Owing to their rapid response, high sensitivity, low cost, ease of use, and suitability for miniaturization and integration, electrochemical sensors have found widespread application in clinical diagnostics, environmental monitoring, and food safety. However, achieving highly sensitive, stable detection of trace analytes in complex real-world samples while maintaining good selectivity remains a key challenge in this field. To address this issue, sensor performance can be effectively enhanced through precise electrode interface engineering, efficient signal amplification strategies, and integrated device design. This paper provides a systematic review of the latest advances in electrochemical sensors. Based on the type of signal output, the principles and characteristics of amperometric, impedance, and potentiometric sensors are introduced. The current status of electrode-modification materials and immobilization techniques is summarized, and various signal amplification methods and their applications for enhancing detection sensitivity are reviewed. Subsequently, miniaturization and integration technologies tailored for on-site analysis are outlined. Furthermore, typical applications in environmental monitoring, food safety, and biomedicine are summarized. Finally, the current challenges facing electrochemical sensors in terms of multifunctionality, long-term stability, and interference resistance are identified, and future research directions regarding standardization and commercialisation are outlined.

A novel cucumber pulp certified reference material (CRM) was prepared for the analysis of plant growth regulator residues, specifically chlormequat chloride (CCC) and 2,4-dichlorophenoxyacetic acid (2,4-D). The matrix CRM candidates were prepared by cucumber pulping, spiking, homogenizing and subpackaging. A reference method of liquid chromatography tandem isotope dilution mass spectrometry (ID-LC-MS/MS) was established for simultaneous measurement of mass fractions of CCC and 2,4-D in cucumber pulp. Interlaboratory value assignment of CCC and 2,4-D in the cucumber pulp CRM was performed using the ID-LC-MS/MS method. The certified values with expanded uncertainties (coverage factor k = 2) were assigned to be 4.1 mg/kg ± 0.4 mg/kg for CCC, 2.0 mg/kg ± 0.2 mg/kg for 2,4-D. Homogeneity assessment was performed on fifteen randomly selected units, and statistical analysis confirmed the CRM's homogeneity for both CCC and 2,4-D, both between and within packages. The long-term stability of the CRM at -20 °C storage condition and short-term stability at 30 °C were monitored for 14 months and nine days, respectively, and no significant trend differences were observed. The uncertainty contributions from characterization, homogeneity and stability were taken into account in uncertainty evaluation. The CRM was officially certified and registered under the number GBW(E)100932 by the State Administration for Market Regulation of the P. R. China.

Multi-environment trials (METs) are essential for maize breeding, but their implementation is often constrained by limited resources, particularly the high cost of phenotyping. To optimize resource allocation, 264 testcrosses derived from 100 inbred lines and three testers were evaluated across six locations. Four genomic prediction models, five cross-validation schemes (CV1–CV5), and five training set proportions (S1–S5) were systematically assessed for predicting grain moisture content (GMC), grain yield (GY), and plant height (PH). Together, the five cross-validation schemes and five training set proportions generated 25 sparse testing strategies. Among the four models, the reaction norm model consistently achieved the highest prediction accuracy, and was therefore selected for subsequent analyses. Averaged across S1–S5, CV1 showed the lowest prediction accuracy, with mean accuracies of 0.361 for GMC, 0.413 for GY, and 0.480 for PH. In contrast, CV2–CV5 achieved higher and comparable accuracies. Increasing the training set proportion from 1/6 (S1) to 5/6 (S5) improved prediction accuracy by 48.3% for GMC, 30.3% for GY, and 26.7% for PH, although further gains became limited once the training set proportion exceeded approximately 50% (S3). In addition, CV3 enabled reliable estimation of parental general combining ability based on predicted hybrid performance, particularly at higher training set proportions. Overall, integrating multi-environment sparse testing with genomic prediction enables efficient hybrid evaluation under limited resources, providing a cost-effective strategy to reduce phenotyping demands and accelerate breeding progress.

