Research on the Application of Molecular Image Processing in Rice Quality Inspection.

Objective: With the improvement of living standards, consumers are paying more and more attention to the quality of rice. Traditional rice quality detection relies on human sensory judgment, which is inaccurate and inefficient. With the continuous development of molecular imaging technology, more and more scholars at home and abroad have begun to pay attention to its application in the nondestructive testing of agricultural products. Molecular imaging technology combines the advantages of spectral technology and image technology, which can achieve rapid, nondestructive and accurate detection of rice quality. In this paper, taking rice as the research object, we carried out nondestructive detection research on rice varieties, moisture and starch content using molecular imaging technology. We proposed a rapid detection method based on molecular imaging technology for rice variety identification, moisture content and starch content. Molecular images of the rice samples from four origins were obtained using a molecular imaging system, the regions of interest of the rice were identified and, spectral data, textural features and morphological features of the rice were extracted. Spectral, textural and morphological features were selected by principal component analysis (PCA), and nine feature wavelengths were obtained and an optimal model was established with an accuracy of 91.67%, which demonstrated the feasibility of molecular imaging. By comparing the models, the BCC-LS-SVR model based on the RB function had the highest accuracy with R2 of 0.989, RMSEP of 0.767%, R2 of 0.985, and RMSEC of 0.591%. Moreover, starchy rice was detected using molecular imaging. The PCA-SVR model based on the RBF kernel function had the highest accuracy with R2 of 0.989, RMSEC of 0.445%, R2 of 0.991, and RMSEP of 0.669%. Our models demonstrated high accuracy in identifying rice varieties, as well as quantifying moisture and starch content, showcasing the feasibility of molecular imaging technology in rice quality assessment. This research offers a rapid, nondestructive, and accurate method for rice quality assessment, promising significant benefits for agricultural producers and consumers.

A smartphone sensing platform for the sensitive and selective detection of clothianidin based on MIP-functionalized lanthanide MOF.

A novel molecularly imprinted nanomaterial (Eu (BTC)-MPS@MIP) was synthesized on the surface of silanized europium-based metal-organic frameworks (Eu (BTC)-MPS) using 1, 3, 5-benzotrioic acid (H3BTC) as a ligand. The resulting Eu (BTC)-MPS@MIP was applied to constructing a smartphone sensing platform for the sensitive and selective detection of clothianidin (CLT) in vegetables. The synthesized Eu (BTC)-MPS@MIP demonstrated the successful formation of a typical core-shell structure featuring a shell thickness of approximately 70 - 80 nm. The developed sensing platform based on Eu (BTC)-MPS@MIP exhibited sensitivity in CLT detection with a detection limit of 4 µg/L and a linear response in the range 0.01 - 10 mg/L at excitation and emission wavelengths of 365 nm and 617 nm, respectively. The fluorescence sensing platform displayed excellent specificity for CLT detection, as evidenced by a high imprinting factor of 3.1. This specificity is primarily attributed to the recognition sites in the molecularly imprinted polymer (MIP) layer. When applied to spiked vegetable samples, the recovery of CLT ranged from 78.9 to 102.0%, with relative standard deviation (RSD) values falling between 2.2 and 6.2%. The quenching mechanism of Eu (BTC)-MPS@MIP toward CLT can be attributed to the inner filter effect (IFE), resulting from the optimal spectral overlap between the absorption spectrum of CLT and the excitation spectra of Eu (BTC)-MPS@MIP. The proposed method has the potential for extension to the detection of other pesticides by replacing the MIP recognition probes.

Microbiota Profiles of Hen Eggs from the Different Seasons and Different Sectors of Shanghai, China.

Hen eggs are one of the most popular foods worldwide, and their safety is critical. Employing 16S rRNA full-length sequencing is an effective way to identify microorganisms on or in eggs. Here, hen eggs collected from poultry farms over four seasons, as well as from markets in Shanghai, were analyzed with third-generation sequencing. Firmicutes (44.46%) and Proteobacteria (35.78%) were the two dominant phyla, and Staphylococcus, Acinetobacter, Aerococcus, Psychrobacter, and Lactobacillus were the dominant genera. The dominant genera on the eggshell surfaces from the farms varied with the seasons, and the highest contamination of Staphylococcus (32.93%) was seen in the eggs collected during the summer. For the market samples, Pseudomonas was the most abundant in content, with Staphylococcus being the most-often genera found on the eggshell surfaces. Moreover, several potential pathogenic bacteria including Riemerella anatipestifer (species), Klebsiella (genus), and Escherichia/shigella (genus) were detected in the samples. The results revealed the impacts of weather on the microbiota deposited on an eggshell's surface, as well as the impacts due to the differences between the contents and the surface. The results can help disinfect eggs and guide antibiotic selection.

