Femtomolar endogenous adenosine triphosphate-responded photoelectrochemical biosensor based on Au@Cu2O core-shell nanocubes for the ultrasensitive determination of Escherichia coli O157:H7 in foods.

Sensitive and precise determination of virulent foodborne pathogens is significant for food safety. Herein, an ultrasensitive photoelectrochemical (PEC) bioanalysis was developed using the endogenous adenosine triphosphate (ATP)-responded Au@Cu2O core-shell nanocubes (Au@Cu2O NCs) to measure Escherichia coli O157: H7 (E. coli O157:H7) in food. Briefly, the phage-functionalized gold wire was used to specifically recognize the target pathogen. With the bacteriolysis of lysozyme, the endogenous ATP molecules were emitted from the captured target bacteria and enriched by another ATP aptamer-modified gold wire. Following the exchange with complementary DNA (cDNA) chains, the bonded ATP would be released. It could simultaneously etch the Au@Cu2O NCs and compete with external circuit electrons to combine photogenerated holes on the Au@Cu2O NCs-modified screen-printed electrode. With the synergy of the two signal amplification mechanisms, a significant attenuation of photocurrent signal appeared even with femtomolar ATP. Therefore, the purpose of ultrasensitive determination of E. coli O157:H7 was realized, which depended on the endogenous ATP rather than exogenous signal probes. The proposed biosensor presented a good analysis performance within 10-106 CFU/mL with a detection limit of 5 CFU/mL. Besides, its specificity, repeatability, and stability were also investigated and acceptable. The detection results for food samples matched well with the results detected by the plate counting method. This work gives an innovative and sensitive signal amplification strategy for PEC bioassays in foodborne pathogens detection.

Constructing a cellulose based chiral liquid crystal film with high flexibility, water resistance, and optical property.

Cellulose nanocrystal (CNC) derived from cellulose can form a liquid crystal film with bright structural color by evaporative-induced self-assembly (EISA). As a new class of photonic liquid crystals material, it has attracted much attention because of its intrinsic unique structural characteristics and excellent optical properties. However, the brittleness and water sensitivity of CNC film have hindered its practical application. Herein, multiple cross-linked networks CNC/(polyethylene glycol diacrylate:polyethylene oxide) (PEGDA:PEO) composite film was prepared through EISA and UV irradiation strategies. The as-prepared film exhibits high-flexibility with a fracture strain of up to 36.40 % and strong water resistance, with water absorption at an equilibrium of only 17.41 %. Moreover, the film retains its structural color in aqueous solution for a long time due to its water stability. The outstanding flexibility and water resistance of CNC composite film are attributed to multiple crosslinked networks (i.e. PEGDA, PEO, and PEDGA-PEO networks), which endow the film with excellent stress dispersion and transferability when stretched and limit film swelling in water without affecting chiral nematic structures of CNC. Overall, this work provides a promising strategy to prepare CNC-based film with high-flexibility, water resistance, and optical property for applications like decoration, sensor, and anti-counterfeiting.

Ultrasensitive and Specific Phage@DNAzyme Probe-Triggered Fluorescent Click Chemistry for On-Site Detection of Foodborne Pathogens Using a Smartphone.

Rapid, specific, and on-site detection of virulent foodborne pathogenic strains plays a key role in controlling food safety. In this work, an ultrasensitive and specific Phage@DNAzyme signal probe was designed to detect foodborne pathogens. The proposed sensing probe was composed of the selected phage and functionalized DNAzyme, which realized the specific recognition of target foodborne pathogens at the strain level and the efficient catalysis of copper(II) based azide-alkyne cycloaddition (CuAAC) click reaction with fluorescent signal, respectively. As a proof of concept, the virulent Escherichia coli O157:H7 (E. coli O157:H7) as the representative analyte was first enriched and purified from the complex food samples by a 4-mercaptophenylboronic acid-modified gold slide. Following, the Phage@DNAzyme probes were specifically combined with the captured E. coli O157: H7 and catalyzed the click reaction between 3-azido-7-hydroxycoumarin and 3-butyn-1-ol with the assistance of Cu(II) to generate a visual fluorescent signal. Finally, the corresponding fluorescent signals were measured by a smartphone to quantify the target concentrations. Under optimized conditions, the bioassay exhibited a wide linear range from 102 to 108 CFU/mL and the detection limit was 50 CFU/mL (S/N = 3). It was further extended to the detection of another foodborne pathogen Salmonella typhimurium with satisfying sensing performances. This work gives a new path for developing rapid, specific, and on-site detection methods for trace levels of pathogenic strains in foods.

