Novel electrochemiluminescence sensing platform for ultrasensitive detection of malathion residue in tea based on SiO2NSs doped Luminol/AgNPs as a signal amplification strategy.

To address the potential hazards of organophosphorus pesticides (OPs) residues in tea, an electrochemiluminescence (ECL) aptasensor based on functionalized nanomaterials was constructed in this work. Firstly, gold nanoparticles (AuNPs) were attached on the surface of multi-walled carbon nanotubes (MWCNTs) by the constant potential electrodeposition to form a compound, and it was utilized to provide excellent immobilization sites for complementary DNA (cDNA). Subsequently, composite nanomaterials were synthesized by a one-pot method with aminated Luminol/silver nanoparticles@silica nanospheres (NH2-Luminol/Ag@SiO2NSs). Finally, NH2-Luminol/Ag@SiO2NSs was combined with a malathion aptamer (Apt) to obtain signal probes (SPs) for the construction of an aptasensor. The aptasensor had a wide linear range (1×10-3-1×103 ng/mL) and a low limit of detection (LOD) (0.3×10-3 ng/mL). It had the virtues of high sensitivity, wonderful stability and excellent specificity, which could be used for the detection of malathion residue in tea. The work provides a proven way for the construction of a rapid and ultrasensitive aptasensor with low-cost.

Application of MXene composites for target gas detection in food safety.

Food contamination has long plagued agriculture, posing significant health risks to consumers. The use of volatile gases for food safety detection has proven highly effective, with composite gas sensors that leverage the two-dimensional material MXene exhibiting notable advancements in detecting various target gases. This paper reviews the progress of MXene-based composite gas sensors in the detection of food safety-related gases. The review begins by examining MXene material synthesis methods and then presents an overview of techniques aimed at enhancing MXene-based sensor detection capabilities. Recently, advancements in MXene composite gas sensors tailored for food safety gases have been highlighted. Finally, challenges encountered in gas-sensing applications of MXene-based composites are outlined, alongside predictions for their future development, aiming to offer insights for the application and advancement of intelligent gas sensors for target gases in food safety.

Combination of Capture-SELEX and Post-SELEX for procymidone-specific aptamer selection and broad-specificity aptamer discovery, and development of aptamer-based lateral flow assay.

BACKGROUND: Due to its wide application, procymidone has become one of the pesticides with high detection rates in supervision and sampling. Therefore, it is necessary to establish a rapid and efficient method for the detection of procymidone. However, an important bottleneck restricting the development of rapid detection methods of procymidone is that its specific recognition elements are rarely reported. In this work, Capture-SELEX and post-SELEX were used in aptamer screening, and the obtained aptamers were used to construct an aptamer-based lateral flow assay (LFA). RESULTS: Firstly, a specific aptamer Seq15 was obtained for procymidone by Capture-SELEX, and its dissociation constant (Kd) was 24.22 nM. Secondly, post-SELEX was used to analyze and modify Seq15 to improve its performance, and the Kd of the truncated sequence Seq15-2 was 21.28 nM. In addition to this, the broad-specificity aptamer Seq17-1 was obtained via post-SELEX. Seq17-1 could broadly recognize dicarboximide fungicides (procymidone, iprodione, chlozolinate, dimethachlon and vinclozolin) and their metabolic derivative (3,5-dichloroaniline). Finally, the specific aptamer-based LFA of procymidone was constructed, and the limit of detection (LOD) was 0.79 ng/mL. Meanwhile, the LODs of dicarboximide fungicides and their metabolic derivative were 0.62, 0.64, 0.71, 0.69, 0.64 and 0.66 ng/mL, respectively. The above LFAs were highly specific and stable, and had been successfully used for the detection of vegetable samples. SIGNIFICANCE: Under the combination of Capture-SELEX and Post-SELEX, this study not only provides specific recognition elements for rapid detection of procymidone, but also provides new ideas for the discovery of broad-specificity aptamers. Combining broad-specificity primary detection and single-specificity quantification, a composite aptamer-based LFA detection platform has been developed, which significantly improves detection efficiency.

