Quantitative Detection Research Articles

Amplification-free and label-free rapid detection of Staphylococcus aureus using solution-gated graphene transistor-based DNA biosensor with hybridization enhancement by interface engineering

Staphylococcus aureus (S. aureus) is one of the leading causes of foodborne illnesses worldwide, posing a significant risk to food quality and safety. However, conventional detection methods often require complex amplification and labeling procedures, which are time consuming and expensive. In this study, an extremely sensitive electrochemical biosensor using a solution-gated graphene transistor (SGGT) was constructed for the amplification-free and label-free rapid detection of S. aureus by utilizing specific single-stranded DNA (ssDNA) to modify the gold (Au) sensing gate. This modified ssDNA was designed to hybridize with the target S. aureus DNA sequence. Interface engineering of the ssDNA-modified sensing gate via optimization of specific target and probe sequences was proposed to improve its hybridization efficiency. This enabled the sensitive quantitative detection of S. aureus DNA. The resulting biosensor exhibited excellent specificity in distinguishing non-complementary, 3-base/9-base DNA mismatch targets of S. aureus DNA and the specific DNA sequences of other common pathogenic bacteria. It also enabled the rapid detection of extracted target DNA sequences in solution (within 27 min) and had a low limit of detection (LoD) of 10−17 M over a wide linear detection range (10−17–10−8 M). Furthermore, the newly-developed biosensor facilitated the real-time and on-site detection of the S. aureus genome (ATCC 6538) with LoD of 10−17 M (103 CFU/mL) in a portable smart-sensing system. This suggests a promising future for the development of rapid, label-free, and amplification-free detection of foodborne illnesses using low-cost, highly sensitive SGGT DNA biosensors with appropriate functionalization and interface engineering of the sensing electrode.

Semiarbitrary qPCR for Sensitive Detection of Circulating miRNA via Terminal Deoxynucleotidyl Transferase-Assisted RNA-Primed DNA Polymerization.

Circulating microRNAs (miRNAs) have recently emerged as noninvasive disease biomarkers. Quantitative detection of circulating miRNAs could offer significant information for clinical diagnosis due to its significance in the development of biological processes. In response to the current challenges of circulating miRNA detection, we introduce a sensitive, selective, and versatile circulating miRNA detection strategy using terminal deoxynucleotidyl transferase (TdT)-catalyzed RNA-primed DNA polymerization (TCRDP) coupled with semiarbitrary qPCR (SAPCR). Semiarbitrary qPCR was first developed here to detect long fragment targets with only a short-known sequence or to detect a short fragment target after extension with terminal transferase. Besides, the subsequent results show that TdT has a preference for RNA, particularly for extending RNAs with purine-rich and unstructured ends. Consequently, utilizing this assay, we have successfully applied it to the quantitative analysis of circulating miR-122 in animal models, a sensitive and informative biomarker for drug-induced liver injury, and as low as 200 zmol of the target is detected with desirable specificity and sensitivity, indicating that the TCRDP-SAPCR can offer a promising platform for nucleic acids analysis.

Electrochemiluminescence Sensor Based on TPEA‐RuMOF: For Highly Selective and Sensitive Detection of Copper Ions

AbstractIn this study, we present the novel combination of AE‐TPEA with RuMOF to construct an electrochemiluminescence (ECL) sensor using a TPEA‐RuMOF composite material specifically for copper ions (Cu2+) detection. Using K2S2O8 as a co‐reactant, we explored the ECL behavior of the TPEA‐RuMOF modified electrode, enabling the quantitative detection of Cu2+. Remarkably, this sensor exhibited a wide linear range from 1×10−5 to 1×10−9 M (R2=0.998) and boasted a detection limit as low as 0.41 nM, which is considerably below the EPA (Environmental Protection Agency) permissible copper ion concentration in drinking water of <1.3 mg/L. our synthesized probe offers enhanced stability and selectivity in copper ion detection. This indicates its considerable potential for high‐performance copper ion detectors. We further validated the analytical applicability of this sensor using river water samples.

