediction.

A random forest of combined features in the classification of cut tobacco based on gas chromatography fingerprinting.

We applied the random forest method to discriminate among different kinds of cut tobacco. To overcome the influence of the descending resolution caused by column pollution and the subsequent deterioration of column efficacy at different testing times, we constructed combined peaks by summing the peaks over a specific elution time interval Deltat. On constructing tree classifiers, both the original peaks and the combined peaks were considered. A data set of 75 samples from three grades of the same tobacco brand was used to evaluate our method. Two parameters of the random forest were optimized using out-of-bag error, and the relationship between Deltat and classification rate was investigated. Experiments show that partial least squares discriminant analysis was not suitable because of the overfitting, and the random forest with the combined features performed more accurately than Naïve Bayes, support vector machines, bootstrap aggregating and the random forest using only its original features.

Accelerated solvent extraction for GC-based tobacco fingerprinting and its comparison with simultaneous distillation and extraction.

An accelerated solvent extraction (ASE) procedure has been developed as a pretreatment method for chemical fingerprinting of volatile and semi-volatile components in cut tobacco. The ASE extraction conditions including temperature, operation pressure and extraction cycles were optimized to maximize extraction yield. The method was validated with repeatability, recovery and linearity. Compared with simultaneous distillation extraction (SDE), ASE provides higher extraction yields, less extraction time, lower solvent consumption and less labor time, and is more suitable for tobacco sample preparation. A typical ASE extract was analyzed by gas chromatography/time-of-flight mass spectrometry (GC-TOFMS). A total of 305 components with signal-to-noise ratio higher than 100 were tentatively identified by NIST05 and Wiley database. Finally, 36 cigarette samples from six cigarette brands were analyzed using the developed chemical fingerprinting method. Partial least squares-discriminant analysis shows good discrimination of different cigarette brands. The results indicate that ASE method can serve as high-throughput sample preparation technique for cigarette chemical fingerprint analysis.

Alteration of transcriptional profile in human bronchial epithelial cells induced by cigarette smoke condensate.

Despite the significance of cigarette smoke for carcinogenesis, the molecular mechanisms that lead to increased susceptibility of human cancers are not well-understood. In our present study, the oncogenic transforming effects of cigarette smoke condensate (CSC) were examined using papillomavirus-immortalized human bronchial epithelial cells (BEP2D). Growth kinetics, saturation density, resistance to serum-induced terminal differentiation, anchorage-independent growth and tumorigenicity in nude mice were used to investigate the various stages of transformation in BEP2D cells. Illumina microarray platforms were used to explore the CSC-induced alteration of global mRNA expression profiles of the earlier period and the advanced stage of CSC-treated BEP2D cells. We showed here that a series of sequential steps arose among CSC-treated immortalized human bronchial epithelial cells, including altered growth kinetics, resistance to serum-induced terminal differentiation, and anchorage-independence growth. In the earlier period of CSC treatment, 265 genes were down-regulated and 63 genes were up-regulated, respectively, and in the advanced stage of CSC treatment, 313 genes were down-regulated and 145 genes were up-regulated, respectively. Notably, among those genes, the expression of some of imprinted genes such as IGF2, NDN, H19 and MEG3 were all silenced or down-regulated in CSC-treated cells. These genes reactivated after 5 microM 5-aza-2-deoxycytidine (5-aza-dC) treatment. These results demonstrated that long-term treatment of human bronchial epithelial cells with CSC may adversely affect their genetic and epigenetic integrity and lead to further transformation.

Fingerprint developing of coffee flavor by gas chromatography-mass spectrometry and combined chemometrics methods.

In this paper, chromatographic fingerprint was firstly used for quality control of tobacco flavors. Based on gas chromatography-mass spectrometry (GC-MS) and combined chemometrics methods, a simple, reliable and reproducible method for developing chromatographic fingerprint of coffee flavor, one of tobacco flavors, was described. Six coffee flavor samples obtained from different locations were used to establish the fingerprint. The qualitative and quantitative analysis of coffee flavor sample from Shenzhen was completed with the help of subwindow factor analysis (SFA). Fifty-two components of 68 separated constituents in coffee flavor sample from Shenzhen, accounting for 88.42% of the total content, were identified and quantified. Then, spectral correlative chromatography (SCC) was used to extract the common peaks from other five studied coffee flavor samples. Thirty-eight components were found to exist in all six samples. Finally, the method validation of fingerprint analysis was performed based on the relative retention time and the relative peak area of common peaks, sample stability and similarity analysis. The similarities of six coffee flavor samples were more than 0.9104 and showed that samples from different locations were consistent to some extent. The developed chromatographic fingerprint was successfully used to differentiate coffee flavor from cocoa flavor and some little difference sample prepared with coffee flavor and cocoa flavor by both similarity comparison and principal component projection analysis. The developed method can be used for quality control of coffee flavor.