Accumulation of trace metal elements in ophiuroids with different feeding types in the North Yellow Sea.

Ophiuroids, as an important group of echinoderms, are widely distributed in marine benthic habitats. Previous studies have identified two primary feeding types of ophiuroids in the Yellow Sea, including carnivorous (Ophiura sarsii vadicola and Stegophiura sladeni) and suspension feeders (Ophiopholis mirabilis). Despite their ecological role in the benthic food webs, little is known about their accumulation of trace metal elements (TMEs). In this study, the content of TMEs (Pb, As, Cd, Hg, Cr, Cu, Zn), methylmercury (MeHg) and δ15N value of three ophiuroids species from the North Yellow Sea were determined. Our results showed that the contents of some TMEs (As, Cd, Cr, Cu and Zn) and MeHg were significantly different in three species of ophiuroid (p < 0.05). There were significant correlations between the accumulations of trace metal elements (Pb, Cd and Zn) and the δ15N value of the ophiuroids (p < 0.05). Additionally, As and Zn exhibited opposite correlations in ophiuroid with two feeding types, which may be related to their host species and different feeding habits. This study provided fundamental data for understanding the distribution of trace metal elements in echinoderms.

Recent progress of the research of metal-organic frameworks-molecularly imprinted polymers (MOFs-MIPs) in food safety detection field.

Food safety is an important cornerstone of protecting human health and life. Therefore, it is of great significance to detect possible pollutants in food sensitively and efficiently. Molecularly imprinted polymers (MIPs) and metal-organic frameworks (MOFs) have been widely used in the adsorption and detection of food pollutants. However, traditional MIPs have problems such as uneven loading of the imprinted cavity and slow mass transfer efficiency. While the adsorption of MOFs has low specificity and cannot accurately identify target molecules. Therefore, some researchers have taken advantage of the high specific recognition abilities of MIPs and the large specific surface areas, high porosity and easy functionalization of MOFs to combine MOFs with MIPs, and have achieved a series of important results in the field of food safety detection. This paper reviews the research progress of the application of MOFs-MIPs in the field of food safety detection from 2019 to 2024. It furnishes researchers interested in this domain with a rapid and comprehensive grasp of the latest research status, it also offers them a chance to anticipate future development trends, thereby supporting the continuous advances of MOFs-MIPs in food safety detection.

Evaluation of fish meal freshness using a metal-oxide semiconductor electronic nose combined with the long short-term memory feature extraction method.

To improve the classification and regression performance of the total volatile basic nitrogen (TVB-N) and acid value (AV) of different freshness fish meal samples detected by a metal-oxide semiconductor electronic nose (MOS e-nose), 402 original features, 62 manually extracted features, manually extracted and selected features by the RFRFE method, and the features extracted by the long short-term memory (LSTM) network were used as inputs to identify the freshness. The classification performance of the freshness grades and the estimation performance of the TVB-N and AV values of fish meal with different freshness were compared. According to the sensor response curve, preprocessing and feature extraction steps were first applied to the original data. Then, five classification algorithms and four regression algorithms were used for modeling. The results showed that a total of 30 features were extracted using the LSTM network, and the number of extracted features was significantly reduced. In the classification, the highest accuracy rate of 95.4% was obtained using the support vector machine method. In the regression, the least squares support vector regression method obtained the best root mean square error (RMSE). The coefficient of determination (R2), RMSE, and relative standard deviation (RSD) between the predicted value of TVBN and the actual value were 0.963, 11.01, and 7.9%, respectively. The R2, RMSE, and RSD between the predicted value of AV and the actual value were 0.972, 0.170, and 6.05%, respectively. The LSTM feature extraction method provided a new method and reference for feature extraction using an E-nose to identify other animal-derived material samples.

Preparation of dual recognition adsorbents based on molecularly imprinted polymers and aptamer for highly sensitive recognition and enrichment of ochratoxin A.