Accurate measurement of the peptide sublancin purity is very important for the application in feed additives. In this study, sublancin was separated and purified from crude samples by using a semi-preparative chromatography. For the purified sublancin sample, a SI-traceable purity assignment strategy was established by using mass balance (MB) and amino acid-based isotope dilution mass spectrometry (AA-IDMS) approaches. The absolute purity measured by MB method was 78.60% ± 0.27% by deducting the amount of all impurities including 5.46% of water, 0.4% of structure-related organic compounds, 15.48% of trifluoroacetate ion residue, and 0.056% of inorganic impurities. Hydrolysis conditions on phenylalanine (Phe), alanine (Ala), leucine (Leu) were optimized and AA-ID-LC-MS/MS measurement of sublancin purity was assigned to be 77.58% ± 0.34%. Additionally, measurement uncertainty was comprehensively evaluated. Therefore, the certified value was assigned to be 78.1% with uncertainty of 1.5%. These established methods can be applicable to SI-traceable determination and development of sublancin certified reference material.

Food quality and safety control remain a global priority, and the accuracy and reliability of measurement results are paramount. Certified reference materials (CRMs) play a pivotal role in quality assurance and analysis systems. In particular, matrix CRMs that closely match real food samples have seen rapid development in recent years, yet a comprehensive review in this area is still lacking. This review discusses the entire production workflow of matrix CRMs, including preparation procedures, homogeneity and stability assessments, and uncertainty evaluation. It also systematically summarizes recent research and application advances in matrix CRMs for the analysis of elements, antibiotics, mycotoxins, pesticides, and persistent organic pollutants in food. Furthermore, current challenges and future directions in the field are critically examined. This work aims to provide a valuable reference for the future development and application of relevant CRMs in food safety and quality analysis.

Simple, efficient and mild extraction of nucleic acids (NAs) represents a promising approach for food safety diagnostic analysis. The magnetic beads (MBs) have potential application value in the separation of NAs due to a variety of obvious capabilities. However, the inadequate NA extraction and separation efficiency of conventional MBs restricts their extensive application. Herein, we have developed a rapid and non-elution 2D layered magnetic MXene nanocomposite (Fe3O4@MXene@PDA@FS) for NAs extraction, which is created by aggregating Fe3O4 beads, MXene and fluorocarbon surfactant (FS) to form an integrated structure with solvent-responsive characteristics. The prepared materials exhibit remarkable extraction capabilities in various complex matrices. Furthermore, the whole extraction procedure can be completed within 30 min and detect as few as 10 copies of NA molecules per sample. The method has significant application prospects in DNA/RNA agricultural detection and early monitoring.

A new large-molecule protein purity-certified reference material (CRM) of bovine lactoferrin, GBW10333, was developed to establish metrological traceability for lactoferrin measurements in dairy products. The purity of bovine lactoferrin was characterized by two independent approaches including mass balance (MB) and isotope dilution mass spectrometry based on amino acids (AA-IDMS). The certified value with expanded uncertainty (k = 2, at a confidence of 95%) was 95.6% ± 3.2% for bovine lactoferrin purity. Homogeneity assessment was carried out by the MB method, and the results indicate that the CRM candidate's between-bottle and within-bottle homogeneity is acceptable. Additionally, long-term stability of 19 months at -20℃ for storage and short-term stability of 14 days at 50℃ for transportation were examined, respectively. The purity bovine lactoferrin CRM will provide a reliable metrological basis for accurate quantification of lactoferrin in milk and dairy products, thereby contributing to both regulatory enforcement and industrial quality assurance.

Reliable reference materials (RMs) are essential for the accurate, traceable, and quantitative detection of genetically modified (GM) crops and their products. In this study, leaves of GM papaya Huanong No. 1 (HN1) and non-GM papaya Tainong No. 2 (TN2) were used as raw materials to prepare genomic DNA (gDNA) certified reference materials (CRMs) at two different concentrations. Digital PCR (dPCR) was employed to evaluate their homogeneity and stability and to conduct collaborative characterization. The prepared 25