Estimation of Chlorophyll Content in Apple Leaves Infected with Mosaic Disease by Combining Spectral and Textural Information Using Hyperspectral Images

Leaf chlorophyll content (LCC) is an important indicator of plant nutritional status and can be a guide for plant disease diagnosis. In this study, we took apple leaves infected with mosaic disease as a research object and extracted two types of information on spectral and textural features from hyperspectral images, with a view to realizing non-destructive detection of LCC. First, the collected hyperspectral images were preprocessed and spectral reflectance was extracted in the region of interest. Subsequently, we used the successive projections algorithm (SPA) to select the optimal wavelengths (OWs) and extracted eight basic textural features using the gray-level co-occurrence matrix (GLCM). In addition, composite spectral and textural metrics, including vegetation indices (VIs), normalized difference texture indices (NDTIs), difference texture indices (DTIs), and ratio texture indices (RTIs) were calculated. Third, we applied the maximal information coefficient (MIC) algorithm to select significant VIs and basic textures, as well as the tandem method was used to fuse the spectral and textural features. Finally, we employ support vector regression (SVR), backpropagation neural network (BPNN), and K-nearest neighbors regression (KNNR) methods to explore the efficacy of single and combined feature models for estimating LCC. The results showed that the VIs model (R2 = 0.8532, RMSE = 2.1444, RPD = 2.6179) and the NDTIs model (R2 = 0.7927, RMSE = 2.7453, RPD = 2.2032) achieved the best results among the single feature models for spectra and texture, respectively. However, textural features generally exhibit inferior regression performance compared to spectral features and are unsuitable for standalone applications. Combining textural and spectral information can potentially improve the single feature models. Specifically, when combining NDTIs with VIs as input parameters, three machine learning models outperform the best single feature model. Ultimately, SVR achieves the highest performance among the LCC regression models (R2 = 0.8665, RMSE = 1.8871, RPD = 2.7454). This study reveals that combining textural and spectral information improves the quantitative detection of LCC in apple leaves infected with mosaic disease, leading to higher estimation accuracy.

Development of quantitative detection methods for four Alzheimer's disease specific biomarker panels using electrochemical immunosensors based on enzyme immunoassay.

Accurate and timely diagnosis of Alzheimer's disease (AD) is necessary to maximize the effectiveness of treatment and using biomarkers for diagnosis is attracting attention as a minimally invasive method with few side effects. Electrochemical immunosensor (EI) is a method that is in the spotlight in the medical and bioanalytical fields due to its portability and field usability. Here, we quantified four AD specific biomarkers using EIs based on enzyme immunoassay. We selected and developed quantitative methods for the biomarkers using screen-printed gold electrodes. For three biomarkers, quantification was performed using competition immunoassays in which antigen-antibody premix mixtures were applied to antigen-immobilized electrodes and the limit of detection (LOD) values were secured, 1.20 ng/ml, 1.30 ng/ml, and 1.74 ng/ml, respectively. For the other, a sandwich immunoassay using antibody pair was selected for quantification and LOD was also achieved as 0.077 ng/ml. All four biomarkers in buffer samples were successfully quantified and reliable R2 values were obtained, and reliable calibration curves were secured for three biomarkers in spiked human serum samples. The immunosensors developed and will be optimized are expected to be used in various fields, including detection of biomarkers for not only AD but also related diseases.

