The preparation of specific antibodies is of critical importance in the immunoassay of small-molecule contaminants in food. However, due to the lack of immunogenicity, these small molecules must be conjugated to a carrier to form complete antigen in order to induce the generation of antibodies, and adjuvants are typically required during the immunization when traditional proteins were used as carriers. Therefore, identifying a substance that possesses both the characteristics of carrier and adjuvant is of significant research importance for antibody preparation. Outer membrane vesicles (OMVs) are nanoscale particles with a bilayer membrane and spherical structure produced by Gram-negative bacteria through natural budding. They contain various pathogen-associated molecular patterns (PAMPs), which could be recognized by pattern recognition receptors (PRRs) on the surface of immune cells, thereby triggering a robust immune response. In this study, OMVs derived from Δlpxl E. coli and chloramphenicol sodium succinate (CSS) were used as the carrier and hapten to synthesize the complete chloramphenicol (CAP) antigen (CSS-Δlpxl-OMV). BALB/c mice were subsequently immunized with this antigen to generate antibodies, with the aim of evaluating the adjuvant effects of Δlpxl-OMV and its potential as a hapten carrier. The results indicated that Δlpxl-OMV not only served as a carrier for binding the hapten to prepare the complete antigen but also exhibited significant adjuvant properties. The synthesized complete antigen possessed significant immunogenicity and could induce the mice to produce antibodies against the target without additional adjuvants.

Postmortem fish products are highly perishable and susceptible to degradation. Researchers have found that cellular changes may contribute to fish flesh deterioration. However, reports on the specific kinds of cell death and their role in postmortem flesh quality changes are limited. In this review, we summarise the postmortem physiological changes and their association with apoptosis, ferroptosis and autophagy. Molecular and biological factors linked with cell death are delineated, and potential effects on fish flesh changes are recapped. The relation between apoptosis, ferroptosis and autophagy and their involvement in flesh softening is discussed. Available evidence indicates that postmortem physiological changes accelerate cell death and that cell death modes can affect fish flesh quality. The specific types of cell death programmes and their varying degrees of impact on the macroscopic quality of fish need further exploration to deepen our understanding of postmortem fish quality changes.

Extraction and purification of nucleic acids are essential for the detection of foodborne pathogens, yet conventional methods are often limited by operational complexity and reliance on specialized instrumentation, restricting their use in low-resource settings. Herein, we report a simple and efficient nucleic acid extraction platform based on a chitosan-derived sponge-like cryogel (CSC), enabling dynamic adsorption-elution-driven separation under mild conditions. The CSC exhibits high nucleic acid binding capacity (88 μg for DNA and 305 μg for RNA per 10 mg material) and rapid adsorption kinetics following a pseudo-second-order model. Isotherm analyses indicate that RNA and DNA binding follow the Langmuir and Freundlich models, respectively, suggesting a combined mechanism of electrostatic interaction and physical entanglement. Notably, the compressible and shape-recoverable structure enables dynamic extraction through simple aspiration-compression operations, eliminating the need for external equipment. For practical application, the CSC was integrated into a Pasteur pipette to construct a portable extraction device. This system allows rapid nucleic acid purification from Vibrio parahaemolyticus and Salmonella in bacterial cultures and milk samples, with direct compatibility for quantitative polymerase chain reaction (qPCR) and recombinase polymerase amplification (RPA)-clustered regularly interspaced short palindromic repeats (CRISPR)/Cas12a assay. The method achieved sensitive detection down to 103 CFU ·mL-1, outperforming a commercial kit. Importantly, the entire extraction process avoids chaotropic salts, organic solvents, and complex instrumentation, offering a simplified and environmentally friendly alternative. This work provides a practical and scalable strategy for nucleic acid purification with potential applications in point-of-care testing for food safety.

