Traceability of Microplastic Fragments from Waste Plastic Express Packages Using Near-Infrared Spectroscopy Combined with Chemometrics.

The pollution from waste plastic express packages (WPEPs), especially microplastic (MP) fragments, caused by the blowout development of the express delivery industry has attracted widespread attention. On account of the variety of additives, strong complexity, and high diversity of plastic express packages (PEPs), the multi-class classification of WPEPs is a typical large-class-number classification (LCNC). The traceability and identification of microplastic fragments from WPEPs is very challenging. An effective chemometric method for large-class-number classification would be very beneficial for the comprehensive treatment of WPEP pollution through the recycling and reuse of waste plastic express packages, including microplastic fragments and plastic debris. Rather than using the traditional one-against-one (OAO) and one-against-all (OAA) dichotomies, an exhaustive and parallel half-against-half (EPHAH) decomposition, which overcomes the defects of the OAO's classifier learning limitations and the OAA's data proportion imbalance, is proposed for feature selection. EPHAH analysis, combined with partial least squares discriminant analysis (PLS-DA) for large-class-number classification, was performed on 750 microplastic fragments of polyethylene WPEPs from 10 major courier companies using near-infrared (NIR) spectroscopy. After the removal of abnormal samples through robust principal component analysis (RPCA), the root mean square error of cross-validation (RMSECV) value for the model was reduced to 0.01, which was 21.5% lower than that including the abnormal samples. The best models of PLS-DA were obtained using SNV combined with SG-17 smoothing and 2D (SNV+SG-17+2D); the latent variables (LVs), the error rates of Monte Carlo cross-validation (ERMCCVs), and the final classification accuracies were 6.35, 0.155, and 88.67% for OAO-PLSDA; 5.37, 0.103, and 87.33% for OAA-PLSDA; and 3.12, 0.054, and 96.00% for EPHAH-PLSDA. The results showed that the EPHAH strategy can completely learn the complex LCNC decision boundaries for 10 classes, effectively break the tie problem, and greatly improve the voting resolution, thereby demonstrating significant superiority to both the OAO and OAA strategies in terms of classification accuracy. Meanwhile, PLS-DA further maximized the covariance and data interpretation abilities between the potential variables and categories of microplastic debris, thereby establishing an ideal performance identification model with a recognition rate of 96.00%.

Dual Gene Detection of H5N1 Avian Influenza Virus Based on Dual RT-RPA.

The H5N1 avian influenza virus seriously affects the health of poultry and humans. Once infected, the mortality rate is very high. Therefore, accurate and timely detection of the H5N1 avian influenza virus is beneficial for controlling its spread. This article establishes a dual gene detection method based on dual RPA for simultaneously detecting the HA and M2 genes of H5N1 avian influenza virus, for the detection of H5N1 avian influenza virus. Design specific primers for the conserved regions of the HA and M2 genes. The sensitivity of the dual RT-RPA detection method for HA and M2 genes is 1 × 10-7 ng/µL. The optimal primer ratio is 1:1, the optimal reaction temperature is 40 °C, and the optimal reaction time is 20 min. Dual RT-RPA was used to detect 72 samples, and compared with RT-qPCR detection, the Kappa value was 1 (p value < 0.05), and the clinical sample detection sensitivity and specificity were both 100%. The dual RT-RPA method is used for the first time to simultaneously detect two genes of the H5N1 avian influenza virus. As an accurate and convenient diagnostic tool, it can be used to diagnose the H5N1 avian influenza virus.

Advances in Detection Techniques for the H5N1 Avian Influenza Virus.

Avian influenza is caused by avian influenza virus infection; the H5N1 avian influenza virus is a highly pathogenic subtype, affecting poultry and human health. Since the discovery of the highly pathogenic subtype of the H5N1 avian influenza virus, it has caused enormous losses to the poultry farming industry. It was recently found that the H5N1 avian influenza virus tends to spread among mammals. Therefore, early rapid detection methods are highly significant for effectively preventing the spread of H5N1. This paper discusses the detection technologies used in the detection of the H5N1 avian influenza virus, including serological detection technology, immunological detection technology, molecular biology detection technology, genetic detection technology, and biosensors. Comparisons of these detection technologies were analyzed, aiming to provide some recommendations for the detection of the H5N1 avian influenza virus.