Determination of trace amounts of metobromuron herbicide residues in fruits by QuEChERS and DLLME methods

Food products have the potential to contain herbicide residues that may pose a threat to human health and the environment, and the determination of these residues at trace levels is extremely important. In this study, a rapid, simple, accurate and environmentally friendly DLLME-QuEChERS method was developed for the sensitive determination of metobromuron at trace levels in coconut-strawberry samples. Mass spectrometry coupled to gas chromatography was used to perform the analysis. Limit of detection (LOD) and limit of quantitation (LOQ) for the DLLME-GC-MS method providing a highly linear range with a coefficient of determination of >0.99, were found to be 4.2 and 13.9 ng/mL, respectively. Following QuEChERS and DLLME, recovery studies on coconut-strawberry samples showed that the developed method can be accurately applied to food matrices with the giving results close to 100 % and low standard deviation values.

Thermophilic Composting as a Means to Evaluate the Biodegradability of Polymers Used in Cosmetic Formulations

In the last decade, a growing demand for sustainable cosmetic ingredients has yielded numerous biodegradation protocols. While OECD (Organization for Economic Co-operation and Development) aquatic assays are suitable for water-borne chemicals, it is crucial for the personal care industry to consider the persistence of plastics in soil, compost, and municipal sludge. Adopting this cradle-to-grave holistic approach would strengthen product appeal while increasing the accuracy and ethical integrity of green product labeling. The aim of our study was to employ quantitative CO2 detection and thermophilic composting protocols specified in ASTM D5338, along with pass level criteria outlined in ASTM D6400, to assess the mineralization of plastics commonly formulated into personal care products. Our results indicate that many cellulose ethers, cationic guars, starches, proteins, and labile polyesters demonstrate satisfactory disintegration, biodegradation, and seed germination rates to secure an ASTM D6400 compostability claim. By contrast, macromolecules designed with carbon–carbon backbones resisted acceptable mineralization in composting experiments, advocating that unadulterated municipal compost lacks the microbial diversity to enzymatically digest many synthetically derived resins. Additionally, polymers that demonstrated acceptable biodegradability in internal and published OECD aquatic studies, including chitosan and polyvinyl alcohol, exhibited limited respiration in local municipal compost; hence, untested correlations between aquatic, soil, and compost testing outcomes should never be assumed.

Electrochemical chiral sensor for recognition of amino acid enantiomers with cyclodextrin-based microporous organic networks

BackgroundChirality is a ubiquitous phenomenon in nature, but enantiomers exhibit different pharmacological activities and toxicological effects. Therefore, Chiral recognition plays a pivotal role in various fields such as life sciences, chemical synthesis, drug development, and materials science. The synthesis of novel chiral composites with well-defined loading capabilities and ordered structures holds significant potential for electrochemical chiral recognition applications. However, the design of selective and stable electrochemical chiral recognition materials remains a challenging task. ResultIn this work, we construct a simple and rapid electrochemical sensing platform for tryptophan (Trp) enantiomer recognition using cyclodextrin-modified microporous organic network as chiral recognition agent. CD-MON with chiral microenvironment was prepared by Sonogashira-Hagihara coupling reaction of the chiral molecule heptyl-6-iodo-6-deoxyβ-cyclodextrin and 1, 4-Diethynylbenzene. The adhesion of BSA makes CD-MON firmly fixed on the electrode surface, and as a chiral protein, it can improve the chiral recognition ability through synergistic effect. Chiral amino acids are in full contact with the chiral microenvironment during pore conduction of MON, and L-Trp is more stably bound to CD-MON/BSA due to steric hindrance, host-guest recognition and hydrogen bonding. Therefore, the electrochemical sensor can effectively identify tryptophan enantiomers (IL-Trp/ID-Trp = 2.02), and it exhibits a detection limit of 2.6 μM for L-Trp. UV–Vis spectroscopy confirmed the adsorption capacity of CD-MON towards tryptophan enantiomers in agreement with electrochemistry results. SignificanceThe prepared chiral sensor has excellent stability, reproducibility (RSD = 3.7%) and selectivity, realizes the quantitative detection of single isomer in tryptophan racemic and quantitative analysis in real samples with 94.0%–101.0% recovery. This work represents the first application of MON in chiral electrochemistry which expands the application scope of chiral sensors and holds great significance in separation science and electrochemical sensing.