In light of the significant risks that mycotoxins posed to public health and environmental safety, this research developed an adsorbent MIPs/Apt/AuNPs@ZIF-67 (MA-AZ) utilizing a dual-recognition approach combining molecularly imprinted polymers (MIPs) and aptamer (Apt). This innovative method enabled the effective and highly selective recognition and enrichment of ochratoxin A (OTA). ZIF-67 was utilized as a carrier with a substantial specific surface area, and gold nanoparticles (AuNPs) were loaded on its surface to fix the thiol-modified Apt on the surface of the carrier. Then, an initiator was used to initiate a polymerization reaction, and the generated MIPs coated Apt/AuNPs@ZIF-67, thereby synthesizing the MA-AZ with a "synergistic recognition" effect. The Apt significantly increased the number of recognition sites within the imprinted cavities, and MIPs played roles in identifying targets, fixing and protecting Apt. The combination of the both produced the effect of "1+1>2". The study on the adsorption performance of MA-AZ found that the adsorption capacity of MA-AZ could reach 65.1 mg/g, and the imprinted factor was 5.48. In addition, MA-AZ exhibited excellent stability, specificity, reusability and recovery rate. Thus, this study offers valuable insights for the recognition and enrichment of hazardous substances, and helps to promote the rapid development of safety detection.

Multifunctional nanoenzyme lateral flow immunoassay strip for rapid and ultrasensitive detection of carbofuran in vegetables.

A lateral flow immunoassay strip (LFIAS) is one of the most frequently rapid test technologies for carbofuran (CAR). Nevertheless, the LFIAS has a poor quantitative capability and low sensitivity. And, it also requires often complex sample handling steps, making testing time longer. In this study, Fe3O4 nanoparticles were successively modified with MIL-100(Fe)-based metal-organic framework (MOF) and chloroplatinic acid hexahydrate to obtain a core-shell complex of Fe3O4-MOF-Pt. The complex had a peroxidase-mimicking activity catalytic function that enabled signal amplification and sensitivity enhancement. Upon coupling with carbofuran monoclonal antibody (CAR-mAb), the magnetic separation properties of the probe enabled target-specific enrichment. The LFIAS based on Fe3O4-MOF-Pt nanocomposites could detect CAR in the range of 0.25-50 ng mL-1 with a limit of detection (LOD) of 0.15 ng mL-1, enabling colorimetric and catalytic analysis. In addition, the method showed high specificity and stability for detecting CAR in various vegetables, and recovery rates of the spiked samples were 91.40%-102.40%. In conclusion, this study provided one-stop detection of "target enrichment-visual inspection". While lowering the LOD, it reduced the detection time and improved the detection efficiency. The multifunctional Fe3O4-MOF-Pt nanocomposite provides an idea for the construction of novel multifunctional probes to improve the detection performance of conventional LFIAS.

Enhanced detection of Aspergillus flavus in peanut kernels using a multi-scale attention transformer (MSAT): Advancements in food safety and contamination analysis.

In this study, a multi-scale attention transformer (MSAT) was coupled with hyperspectral imaging for classifying peanut kernels contaminated with diverse Aspergillus flavus fungi. The results underscored that the MSAT significantly outperformed classic deep learning models, due to its sophisticated multi-scale attention mechanism which enhanced its classification capabilities. The multi-scale attention mechanism was utilized by employing several multi-head attention layers to focus on both fine-scale and broad-scale features. It also integrated a series of scale processing layers to capture features at different resolutions and incorporated a self-attention mechanism to integrate information across different levels. The MSAT model achieved outstanding performance in different classification tasks, particularly in distinguishing healthy peanut kernels from those contaminated with aflatoxigenic fungi, with test accuracy achieving 98.42±0.22%. However, it faced challenges in differentiating peanut kernels contaminated with aflatoxigenic fungi from those with non-aflatoxigenic contamination. Visualization of attention weights explicitly revealed that the MSAT model's multi-scale attention mechanism progressively refined its focus from broad spatial-spectral features to more specialized signatures. Overall, the MSAT model's advanced processing capabilities marked a notable advancement in the field of food quality safety, offering a robust and reliable tool for the rapid and accurate detection of Aspergillus flavus contaminations in food.