Protected Geographical Indication Discrimination of Zhejiang and Non-Zhejiang Ophiopogonis japonicus by Near-Infrared (NIR) Spectroscopy Combined with Chemometrics: The Influence of Different Stoichiometric and Spectrogram Pretreatment Methods.

This paper presents a method for the protected geographical indication discrimination of Ophiopogon japonicus from Zhejiang and elsewhere using near-infrared (NIR) spectroscopy combined with chemometrics. A total of 3657 Ophiopogon japonicus samples from five major production areas in China were analyzed by NIR spectroscopy, and divided into 2127 from Zhejiang and 1530 from other areas ('non-Zhejiang'). Principal component analysis (PCA) was selected to screen outliers and eliminate them. Monte Carlo cross validation (MCCV) was introduced to divide the training set and test set according to a ratio of 3:7. The raw spectra were preprocessed by nine single and partial combination methods such as the standard normal variable (SNV) and derivative, and then modeled by partial least squares regression (PLSR), a support vector machine (SVM), and soft independent modeling of class analogies (SIMCA). The effects of different pretreatment and chemometrics methods on the model are discussed. The results showed that the three pattern recognition methods were effective in geographical origin tracing, and selecting the appropriate preprocessing method could improve the traceability accuracy. The accuracy of PLSR after the standard normal variable was better, with R2 reaching 0.9979, while that of the second derivative was the lowest with an R2 of 0.9656. After the SNV pretreatment, the accuracy of the training set and test set of SVM reached the highest values, which were 99.73% and 98.40%, respectively. The accuracy of SIMCA pretreated with SNV and MSC was the highest for the origin traceability of Ophiopogon japonicus, which could reach 100%. The distance between the two classification models of SIMCA-SNV and SIMCA-MSC is greater than 3, indicating that the SIMCA model has good performance.

Low-Cost Detection of Methane Gas in Rice Cultivation by Gas Chromatography-Flame Ionization Detector Based on Manual Injection and Split Pattern.

Rice cultivation is one of the most significant human-created sources of methane gas. How to accurately measure the methane concentration produced by rice cultivation has become a major problem. The price of the automatic gas sampler used as a national standard for methane detection (HJ 38-2017) is higher than that of gas chromatography, which greatly increases the difficulty of methane detection in the laboratory. This study established a novel methane detection method based on manual injection and split pattern by changing the parameters of the national standard method without adding any additional automatic gas samplers. The standard curve and correlation coefficient obtained from the parallel determination of methane standard gas were y = 2.4192x + 0.1294 and 0.9998, respectively. Relative standard deviation (RSD, <2.82%), recycle rate (99.67−102.02%), limit of detection (LOD, 0.0567 ppm) and limit of quantification (LOQ, 0.189 ppm) of this manual injection method are satisfying, demonstrating that a gas chromatography-flame ionization detector (GC-FID), based on manual injection at a split ratio (SR) of 5:1, could be an effective and accurate method for methane detection. Methane gases produced by three kinds of low-methane rice treated with oxantel pamoate acid, fumaric acid and alcohol, were also collected and detected using the proposed manual injection approach Good peak shapes were obtained, indicating that this approach could also be used for quantification of methane concentration.

Development of a Phage-Displayed Nanobody-Based Competitive Immunoassay for the Sensitive Detection of Soybean Agglutinin.

Soybean agglutinin (SBA) is a primary antinutritional factor in soybeans that can inhibit the growth of humans and mammals, disrupt the intestinal environment, and cause pathological changes. Therefore, detecting and monitoring SBA in foods is essential for safeguarding human health. In this paper, M13 phage-displayed nanobodies against SBA were isolated from a naive nanobody library. An M13 phage-displayed nanobody-based competitive enzyme-linked immunosorbent assay (P-cELISA) was then established for SBA analysis using biotinylated anti-M13 phage antibody (biotin-anti-M13) and streptavidin poly-HRP conjugate (SA-poly-HRP). The biotin-anti-M13@SA-poly-HRP probe can easily amplify the detection signal without the chemical modifications of phage-displayed nanobodies. The established P-cELISA presented a linear detection range of 0.56-250.23 ng/mL and a limit of detection (LOD) of 0.20 ng/mL, which was 12.6-fold more sensitive than the traditional phage-ELISA. Moreover, the developed method showed good specificity for SBA and acceptable recoveries (78.21-121.11%) in spiked wheat flour, albumen powder, and whole milk powder. This study proposes that P-cELISA based on biotin-anti-M13@SA-poly-HRP may provide a convenient and effective strategy for the sensitive detection of SBA.