Ultrasensitive monitoring of PCB77 in environmental samples using a visible-driven photoelectrochemical sensing platform coupling with exonuclease I assisted in target recycling

Due to the urgent need for detecting trace amounts of 3,3′,4,4′-tetrachlorobiphenyl (PCB77) in the environment, we have developed an efficient and visible-driven photoelectrochemical (PEC) sensing platform based on carbon quantum dots (CQDs) modified titanium dioxide nanorods (TiO2 NRs), coupling with exonuclease I (Exo I) assisted in target recycling for significant signal amplification. CQDs/TiO2 NRs with high visible-light absorption ability and electron-hole separation efficiency is used as photoactive substrate for anchoring anti-PCB77 aptamer and its complementary DNA (cDNA). With the addition of PCB77, the specific interaction between PCB77 and its aptamer forces aptamer to separate from the electrode surface, resulting in an increase in photocurrent density. Adding Exo I in the test system, a self-catalytic target cycle was motivated, which significantly increased the PEC signal by more than twice, achieving signal amplification. The relationship between the photocurrent density changes and the concentrations of PCB77 are utilized to achieve quantitative detection of PCB77. The designed PEC sensing platform has good analytical performance with a detection limit as low as 0.33 pg L−1, high selectivity and stability. Moreover, the PEC sensor is successfully used to evaluate the content of PBC77 in the environment samples. The established sensing platform provides a simple and efficient method for detecting trace amounts of PCB77 in the environment.

Magnetic surface-imprinted polymer microspheres coupled with HPLC-MS/MS for sensitive detection of amphetamine-type drugs in water

Magnetic surface imprinted polymer microspheres (Fe3O4@MIPs) were successfully synthesized via Pickering emulsion polymerization, utilizing N-Methylphenethylamine as a surrogate template for amphetamine-type drugs. Fe3O4@MIPs not only possessed excellent dispersibility and enough magnetic properties in aqueous solutions, but also displayed good selectivity towards six amphetamines, with an imprinting factor ranging from 1.8 to 2.6. The adsorption kinetics closely aligned with the pseudo-second-order model, and the adsorption efficiency exceeds 80 % for each amphetamine at equilibrium. Fe3O4@MIPs were then employed as the efficient adsorbents for the extraction of amphetamine drugs. Extraction parameters, including sample pH, the mass of adsorbent, and the type and volume of eluting solvent, were carefully optimized. In combination with the high performance liquid chromatography tandem triple quadrupole mass spectrometry (HPLC-MS/MS), a selective magnetic solid-phase extraction (MISPE) method utilizing Fe3O4@MIPs was developed for the detection of six amphetamines in water samples. The limits of detection and limits of quantitation were determined to be 5.2∼23 ng L−1 and 17∼77 ng L−1, respectively. Recoveries for the six target drugs from lake water and sewage samples fell within the range of 87.2∼110 %. Additionally, the MISPE-HPLC-MS/MS method exhibited excellent repeatability, with a precision below 8.5 % at two spiking levels. The prepared Fe3O4@MIPs possessed the advantages of high selectivity, straightforward preparation, facile separation and good reusability, and was highly suitable for the efficient extraction of amphetamine-type substances in complex environmental water.

Hydrogen peroxide positively regulates ABA signaling via oxidative modification of the C2H2-type zinc finger protein ZFP36 in rice