Impact of sea ice on the physicochemical characteristics of marine aerosols in the Arctic Ocean.

Marine aerosols (MA) can be influenced by sea ice concentration, potentially playing a pivotal role in the formation of cloud condensation nuclei and exerting an impact on regional climate. In this study, a high-resolution aerosol observation system was employed to measure the concentration and size of aerosols in the floating ice region and seawater region of the Arctic Ocean during the 8th and 9th Chinese Arctic Expedition Research Cruise. The identification of aerosol sources was conducted using a modified positive definite matrix factorization method and a backward air mass trajectory model. Two types of MA including the sea-salt aerosol (SSA) and the marine biogenic aerosol (BA) were identified and their concentrations were calculated. Then the physical-chemical characteristics of MA in the floating ice region and seawater region were compared under normalized conditions (-2.5 °C < T < -0.1 °C; 5.80 m/s < WS < 10.95 m/s) to discern the impact of sea ice. A unimodal distribution was observed for MA number concentration with a dominant peak ranging from 0.5 µm to 1.0 µm in size range. The findings revealed that the presence of sea ice cover led to a significant reduction of 52.2 % in the number concentration of SSA, while exerting minimal influence on its composition. BA number concentration in the floating ice region was 33.3 % higher than that in the seawater region. Strong winds (wind speed >6.5 m/s) transported organic matter and nutrients entrapped in sea ice into the atmosphere, leading to an increase in BA concentration. However, the presence of sea ice cover hampered the exchange of biogenic gases between the ocean and air, resulting in a reduction of secondary BA formation. Our study elucidates the correlation between MA release and sea ice coverage in the Arctic Ocean, thereby establishing a theoretical foundation for climate prediction models.

An exonuclease III-driven dual-mode aptasensor based on Au-Pd@Fc nanozyme and magnetic separation pretreatment for aminoglycoside antibiotics detection.

A novel dual-mode aptasensor was constructed for aminoglycoside antibiotics (AAs) detection by using a broad-spectrum aptamer as a biorecognition element, and Au-Pd@Fc functionalized by signal DNA as nanoprobes. In electrochemical mode, the target-induced cyclic amplification reaction run under the action of exonuclease-III, which increased the number of nanoprobes on the electrode surface. AAs could be quantitatively detected with LOD of 0.0355 ± 0.00613 nM. In colorimetric mode, the Au-Pd@Fc nanozyme catalyzed the color reaction of 3,3',5,5'-tetramethylbenzidine. The blue-shifted absorbance will be observed with the change of AAs concentration, and the LOD was 0.0458 ± 0.00572 nM. Furthermore, a magnetic molecular-imprinted material capable of specific adsorption of AAs was prepared on milk sample pretreatment. The aptasensor was used to detect 10 kinds of AAs in milk and the recoveries were 97.19 ± 4.41% âˆ¼ 98.70 ± 4.45% and 96.38 ± 3.53%-97.54 ± 4.13% in electrochemical and colorimetric methods. This work provided a theoretical basis for the application of aptamers in simultaneous detection of antibiotics.

Wheel-Running Exercise Alleviates Anxiety-Like Behavior via Down-Regulating S-Nitrosylation of Gephyrin in the Basolateral Amygdala of Male Rats.

Physical exercise has beneficial effect on anxiety disorders, but the underlying molecular mechanism remains largely unknown. Here, it is demonstrated that physical exercise can downregulate the S-nitrosylation of gephyrin (SNO-gephyrin) in the basolateral amygdala (BLA) to exert anxiolytic effects. It is found that the level of SNO-gephyrin is significantly increased in the BLA of high-anxiety rats and a downregulation of SNO-gephyrin at cysteines 212 and 284 produced anxiolytic effect. Mechanistically, inhibition of SNO-gephyrin by either Cys212 or Cys284 mutations increased the surface expression of GABAAR γ2 and the subsequent GABAergic neurotransmission, exerting anxiolytic effect in male rats. On the other side, overexpression of neuronal nitric oxide synthase in the BLA abolished the anxiolytic-like effects of physical exercise. This study reveals a key role of downregulating SNO-gephyrin in the anxiolytic effects of physical exercise, providing a new explanation for protein post-translational modifications in the brain after exercise.

