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.

Domestication, breeding, omics research, and important genes of Zizania latifolia and Zizania palustris.

Wild rice (Zizania spp.), an aquatic grass belonging to the subfamily Gramineae, has a high economic value. Zizania provides food (such as grains and vegetables), a habitat for wild animals, and paper-making pulps, possesses certain medicinal values, and helps control water eutrophication. Zizania is an ideal resource for expanding and enriching a rice breeding gene bank to naturally preserve valuable characteristics lost during domestication. With the Z. latifolia and Z. palustris genomes completely sequenced, fundamental achievements have been made toward understanding the origin and domestication, as well as the genetic basis of important agronomic traits of this genus, substantially accelerating the domestication of this wild plant. The present review summarizes the research results on the edible history, economic value, domestication, breeding, omics research, and important genes of Z. latifolia and Z. palustris over the past decades. These findings broaden the collective understanding of Zizania domestication and breeding, furthering human domestication, improvement, and long-term sustainability of wild plant cultivation.

Characterization and transcriptomic analysis of a native fungal pathogen against the rice pest Nilaparvata lugens.

The brown planthopper (BPH), Nilaparvata lugens, is one of the most destructive pests of rice. Given the threats posed by insecticide resistance to its control, eco-friendly strategies based on microbial pathogens emerged as a promising biocontrol alternative. In the present study, we isolated a native fungal pathogen against BPH from infected BPH cadavers and preliminarily identified as a strain of Aspergillus fumigatus based on morphological and molecular methods. Laboratory bioassay revealed that this fungal strain was highly virulent to BPH both at nymphal and adult stages, with the median lethal times (LT50) of 7.5 and 5.8 days under high conidial concentration of 1 × 109 conidia mL-1. A genome-wide view of gene expressions in BPH against fungal attack was analyzed by transcriptomic sequencing and consequently a large number of differentially expressed genes that mainly involved in host immune defense and cell detoxification were found. RNAi-mediated knockdown of an upregulated gene encoding a serine protease (NlSPN) could cause a significant decrease in BPH survival. Combination of dsRNA injection and fungal infection showed an additive effect on BPH mortality, which provided clues to develop new pest management strategies against BPH.

Overview of the preparation method, structure and function, and application of natural peptides and polypeptides.

Natural polypeptides, a kind of molecular polymer with obvious biological activity, are widely existing in nature. They participate in various physiological activities of living organisms and play an important role in promoting human health. They are also widely applied in medicine, food, and cosmetic industries. By searching literature from Pubmed, Google Scholar, Web of Science, Springer Link and Elsevier, this work presents an overview of the preparation methods, the relationship between structure and function, and the application of natural polypeptides. The preparation methods mainly include solvent extraction, enzymatic decomposition, microbiological fermentation, chemical synthesis, genetic engineering recombination, and using cell free system. Natural polypeptide's physiological function mainly includes antioxidative, antibacterial, antihypertensive. This review could provide scientific basis for the research and development of natural polypeptide.

A reverse transcription-cross-priming amplification method with lateral flow dipstick assay for the rapid detection of Bean pod mottle virus.

Bean pod mottle virus (BPMV) is a destructive virus that causes serious economic losses in many countries every year, highlighting the importance of its effective detection. In this study, we developed a fast reverse transcription-cross-priming amplification (RT-CPA) coupled with lateral flow dipstick (LFD) diagnostic method for BPMV detection. The RT-CPA-LFD assay that targets the coat protein gene of BPMV was highly specific against diagnosing four other common viruses transmitted by soybean seeds, i.e., Southern bean mosaic virus (SBMV), Tomato ringspot virus (ToRSV), Arabis mosaic virus (ArMV), and Tobacco ringspot virus (TRSV). The sensitivities of the real-time fluorescent RT-CPA and the RT-CPA-LFD assay were at least 50 pg/µl and 500 pg/µl, respectively. Despite a compromise in the limit of detection of the RT-CPA method compared with TaqMan-MGB real-time RT-PCR, our results demonstrated a notably better performance in the detection of field samples of BPMV-infested soybean seeds. With the advantages of efficiency and convenience by visual determination, the RT-CPA-LFD assay presents a potential application for the rapid and accurate detection of BPMV in routine tests.

