Organic Cation Receptor for Colorimetric Lateral Flow Device: Detection of Zearalenone in Food Samples

Designing flexible aliphatic linker based molecular imprinted covalent organic framework for rapid and selective extraction and detection of trace zearalenone

Food and environment contaminations by zearalenone (ZEN) has aroused serious issues in public health. Sensitive and accurate detection of ZEN remains a daunting challenge due to complex interference and low residue in real samples. Herein, we report a novel molecular imprinted covalent organic framework with flexible aliphatic linkers (ALCOF-MIP) for rapid and selective extraction of ZEN in real samples. Flexible aliphatic linkers were employed to regulate the molecular conformation and enhance hydrophily, enabling ALCOF-MIP to possess high selectivity and fast kinetics for ZEN extraction. ALCOF-MIP with selective imprinting sites displayed the maximum adsorption capacity for ZEN (1250 mg g-1, exceeding most of reported adsorbents). Furthermore, the ALCOF-MIP based solid-phase extraction coupled with high-performance liquid chromatography gave a wide linear range (1-500 ng mL-1), low detection limit (0.06 ng mL-1) and high precision (≤3.2 %). The recovery of spiked ZEN in real samples ranged from 90.7 % to 99.1 %. The proposed method is promising for monitoring mycotoxin residues and assessing food safety without matrix interferences.

Tailoring shell thickness in Au@Cu2O nanoparticles for enhanced mimetic peroxidase activity: a colorimetric aptasensor for zearalenone detection

Zearalenone (ZEN), a prevalent mycotoxin in agricultural crops, poses significant risks to human and animal health due to its bioaccumulation potential within the food chain. In this study, Au@Cu2O core-shell nanoparticles with precisely controlled Cu2O shell thickness were synthesized through a gold nanoparticle (AuNPs)-mediated self-assembly strategy by modulating the amount of AuNPs. Systematic analysis revealed an inverse correlation between peroxidase-like activity and shell thickness. Consequently, a high-sensitivity colorimetric aptasensor for ZEN detection was developed via the integration of Au@Cu2O nanoparticles with ZEN-specific aptamers. The Au@Cu2O nanoparticles function as signal amplifiers, while the aptamers provide target specificity. Under optimal conditions, the aptasensor demonstrated a linear dynamic range of 0.0005-5 μg/L for ZEN, with colorimetric signal intensities exhibiting exceptional specificity for ZEN, with negligible cross-reactivity to co-occurring mycotoxins (AFB1, AFB2, OTA, DON, T-2), while achieving stable detection in real agricultural matrices, including wheat flour and cornmeal. Hence, this work not only offers a novel strategy for ZEN monitoring in food but also advances the rational design of core-shell nanomaterials for biosensing applications.

Machine learning driven metal oxide-based portable sensor array for on-site detection and discrimination of mycotoxins in corn sample

Cereals, grains, and feedstuffs are prone to contamination by fungi during various stages from growth to storage. These fungi may produce harmful mycotoxins impacting food quality and safety. Thus, the development of quick and reliable methods for on-site application is crucial for ensuring food safety and quality monitoring. Herein, we have developed an efficient sensor array based on hierarchically modified metal oxides with azodye-based metal complexes for on-site detection and segregation of harmful mycotoxins present in corn samples. The functionalized material has been fully characterized utilizing various sophisticated techniques. The sensor array successfully detected and differentiated five different mycotoxins with 100 % efficiency, validated by linear discriminant analysis (LDA) score plots. The limit of detection, as determined from calibration curves, ranges from 0.02 to 0.09 ppm for the respective mycotoxins. Additionally, the sensor array has also demonstrated 100 % accuracy in discriminating binary and ternary ratios of mycotoxins in real sample analyses.

Pyrene functionalized organic cation receptor-based "turn-on" fluorescence approach for monitoring of chlorpyrifos in food, soil, and water samples

BACKGROUND

The unregulated use of pesticides by farmers, for crop productivity results in widespread contamination of organophosphates in real environmental samples, which is a growing societal concern about their potential health effects. The conventional approaches for the monitoring these organophosphate-based pesticides which include immunoassays, electrochemical methods, immunosensors, various chromatography techniques, along with some spectroscopic methods, are either costly, sophisticated, or involves the use of different metal complexes. Therefore, there is an urgent need for sensitive, quick, and easy-to-use detection techniques for the screening of widely used organophosphate-based pesticides.