The rice zinc finger protein ZFP36 serves as a pivotal regulator of the hydrogen peroxide (H2O2) signaling pathway in response to abscisic acid (ABA). Its role is crucial for integrating H2O2 signals with the plant defense mechanisms against water deficit and oxidative stress. However, it remains unclear whether ZFP36 directly modulates ABA-induced H2O2 signaling. This study explored the effects of oxidative post-translational modifications (OxiPTMs) on ZFP36 in rice, with an emphasis on the H2O2-induced oxidation through its cysteine (Cys) residues. We found that ZFP36 undergoes oxidative modification as a target of H2O2 in the presence of ABA, specifically at Cys32. Employing quantitative detection and fluorescence assays, we observed that ZFP36 oxidation enhances the expression and activity of genes encoding protective antioxidant enzymes. Moreover, our investigation into the thioredoxin (Trx) and glutaredoxin (Grx) families revealed that OsTrxh1 facilitates the reduction of oxidized ZFP36. Genetic evidence indicates that ZFP36 positively influences rice resilience to oxidative and water stress, while OsTrxh1 exerts an opposing effect. These insights reveal a distinctive pathway for plant cells to perceive ABA-induced H2O2 signaling, advance our comprehension of H2O2 signaling dynamics, and ABA-related plant responses, and lay a vital groundwork for enhancing crop stress tolerance.

Dual NIR-channel fluorescent probe for detecting ONOO− in vitro and vivo

As one of endogenous reactive oxygen species (ROS), peroxynitrite (ONOO−) performs various functions in both pathological and physiological mechanisms. In this work, an optical and near-infrared (NIR) fluorescent probe (NX), which based on 3-dihydro-1H-xanthene and 2-dicyanomethylene-3-cyano-4,5,5-trimethyl-2,5-dihydrofuran (TCF) group was designed and prepared to detect ONOO−. This probe revealed an obvious optical and a fluorescent response when ONOO− was present and it exhibited higher selectivity over other ROS. Especially, the dual NIR fluorescence changes at 660 and 800 nm allowed quantitative detection of ONOO− in the range of 15–40 μM, and the detection limit was 82 nM. Finally, the probe was effectively employed to visualize exogenous and endogenous ONOO− in HepG2 cells and zebrafish, respectively. All the results indicated the dual NIR-channel probe could serve as a potent detecting tools in studying ONOO− in vitro and in vivo.

Quantitative Virus-Associated RNA Detection to Monitor Oncolytic Adenovirus Replication.

Oncolytic adenoviruses are in development as immunotherapeutic agents for solid tumors. Their efficacy is in part dependent on their ability to replicate in tumors. It is, however, difficult to obtain evidence for intratumoral oncolytic adenovirus replication if direct access to the tumor is not possible. Detection of systemic adenovirus DNA, which is sometimes used as a proxy, has limited value because it does not distinguish between the product of intratumoral replication and injected virus that did not replicate. Therefore, we investigated if detection of virus-associated RNA (VA RNA) by RT-qPCR on liquid biopsies could be used as an alternative. We found that VA RNA is expressed in adenovirus-infected cells in a replication-dependent manner and is secreted by these cells in association with extracellular vesicles. This allowed VA RNA detection in the peripheral blood of a preclinical in vivo model carrying adenovirus-injected human tumors and on liquid biopsies from a human clinical trial. Our results confirm that VA RNA detection in liquid biopsies can be used for minimally invasive assessment of oncolytic adenovirus replication in solid tumors in vivo.

A ratiometric fluorescent sensor based on S-doped BCNO quantum dots and Au nanoclusters combined with 3D-printing portable device for the detection of malachite green.

Sulfur-doped BCNO quantum dots (S-BCNO QDs) emitting green fluorescence were prepared by elemental doping method. The ratiometric fluorescence probe with dual emissions was simply established by mixed S-BCNO QDs with gold nanoclusters (GSH-Au NCs). Because the emission spectrum of Au NCs (donor) at 615nm overlapped well with the ultraviolet absorption of malachite green (MG), fluorescence resonance energy transfer (FRET) can be achieved. When the concentration of MG increased, the fluorescence intensity (F495) of S-BCNO QDs decreased slowly, while the fluorescence intensity (F615) of Au NCs decreased sharply.The fluorescence intensity ratio of F615/F495 decreased with the increase of MG. By plotting the F615/F495 values against MG concentration, a sensitive and rapid detection of MG was possible with a wide detection range (0.1-50 µM) and a low detection limit of 10 nM. Due to the accompanying fluorescence color change from pink to blue-green, it can be used for visual detection. A three dimensional-printing device utilizing digital image colorimetry to capture color changes through the built-in camera, enables quantitative detection of MG with a good linearity between the values of red/green ratioand MG concentrations at the range 1-50 µM. This sensing platform had a range of advantages, including high cost-effectiveness, portability, ease of operation, and high sensitivity. Furthermore, the sensing platform was successfully applied tothe detection of MG in real water sample and fish samples, thereby verifying the reliability and effectiveness of this sensing platform in water quality monitoring and food safety.