Trade-off between defense priming by herbivore-induced plant volatiles and constitutive defense in tomato.

BACKGROUND: Herbivore-induced plant volatiles (HIPVs) can prime plant defenses and enhance herbivore resistance in neighboring plants. Although a trade-off between constitutive defense and HIPV emission has been documented in many plant species, little is known about the effect of HIPV variation on defense priming, and whether there is a trade-off between defense priming and constitutive defense in neighboring plants. RESULTS: Using three tomato genotypes, including two wild types [Moneymaker (MM) and Castlemart (CM)] and one jasmonic acid (JA) overexpression 35S::prosys genotype, we investigated the effects of exposure to volatiles from plants infested by beet armyworm (Spodoptera exigua) caterpillars on the defenses and resistance of conspecific neighboring plants. We also analyzed the HIPV emissions from the three genotypes and their constitutive defense and resistance. Exposure to volatiles from S. exigua-infested MM plants primed an array of defensive responses (including the accumulation of JA and PI-II protein and the expression of the defense genes PI-I and PI-II), and enhanced plant resistance against the caterpillars. In contrast, exposure to volatiles from S. exigua-infested CM or 35S::prosys did not result in defense priming or an increase in plant resistance. Analyses of HIPVs and gene expression indicated that defense priming in MM was due to enhanced emission of ß-ocimene and linalool. We further demonstrated that levels of constitutive defense and resistance are low in MM and high in CM and 35S::prosys, suggesting a negative correlation between defense priming and constitutive defense. CONCLUSION: Our findings suggest that there is a trade-off between defense priming by HIPVs and constitutive defense in tomato. This suggests that defense priming should be used with caution in agriculture. © 2020 Society of Chemical Industry.

Potential Drug Targets Against Hepatitis B Virus Based on Both Virus and Host Factors.

BACKGROUND: Hepatitis B is a very harmful and epidemic disease caused by hepatitis B virus (HBV). Although an effective anti-HBV vaccine is available, chronic infection poses still a huge health burden in the whole world. The present anti-HBV drugs including nucleoside analogues and interferonalpha have their limitations without exception. There is no effective drug and therapeutic method that can really and truly cure hepatitis B so far. The variability of HBV genome results in that a significant number of patients develop drug resistance during the long-term use of anti-HBV drugs. Hence, it is urgently needed to discover novel targets and develop new drugs against hepatitis B. OBJECTIVE: The review aims to provide the theory support for designing of the anti-HBV innovative drugs by offering a summary of the current situation of antiviral potential targets. RESULTS AND CONCLUSION: Since HBV is obligate intracellular parasite, and as such it depends on host cellular components and functions to replicate itself. The targeting both virus and host might be a novel therapeutic option for hepatitis B. Accordingly, we analyse the advances in the study of the potential drug targets for anti-HBV infection, focusing on targeting virus genome, on targeting host cellular functions and on targeting virus-host proteins interactions, respectively. Meanwhile, the immune targets against chronic hepatitis B are also emphasized. In short, the review provides a summary of antiviral therapeutic strategies to target virus factors, host factors and immune factors for future designing of the innovative drug against HBV infection.

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.

Jasmonic Acid-Dependent Defenses Play a Key Role in Defending Tomato Against Bemisia tabaci Nymphs, but Not Adults.