RESULTS

Herein, we demonstrates the metal-free detection of CPF pesticide in aqueous medium, based on the organic nanoparticles of benzimidazole-based cationic receptor (R1-ONPs), and thoroughly analyzed using advanced techniques such as AFM, FESEM, and DLS etc. The photophysical investigations revealed that developed R1-ONPs exhibited high selectivity towards chlorpyrifos with an enhancement in fluorescence emission. Further, the observed pyrene excimer-based "turn-on" fluorescence mechanism, and the interaction between developed sensor and chlorpyrifos has been validated utilizing 1H, and 31P NMR spectroscopy. The developed sensor can effectively quantify chlorpyrifos up to a detection limit of 18.9 nM (3σ method) with a range of 0-120 μM as well as below the cutoff limit set by FAO. Moreover, the real-time application of developed sensor (R1-ONPs) was evaluated to monitor chlorpyrifos in spiked food, water, and soil samples with good (%) recovery.

SIGNIFICANCE

The development of metal-free, pyrene-excimer-based "Turn-On" fluorescent sensor offers a novel, eco-friendly strategy for the detection of chlorpyrifos in aqueous medium. Additionally, its ability to quantify the chlorpyrifos at levels as low as those set by FAO makes it more efficient tool for monitoring the environmental toxicity ensuring better protection for human, and animal health.

Fluorescent Ionic Liquid Aggregates: A Self-Assembled Approach for Pesticide Detection and Catalysis

The unregulated use of pesticides, industrial discharge of heavy metals, waste, and agricultural runoff may contaminate surface water and groundwater, consequently threatening ecosystems and human health. Thus, the sensitive detection and degradation of pesticides are essential for safety. In this context, herein, we have developed benzimidazolium-based fluorescent surfactant assemblies TA-1/SDS and TA-2/SDBS, which exhibit aggregation-induced emission enhancement in an aqueous medium. The aggregates (TA-1/SDS and TA-2/SDBS) displayed a turn-on emission response upon interaction with carbendazim and azamethiphos with limits of detection 7.5 and 7.8 nM, respectively. The FE-SEM and AFM studies revealed that TA-1/SDS and TA-2/SDBS undergo self-assembly with the addition of AZA and CBZ, resulting in the formation of dendritic structures. In addition to the quantification of AZA and CBZ, TA-1/SDS and TA-2/SDBS have also been evaluated to degrade both pesticides and validated using 31P NMR spectroscopy and LC-MS spectrometry.

Benzimidazolium Salt Modified Microporous Silica-Coupled Iron Oxide Nanoparticles: Material Engineered for Nitrate Removal

Today's extensive use of inorganic fertilizers in agricultural techniques has increased the concentration of nitrate in drinking water beyond safety limits, causing serious health problems in humans such as thyroidism and methemoglobinemia. Therefore, the present work describes the synthesis of a benzimidazolium salt-based fluorescent chemosensor (KG3) via a multistep synthesis which detects nitrate ions in aqueous medium. This was validated using various analytical techniques such as fluorescence spectroscopy, UV-visible spectroscopy, and electrochemical studies with a detection limit of 0.032 μM without any interference from other active water pollutants. Subsequently, KG3 is further modified with the help of iron oxide nanoparticles (Fe3O4 NPs) and silica to obtain the SiO2@Fe3O4-KG3 nanocomposite, which was immobilized over a polyether sulfone membrane and evaluated for removal of nitrate ions from groundwater with a removal efficiency of 96%. Moreover, the engineered composite membrane can serve as a solid-state fluorescence sensor to detect NO3- ions, which was demonstrated through a portable mobile-based prototype employing a hue, saturation, and value parameter model.

A potential-controlled electrochromic visual biosensor based on distance readout for zearalenone detection

In this work, a potential-controlled electrochromic visual biosensor was developed for detecting zearalenone (ZEN) using a distance readout strategy. The sensor chip includes a square detection area and a folded signal output area created with laser etching technology. The detection area is modified with graphene oxide and ZEN aptamer, while Prussian blue (PB) is electrodeposited onto the signal output channel. When an appropriate voltage is applied, PB in the signal output area is reduced to colorless Prussian white (PW). The target ZEN molecules have the capability to release aptamers from graphene oxide (GO) surface in the detection area, resulting in a subsequent change in the potential of the visual signal output channel. This change determines the length of the channel that changes from blue to colorless, with the color change distance being proportional to the ZEN concentration. Using this distance readout strategy, ZEN detection within the range of 1 ng/mL to 300 ng/mL was achieved, with a detection limit of 0.29 ng/mL.