Summertime carbonyl compounds in an urban area in the North China Plain: Identification of sources, key precursors and their contribution to O3 formation.

Carbonyl compounds are critical components of volatile organic compounds, which significantly participate in the photochemical formation of atmospheric ozone and thus threaten human health. Here we measured 15 C1-C8 carbonyl compounds at an urban site in Linyi, a typically industrialised city in the North China Plain (NCP). Formaldehyde (3.89 ppbv), acetaldehyde (1.66 ppbv) and acetone (2.03 ppbv) were found to be the top three carbonyl compounds, accounting for 76.11% of the total concentration of carbonyl compounds. Anthropogenic secondary formation was recognised as the main source of the top five carbonyl compounds, which included formaldehyde, acetaldehyde, acetone, butyraldehyde and benzaldehyde, and accounted for 46-54% of all sources. Alkenes were the most important precursors of formaldehyde and acetaldehyde, suggesting that reducing the emission of alkenes from anthropogenic sources is an effective way to control carbonyl compound pollution in Linyi. Furthermore, the photolysis of carbonyl compounds played a significant role (68-75%) as sources of HO2• and RO2• and thus made a significant contribution (14.6%) to the photochemical formation of O3. This study highlights the importance of anthropogenic secondary formation as a source of carbonyl compounds and provides a scientific basis for O3 pollution control in carbonyl compound-enriched cities in the NCP.

Adams-based hierarchical features fusion network for image dehazing.

Recent developments in Convolutional Neural Networks (CNNs) have made them one of the most powerful image dehazing methods. In particular, the Residual Networks (ResNets), which can avoid the vanishing gradient problem effectively, are widely deployed. To understand the success of ResNets, recent mathematical analysis of ResNets reveals that a ResNet has a similar formulation as the Euler method in solving the Ordinary Differential Equations (ODE's). Hence, image dehazing which can be formulated as an optimal control problem in dynamical systems can be solved by a single-step optimal control method, such as the Euler method. This optimal control viewpoint provides a new perspective to address the problem of image restoration. Motivated by the advantages of multi-step optimal control solvers in ODE's, which include better stability and efficiency than single-step solvers, e.g. Euler, we propose the Adams-based Hierarchical Feature Fusion Network (AHFFN) for image dehazing with modules inspired by a multi-step optimal control method named the Adams-Bashforth method. Firstly, we extend a multi-step Adams-Bashforth method to the corresponding Adams block, which achieves a higher accuracy than that of single-step solvers because of its more effective use of intermediate results. Then, we stack multiple Adams blocks to mimic the discrete approximation process of an optimal control in a dynamical system. To improve the results, the hierarchical features from stacked Adams blocks are fully used by combining Hierarchical Feature Fusion (HFF) and Lightweight Spatial Attention (LSA) with Adams blocks to form a new Adams module. Finally, we not only use HFF and LSA to fuse features, but also highlight important spatial information in each Adams module for estimating the clear image. The experimental results using synthetic and real images demonstrate that the proposed AHFFN obtains better accuracy and visual results than that of state-of-the-art methods.

Metabolomics and proteomics reveal the toxicological mechanisms of florfenicol stress on wheat (Triticum aestivum L.) seedlings.