Improving English language skills through learning Mathematic contents: From the expertise reversal effect perspective.

BACKGROUND: Previous research in the field of content and language integrated learning (CLIL) has not yet comprehensively investigated the interaction between learners' expertise and the instructional effectiveness. AIMS: Taking cognitive load theory as the theoretical framework, a study was conducted to investigate the expertise reversal effect on learning English and mathematics simultaneously: whether an integrated approach (i.e. learning both English and mathematics simultaneously) could facilitate the acquisition of mathematic skills and English linguistic skills as a foreign language more effectively and efficiently than a separated learning approach (i.e. learning Mathematics and English separately). MATERIALS: The materials for the integrated learning approach were in English-only, and the materials for the separated learning approach were in English-and-Chinese. Both sets of materials were given as reading content for teaching mathematic skills and English as a foreign language. METHODS: The study adopted a 2 (language expertise: low vs. high) × 2 (instruction: integrated vs. separated) between-subject factorial design with instructional approaches and learners' expertise in English as independent variables, the learning performance in Mathematics and English with the cognitive load ratings as the dependent variables. Sixty-five Year-10 students with lower expertise in English and 56 Year-2 college students with higher expertise in English in China were recruited and allocated to two instructional conditions respectively. RESULTS: An expertise reversal effect was confirmed: the English and mathematics integrated learning approach was more effective for higher expertise learners while the English and mathematics separated learning condition was more beneficial for lower expertise learners.

A fast, sensitive, low-cost electrochemical paper-based chip for real-time simultaneous detection of cadmium (â ¡) and lead (â ¡) via aptamer.

A novel electrochemical paper-based microfluidic chip was firstly developed to simultaneously detect cadmium (Ⅱ) and lead (Ⅱ) in vegetable and fruit samples. The patterned filter paper was prepared through the printing of three-electrode patterns on filter paper using an automatic screen-printing machine. Portable and low-cost (less than $1) electrochemical paper-based chips are prepared by filling conductive ink and hot pressing. The paper-based chip could realize signal amplification through gold nanoparticles and seed solutions. Cadmium (Ⅱ) and lead (Ⅱ) were sensitively detected by their aptamers labeled with methylene blue and ferrocene, separately. Under the optimal experimental parameters, the paper-based chip detected cadmium (Ⅱ) and lead (Ⅱ) as low as 23.31 and 46.23 pmol/L (3σ) with a wide linear range from 0.1 to 1000 nmol/L and exhibited excellent selectivity. The RSD was 6.41% (cadmium (Ⅱ)) and 4.20% (lead (Ⅱ)). Compared with other methods, the paper-based chip could complete the detection within 15 min and could be stored at -20 °C for 5 days. Furthermore, the results for vegetable and fruit samples were agreed with the results of the graphite furnace atomic absorption spectrophotometer, in which the recovery rates were 93.20%-95.80%.

Inhibition of CRISPR-Cas12a trans-cleavage by lead (II)-induced G-quadruplex and its analytical application.

In this work, the inhibition of clustered regularly interspaced short palindromic repeats (CRISPR) - CRISPR associated protein (Cas) trans-cleavage by Pb2+-induced G-quadruplex has been firstly explored to detect Pb2+ in tea beverage and milk. In absence of Pb2+, the Na+-induced G-quadruplex can be cleaved by CRISPR-Cas12a. In contrast, Pb2+ can competitively combine with G-quadruplex, resulting in its conformational changes and resistance to trans-cleavage of CRISPR-Cas12a. Therefore, the fluorescence resonance energy transfer can happen. Pb2+ can be detected in a linear range from 100 nM to 5 µM with a lowest detection limit of 2.6 nM and a relative standard deviation of 4.32%. In summary, this work not only provides a new method for Pb2+ detection based on its induced G-quadruplex inhibition on CRISPR-Cas12a trans-cleavage, but also broadens the application of CRISPR-Cas system for heavy metal analysis in the field of food safety.