Establishment of Indirect Competitive Enzyme-linked Immunosorbent Assay (ic-ELISA) for Copper ion (Cu2+) in Raw Meat Products.

Adding an appropriate amount of copper to feed can promote the growth and development of livestock; however, a large amount of heavy metal copper can accumulate in livestock through the enrichment effect, which poses a serious threat to human health. Traditional Cu2+ detection relies heavily on complex and expensive instruments, such as inductively coupled plasma-optical emission spectrometry (ICP-OES) and inductively coupled plasma-mass spectrometry (ICP-MS); thus, convenient and simple rapid detection technologies are urgently needed. In this paper, synthesized copper antigens were used to immunize mice and highly specific anticopper monoclonal antibodies were obtained, which were verified to exhibit high affinity and specificity. Based on the above antibodies, an indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) was established for the rapid detection of copper content in pork. The standard inhibition curve of the method was obtained by antigen-antibody working concentration screening, in which the half inhibitory concentration (IC50) was 11.888 ng/mL, the limit of detection (LOD) was 0.841 ng/mL and the correlation coefficient R2 of the curve was 0.998. In the additive recovery experiment, the recovery rate ranged from 90% to 110%, and the coefficient of variation (CV) was less than 10%, indicating that the method achieved high accuracy and precision. Finally, the results of ic-ELISA combined with Bland-Altman analysis showed a high correlation with ICP-MS, and the correlation coefficient (R2) reached 0.990 when the copper concentration was less than 200 ng/mL. Thus, the ic-ELISA method exhibits high reliability.

Application of an improved hollow fiber liquid phase microextraction technique coupled to LC-MS/MS to studying migration of fluorescent whitening agents from plastic food contact materials.

In this paper, a new hollow fiber liquid-phase microextraction method was developed to improve the extraction of five fluorescent whitening agents that migrated from plastics food contact materials. Influencing factors, such as the types of membrane, the extraction solvent, the stirring speed, the addition of salt ion, and extraction time, were investigated in detail. Under the optimal conditions, high enrichment factors (71-205) can be obtained with 15 µL extraction solvent. The new method is advantageous; the polypropylene hollow fiber membrane modified by sepiolite nanoparticles had excellent solvent binding force and mass transfer effect compared with the conventional extraction technique. The extracts were analyzed by high performance liquid chromatography-tandem mass spectrometry, the limits of detection were 0.3 or 0.9 ng kg-1 with good correlation coefficients (r2 ≥ 0.9940) for the five fluorescent whitening agents. The intra-day and inter-day recoveries ranged between 82.6% and 112%, with a relative standard deviation of less than 12%. The established method was successfully applied to the analysis of fluorescent whitening agent migration from four types of plastic food contact materials immersed in three food simulants.

[Development of a colloidal gold based immunochromatographic strip for 8-OHdG detection].

8-hydroxy-2'-deoxyguanosine (8-OHdG) is a sensitive and stable biomarker for evaluating DNA oxidative damage. A rapid and sensitive colloidal gold immunochromatographic strip was developed for 8-OHdG detection by a competitive method. The sample pad (glass cellulose film), bonding pad (glass cellulose film), nitrocellulose film and absorbent pad were pasted on the polyvinyl chloride (PVC) base plate to construct the test strip. Colloidal gold (AuNPs) was prepared by the reduction of chloroauric acid with sodium citrate. 8-OHdG antibody (Ab) was coated on the outer layer of AuNPs to form Ab@AuNPs as a probe. Bovine serum albumin (BSA) and 8-OHdG were conjugated with carbodiimide hydrochloride to prepare an artificial antigen, which was used as the coating antigen of detection line. Goat anti mouse polyclonal antibody IgG was used as the coating antibody of control line. The experimental parameters were optimized including the type of nitrocellulose membrane, the formula of loading solution, and the spraying amount of gold labeled antibody. The results showed that the appropriate nitrocellulose membrane was CN 95. The optimal loading solution included BSA (1%), Tween-20 (3%), sucrose (3%) and NaCl (0.9%). The optimal spraying amount of gold labeled antibody was 4 µL. 8-OHdG can be detected by the strip under visible light, and the level of 8-OHdG in urine can be preliminarily determined by comparing the color intensity of T line and C line. The 8-OHdG concentration in urine was further calculated by the gray value of T line and the threshold of detection was 2.55 µg/L. This colloidal gold immunochromatographic strip is simple, rapid and specific for detecting 8-OHdG in human urine to preliminarily evaluate the human status.