Ultra-sensitive electrochemical sensor based on in situ grown ultrafine HKUST-1 nanoparticles @ graphite nanosheets and core-shell structured MoO3-polypyrrole nanowires for the detection of rutin in orange juice.

Rutin extracted from natural plants has important medical value, so developing accurate and sensitive quantitative detection methods is one of the most important tasks. In this work, HKUST-1@GN/MoO3-Ppy NWs were utilized to develop a high-performance rutin electrochemical sensor in virtue of its high conductivity and electrocatalytic activity. The morphology, crystal structure, and chemical element composition of the fabricated sensor composites were characterized by SEM, TEM, XPS, and XRD. Electrochemical techniques including EIS, CV, and DPV were used to investigatethe electrocatalytic properties of the prepared materials. The electrochemical test conditions were optimized to achieve efficient detection of rutin. The 2-electron 2-proton mechanism, consisting of several rapid and sequential phases, is postulated to occur during rutin oxidation. The results show that HKUST-1@GN/MoO3-Ppy NWs have the characteristics of large specific surface area, excellent conductivity, and outstanding electrocatalytic ability. There is a significant linear relationship between rutin concentration and the oxidation peak current of DPV. The linear range is 0.50-2000 nM, and the limit of detection is 0.27 nM (S/N = 3). In addition, the prepared electrode has been confirmed to be useful for rutin analysis in orange juice.

Pixel-level automatic detection and quantification of running bands on rail surfaces

The running band on the rail surface serves as a crucial indicator of the wheel-rail contact relationship, making quantitative detection of the running band vital for railroad inspection and maintenance. However, current rail running band detection methods remain manual, and leveraging state-of-the-art deep learning technology can significantly enhance detection efficiency and minimize the reliance on human labor. This paper presents an improved version of ShuttleNet, called ShuttleNetM2T, for rail surface running band detection, emphasizing high stability. Efficient self-attention in ShuttleNetM2T captures global information, maintaining efficiency and rectifying issues like misrecognition and incomplete edges. Experimental results show ShuttleNetM2T achieves 0.9823 average F-measure and 0.9653 average Intersection-Over-Union on test images. For automatic running band width detection, we propose a pixel-to-physical distance conversion-based calculation, yielding just 0.625% relative error. Overall, the findings in this paper facilitate accurate detection and automatic calculation of the running band width, with promising applications in intelligent rail surface detection.

6-benzylaminopurine highly sensitive analysis by SPR sensor with bifunctional magnetic molecularly imprinted polymers nanoparticles

A highly sensitive Surface Plasmon Resonance (SPR) sensor coupled magnetic molecularly imprinted polymers nanoparticles (MMIPs NPs) was developed and validated for the determination of 6-benzylaminopurine (6-BA) in vegetables. MMIPs NPs were synthesized using methacrylic acid (MAA) and sodium p-styrene sulfonate (SSS) as functional monomers. The SPR exhibited a linear dependence on 6-BA concentration in the range 5–300 pg/mL with a low limit of detection (3.02 pg/mL) and limit of quantitation (10.08 pg/mL). The SPR signal of 6-BA-captured MAA/SSS-MMIPs NPs is higher than those of the structural analogues (6-KT and 2-IP: 1.72 and 2.12 times) and the non-structural analogues (2, 4-D and NAA: 2.31 and 2.57 times), indicating the SPR sensor has good selectivity for 6-BA. The recovery of the established method was between 93.8% and 108.6% with a coefficient of variation less than 9.2% in four vegetables. This SPR sensor shows great potential in detecting 6-BA in more vegetables.