Single-domain antibodies (sdAbs) derived from naive phage display libraries offer a time-efficient alternative to animal immunization but often exhibit suboptimal affinity, particularly for small-molecule haptens, where restricted binding interfaces limit the efficacy of traditional saturation mutagenesis. For instance, the wild-type sdAb (B1)-targeting ethoxyquin (EQ) exhibits a moderate equilibrium dissociation constant (KD) at the submicromolar level (within the 10-7 M range), restricting its practical sensitivity. To overcome the structural and energetic barriers inherent in hapten recognition, a "structure-guided directed modification" strategy was developed that focuses on conformational tuning rather than simple side-chain replacement. Integrating AlphaFold2 modeling and AutoDock mechanistic analysis identified key interactions (e.g., the ASP19-EQ-N8 hydrogen bond). Subsequently, a random single-amino acid insertion strategy was implemented within the CDR3 loop (residues 77-90) to fine-tune local loop geometry. Top candidates were screened via MM/GBSA binding free energy calculations and experimentally validated using biolayer interferometry. This approach yielded three high-affinity mutants-77A, 79C, and 85H-with calculated ΔΔG values of -10.56, -4.35, and -6.69 kcal/mol, respectively. The mutants achieved enhanced affinities in the tens-of-nanomolar range (down to 35.1 nM), representing up to approximately 3 times overall improvement. Importantly, orthogonal surface plasmon resonance analysis using nonconjugated, free EQ successfully verified this affinity maturation trend, showing that mutant 79C bound free EQ with a KD of 1.30 × 10-5 M (a 2.3 times improvement over wild-type) through simultaneously accelerated association and slowed dissociation. Mechanistically, this substantial increase in affinity is attributed not only to reinforced noncovalent networks that significantly stabilize the complex but also to favorable CDR3 geometric outward flips that alleviate steric hindrance, leading to an approximate 3.8 times acceleration in the kon. Crucially, these mutants demonstrated notable anti-interference tolerance in complex aquatic food matrices (e.g., sea bass extracts). Ultimately, this work provides a practical and efficient computational framework for assisting the rapid evolution of low-affinity hapten sdAbs into high-performing biorecognition elements with potential for next-generation biosensing architectures.

Surface-enhanced Raman scattering (SERS) substrates hold great potential for rapid food monitoring, but the inability to reconcile high enhancement, uniformity, and stability presents a critical trilemma for substrate design and practical applications. Here, inspired by the hierarchical structure of lychee, we developed an innovative "integrated balanced enhancement-protection" strategy, fabricating a lychee-like Au@Ag/Au nanoarray chip via a simple, uniform oil/water/oil (O/W/O) self-assembly technique. This design mimics the architecture of lychee: the outer Au layer, modeled after lychee's peel, provides chemical protection; the inner Au@Ag layer, mirroring lychee's seed and flesh, delivers strong plasmonic enhancement. The unique bilayer nanoarchitecture, featuring dense and vertically coupled plasmonic hotspots, ensures highly efficient electromagnetic (EM) field by Au-Ag synergistic effects. It demonstrates an analytical enhancement factor (AEF) of 2.30 x 10(6), uniformity with a relative standard deviation (RSD) of 6.55 %, and stability with 93.26 % signal retention over 60 days. When coupled with a universal pretreatment protocol to minimize matrix interference, the platform enables sensitive and reliable quantitative detection of three representative food additives, including potassium sorbate (PS), sodium benzoate (SB), and sodium saccharin (SS) in complex fruit matrices. The limit of detection (LOD) for all analytes was below 75 mg/kg, substantially surpassing the national regulatory standards of China. Importantly, the chip demonstrated high recoveries (86.62-102.49 %) and low RSD (< 9 %) across multiple fruit types. Beyond food safety, this scalable, low-cost approach not only overcomes SERS substrate bottlenecks but also provides a viable field-deployable tool with broader implications for SERS-based analysis.

Smartphone-based colorimetric assays are attractive for on-site analysis but often suffer from measurement instability caused by ambient illumination and imaging conditions, as well as limited sensitivity from conventional single-channel color readout. Herein, an AlphaFold-engineered nanobody biosensor was developed for enrofloxacin (ENR) by integrating active-illumination imaging with smartphone-based multidimensional color analysis to enable interference-resistant, enclosure-free detection. A specially engineered light source generates intense, spatially uniform diffuse illumination that dominates image acquisition, effectively suppressing ambient-light interference and eliminating the need for a light-shielding enclosure. Multidimensional descriptors extracted from RGB, HSV, and CIELAB (Lab) color spaces were fused to improve discrimination of subtle color changes and enhance readout sensitivity. Under variable lighting, the coefficient of variation was stabilized at 8-10%, compared with 66-97% without active illumination. The biosensor achieved an LOD of 2.93 ng/mL for ENR, which was further reduced to 1.91 ng/mL using a fused parameter (Senh), representing a 34.8% improvement in sensitivity. The assay also showed good performance in spiked marine fish samples, supporting its on-site applicability. Overall, this study presents a strategy whereby active illumination minimizes environmental interference and data-fusion-based multidimensional analysis enhances readout sensitivity for portable and adaptable detection.

