[Determination of 22 mycotoxins in milk by liquid chromatography-quadrupole/orbitrap mass spectrometry].

Mycotoxins have carcinogenic, mutagenic, hepatotoxic, nephrotoxic, immunotoxic, neurotoxic, and teratogenic properties. Thus, these substances have attracted significant attention because they pose a threat to human health. As research on mycotoxins deepens, new structural analogues of mycotoxins are constantly being discovered. In this study, a method based on high performance liquid chromatography-quadrupole/orbitrap mass spectrometry was established for the simultaneous determination of 22 mycotoxins in milk. A simple, effective, and rapid pretreatment method was optimized by focusing on the solvent type, extractant volume, and extracting salt based on the characteristics of the mycotoxins and sample matrix. The analytes were extracted using 0.5% formic acid acetonitrile solution and added with sodium chloride to separate fats from water. The samples were centrifuged at 8000 r/min (4 ℃) for 5 min using a centrifuge and then concentrated using nitrogen. The dry residue was dissolved with 50% methanol aqueous solution. Twenty-two mycotoxins were separated on a ZORBAX Eclipse Plus C18 chromatographic column (100 mm×2.1 mm, 1.7 µm), and quantitative analysis was performed using the isotope internal standard method. The analytes were determined by liquid chromatography-quadrupole/orbitrap mass spectrometry in positive electrospray ionization mode. Qualitative analyses of the compounds were performed in full mass spectrometry/data-dependent tandem mass spectrometry (MS/dd-MS2) mode. Good linearities in the range of 0.5-100.0 µg/L were observed for the 22 mycotoxins, and the correlation coefficients (R2) were greater than 0.999. The limits of detection (S/N=3) and quantification (S/N=10) ranged from 0.3 to 0.5 µg/kg and from 1.0 to 1.5 µg/kg, respectively. The average recoveries of the 22 mycotoxins at three spiked levels of 1.5, 5.0, and 15 µg/kg were between 84.7% and 100.8%, with relative standard deviations (RSDs) of 1.2%-9.9%. These findings indicate that the method has high sensitivity and accuracy as well as good precision. Finally, the method was applied to the detection and analysis of mycotoxins in 25 actual commercial milk samples. The results revealed that the selected samples were not contaminated with any of the mycotoxins analyzed. Thus, the proposed method is useful as a quick preprocessing and confirmatory method for the simultaneous determination of mycotoxins in milk.

Synthesis of Multi-Functional Carbon Quantum Dots for Targeted Antitumor Therapy.

Carbon dots are nano-sized photoluminescence materials which have good biocompatibility and low cytotoxicity, while the previously synthesized carbon dots lack tumor targeting capability and therapy function so that it cannot achieve the purpose of diagnosis and treatment. Herein, a new kind of multi-functional carbon dots (GFCDs) is promising to be applied in tumor cells imaging and clinical targeted therapy. Gallic acid (GA) was used as the carbon resource and antitumor active molecule, folic acid (FA) was used as the nitrogen resource and tumor targeting molecule, and citric acid monohydrate (CA) was used as the auxiliary carbon source. Multi-functional GACDs were synthesized by a simple one-step microwave-assisted procedure and analyzed with UV - vis spectrophotometer, fourier transform infrared spectrometer, transmission electron microscopy and X-ray photoelectron spectrometer. Results show that the diameter of GFCDs is about 3 nm. And GFCDs are pale-yellow under natural light which turn blue under 360 nm UV lamp. Besides ester bond is the connecting mode between functional molecules. In addition, the results of in vitro cell imaging experiments and in vivo antitumor experiments demonstrate the targeting imaging and antitumor abilities towards Hela cells. The synthesis route and properties of GFCDs.

[Rapid determination of 13 ultraviolet absorbents in plastic food contact materials by ultra-performance convergence chromatography].

A rapid method based on ultra-performance convergence chromatography (UPC2) was developed for the analysis of 13 ultraviolet (UV) absorbents in plastic food contact materials. The UV absorbents were extracted from plastic food contact materials by supersonic extraction with methanol, purified by C18 solid phase extraction column, and analyzed via UPC2 before filtration with an organic filtration membrane (0.22 µm). An ACQUTY UPC2 HSS C18 SB chromatographic column (150 mm×3.0 mm, 1.8 µm) was used for the detection of the UV absorbents. An effective separation was achieved within 4 min under the optimized conditions. The mobile phases were supercritical carbon dioxide and isopropanol as a modifier. The results showed that the 13 UV absorbents exhibited good linear relationships in the respective linear ranges with the correlation coefficients no less than 0.9985. The limits of detection (S/N=3) were in the range of 0.05-0.15 mg/kg. The recoveries were from 86.8% to 115.7%, and the relative standard deviations were between 0.73% and 5.61%. This method is rapid, convenient, accurate and reliable, and can be used for the rapid determination of the 13 UV absorbents in plastic food contact materials.

Determination of Pb, Cr, Cd, and As in Aluminum-Plastic Packaging Materials via Inductively Coupled Plasma-Mass Spectrometry with Microwave Digestion.