Decentralized food safety and authentication on cellulose paper-based analytical platform: A review

Food safety and authenticity analysis play a pivotal role in guaranteeing food quality, safeguarding public health, and upholding consumer trust. In recent years, significant social progress has presented fresh challenges in the realm of food analysis, underscoring the imperative requirement to devise innovative and expedient approaches for conducting on-site assessments. Consequently, cellulose paper-based devices (PADs) have come into the spotlight due to their characteristics of microchannels and inherent capillary action. This review summarizes the recent advances in cellulose PADs in various food products, comprising various fabrication strategies, detection methods such as mass spectrometry and multi-mode detection, sampling and processing considerations, as well as applications in screening food safety factors and assessing food authenticity developed in the past 3 years. According to the above studies, cellulose PADs face challenges such as limited sample processing, inadequate multiplexing capabilities, and the requirement for workflow integration, while emerging innovations, comprising the use of simplified sample pretreatment techniques, the integration of advanced nanomaterials, and advanced instruments such as portable mass spectrometer and the innovation of multimodal detection methods, offer potential solutions and are highlighted as promising directions. This review underscores the significant potential of cellulose PADs in facilitating decentralized, cost-effective, and simplified testing methodologies to maintain food safety standards. With the progression of interdisciplinary research, cellulose PADs are expected to become essential platforms for on-site food safety and authentication analysis, thereby significantly enhancing global food safety for consumers.

Development of a "Signal-On" Fluorescent Aptasensor for Highly Selective and Sensitive Detection of ZEN in Cereal Products Using Nitrogen-Doped Carbon Dots Based on the Inner Filter Effect

This study aimed to develop a novel fluorescent aptasensor for the quantitative detection of zearalenone (ZEN), addressing the limitations of conventional detection techniques in terms of speed, sensitivity, and ease of use. Nitrogen-doped carbon dots (N-CDs) were synthesized via the hydrothermal method, resulting in spherical particles with a diameter of 3.25 nm. These N-CDs demonstrated high water solubility and emitted a bright blue light at 440 nm when excited at 355 nm. The fluorescence of N-CDs was quenched by dispersed gold nanoparticles (AuNPs) through the inner filter effect, while aggregated AuNPs induced by NaCl did not affect the fluorescence of N-CDs. The aptamer could protect AuNPs from NaCl-induced aggregation, but the presence of ZEN weakened this protective effect. Based on this principle, optimal conditions for ZEN detection included 57 mM NaCl, 12.5 nM aptamer concentration, incubation of AuNPs with NaCl for 15 min in Tris-EDTA(TE) buffer, and incubation of aptamer with ZEN and NaCl for 30 min. Under these optimized conditions, the "signal-on" fluorescent aptasensor for ZEN detection showed a linear range of 0.25 to 200 ng/mL with a low detection limit of 0.0875 ng/mL. Furthermore, the developed aptasensor exhibited excellent specificity and could rapidly detect ZEN in corn flour samples or corn oil, achieving satisfactory recovery rates ranging from 84.7% to 108.6%. Therefore, this study presents an economical, convenient, sensitive, and rapid method for accurately quantifying ZEN in cereal products.

Ultrasensitive detection of zearalenone based on electrochemiluminescent immunoassay with Zr-MOF nanoplates and Au@MoS2 nanoflowers

In this work, an effective competitive-type electrochemiluminescence (ECL) immunosensor was constructed for zearalenone determination by using Zr-MOF nanoplates as the ECL luminophore and Au@MoS2 nanoflowers as the substrate material. Zr-MOF have an ultra-thin sheet-like structure that accelerates the transfer of electrons, ions and co-reactant intermediates, which exhibited strong and stable anodic luminescence. The three-dimensional Au@MoS2 nanoflowers would form a thin film modification layer on the glassy carbon electrode (GCE). And its good electrical conductivity and higher specific surface area utilization further improving the sensitivity of the ECL immunosensor. Under the optimized conditions, the proposed immunosensor exhibited satisfactory stability, sensitivity and accuracy, and its ECL signal was proportional to the logarithm of ZEN concentration (0.0001-100 ng/mL) and the limit of detection (LOD) was 0.034 pg/mL. In addition, the results of recovery experiment acquired for wheat flour and pig urine samples further proved the feasibility of the immunosensor for the detection of real samples, indicating its potential for ultrasensitive detection of ZEN.