Quantum-Dot-Bead-Based Fluorescence-Linked Immunosorbent Assay for Sensitive Detection of Cry2A Toxin in Cereals Using Nanobodies.

In this study, a quantum-dot-bead (QB)-based fluorescence-linked immunosorbent assay (FLISA) using nanobodies was established for sensitive determination of the Cry2A toxin in cereal. QBs were used as the fluorescent probe and conjugated with a Cry2A polyclonal antibody. An anti-Cry2A nanobody P2 was expressed and used as the capture antibody. The results revealed that the low detection limit of the developed QB-FLISA was 0.41 ng/mL, which had a 19-times higher sensitivity than the traditional colorimetric ELISA. The proposed assay exhibited a high specificity for the Cry2A toxin, and it had no evident cross-reactions with other Cry toxins. The recoveries of Cry2A from the spiked cereal sample ranged from 86.6-117.3%, with a coefficient of variation lower than 9%. Moreover, sample analysis results of the QB-FLISA and commercial ELISA kit correlated well with each other. These results indicated that the developed QB-FLISA provides a potential approach for the sensitive determination of the Cry2A toxin in cereals.

Fingerprint Approaches Coupled with Chemometrics to Discriminate Geographic Origin of Imported Salmon in China's Consumer Market.

Of the salmon sold in China's consumer market, 92% was labelled as Norwegian salmon, but was in fact was mainly imported from Chile. The aim of this study was to establish an effective method for discriminating the geographic origin of imported salmon using two fingerprint approaches, Near-infrared (NIR) spectroscopy and mineral element fingerprint (MEF). In total, 80 salmon (40 from Norway and 40 from Chile) were tested, and data generated by NIR and MEF were analysed via various chemometrics. Four spectral preprocessing methods, including vector normalization (VN), Savitzky Golay (SG) smoothing, first derivative (FD) and second derivative (SD), were employed on the raw NIR data, and a partial least squares (PLS) model based on the FD + SG9 pretreatment could successfully differentiate Norwegian salmons from Chilean salmons, with a R2 value of 98.5%. Analysis of variance (ANOVA) and multiple comparative analysis were employed on the contents of 16 mineral elements including Pb, Fe, Cu, Zn, Al, Sr, Ni, As, Cr, V, Se, Mn, K, Ca, Na and Mg. The results showed that Fe, Zn, Al, Ni, As, Cr, V, Se, Ca and Na could be used as characteristic elements to discriminate the geographical origin of the imported salmon, and the discrimination rate of the linear discriminant analysis (LDA) model, trained on the above 10 elements, could reach up to 98.8%. The results demonstrate that both NIR and MEF could be effective tools for the rapid discrimination of geographic origin of imported salmon in China's consumer market.

Establishment of an Indirect Competitive Enzyme-Linked Immunosorbent Method for the Detection of Heavy Metal Cadmium in Food Packaging Materials.

Heavy metals in food packaging materials have been indicated to release into the environment at slow rates. Heavy metal contamination, especially that of cadmium (Cd), is widely acknowledged as a global environment threat that leads to continuous growing pollution levels in the environment. Traditionally, the detection of the concentration of Cd relies on expensive precision instruments, such as inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma-atomic emission spectrometry (ICP-AES). In this study, an indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) based on a specific monoclonal antibody was proposed to rapidly detect Cd. The half-inhibitory concentration and detection sensitivity of the anti-cadmium monoclonal antibody of the ic-ELISA were 5.53 ng mL-1 and 0.35 ng mL-1, respectively. The anti-Cd monoclonal antibody possessed high specificity while diagnosising other heavy metal ions, including Al (III), Ca (II), Cu (II), Fe (III), Hg (II), Mg (II), Mn (II), Pb (II), Zn (II), Cr (III) and Ni (II). The average recovery rates of Cd ranged from 89.03-95.81% in the spiked samples of packing materials, with intra- and inter-board variation coefficients of 7.20% and 6.74%, respectively. The ic-ELISA for Cd detection was applied on 72 food packaging samples that consisted of three material categories-ceramic, glass and paper. Comparison of the detection results with ICP-AES verified the accuracy of the ic-ELISA. The correlation coefficient between the ic-ELISA and the ICP-AES methods was 0.9634, demonstrating that the proposed ic-ELISA approach could be a useful and effective tool for the rapid detection of Cd in food packaging materials.