Lateral flow immunoassays (LFIAs) are widely used point-of-care analytical tools because of their simplicity, rapid response, and low cost; however, conventional colorimetric readouts suffer from limited sensitivity and poor quantitative reliability. Although surface-enhanced Raman scattering (SERS)-based LFIAs provide significantly improved sensitivity, their quantitative performance is often compromised by stochastic interparticle plasmonic coupling, which generates unpredictable hotspots and weakens the correlation between Raman intensity and probe number. Herein, we report a gold-core passivated nanocage nanoparticle (Au@PNC-K4[Fe(CN)6] NPs) that enables probe-number-dependent Raman responses for reliable quantitative LFIA detection. The probes were fabricated via selective metal replacement to form a gold-core Au-Ag alloy nanocage with abundant internal nanogaps and an outer alloy cage that spatially confines plasmonic fields. Encapsulated potassium ferrocyanide serves as an internal Raman reporter with a characteristic signal at 2085cm-1 in the Raman-silent region. The outer Au-Ag alloy cage suppresses outward plasmonic propagation, thereby attenuating interparticle plasmonic coupling while confining electromagnetic enhancement within intrinsic nanogap hotspots. As a result, Raman signals become more closely associated with probe quantity with reduced influence from environmental perturbations. When integrated into a competitive LFIA for chlorpyrifos (CPF) detection, the platform exhibited a wide linear range of 1-512ng/mL with a limit of detection (LOD) of 0.39ng/mL, together with high specificity and satisfactory recoveries of 98.2-113.7% in spiked apple, celery, and green pepper samples. This nanocage-based plasmonic regulation provides a structural strategy for improving the quantitative reliability of SERS-LFIAs and advances reliable point-of-care analysis.

Anthocyanins are natural pH-sensitive pigments with potential for intelligent food packaging, but their poor stability under environmental stress limits practical use. Herein, a highly stable intelligent indicator patch was developed by combined incorporation of UiO-66-NH2, a metal-organic framework, and 2,5-dihydroxybenzoic acid. This dual-modulation strategy significantly enhanced anthocyanins stability through hydrogen bonding and van der Waals interactions. The optimized indicator patch maintained color integrity for over 30 days at ambient temperature and more than 6 months at 4 °C in darkness. It exhibited excellent pH responsiveness and high selectivity to spoilage amines (e.g., NH3, dimethylamine, trimethylamine) over common volatile interferents. When applied to Litopenaeus vannamei, the patch's color change correlated strongly with total volatile basic nitrogen (TVB-N) values (r > 0.93), accurately identifying freshness stages. The indicator patch showed high batch-to-batch reproducibility (RSD < 5%) and anti-interference capability. This study provides a feasible approach to commercialize anthocyanin-based freshness indicators for intelligent packaging.

Anthocyanins are natural pH-sensitive pigments with potential for intelligent food packaging, but their poor stability under environmental stress limits practical use. Herein, a highly stable intelligent indicator patch was developed by combined incorporation of UiO-66-NH2, a metal-organic framework, and 2,5-dihydroxybenzoic acid. This dual-modulation strategy significantly enhanced anthocyanin stability through hydrogen bonding and van der Waals interactions. The optimized indicator patch maintained color integrity for over 30 days at ambient temperature and more than 6 months at 4 °C in darkness. It exhibited excellent pH responsiveness and high selectivity to spoilage amines (e.g., NH3, dimethylamine, trimethylamine) over common volatile interferents. When applied to Litopenaeus vannamei, the patch's color change correlated strongly with total volatile basic nitrogen (TVB-N) values (r > 0.93), accurately identifying freshness stages. The indicator patch showed high batch-to-batch reproducibility (RSD < 5%) and anti-interference capability. This study provides a feasible approach to commercialize anthocyanin-based freshness indicators for intelligent packaging.