Spatioselective Occlusion of Copolymer Nanoparticles within Calcite Crystals Generates Organic-Inorganic Hybrid Materials with Controlled Internal Structures.

Efficient occlusion of particulate additives into a single crystal has garnered an ever-increasing attention in materials science because it offers a counter-intuitive yet powerful platform to make crystalline nanocomposite materials with emerging properties. However, precisely controlling the spatial distribution of the guest additives within a host crystal remains highly challenging. We herein demonstrate a unique, straightforward method to engineer the spatial distribution of copolymer nanoparticles within calcite (CaCO3) single crystals by judiciously adjusting initial [Ca2+] concentration used for the calcite precipitation. More specifically, polymerization-induced self-assembly is employed to synthesize well-defined and highly anionic poly(3-sulfopropyl methacrylate potassium)41-block-poly(benzyl methacrylate)500 [PSPMA41-PBzMA500] diblock copolymer nanoparticles, which are subsequently used as model additives during the growth of calcite crystals. Impressively, such guest nanoparticles are preferentially occluded into specific regions of calcite depending on the initial [Ca2+] concentration. These unprecedented phenomena are most probably caused by dynamic change in electrostatic interaction between Ca2+ ions and PSPMA41 chains based on systematic investigations. This study not only showcases a significant advancement in controlling the spatial distribution of guest nanoparticles within host crystals, enabling the internal structure of composite crystals to be rationally tailored via a spatioselective occlusion strategy, but also provides new insights into biomineralization.

Novel cross-linkable fluorescent probe with oriented antibody to enhance lateral immunoassay strip for the detection of acetamiprid.

Time-resolved fluorescent lateral immunoassay strip (TRFLIS) is a reliable and rapid method for detecting acetamiprid. However, its sensitivity is often affected by the structural patterns and stability of the fluorescent probe. Researchers have shown significant interests in using goat anti-mouse IgG (GaMIgG) which is indirectly bound to time-resolved fluorescent microsphere (TRFM) and antibody. This allowed for oriented modification of the antibody. However, the stability of fluorescent probe in this binding mode remained unexplored. Herein, 1-ethyl-(3-dimethylaminopropyl) carbodiimide hydrochloride was innovatively used as a cross-linking agent to enhance the binding of antibody to GaMIgG, which improved the stability of the fluorescent probe. Under optimal working conditions, this strategy exhibited a wide linear response range of 5-700 ng/mL. Its limit of detection (LOD) was 0.62 ng/mL, the visual LOD was 5 ng/mL, and the limit of quantification (LOQ) of 2.06 ng/mL. Additionally, under tomato matrix, leek matrix and Chinese cabbage matrix, the linear response ranges were 5-400, 5-300, and 5-700 ng/mL, with LODs of 0.16, 0.60, and 0.41 ng/mL, with LOQs of 0.53, 2.01 and 1.37 ng/mL, respectively. In conclusion, this strategy effectively reduced the dosage of acetamiprid antibody compared with TRFM directly linking acetamiprid antibody, and greatly increased the sensitivity of TRFLIS. Meanwhile, it demonstrated outstanding specificity and accuracy in acetamiprid detection and had been successfully applied to vegetable samples. This method enables rapid and accurate detection of large-volume samples by combining qualitative and quantitative methods. As such, it has great potential in the development of low-cost and high-performance immunochromatographic platforms.

Novel ratiometric electrochemical aptasensor based on broad-spectrum aptamer recognition for simultaneous detection of penicillin antibiotics in milk.