4,5,6,7-Tetra-chloro-2-(2,2,2-trifluoro-eth-yl)isoindoline-1,3-dione.

In the title compound, C(10)H(2)Cl(4)F(3)NO(2), the isoindoline ring system is almostplanar, the maximum atomic deviation being 0.064 (2) Å. The C-C bond of the ethyl-ene group is twisted with respect to the isoindoline plane by a dihedral angle of 59.58 (12)°. In the crystal, weak inter-molecular C-H⋯F hydrogen bonding links the mol-ecules into supra-molecular chains running along the a axis. A short inter-molecular Cl⋯O contact of 2.950 (3) Šis also observed.

4,5,6,7-Tetra-chloro-2-(4-fluoro-phen-yl)isoindoline-1,3-dione.

The title compound, C(14)H(4)Cl(4)FNO(2), has crystallographic twofold symmetry with the N and F atoms and two C atoms of the benzene ring located on a twofold rotation axis. The isoindole-dione ring system is almost planar [maximum atomic deviation = 0.036 (3) Å], and is twisted with respect to the florobenzene ring, making a dihedral angle of 58.56 (16)°. Weak inter-molecular C-H⋯Cl hydrogen bonding is present in the crystal structure.

2-(2,2,2-Trifluoro-eth-yl)isoindoline-1,3-dione.

In the title compound, C(10)H(6)F(3)NO(2), the isoindole ring system is planar, the maximum atomic deviation being 0.012 (2) Å. The C-C bond of the trifluoro-ethyl group is twisted with respect to the isoindole ring by a dihedral angle of 62.58 (17)°. Weak inter-molecular C-H⋯O and C-H⋯F hydrogen bonding is present in the crystal structure.

N-(3,4-Difluoro-phen-yl)phthalimide.

In the title compound, C(14)H(7)F(2)NO(2), the phthalimide ring system is nearly planar [maximum atomic deviation = 0.028 (1) Å] and it is twisted with respect to the attached benzene ring, making a dihedral angle of 55.70 (6)°. Weak inter-molecular C-H⋯F hydrogen bonds are present in the crystal structure.

N-(2,3,4-Trifluoro-phen-yl)phthalimide.

In the title compound, C(14)H(6)F(3)NO(2), the benzene ring and the phthalimide ring system make a dihedral angle of 60.12 (7)°. Weak inter-molecular C-H⋯O and C-H⋯F hydrogen bonds are present in the crystal structure.

4,5,6,7-Tetra-chloro-N-(2-fluoro-phen-yl)phthalimide.

In the title compound, C(14)H(4)Cl(4)FNO(2), the benzene ring and the phthalimide plane are nearly planar, the maximum deviations being 0.005 (2) and 0.010 (2) Å, respectively, but the mol-ecule as a whole is not planar: the dihedral angle between the two planar ring systems is 68.06 (10)°. A short Cl⋯O contact of 2.914 (2) Šexists in the crystal structure.

Tracing Geographical Origins of Teas Based on FT-NIR Spectroscopy: Introduction of Model Updating and Imbalanced Data Handling Approaches.

This work presents a reliable approach to trace teas' geographical origins despite changes in teas caused by different harvest years. A total of 1447 tea samples collected from various areas in 2014 (660 samples) and 2015 (787 samples) were detected by FT-NIR. Seven classifiers trained on the 2014 dataset all succeeded to trace origins of samples collected in 2014; however, they all failed to predict origins for the 2015 samples due to different data distributions and imbalanced dataset. Three outlier detection based undersampling approaches-one-class SVM (OC-SVM), isolation forest and elliptic envelope-were then proposed; as a result, the highest macro average recall (MAR) for the 2015 dataset was improved from 56.86% to 73.95% (by SVM). A model updating approach was also applied, and the prediction MAR was significantly improved with increase in the updating rate. The best MAR (90.31%) was first achieved by the OC-SVM combined SVM classifier at a 50% rate.

Methyl 6-bromo-7-meth-oxy-1,3-benzodioxole-5-carboxyl-ate.

The non-H atoms of the title compound, C(10)H(9)BrO(5), are essentially coplanar, with the exception of the ester group [the O=C-O-C torsion angle is -143.4 (3)°].