The silverleaf whitefly Bemisia tabaci is an important and invasive crop pest in many countries. Previous laboratory studies with Arabidopsis demonstrated that B. tabaci can suppress jasmonic acid (JA) defenses and thereby enhance B. tabaci performance. Whether B. tabaci can suppress JA-regulated host plant defenses in field is unknown. In the present study, we found that, relative to wild-type (WT) tomato plants, transgenic tomato mutants that activated JA defenses (35s::prosys) or impaired JA defenses (spr-2 and def-1) did not affect the survival or reproduction of B. tabaci adults in growth chamber experiments. In contrast, tomato mutants that activated JA defenses slowed B. tabaci nymphal development, while mutants that impaired JA defenses accelerated nymphal development. These effects of JA defenses on nymphal development were also documented under semi-field conditions. Changes in the expression of defense genes and in the production of phytohormones indicated that B. tabaci adults can suppress JA-dependent defenses after infestation for >72 h. The suppression of JA was correlated with the induction of salicylic acid (SA) in B. tabaci-infested leaves under laboratory and under semi-field conditions. If SA signaling was blocked, JA accumulation increased in infested leaves and B. tabaci nymphal development was delayed. These results indicate that, although JA signaling helps in mediating tomato responses against B. tabaci nymphs, B. tabaci can inhibit JA biosynthesis and its action in an SA-dependent manner.

Structure Properties and Mechanisms of Action of Naturally Originated Phenolic Acids and Their Derivatives against Human Viral Infections.

BACKGROUND: A great effort has been made to develop efficacious antiviral drugs, but many viral infections are still lack of efficient antiviral therapies so far. The related exploration of natural products to fight viruses has been raised in recent years. Natural compounds with structural diversity and complexity offer a great chance to find new antiviral agents. Particularly, phenolic acids have attracted considerable attention owing to their potent antiviral abilities and unique mechanisms. The aim of this review is to report new discoveries and updates pertaining to antiviral phenolic acids. METHODS: The relevant references on natural phenolic acids were searched. The antiviral phenolic acids were classified according to their structural properties and antiviral types. Meanwhile, the antiviral characteristics and structure-activity relationships of phenolic acids and their derivatives were summarized. RESULTS: The review finds that natural phenolic acids and their derivatives possessed potent inhibitory effects on multiple virus in humans such as human immunodeficiency virus, hepatitis C virus, hepatitis B virus, herpes simplex virus, influenza virus and respiratory syncytial virus. In particular, caffeic acid/gallic acid and their derivatives exhibited outstanding antiviral properties by a variety of modes of action. CONCLUSION: Naturally derived phenolic acids especially caffeic acid/gallic acid and their derivatives may be regarded as novel promising antiviral leads or candidates. Additionally, scarcely any of these compounds has been used as antiviral treatment in clinical practice. Therefore, these phenolic acids with diverse skeletons and mechanisms provide us an excellent resource for finding novel antiviral drugs.

Stable Isotope Ratio and Elemental Profile Combined with Support Vector Machine for Provenance Discrimination of Oolong Tea (Wuyi-Rock Tea).

This paper focused on an effective method to discriminate the geographical origin of Wuyi-Rock tea by the stable isotope ratio (SIR) and metallic element profiling (MEP) combined with support vector machine (SVM) analysis. Wuyi-Rock tea (n = 99) collected from nine producing areas and non-Wuyi-Rock tea (n = 33) from eleven nonproducing areas were analysed for SIR and MEP by established methods. The SVM model based on coupled data produced the best prediction accuracy (0.9773). This prediction shows that instrumental methods combined with a classification model can provide an effective and stable tool for provenance discrimination. Moreover, every feature variable in stable isotope and metallic element data was ranked by its contribution to the model. The results show that δ2H, δ18O, Cs, Cu, Ca, and Rb contents are significant indications for provenance discrimination and not all of the metallic elements improve the prediction accuracy of the SVM model.

Rapid discrimination of the geographical origins of an oolong tea (anxi-tieguanyin) by near-infrared spectroscopy and partial least squares discriminant analysis.

This paper focuses on a rapid and nondestructive way to discriminate the geographical origin of Anxi-Tieguanyin tea by near-infrared (NIR) spectroscopy and chemometrics. 450 representative samples were collected from Anxi County, the original producing area of Tieguanyin tea, and another 120 Tieguanyin samples with similar appearance were collected from unprotected producing areas in China. All these samples were measured by NIR. The Stahel-Donoho estimates (SDE) outlyingness diagnosis was used to remove the outliers. Partial least squares discriminant analysis (PLSDA) was performed to develop a classification model and predict the authenticity of unknown objects. To improve the sensitivity and specificity of classification, the raw data was preprocessed to reduce unwanted spectral variations by standard normal variate (SNV) transformation, taking second-order derivatives (D2) spectra, and smoothing. As the best model, the sensitivity and specificity reached 0.931 and 1.000 with SNV spectra. Combination of NIR spectrometry and statistical model selection can provide an effective and rapid method to discriminate the geographical producing area of Anxi-Tieguanyin.