Pesticide residues pose serious risks to food safety, highlighting the need for rapid, sensitive, and cost-effective detection methods. We developed a modular indirect labeling surface-enhanced Raman scattering immunochromatography (SERS-ICA) that decouples the signal module from the recognition module. Au@Ag nanoparticles preloaded with 5,5'-dithiobis (2-nitrobenzoic acid) (DTNB) were conjugated with goat anti-mouse IgG to form a universal signal probe, onto which target-specific monoclonal antibodies were docked before use. This design avoids repeated probe synthesis and reduces antibody consumption by up to two orders of magnitude compared with direct labeling. After optimization of nanoparticle size, Ag shell thickness, reporter loading, and storage conditions, the system exhibited high signal stability. Using carbofuran as a model analyte, the SERS-ICA achieved a linear range of 0.0001-10 ng mL-1 (R2 = 0.985) and a detection limit of 0.51 pg mL-1, with high specificity, reproducibility, and robust performance in spiked pear, carrot, and potato samples.

The determination of multiclass veterinary drug residues in food is fundamentally constrained by the irreconcilable conflict between the extremely broad polarity of analytes and the dynamic, heterogeneous nature of complex matrices. Current mainstream sample preparation methods typically rely on static, compromise-driven conditions that limit optimal recovery for polarity-extreme compounds. This review articulates a paradigm shift by establishing the “Dynamic Polarity Window” (DPW) as a framework for rational design. Unlike static methods, DPW enables programmable polarity adjustment across pretreatment stages to match analyte-specific requirements. We critically evaluate conventional techniques through this polarity-centric lens and synthesize a toolkit of programmable strategies—encompassing solvent engineering, salting-out, pH/temperature levers, and microenvironment control—guided by physicochemical parameters. This framework enables the transition from passive, universal extraction to active, on-demand separation, enhancing selectivity and robustness. We finally outline key future directions to bridge the prediction-experiment gap, develop sustainable solvents, and integrate automation for robust residue analysis.

BACKGROUND:Reliable quantification of nitrite in complex food matrices using surface-enhanced Raman scattering (SERS) remains challenging due to signal drift and SERS substrate variability. Conventional internal standard (IS) strategies often occupy plasmonic hot spots, limiting analyte accessibility and compromising detection performance. RESULTS:Herein, we report a size-complementary modular self-calibrated co-assembled (SCCA) SERS platform that integrates large gold nanoparticles (LAuNPs) with Au@Prussian blue (PB) core-shell nanospheres via interfacial self-assembly. The Au@PB nanospheres physically occupy the interparticle gaps of LAuNP arrays, providing both structural uniformity and a built-in Raman reference band at 2128 cm-1 for ratiometric self-calibration without competing for plasmonic hot spots and compromising SERS sensitivity. The resulting SCCA substrate exhibits dense electromagnetic hot spots and good reproducibility, achieving quantitative nitrite detection through an acid-promoted S-nitrosation reaction with 2-thiobarbituric acid that generates a characteristic Raman band at 685 cm-1. The method delivers a linear range of 0.15-2 mg/L, a limit of detection of 0.0368 mg/L, and excellent anti-interference tolerance in real food samples including cured fish, sausage, and pickled cucumber. The substrate retains 91.51% signal intensity after 60 days, confirming outstanding stability. SIGNIFICANCE AND NOVELTY:This work presents a universal strategy for constructing self-calibrated SERS substrates by spatially decoupling calibration elements from plasmonic hotspots. The SCCA design eliminates the intrinsic conflict between sensitivity and quantitative reliability, offering a modular and scalable approach for ratiometric SERS analysis.