A rapid, simple, specific liquid chromatographic-electrospray mass spectrometry method for the determination of finasteride in human plasma and its application to pharmacokinetic study.

A fast, accurate, sensitive, selective and reliable method using reversed-phase high-performance liquid chromatography-mass spectrometry coupling with an electrospray ionization interface was developed and validated for the determination of finasteride in human plasma. After deprotienation with acetonitrile, centrifugation, evaporation to dryness and dissolving in mobile phase, satisfactory separation was achieved on a Hypersil-Keystone C(18) reversed-phase column using a mobile phase consisting of acetonitrile-water (46:54, v/v), 0.1% acetic acid and 0.1% trifluoracetic acid. Carbamazepine (IS) was used as internal standard. This method involved the use of the [M+H](+) ions of finasteride and IS at m/z 373 and 237 with the selective ion monitoring (SIM) mode. The calibration curve was linear in the range of 0.2-120 ng ml(-1). The limit of quantification for finasteride in plasma was 0.2 ng ml(-1) with good accuracy and precision. The intra-assay precision and accuracy were in the range of 2.1-11.2% and -1.3% to 8.5%, respectively. The inter-assay precision and accuracy were in the order of 3.4-12.1% and -1.5% to 11.5%, respectively. The mean sample extract recoveries of the method were higher than 85% and 74% for finasteride and internal standard (IS), respectively. The assay has been successfully used to estimate the pharmacokinetics of finasteride after oral administration of a 5mg tablet of finasteride to 24 healthy volunteers.

Comparative analysis of the volatile components in cut tobacco from different locations with gas chromatography-mass spectrometry (GC-MS) and combined chemometric methods.

A combined approach of subwindow factor analysis and orthogonal projection resolution was used to analyze the volatile components of cut tobacco samples from different sources. After extracted with simultaneous distillation and extraction method, the volatile components in cut tobacco from five different locations were detected by GC-MS. Then, the qualitative and quantitative analysis of the volatile components of cut tobacco from Changde area was completed with the help of subwindow factor analysis resolving two-dimensional original data into pure mass spectra and chromatograms. One hundred and two volatile components among 138 separated peaks were identified and quantified, accounting for about 88.90% of the total content. Finally, orthogonal projection method was used to extract the common peaks from different locations. Among the identified components, there were 74 components coexisting in five studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprints. It was the first time to apply orthogonal projection method to compare different cut tobacco samples, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex cut tobacco samples. The developed method can be used to compare the sameness and differences of cut tobacco from different sources and for quality control of cigarette production and materials.

Inhibition by N'-nitrosonornicotine of the catalytic activity of glutamate dehydrogenase in alpha-ketoglutarate amination.

The effect of N'-nitrosonornicotine (NNN), one of the tobacco-specific nitrosamines, on the catalytic activity of glutamate dehydrogenase (GLDH) in the alpha-ketoglutarate amination, using reduced nicotinamide adenine dinucleotide as coenzyme, was studied by a chronoamperometric method. The maximum reaction rate of the enzyme-catalyzed reaction and the Michaelis-Menten constant, or the apparent Michaelis-Menten constant, were determined in the absence and presence of NNN. NNN remarkably inhibited the bio-catalysis activity of GLDH, and was a reversible competitive inhibitior with K(i), estimated as 199 micromol l(-1) at 25 degrees C and pH 8.0.

A kinetic model and its parameter estimation for the process of binding copper to human serum albumin by a voltammetric method.

Linear sweep anodic stripping voltammetry was applied to determine the concentration of free copper ions in the process of binding copper to human serum albumin (HSA) on the mercaptoethane sulfonate modified gold electrode surface. A kinetic model of two consecutive steps for the process of binding copper to HSA was first proposed on the basis of the electrochemical results and compared with a parallel kinetic response model by using residual analysis. The experimental data of the stripping peak currents with time was fitted according to the model and the kinetic parameters, binding rate constants, k1 and k2, were estimated to be 0.411 and 0.055 min(-1), respectively.