Combining electronic tongue array and chemometrics for discriminating the specific geographical origins of green tea.

The feasibility of electronic tongue and multivariate analysis was investigated for discriminating the specific geographical origins of a Chinese green tea with Protected Designation of Origin (PDO). 155 Longjing tea samples from three subareas were collected and analyzed by an electronic tongue array of 7 sensors. To remove the influence of abnormal measurements and samples, robust principal component analysis (ROBPCA) was used to detect outliers in each class. Partial least squares discriminant analysis (PLSDA) was then used to develop a classification model. The prediction sensitivity/specificity of PLSDA was 1.000/1.000, 1.000/0.967, and 0.950/1.000 for longjing from Xihu, Qiantang, and Yuezhou, respectively. Electronic tongue and chemometrics can provide a rapid and reliable tool for discriminating the specific producing areas of Longjing.

Rapid analysis of adulterations in Chinese lotus root powder (LRP) by near-infrared (NIR) spectroscopy coupled with chemometric class modeling techniques.

This paper develops a rapid analysis method for adulteration identification of a popular traditional Chinese food, lotus root powder (LRP), by near-infrared spectroscopy and chemometrics. 85 pure LRP samples were collected from 7 main lotus producing areas of China to include most if not all of the significant variations likely to be encountered in unknown authentic materials. To evaluate the model specificity, 80 adulterated LRP samples prepared by blending pure LRP with different levels of four cheaper and commonly used starches were measured and predicted. For multivariate quality models, two class modeling methods, the traditional soft independent modeling of class analogy (SIMCA) and a recently proposed partial least squares class model (PLSCM) were used. Different data preprocessing techniques, including smoothing, taking derivative and standard normal variate (SNV) transformation were used to improve the classification performance. The results indicate that smoothing, taking second-order derivatives and SNV can improve the class models by enhancing signal-to-noise ratio, reducing baseline and background shifts. The most accurate and stable models were obtained with SNV spectra for both SIMCA (sensitivity 0.909 and specificity 0.938) and PLSCM (sensitivity 0.909 and specificity 0.925). Moreover, both SIMCA and PLSCM could detect LRP samples mixed with 5% (w/w) or more other cheaper starches, including cassava, sweet potato, potato and maize starches. Although it is difficult to perform an exhaustive collection of all pure LRP samples and possible adulterations, NIR spectrometry combined with class modeling techniques provides a reliable and effective method to detect most of the current LRP adulterations in Chinese market.

Combining local wavelength information and ensemble learning to enhance the specificity of class modeling techniques: Identification of food geographical origins and adulteration.

Class modeling techniques are required to tackle various one-class problems. Because the training of class models is based on the target class and the origins of future test objects usually cannot be exactly predefined, the criteria for feature selection of class models are not very straightforward. Although feature reduction can be expected to improve class models performance, more features retained can provide a sufficient description of the sought-for class. This paper suggests a strategy to balance class description and model specificity by ensemble learning of sub-models based on separate local wavelength intervals. The acceptance or rejection of a future object can be explicitly determined by examining its acceptance frequency by sub-models. Considering the lack of information about sub-model independence, we propose to use a data-driven method to control the sensitivity of the ensemble model by cross validation. In this way, all the wavelength intervals are used for class description and the local wavelength intervals are highlighted to enhance the ability to detect out-of-class objects. The proposed strategy was performed on one-class partial least squares (OCPLS) and soft independent modeling of class analogy (SIMCA). By analysis of two infrared spectral data sets, one for geographical origin identification of white tea and the other for discrimination of adulterations in pure sesame oil, the proposed ensemble class modeling method was demonstrated to have similar sensitivity and better specificity compared with total-spectrum SIMCA and OCPLS models. The results indicate local spectral information can be extracted to enhance class model specificity.