Lipid co-extraction is a major source of matrix interference in detecting chemical hazards in animal-derived foods, but its mechanisms remain largely unexplored. This study focuses on ethoxyquin as a model contaminant to analyze matrix interference in Gold immunochromatographic assays and identifies lipid extracts as the primary source of interference. The degree of interference showed significant correlations with both crude fat content (tau = 0.893, p < 0.01) and analyte lipophilicity (tau = 0.990, p < 0.01), indicating a polarity-driven process rather than nonspecific physical effects. Lipidomic profiling and spiking experiments identified phosphatidylcholine as a key lipid species responsible for interference. Spectroscopic analysis confirmed that PC self-assembles into colloidal structures, sequestering hydrophobic analytes and reducing their effective availability for antibody recognition during immunochemical detection. Guided by these insights, we developed a polarity-selective two-step extraction strategy to mitigate lipid-induced interference. This method reduced co-extracted lipids by over 97% and enabled reliable on-site detection of ethoxyquin at 10 mu g/kg across various high-fat food matrices. The strategy's applicability was further validated with other nonpolar compounds, demonstrating its broader relevance. This study provides mechanistic insights and practical strategies to improve the reliability of rapid screening for nonpolar chemical hazards in lipid-rich foods.

Hypoxanthine (Hx) is an important biomarker for food freshness and clinical diagnosis, necessitating rapid and reliable on-site detection methods. Paper-based enzyme sensors offer a promising solution, yet their practical application is severely constrained by poor storage stability at room temperature. Herein, we report a bioinspired paper-based enzyme sensor for Hx detection based on enzyme stabilization at the single-enzyme level. Each xanthine oxidase (XOD) molecule was encapsulated within a conformal silica shell with three different silica precursors, achieving single-enzyme-level silicification and yielding XOD@Si with enhanced catalytic activity and structural stability. Further integration of XOD@Si with pullulan network on nitrocellulose membrane resulted in excellent color uniformity and signal intensity. The sensor exhibited a linear response of 19.5–625 μM and a limit of detection of 6.7 μM. With good selectivity and reliable quantitative capability, the sensor performed well in liquid meat soup and enabled “attach-and-read” assessment of meat freshness. Notably, the biomimetic dual-protection strategy conferred excellent storage stability, maintaining stable signal output for several weeks at room temperature, thereby overcoming a major limitation of conventional paper-based enzyme sensors. This work provides a versatile and scalable strategy for stabilizing enzymes on paper substrates, contributing to the development of stable, low-cost, and field-deployable biosensing platforms.

Conventional anthocyanin-based colorimetric indicator labels can achieve qualitative differentiation of seafood freshness levels, but exhibit low responsiveness to early-stage freshness changes. Herein, a high-sensitive smart hydrogel patch with multiplexed colorimetric and surface-enhanced Raman spectroscopy (SERS) features was developed. The structural basis of anthocyanins served as a novel colorimetric and SERS dual-mode sensing unit for smart hydrogel patch was first uncovered. The colorimetric function of the patch can be used to qualitatively identify the freshness of seafood, and the SERS function can be used to quantitatively detect the TVB-N content in seafood. The results revealed that within a pH range of 2.0 to 12.0, the patch's color shifted from bright red to dark green, accompanied by alterations in anthocyanin's characteristic Raman peaks at 1287 cm-1, 1320 cm-1, and 1642 cm-1 due to structural transitions. This study provides a new method for sensitive detection of seafood freshness using a smart hydrogel patch.

In this work, a novel method for sensitive detecting heavy metal Pb (II) in aquatic products was developed using UiO-66-NH2@tannic acid (UiO-66-NH2@TA) solid-phase extraction combined with laser-induced breakdown spectroscopy (LIBS). UiO-66-NH2@TA adsorbent could effectively extract Pb (II) from the digestive solution of aquatic products. Characterization of the morphology of the adsorbent was performed using transmission electron microscopy and scanning electron microscopy. The optimal experimental conditions for LIBS detection, including sample preparation, substrate type, laser energy, and delay time, were investigated. The results showed that the strongest Pb I 405.7 nm spectral signal can be obtained by dripping UiO-66-NH2@TA adsorbent onto a silicon wafer for LIBS testing. The limit of detection and limit of quantification for Pb (II) in aqueous solution were 0.18 mu g/mL and 0.61 mu g/mL, respectively. The calibration curve demonstrated good sensitivity and accuracy for Pb (II) detection with a correlation coefficient of 0.9905. Spiked recovery experiments on large yellow croakers and scallops yielded recovery rates of 75.25 % - 99.08 %, which was consistent with the results from atomic absorption spectrometry. This study underscores the potential of the solid-phase extraction combined with laser-induced breakdown spectroscopy for practical application in food safety monitoring, demonstrating its effectiveness and reliability in detecting Pb (II) in aquatic products.