To effectively monitor multi-residues of penicillin antibiotics (PENs) in milk, we developed a novel ratiometric electrochemical aptasensor enabling simultaneous detection of PENs. The aptasensor employed a broad-spectrum aptamer as a recognition element, niobium carbide functionalized with methylene blue (Nb2C-MB) as a reference signal generator, and a ferrocene-labeled aptamer (Fc-Apt) as an output signal. Electrodes were modified with Fe-N-C doped carbon nanotubes (Fe-N-C-CNTs) to amplify detection signals further. During detection, Fc-Apt binding to PENs decreased Fc current intensity (IFc) and increased MB current intensity (IMB). The simultaneous detection of PENs was achieved using IMB/IFc as a quantitative signal. Under optimal conditions, a good linear relationship between IMB/IFc and antibiotic concentration was observed, indicating the aptasensor had a robustness. The limits of detection of aptasensor for four penicillin antibiotics and their mixed targets were 0.093-0.191 nM. This work provides a new approach to multi-residue detection of the same class of antibiotics.

X-ray activated near-infrared persistent luminescence nanoparticles for trimodality in vivo imaging.

As promising luminescence nanoparticles, near-infrared (NIR) persistent luminescence nanoparticles (PLNPs) have received extensive attention in the field of high-sensitivity bioimaging in recent years. However, NIR PLNPs face problems such as short excitation wavelengths and single imaging modes, which limit their applications in in vivo reactivated imaging and multimodal imaging. Here, we report for the first time novel Gd2GaTaO7:Cr3+,Yb3+ (GGTO) NIR PLNPs that integrate X-ray activated NIR persistent luminescence (PersL), high X-ray attenuation and excellent magnetic properties into a single nanoparticle (NP). In this case, Cr3+ is used as the luminescence center. The co-doped Yb3+ and coating effectively enhance the X-ray activated NIR PersL. At the same time, the presence of the high-Z element Ta also makes the GGTO NPs exhibit high X-ray attenuation performance, which can be used as a CT contrast agent to achieve in vivo CT imaging. In addition, since the matrix contains a large amount of Gd, the GGTO NPs show remarkable magnetic properties, which can realize in vivo MR imaging. GGTO NPs combine the trimodal benefits of X-ray reactivated PersL, CT and MR imaging and are suitable for single or combined applications that require high sensitivity and spatial resolution imaging.

Periodate oxidation-mediated nanocelluloses: Preparation, functionalization, structural design, and applications.

In recent years, the remarkable progress in nanotechnology has ignited considerable interest in investigating nanocelluloses, an environmentally friendly and sustainable nanomaterial derived from cellulosic feedstocks. Current research primarily focuses on the preparation and applications of nanocelluloses. However, to enhance the efficiency of nanofibrillation, reduce energy consumption, and expand nanocellulose applications, chemical pre-treatments of cellulose fibers have attracted substantial interest and extensive exploration. Various chemical pre-treatment methods yield nanocelluloses with diverse functional groups. Among these methods, periodate oxidation has garnered significant attention recently, due to the formation of dialdehyde cellulose derived nanocellulose, which exhibits great promise for further modification with various functional groups. This review seeks to provide a comprehensive and in-depth examination of periodate oxidation-mediated nanocelluloses (PONCs), including their preparation, functionalization, hierarchical structural design, and applications. We believe that PONCs stand as highly promising candidates for the development of novel nano-cellulosic materials.

Equilibrium Moisture Mediated Esterification Reaction to Achieve Over 100% Lignocellulosic Nanofibrils Yield.