Although the ecological impacts of antibiotics have received attention worldwide, research on the toxicity of florfenicol is still limited. We conducted a metabolomic and proteomic study on wheat (Triticum aestivum L.) seedlings to reveal the toxicological mechanism of florfenicol. The growth of the wheat seedlings was found to be inhibited by florfenicol. Antioxidant enzyme activities (superoxide dismutase, peroxidase and catalase), malondialdehyde content and membrane permeability increased with increasing florfenicol concentration. The contents of chlorophyll and chlorophyll synthesis precursor substances (Proto IX, Mg-proto IX and Pchlide), photosynthetic and respiration rates, and chlorophyll fluorescence parameters decreased, indicating that photosynthesis was inhibited. The ultrastructure of chloroplasts was destroyed, as evidenced by the blurred membrane surface, irregular grana arrangement, irregular thylakoid lamella structure, and increased plastoglobuli number. Proteome analysis revealed that up-regulated proteins were highly involved in protein refolding, translation, oxidation-reduction, tricarboxylic acid cycle (TCA cycle), reactive oxygen species metabolic process, cellular oxidant detoxification, and response to oxidative stress. The down-regulated proteins were mainly enriched in photosynthesis-related pathways. In the metabolome analysis, the content of most of the metabolites in wheat leaves, such as carbohydrates and amino acids increased significantly (p < 0.05). Combined pathway analysis showed that florfenicol stress stimulated the TCA cycle pathway and downregulated the photosynthesis pathway.

Metabolomic analysis reveals the impact of ketoprofen on carbon and nitrogen metabolism in rice (Oryza sativa L.) seedling leaves.

Pharmacologically active compounds (PACs) are becoming common pollutants in the natural environment, posing potential risks to crop quality; however, the toxic effects and metabolic changes that they cause in agricultural plants remain unclear. Here, we investigated the effects of ketoprofen on respiration rate, ATP synthesis, carbon and nitrogen metabolism, and metabolomics in rice seedling leaves. The results showed that ketoprofen treatment adversely affected the respiration rate, ATP content, H+-ATPase activity and induced changes in the contents of carbon assimilation products (soluble sugar, reducing sugar, sucrose, and starch) and the activities of key enzymes in carbon metabolism (sucrose synthase (SS), sucrose phosphate synthase (SPS), and sucrose invertase (InV)). The contents of nitrate, ammonium, and free amino acids, and the activities of key enzymes involved in nitrogen metabolism (nitrate reductase (NR), nitrite reductase (NiR), glutamine synthetase (GS), glutamate synthase (GOGAT), and glutamate dehydrogenase (GDH)) were also affected in a concentration-dependent manner. Metabolomics analysis showed that ketoprofen disturbed the type and content of metabolites (amino acids, carbohydrates, and secondary metabolites) to varying degrees and perturbed key metabolic pathways (substance synthesis and energy metabolism), ultimately resulting in the reduction of rice seedling biomass. This study provides important information and a useful reference for the accurate assessment of the environmental risks of PACs.

Mining, identification and function analysis of microRNAs and target genes in peanut (Arachis hypogaea L.).

In the present investigation, a total of 60 conserved peanut (Arachis hypogaea L.) microRNA (miRNA) sequences, belonging to 16 families, were identified using bioinformatics methods. There were 392 target gene sequences, identified from 58 miRNAs with Target-align software and BLASTx analyses. Gene Ontology (GO) functional analysis suggested that these target genes were involved in mediating peanut growth and development, signal transduction and stress resistance. There were 55 miRNA sequences, verified employing a poly (A) tailing test, with a success rate of up to 91.67%. Twenty peanut target gene sequences were randomly selected, and the 5' rapid amplification of the cDNA ends (5'-RACE) method were used to validate the cleavage sites of these target genes. Of these, 14 (70%) peanut miRNA targets were verified by means of gel electrophoresis, cloning and sequencing. Furthermore, functional analysis and homologous sequence retrieval were conducted for target gene sequences, and 26 target genes were chosen as the objects for stress resistance experimental study. Real-time fluorescence quantitative PCR (qRT-PCR) technology was applied to measure the expression level of resistance-associated miRNAs and their target genes in peanut exposed to Aspergillus flavus (A. flavus) infection and drought stress, respectively. In consequence, 5 groups of miRNAs & targets were found accorded with the mode of miRNA negatively controlling the expression of target genes. This study, preliminarily determined the biological functions of some resistance-associated miRNAs and their target genes in peanut.