Automatic and rapid discrimination of cotton genotypes by near infrared spectroscopy and chemometrics.

This paper reports the application of near infrared (NIR) spectroscopy and pattern recognition methods to rapid and automatic discrimination of the genotypes (parent, transgenic, and parent-transgenic hybrid) of cotton plants. Diffuse reflectance NIR spectra of representative cotton seeds (n = 120) and leaves (n = 123) were measured in the range of 4000-12000 cm(-1). A practical problem when developing classification models is the degradation and even breakdown of models caused by outliers. Considering the high-dimensional nature and uncertainty of potential spectral outliers, robust principal component analysis (rPCA) was applied to each separate sample group to detect and exclude outliers. The influence of different data preprocessing methods on model prediction performance was also investigated. The results demonstrate that rPCA can effectively detect outliers and maintain the efficiency of discriminant analysis. Moreover, the classification accuracy can be significantly improved by second-order derivative and standard normal variate (SNV). The best partial least squares discriminant analysis (PLSDA) models obtained total classification accuracy of 100% and 97.6% for seeds and leaves, respectively.

Analysis of the genetic relationships from different genetic systems between the amylose content and the appearance quality of indica rice across environments

The genetic relationships between amylose content (AC) and appearance quality traits of indica rice (Oryza sativa L.) were investigated using conditional analysis and unconditional analysis in present experiment. The results from the unconditional analysis indicated that AC of rice positively correlated with brown rice (BR, i.e., dehulled but unmilled rice) length (BRL), width (BRW) and thickness (BRT), but was negatively correlated with the ratio of length to width (RLW). The conditional analysis showed that weight of brown rice (WBR) negatively affected the genetic relationships between AC and the appearance quality traits of rice except between AC and BRW, while the genetic relationships between AC and most appearance quality traits were negatively affected by protein content (PC). However, these influences were not apparent due to the impact of WBR or PC on the most covariance components of the different genetic systems between AC and the appearance quality traits. The conditional analysis showed that it was possible to improve AC while significantly reduce BRL and BRT under maintaining WBR. Furthermore, AC could be improved when BRL was reduced under maintaining PC, but BRW and BRT could be significantly increased.

Analysis of the phylogenetic relationships among several species of Gramineae using ACGM markers.

To study the transferability of rice (Oryza sativa L.) genome data, we used amplified consensus genetic markers to analyze the phylogenetic relationships among several species and genera in Gramineae. Ten accessions representing five grass genera (Oryza, Zea, Setaria, Triticum, and Phyllostachys) were used. According to the genetic distances, a cluster tree was constructed. The relationships among the five genera could be simply described as ((Oryza + (Zea +Setaria)) +Triticum) +Phyllostachys. The results suggest that the genetic distance between rice and maize (Z. mays L.) or rice and millet (Setaria italica L.) is closer than that between rice and wheat (Triticum aestivum L) or rice and bamboo.

Genetic analysis for F1 yield traits with conditional approach in island cotton (Gossypium barbadense L.).

A genetic model with additive, dominance and genotype x environment interaction effect was employed to analyze the 3-year data of F(1) hybrids from 5 x 4 diallel cross, whose parents were Island cotton and had different fruit branch types. Unconditional and conditional genetic variances were conducted for analyze genetic impacts of yield components on yield. Results of unconditional genetic variances showed that there were no additive variance of total lint yield. But conditional additive effects of total lint yield, when excluding the phenotype of boll weight, boll number at prefrost, boll number at postfrost, and lint yield at prefrost, indicated that improving the additive effects of the total lint yield was still possible. Crossing and selecting component traits with high contributive additive effects could obtain good offsprings. Yield components contributed large dominance effects to the heterosis of lint yield at prefrost and total lint yield in crosses. Yield component traits were controlled with each other. The traits having positive contributive effects could be applied to further improve target traits.