Lignocellulosic nanofibrils (LCNFs) isolation is recognized as an efficient strategy for maximizing biomass utilization. Nevertheless, achieving a 100% yield presents a formidable challenge. Here, an esterification strategy mediated by the equilibrium moisture in biomass is proposed for LCNFs preparation without the use of catalysts, resulting in a yield exceeding 100%. Different from anhydrous chemical thermomechanical pulp (CTMP0%), the presence of moisture (moisture content of 7 wt%, denoted as CTMP7%) introduces a notably distinct process for the pretreatment of CTMP, comprising the initial disintegration and the post-esterification steps. The maleic acid, generated through maleic anhydride (MA) hydrolysis, degrades the recalcitrant lignin-carbohydrate complex (LCC) structures, resulting in esterified CTMP7% (E-CTMP7%). The highly grafted esters compensate for the mass loss resulting from the partial removal of hydrolyzed lignin and hemicellulose, ensuring a high yield. Following microfluidization, favorable LCNF7% with a high yield (114.4 ± 3.0%) and a high charge content (1.74 ± 0.09 mmol g-1) can be easily produced, surpassing most previous records for LCNFs. Additionally, LCNF7% presented highly processability for filaments, films, and 3D honeycomb structures preparation. These findings provide valuable insights and guidance for achieving a high yield in the isolation of LCNFs from biomass through the mediation of equilibrium moisture.

Stable detection of diazinon residues in vegetables by an electrochemiluminescent aptasensor based on the in-situ production of H2O2 from dual-catalytic glucose.

Stable detection of diazinon (DZN) residues in vegetables is important for food safety. In this work, an electrochemiluminescence (ECL) aptasensor with dual-catalytic glucose in-situ production of H2O2 was constructed for the stable detection of DZN in vegetables. Firstly, MWCNTs@MB was prepared using π-π stacking interactions between methylene blue (MB) and multi-walled carbon nanotubes (MWCNTs) to enhance the loading of MB on an electrode and thus catalyze the generation of H2O2 from glucose. Secondly, Cu2O@AuNPs was formed by loading AuNPs on the surface of Cu2O through spontaneous reduction reaction, which improved the interfacial charge transfer, Cu2O nano-enzyme had glucose oxidase mimicking activity and could further catalyze the production of more H2O2 from glucose. MWCNTs@MB and Cu2O@AuNPs played a key role in the in-situ generation of co-reacting reagent H2O2, which solved the problem of unstable detection caused by the easy decomposition of the H2O2 solution added to the luminescence system. In addition, the aptamer was immobilized on the electrode surface by forming Au-S bonds with Cu2O@AuNPs. As a result, the ECL aptasensor performed good linearity in 1.00 pg mL-1-1.00 µg mL-1 and a low limit of detection (LOD) to 0.39 pg mL-1 (S/N = 3). This work provided an effective method for the accurate and stable detection of DZN residues in vegetables, which was of great significance in ensuring food safety and assessing the environmental risk of DZN.

Prediction of total volatile basic nitrogen (TVB-N) in fish meal using a metal-oxide semiconductor electronic nose based on the VMD-SSA-LSTM algorithm.

BACKGROUND: The total volatile basic nitrogen (TVB-N) is the main indicator for evaluating the freshness of fish meal, and accurate detection and monitoring of TVB-N is of great significance for the health of animals and humans. Here, to realize fast and accurate identification of TVB-N, in this article, a self-developed electronic nose (e-nose) was used, and the mapping relationship between the gas sensor response characteristic information and TVB-N value was established to complete the freshness detection. RESULTS: The TVB-N variation curve was decomposed into seven subsequences with different frequency scales by means of variational mode decomposition (VMD). Each subsequence was modelled using different long short-term memory (LSTM) models, and finally, the final TVB-N prediction result was obtained by adding the prediction results based on different frequency components. To improve the performance of the LSTM, the sparrow search algorithm (SSA) was used to optimize the number of hidden units, learning rate and regularization coefficient of LSTM. The prediction results indicated that the high accuracy was obtained by the VMD-LSTM model optimized by SSA in predicting TVB-N. The coefficient of determination (R2), the root-mean-squared error (RMSE) and relative standard deviation (RSD) between the predicted value and the actual value of TVBN were 0.91, 0.115 and 6.39%, respectively. CONCLUSIONS: This method improves the performance of e-nose in detecting the freshness of fish meal and provides a reference for the quality detection of e-nose in other materials. © 2024 Society of Chemical Industry.