Integration of Image Pattern Recognition and Photon Sensor for Analyzing Cytokine Gene Expression Using πCode MicroDisc.

Current quantitative gene expression detection in genomic and transcriptomic research heavily relies on quantitative real-time PCR (qPCR). While existing multiplex gene detection techniques offer simultaneous analysis of multiple targets, we present an alternative assay capable of detecting gene expression simultaneously within a single well. This highly sensitive method utilizes πCode MicroDiscs, featuring unique identification patterns and fluorescent detection. Our study compared this multiplex πCode platform with a qPCR platform for profiling cytokine gene expression. The πCode MicroDisc assay successfully demonstrated the expression of polymerization markers for M1- and M2-like macrophages generated from THP-1-derived macrophages in a qualitative assay. Additionally, our findings suggest a pattern agreement between the πCode assay and the qPCR assay, indicating the potential of the πCode technology for comparative gene expression analysis. Regarding the inherent sensitivity and linearity, the developed πCode assay primarily provides qualitative gene expression to discriminate the polarization of macrophages. This remarkable capability presents substantial advantages for researchers, rendering the technology highly suitable for high-throughput applications in clinical diagnosis and disease monitoring.

Coral-like silver citrate as robust laccase mimetics in a novel colorimetric aptasensor for sensitive and highly selective detection of histamine in food

The colorimetric methods for histamine detection still face some challenges in accuracy and stability. Herein, a novel colorimetric aptasensor for sensitive and highly selective detection of histamine was developed based on the enhancement of silver citrate (AgCit) laccase-mimic activity. It has been confirmed that H2 aptamer enhances the affinity of AgCit to the chromogenic substrate, and promotes the generation of semiquinone radical in the laccase-mimic catalytical system. The color change of the sensing solution can be distinguished by the naked eye, and easily converted to the corresponding RGB value by a smartphone for the quantitative and rapid detection of histamine. The aptasensor has a limit of detection (LOD) as low as 27 μg L−1, and maintains high selectivity for histamine in the presence of other competitive substances. It is strongly believed that the design of a colorimetric aptasensor can provide a simple and versatile platform for histamine detection in food.

Rapid identification and quantitative analysis of malachite green in fish via SERS and 1D convolutional neural network

Rapid and quantitative detection of malachite green (MG) in aquaculture products is very important for safety assurance in food supply. Here, we develop a point-of-care testing (POCT) platform that combines a flexible and transparent surface-enhanced Raman scattering (SERS) substrate with deep learning network for achieving rapid and quantitative detection of MG in fish. The flexible and transparent SERS substrate was prepared by depositing silver (Ag) film on the polydimethylsiloxane (PDMS) film using laser molecular beam epitaxy (LMBE) technique. The wrinkled Ag NPs@PDMS film exhibits high SERS activity, excellent reproducibility and good mechanical stability. Additionally, the fast in situ detection of MG residues onfishscales was achieved by using the wrinkled Ag NPs/PDMS film and a portable Raman spectrometer, with a minimum detectable concentration of 10-6 M. Subsequently, a one-dimensional convolutional neural network (1D CNN) model was constructed for rapid quantification of MG concentration. The results demonstrated that the 1D CNN quantitative analysis model possessed superior predictive performance, with a coefficient of determination (R2) of 0.9947 and a mean squared error (MSE) of 0.0104. The proposed POCT platform, integrating a transparent flexible SERS substrate, a portable Raman spectrometer and a 1D CNN model, provides an efficient strategy for rapid identification and quantitative analysis of MG in fish.