Programmable DNA tweezers-SDA for ultra-sensitive signal amplification fluorescence sensing strategy

BACKGROUND

DNA tweezers, classified as DNA nanomachines, have gained prominence as multifunctional biosensors due to their advantages, including a straightforward structure, response mechanism, and high programmability. While the DNA tweezers demonstrate simultaneous, rapid, and stable responses to different targets, their detection sensitivity requires enhancement. Some small molecules, such as mycotoxins, often require more sensitive detection due to their extremely high toxicity. Therefore, more effective signal amplification strategies are needed to further enhance the sensitivity of DNA tweezers in biosensing.

RESULTS

We designed programmable DNA tweezers that detect small-molecule mycotoxins and miRNAs through simple sequence substitution. While the DNA tweezers demonstrate simultaneous, rapid, and stable responses to different targets, their detection sensitivity requires enhancement. We introduced the Strand Displacement Amplification (SDA) technique to address this limitation, proposing a strategy of novel programmable DNA tweezers-SDA ultrasensitive signal amplification fluorescence sensing. We specifically investigate the effectiveness of this approach concerning signal amplification for two critical mycotoxins: aflatoxin B1 (AFB1) and zearalenone (ZEN). Results indicate that the detection ranges of AFB1 and ZEN via this strategy were 1-10,000 pg mL -1 and 10-100,000 pg mL -1, respectively, with corresponding detection limits of 0.933 pg mL -1 and 1.07 pg mL -1. Compared with the DNA tweezers direct detection method for mycotoxins, the newly constructed programmable DNA tweezers-SDA fluorescence sensing strategy achieved a remarkable 104-fold increase in the detection sensitivity for AFB1 and ZEN.

SIGNIFICANCE

The constructed programmable DNA tweezers-SDA ultrasensitive signal-amplified fluorescence sensing strategy exhibits excellent detection performance for mycotoxins. The superb versatility of this strategy allows the developed method to be easily used for detecting other analytes by simply replacing the aptamer and cDNA, which has incredible potential in various fields such as food safety screening, clinical diagnostics, and environmental analysis.

A sensitive electrochemical aptasensor for zearalenone detection based on target-triggered branched hybridization chain reaction and exonuclease I-assisted recycling

Traditional methods for detecting antibiotic and mycotoxin residues rely on large-scale instruments, which are expensive and require complex sample pretreatment processes and professional operators. Although aptamer-based electrochemical sensors have the advantages of simplicity, speed, low cost, and high sensitivity, most aptamer-based sensors lack a signal amplification strategy due to their direct use of aptamers as probes, resulting in insufficient sensitivity. To solve the sensitivity problem in the electrochemical detection process, a novel electrochemical sensing strategy was established for ultrasensitive zearalenone (ZEN) detection on the basis of exonuclease I (Exo I) and branched hybridization chain reaction (bHCR) to amplify the signal. The amplification strategy showed excellent analytical performance towards ZEN with a low detection limit at 3.1×10-12 mol/L and a wide linear range from 10-11 to 10-6 mol/L. Importantly, the assay was utilized in the corn powder samples with satisfactory results, holding promising applications in food safety detection and environmental monitoring.

Recent Advances in Recognition Receptors for Electrochemical Biosensing of Mycotoxins-A Review

Mycotoxins are naturally occurring toxic secondary metabolites produced by fungi in cereals and foodstuffs during the stages of cultivation and storage. Electrochemical biosensing has emerged as a rapid, efficient, and economical approach for the detection and quantification of mycotoxins in different sample media. An electrochemical biosensor consists of two main units, a recognition receptor and a signal transducer. Natural or artificial antibodies, aptamers, molecularly imprinted polymers (MIP), peptides, and DNAzymes have been extensively employed as selective recognition receptors for the electrochemical biosensing of mycotoxins. This article affords a detailed discussion of the recent advances and future prospects of various types of recognition receptors exploited in the electrochemical biosensing of mycotoxins.