Microwave digestion was performed to study the pretreatment methods of aluminum-plastic packaging materials (APPMs). Five different digestion reagent combinations and proportions were thoroughly considered. Digestion results indicated that the most suitable reagent combination was sulfuric and nitric acids with the optimal proportion of 1∶7 after the orthogonal experiment. Moreover, the possible reasons of the experimental phenomenon were analyzed. The contents of Pb, Cr, Cd, and As in APPMs were subsequently determined via inductively coupled plasma-mass spectrometry (ICP-MS). The satisfactory linearity of calibration curves was obtained with the linear correlation coefficients above 0.999 5, and the instrument detection limits of Pb, Cr, Cd, and As for the current method were 0.215, 0.067, 0.006 and 0.020 ng·mL-1, respectively. Furthermore, the recoveries of standard addition ranged from 83.8% to 111.6%, and the relative standard deviations ranged from 0.5% to 7.4%. Two independent parallel determination results of Pb, Cr, Cd, and As in APPMs were approaching, and the student's t-test (confidence level, α=0.05) showed that the determination results had no significant differences. In conclusion, the present method exhibited fine linearity, low detection limit, high recovery, and good precision, which can accurately be utilized to analyze Pb, Cr, Cd, and As elements in APPMs or other similar materials.

Application of the standard addition method for the determination of acrylamide in heat-processed starchy foods by gas chromatography with electron capture detector.

A gas chromatography electron capture detector (GC-ECD) using the standard addition method was developed for the determination of acrylamide in heat-processed foods. The method entails extraction of acrylamide with water, filtration, defatting with n-hexane, derivatization with hydrobromic acid and saturated bromine-water, and liquid-liquid extraction with ethyl acetate. The sample pretreatment required no SPE clean-up and concentration steps prior to injection. The final extract was analyzed by GC-ECD. The chromatographic analysis was performed on polar columns, e.g. Supelcowax-10 capillary column, and good retention and peak response of the analyte were achieved under the optimal conditions. The qualification of the analyte was by identifying the peak with same retention time as standard compound 2,3-DBPA and confirmed by GC-MS. GC-MS analysis confirmed that 2,3-DBPA was converted to 2-BPA nearly completely on the polar capillary column, whether or not treated with triethylamine. A four-point standard addition protocol was used to quantify acrylamide in food samples. The limit of detection (LOD) was estimated to be 0.6µg/kg on the basis of ECD technique. Validation and quantification results demonstrated that the method should be regarded as a low-cost, convenient, and reliable alternative for conventional investigation of acrylamide.

Recognition for avian influenza virus proteins based on support vector machine and linear discriminant analysis.

Total 200 properties related to structural characteristics were employed to represent structures of 400 HA coded proteins of influenza virus as training samples. Some recognition models for HA proteins of avian influenza virus (AIV) were developed using support vector machine (SVM) and linear discriminant analysis (LDA). The results obtained from LDA are as follows: the identification accuracy (R ia) for training samples is 99.8% and R ia by leave one out cross validation is 99.5%. Both R ia of 99.8% for training samples and R ia of 99.3% by leave one out cross validation are obtained using SVM model, respectively. External 200 HA proteins of influenza virus were used to validate the external predictive power of the resulting model. The external R ia for them is 95.5% by LDA and 96.5% by SVM, respectively, which shows that HA proteins of AIVs are preferably recognized by SVM and LDA, and the performances by SVM are superior to those by LDA.

Structural parameterization and functional prediction of antigenic polypeptome sequences with biological activity through quantitative sequence-activity models (QSAM) by molecular electronegativity edge-distance vector (VMED).

Only from the primary structures of peptides, a new set of descriptors called the molecular electronegativity edge-distance vector (VMED) was proposed and applied to describing and characterizing the molecular structures of oligopeptides and polypeptides, based on the electronegativity of each atom or electronic charge index (ECI) of atomic clusters and the bonding distance between atom-pairs. Here, the molecular structures of antigenic polypeptides were well expressed in order to propose the automated technique for the computerized identification of helper T lymphocyte (Th) epitopes. Furthermore, a modified MED vector was proposed from the primary structures of polypeptides, based on the ECI and the relative bonding distance of the fundamental skeleton groups. The side-chains of each amino acid were here treated as a pseudo-atom. The developed VMED was easy to calculate and able to work. Some quantitative model was established for 28 immunogenic or antigenic polypeptides (AGPP) with 14 (1-14) A(d) and 14 other restricted activities assigned as "1"(+) and "0"(-), respectively. The latter comprised 6 A(b)(15-20), 3 A(k)(21-23), 2 E(k)(24-26), 2 H-2(k)(27 and 28) restricted sequences. Good results were obtained with 90% correct classification (only 2 wrong ones for 20 training samples) and 100% correct prediction (none wrong for 8 testing samples); while contrastively 100% correct classification (none wrong for 20 training samples) and 88% correct classification (1 wrong for 8 testing samples). Both stochastic samplings and cross validations were performed to demonstrate good performance. The described method may also be suitable for estimation and prediction of classes I and II for major histocompatibility antigen (MHC) epitope of human. It will be useful in immune identification and recognition of proteins and genes and in the design and development of subunit vaccines. Several quantitative structure activity relationship (QSAR) models were developed for various oligopeptides and polypeptides including 58 dipeptides and 31 pentapeptides with angiotensin converting enzyme (ACE) inhibition by multiple linear regression (MLR) method. In order to explain the ability to characterize molecular structure of polypeptides, a molecular modeling investigation on QSAR was performed for functional prediction of polypeptide sequences with antigenic activity and heptapeptide sequences with tachykinin activity through quantitative sequence-activity models (QSAMs) by the molecular electronegativity edge-distance vector (VMED). The results showed that VMED exhibited both excellent structural selectivity and good activity prediction. Moreover, the results showed that VMED behaved quite well for both QSAR and QSAM of poly-and oligopeptides, which exhibited both good estimation ability and prediction power, equal to or better than those reported in the previous references. Finally, a preliminary conclusion was drawn: both classical and modified MED vectors were very useful structural descriptors. Some suggestions were proposed for further studies on QSAR/QSAM of proteins in various fields.