Aflatoxin (AFT) is a toxic carcinogen and mutagen produced mainly by Aspergillus species. Dietary intake is the main route of exposure to AFT in humans, and DNA damage caused by AFT exposure receives wide concern as an endogenous factor in the pathogenesis of liver cancer. The systematic exploration on the toxicity mechanism of AFB1—the most toxic AFT subtype—is of great significance for the prevention and control of liver cancer. In this work, three adduct models, gap-AFT (GA), mispairing-AFT (MA), and insertion-AFT (IA), have been defined based on all the available three-dimensional structures of AFT in complex with DNA. In addition, their molecular recognition and conformational change features were investigated via comparative molecular dynamics (MD) simulations. Subsequently, the effects of six adduct models resulted from both AFB1-N7-dG and AFB1-Fapy on the recognition by DNA polymerase IV (Dpo4) were analyzed, with the possible toxicity mechanism of the destruction against DNA replication being given. Specifically, AFT partially destroyed the conservative structure including dATP and Ca2+ ion in the catalytic center of Dpo4. Moreover, the extent of disruption from AFB1-Fapy was slightly higher than that from AFB1-N7-dG. This work enriches the mechanism of AFT toxicity and provides clinical theoretical guidance for the control of human injuries caused by AFT exposure, making a contribution in the field of food and environmental safety. The experimental structure of 16 aflatoxin-containing DNA systems was obtained from the protein database ( http://www.rcsb.org/ ), and the relevant structural parameters of DNA were analyzed using the Curves program, revealing the effect of AFT binding on DNA structural deformability. The initial models of the AFB1-N7-dG and AFB1-Fapy adducts were structurally optimized at the B3LYP-D3/6-311G(d,p) level of theory using the Gaussian 09 software package. Molecular dynamics simulations were performed using the AMBER 20 software package. The following force-field combination was employed: the AMBER ff19SB force field for the protein, the OL15 force field for DNA, and specialized parameters for key system components. The catalytic Ca2⁺ ions were described using the 12-6 Lennard-Jones non-bonded parameters developed by Li and Merz. For the dATP substrate, parameters including the refined partial charges for the triphosphate moiety were adopted from the specialized nucleotide force-field set based on the work of Meagher, Redman, and Carlson. All-atom simulations were conducted, yielding stable and physically reasonable trajectories. RDG analysis of covalent binding regions of DNA and AFT using the Multiwfn 3.8 program to visualize the type, intensity, and variation of weak intermolecular interactions; the molecular mechanics/Poisson-Boltzmann solvent area (MM/PBSA) method was used to calculate the binding free energy between protein and DNA. Subsequently, the energy decomposition technology based on the MM/GBSA method was used to quantitatively analyze the key residues in dATP recognition in Dpo4.

Agronomic traits in maize (Zea mays L.) are complex and modulated by pleiotropic loci and interconnected genetic networks. However, the traditional single-trait genome-wide association study (GWAS) method often misses genetic associations among traits, overlooks pleiotropic effects, and underestimates shared regulatory mechanisms. In the current study, we employed multi-trait analysis of GWAS (MTAG) and constructed a genetic network to dissect the genetic architecture of 18 agronomic traits across a genetically diverse panel of 2,448 maize inbred lines. Incorporating MTAG significantly improved the detection of pleiotropic loci that had not been detected by single-trait GWAS. Using a genetic network, we uncovered numerous previously unrecognized connections among traits related to plant architecture, yield, and flowering time. The 49 detected hub nodes, including Zm00001d028840 and Zm00001d033859 (knotted1), influence multiple traits. Co-expression analysis of candidate genes across two developmental stages validated their distinct yet complementary roles, with Zm00001d028840 linked to early cell wall remodeling and Zm00001d033849 involved in chromatin remodeling during tasseling. Moreover, we integrated results from GWAS, MTAG, and genetic network analyses to prioritize pleiotropic loci and hub genes that regulate multiple agronomic traits. This integrative approach offers a practical framework for selecting stable, multi-trait-associated targets, thereby supporting more precise and efficient crop improvement strategies.

β-lactam Antibiotics (BLA) are characterized by the presence of lactam rings, which are widely used and have a huge market scale. Currently, the production of BLA is primarily achieved through a chemical process, which introduces a large number of toxic compounds, resulting inrelatively high environmental costs. As a part of green chemistry, the enzymatic production of BLA is gaining attention because it is non-toxic and pollution-free. This review focuses on industrial enzymes for BLA biosynthesis, which is critical for understanding the reaction process and addressing the deficiencies of low enzyme stability and activity. In this work, a focused dataset of industrial enzymes involved in BLA biosynthesis was constructed, and the structural characteristics of these enzymes were analyzed based on substrate specificity. Subsequently, eight representative enzyme molecules from the database were selected for detailed analyses, particularly focusing on substrate recognition and action mechanisms. Finally, some suggestions for the semi-rational design of enzymes are put forward given the defects existing in BLA biosynthesis. This review not only partially reveals the structure-function relationship of industrial enzyme molecules used in BLA enzymatic synthesis, but also contributes to the semi-rational design of subsequent enzymes, showing certain theoretical significance and application value.