Highly Sensitive Immunochromatographic Detection of Zearalenone Based on Ultrabright Red-Emitted Aggregation-Induced Luminescence Nanoprobes

Highly luminescent nanospheres have been demonstrated in enhancing the sensitivity of lateral flow immunoassay (LFIA) due to their loading numerous luminescent dyes. However, the photoluminescence intensities of existing luminescent nanospheres are limited due to the aggregation-caused quenching effect. Herein, highly luminescent aggregation-induced emission luminogens embedded nanospheres (AIENPs) with red emission were introduced as signal amplification probes of LFIA for quantitative detection of zearalenone (ZEN). Optical properties of red-emitted AIENPs were compared with time-resolved dye-embedded nanoparticles (TRNPs). Results showed that red-emitted AIENPs have stronger photoluminescence intensity on the nitrocellulose membrane and superior environmental tolerance. Additionally, we benchmarked the performance of AIENP-LFIA against TRNP-LFIA using the same set of antibodies, materials, and strip readers. Results showed that AIENP-LFIA exhibits good dynamic linearity with the ZEN concentration from 0.195 to 6.25 ng/mL, with half competitive inhibitory concentration (IC₅₀) and detection of limit (LOD) at 0.78 and 0.11 ng/mL, respectively. The IC₅₀ and LOD are 2.07- and 2.36-fold lower than those of TRNP-LFIA. Encouragingly, the precision, accuracy, specificity, practicality, and reliability of this AIENP-LFIA for ZEN quantitation were further characterized. The results verified that the AIENP-LFIA has good practicability for the rapid, sensitive, specific, and accurate quantitative detection of ZEN in corn samples.

A high-performance Calix@ZnO based bifunctional nanomaterial for selective detection and degradation of toxic azinphos methyl in environmental samples

One of the key tenets of sustainable agriculture and food safety is the removal of toxic pesticides from the environment. However, developing reliable, affordable, and efficient methods for detecting and degrading pesticides into non-toxic degradable products remains an immediate matter of concern. Herein, we attempt to develop a strategy for the detection as well as degradation of highly toxic phosphorodithioate pesticide, Azinphos methyl (AZM), using hybrid zinc oxide nanoparticles (ZnO NPs). Considering the non-selectivity of bare ZnO and receptor R1, we have fabricated the heterocalixarene-based Calix (R1) over zinc oxide (ZnO) surface in situ via the sol-gel process. The synthesized heterocaliaxrene-modified ZnO (R1@ZnO) NPs show an excellent affinity for the selective and sensitive detection of AZM with a tremendously low limit of detection (68 mg L^-1) and no interference from other pesticides. Degradation of AZM was fully supported by fluorescence spectroscopy, scanning electron microscopy (SEM), ¹H NMR titrations, FTIR spectroscopy, cyclic voltammetry, and mass spectroscopy, which unequivocally confirmed the formation of non-toxic products. According to our findings, R1@ZnO NPs are sustainable nanomaterials that can be employed for environmental remediation since they operate in an aqueous medium.

Machine Learning-Based Analytical Systems: Food Forensics

Despite a large amount of money being spent on both food analyses and control measures, various food-borne illnesses associated with pathogens, toxins, pesticides, adulterants, colorants, and other contaminants pose a serious threat to human health, and thus food safety draws considerable attention in the modern pace of the world. The presence of various biogenic amines in processed food have been frequently considered as the primary quality parameter in order to check food freshness and spoilage of protein-rich food. Various conventional detection methods for detecting hazardous analytes including microscopy, nucleic acid, and immunoassay-based techniques have been employed; however, recently, array-based sensing strategies are becoming popular for the development of a highly accurate and precise analytical method. Array-based sensing is majorly facilitated by the advancements in multivariate analytical techniques as well as machine learning-based approaches. These techniques allow one to solve the typical problem associated with the interpretation of the complex response patterns generated in array-based strategies. Consequently, the machine learning-based neural networks enable the fast, robust, and accurate detection of analytes using sensor arrays. Thus, for commercial applications, most of the focus has shifted toward the development of analytical methods based on electrical and chemical sensor arrays. Therefore, herein, we briefly highlight and review the recently reported array-based sensor systems supported by machine learning and multivariate analytics to monitor food safety and quality in the field of food forensics.