In surface-enhanced Raman spectroscopy (SERS) detection of drug residues, food matrices, especially the protein corona around nanomaterials, pose challenges to accurate detection. This study used sea bass, a fish product with a complex matrix, and malachite green as a target fish drug to investigate these effects. Multiple techniques were used to elucidate the interactions among proteins, malachite green, and gold nanoparticles (AuNPs). The detection limit of malachite green in fish extract (740 μg/L) was much higher than in standard solutions (0.42 μg/L). At a protein concentration of 0.5 mg/mL, a uniform protein corona formed around the AuNPs, resulting in an aggregation-sedimentation rate of 9.23 %. Malachite green adsorption by AuNPs decreased by 99 % after protein corona formation. The work reveals how protein corona affects SERS detection of fish drugs, guiding development of signal regulation strategies for enhanced SERS sensitivity in food safety.

The presence of malachite green (MG) residues in aquatic products poses a significant threat to food safety. While label-free Surface-enhanced Raman scattering (SERS) technologies have been developed for detecting malachite green, it faces the challenge of limited sensitivity and specificity. A new immunochromatographic assay (ICA) based on SERS method using Au-DTNB@Ag-mAb as an immunoprobe was established for the in-situ, specific, and ultrasensitive detection of MG in fish samples. The immunoprobe was produced by connecting the Raman reporter 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB) between the Au-core and Ag-shell and binding the MG monoclonal antibody (mAb) on the surface of the Au-DTNB@AgNPs. The SERS signal of DTNB on the test line of the ICA strip has been recorded to determine MG quantitatively. The method demonstrated high specificity for MG detection, with a limit of detection as low as 0.1 pg/mL. The SERS-ICA confirmed outstanding results for analyzing actual fish samples with recoveries of 70.93-93.90 %. The study indicated that the SERS-ICA method was able to directly detect MG with excellent sensitivity, specificity, and accuracy, and could serve as a potent technique for in-situ analyzing other harmful substances in foods.

Ethoxyquin (EQ), a common antioxidant in animal feed and aquatic products, poses health risks such as hepatorenal damage and teratogenicity. Conventional detection methods, while sensitive, are often complex and costly. This study introduces a novel pH-dependent extraction strategy to mitigate matrix interference from lipid co-extracts in Gold Immunochromatographic Assay (GICA). This study introduces a pH-dependent extraction strategy leveraging EQ's LogD range, coupled with Plackett-Burman and Box-Behnken experimental designs, to rapidly establish a simplified pretreatment protocol. The method achieved a 10 μg/kg detection limit-below international thresholds-by eliminating lipid matrix interference through pH adjustment. The method's effectiveness was confirmed through validation and comparison with the Chinese national standard method using real samples. This work not only advances the rapid analysis of EQ in food safety monitoring but also provides a versatile framework for designing simplified pretreatment protocols for detecting highly non-polar compounds.

Early and rapid detection of the freshness of aquatic products is crucial for their quality control. Hypoxanthine is considered as a key metabolite during the early stage of spoilage in aquatic products. In this study, we investigated a machine learning-assisted colorimetric method for hypoxanthine detection, utilizing an ultraviolet (UV)-enhanced xanthine oxidase (XOD)/mimetic peroxidase cascade reaction. UV irradiation effectively enhanced the peroxidase-like activity of bimetallic Fe/Ni metal organic framework (Fe7Ni3 MOF), thereby enhancing the efficiency of hypoxanthine detection. Results revealed that under UV irradiation conditions, the UV-enhanced XOD/Fe7Ni3 MOF cascade reaction can detect hypoxanthine within 4-70 mu mol/L, with a detection limit of 1.63 mu mol/L. This method allowed for the detection of hypoxanthine in large yellow croakers and shrimps, achieving spiked recovery rates ranging from 92.16 % to 127.31 %. By capturing colorimetric color images using a smartphone and extracting nine chromatic information parameters, support vector machine regression (SVMR) model was used to predict hypoxanthine content, exhibiting a coefficient of determination for prediction (R2P) of 0.946 and a ratio of performance to deviation of 3.79. This study offers a novel alternative method for the rapid detection of quality changes in aquatic products.