Genotype, environment, and genotype-by-environment (G×E) interactions play a critical role in shaping crop phenotypes. Here, a large-scale, multi-environment hybrid maize dataset is used to construct and validate an automated machine learning framework that integrates environmental and genomic data for improved accuracy and efficiency in genetic analyses and genomic predictions. Dimensionality-reduced environmental parameters (RD_EPs) aligned with developmental stages are applied to establish linear relationships between RD_EPs and traits to assess the influence of environment on phenotype. Genome-wide association study identifies 539 phenotypic plasticity trait-associated markers (PP-TAMs), 223 environmental stability TAMs (Main-TAMs), and 92 G×E-TAMs, revealing distinct genetic bases for PP and G×E interactions. Training genomic prediction models with both TAMs and RD_EPs increase prediction accuracy by 14.02% to 28.42% over that of genome-wide marker approaches. These results demonstrate the potential of utilizing environmental data for improving genetic analysis and genomic selection, offering a scalable approach for developing climate-adaptive maize varieties.

m(6)A methylation detection is crucial for understanding RNA functions, revealing disease mechanisms, guiding drug development and advancing epigenetics research. Nevertheless, high-throughput sequencing and liquid chromatography-based traditional methods still face challenges to rapid and direct detection of m(6)A methylation. Here we report a DNAzyme-based and smartphone-assisted electrochemical biosensor for rapid detection of m(6)A. We initially identified m(6)A methylation-sensitive DNAzyme mutants through site mutation screening. These mutants were then combined with tetrahedral DNA to modify the electrodes, creating a 3D sensing interface. The detection of m(6)A was accomplished by using DNAzyme to capture and cleave the m(6)A sequence. The electrochemical biosensor detected the m(6)A sequence at nanomolar concentrations with a low detection limit of 0.69 nM and a wide detection range from 10 to 10(4) nM within 60 min. As a proof of concept, the 3 '-UTR sequence of rice was selected as the m(6)A analyte. Combined with a smartphone, our biosensor shows good specificity, sensitivity, and easy-to-perform features, which indicates great prospects in the field of RNA modification detection and epigenetic analysis.

Digital PCR, as an advanced technique for absolute nucleic acid quantification, has been widely used in the value assignment and characterization of reference materials, including in vitro diagnostic reference standards. However, few studies have systematically evaluated the impact of different digital PCR platforms and nucleic acid extraction kits on the quantification of reference materials. In this study, we established a highly specific and reproducible digital PCR assay for the hepatitis B virus and systematically evaluated the influences of commercial digital PCR platforms, primer-probe sets, and nucleic acid extraction kits on reference materials quantification. Results demonstrated good consistency in quantitative measurements across mainstream commercial digital PCR platforms based on different technical principles, with a mean interplatform coefficient of variation (CV) of 9.05%. Notably, nucleic acid extraction efficiency demonstrated the greatest impact on quantification accuracy, with a mean CV across different extraction kits of 76.66%. Primer-probe design also contributed substantially to the measurement uncertainty. These findings provide important insights that support the standardization of digital PCR protocols for reference materials quantification.

Fluoroquinolones are a popular class of antibiotics, which can lead to residues in food and the environment due to their abuse and illegal use. Consequently, this can pose a threat to human health. We hypothesized that a core-shell structured magnetic lanthanide metal-organic framework could serve as an effective dual-mode nanosensor, leveraging its antenna effect and peroxidase (POD)-like activity for the sensitive detection of fluoroquinolones. Herein, a novel Fe₃O₄@EuMOF-based platform was developed to establish a rapid and sensitive fluorescence/colorimetric dual-mode method for detecting fluoroquinolones. The established method demonstrated excellent sensitivity for fluoroquinolones with limit of detections (LODs) of 18.6 nM (fluorescence) and 37.5 nM (colorimetric). Furthermore, this novel method has been successfully applied to detect fluoroquinolones in various food matrix sample with significant recoveries (87.3-107.9 %) and relative standard deviations (RSD) of <8 %. This research provided a sensitive and accurate sensing platform for monitoring fluoroquinolones in various food samples.

Nanozymes, as a new type of artificial enzyme, have been regarded as an alternative to traditional agrochemicals and an excellent choice for nano-sensing applications in the field of agriculture, gradually attracted extensive attention from researchers. In this paper, the catalytic mechanism, synthetic methods and surface modification methods of different nanozymes were systematically analyzed from the classification of nanozymes. Based on these basic studies, this paper summarizes three application directions of nanozymes in agriculture: detection of harmful substances in agricultural products (such as pesticide residues, heavy metal ions, etc.), agricultural technology promotion (such as promoting crop growth, degrading pollutants, etc.) and development of new plant wearable sensors (such as real-time monitoring of plant physiological indicators). Finally, in view of the challenges faced by nanozymes in stability, large-scale production and environmental safety, the key directions of future research were proposed, including the development of multifunctional nanozymes, the establishment of standardized evaluation systems and the exploration of sustainable green synthesis routes. These insights laid an important theoretical foundation for the in-depth application of nanozymes in precision agriculture and sustainable agriculture.

Analytical chemistry is experiencing a growing demand for reliable and traceable results, which have significant implications for public health and food safety. The COVID-19 pandemic further underscores the need for accurate and dependable molecular diagnostics. Nucleic acid-based reference materials (NARMs) play a crucial role in ensuring the quality of results. Notably, NARMs have gained increased attention following the outbreak of COVID-19. While previous reviews introduced NARMs but overlooked their applications in different fields. Moreover, the integration of multiple methods represents a new trend in the preparation of NARMs, but these have not appeared in previous reviews. Therefore, this review delineates NARMs classification, synthesizes characterization techniques, reviews their applications in virus diagnosis, animal diseases, pathogenic microorganisms, genetic diseases and genetically modified organism detection, and provides a perspective on NARMs’ development and current challenges. In-depth study of NARMs will be significant for precise molecular diagnostics in biology, agriculture and public health.

This study aimed to develop Certified Reference Materials (CRMs) for the accurate determination of perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) residues in prawn. The raw materials were prepared by feeding prawns with drugs and then processing them into powder. The homogeneity, stability, and characteristics of these matrix CRMs were examined by liquid chromatography tandem mass spectrometry (LC-MS/MS) and isotope labeling internal standard method. The certified value of PFOS in prawn powder was 30.24 µg/kg with an uncertainty of 0.25 µg/kg (k = 2). The certified value for PFOA in prawn was 20.22 µg/kg with an uncertainty of 0.18 µg/kg (k = 2). The homogeneity of the samples, long-term stability at −20 °C for 6 months, and short-term stability at an extreme temperature of 50 °C for 7 days were also evaluated in detail. The results showed that the samples were stable and homogeneous under the above conditions.

BACKGROUND:Insect-derived proteins constitute an underutilized biological resource requiring urgent exploration to address global food protein shortages. However, their widespread application is hindered by the allergenic potential, particularly phospholipase A2 (PLA2), a highly immunoreactive allergen prevalent in edible insects such as ants and honeybees. OBJECTIVE:This study systematically investigated the molecular mechanism underlying quercetin-mediated reduction in PLA2 allergenicity, aiming to establish a novel strategy for developing hypoallergenic insect protein resources. METHODS AND RESULTS:Through integrated computational and experimental approaches, we identified quercetin's dual non-covalent and covalent binding capabilities with PLA2. Molecular docking revealed robust interactions (the binding energy of -6.49 kcal/mol) within the catalytic pocket. Meanwhile, mass spectrometry specifically identified Cys37 as the covalent modification site, which can bind to quercetin and increase the gyration radius (Rg) of PLA2 within 75-125 ns. Molecular dynamics simulations illustrated quercetin-induced conformational changes affecting critical antigenic epitopes. Murine experiments further confirmed that quercetin-modified PLA2 exhibited significantly reduced IgE reactivity and allergic responses compared to native PLA2, as demonstrated by assessments of anaphylactic behavior, histopathological changes, and measurements of serum IgE antibody and biogenic amine levels. CONCLUSIONS:Collectively, these findings provide a transformative approach to safely utilize insect-derived proteins for sustainable nutrition solutions.