Smartphone-integrated fluorescent quenching immunochromatographic test strips designed for the determination of sesame allergens in food samples

Deep learning assisted quantitative detection of cardiac troponin I in hierarchical dendritic copper-nickel nanostructure lateral flow immunoassay

The rising demand for point-of-care testing (POCT) in disease diagnosis has made LFIA sensors based on dendritic metal thin film (HD-nanometal) and background fluorescence technology essential for rapid and accurate disease marker detection, thanks to their integrated design, high sensitivity, and cost-effectiveness. However, their unique 3D nanostructures cause significant fluorescence variation, challenging traditional image processing methods in segmenting weak fluorescence regions. This paper develops a deep learning method to efficiently segment target regions in HD-nanometal LFIA sensor images, improving quantitative detection accuracy. We propose an improved UNet++ network with attention and residual modules, accurately segmenting varying fluorescence intensities, especially weak ones. We evaluated the method using IoU and Dice coefficients, comparing it with UNet, Deeplabv3, and UNet++. We used an HD-nanoCu-Ni LFIA sensor for cardiac troponin I (cTnI) as a case study to validate the method's practicality. The proposed method achieved a 96.3% IoU, outperforming other networks. The R2 between characteristic quantity and cTnI concentration reached 0.994, confirming the method's accuracy and reliability. This enhances POCT accuracy and provides a reference for future fluorescence immunochromatography expansion.

Sesame Detection in Food Using DNA-Functionalized Gold Nanoparticles: A Sensitive, Rapid, and Cost-Effective Colorimetric Approach

Food safety control is a key issue in the food and agriculture industries. For such purposes, developing miniaturized analytical methods is critical for enabling the rapid and sensitive detection of food supplements, allergens, and pollutants. Here, a novel bioanalytical methodology based on DNA-functionalized gold nanoparticles (AuNPs) and colorimetric detection was developed to detect the presence of sesame (a major allergen) through sesame seed DNA as a target, in food samples. The presence of sesame DNA induces controlled nanoparticle aggregation/desegregation, resulting in a color change (from blue to red) proportional to sesame DNA concentration. The incorporation of multicomponent nucleic acid enzymes (MNAzymes) in this strategy has been carried out to perform an isothermal signal amplification strategy to improve the sensitivity of detection. Also, open-source software for color analysis was used to ensure an unbiased visual color-change detection, enhancing detection accuracy and sensitivity and opening the possibility of performing a simple and decentralized analyte detection. The method successfully detected the presence of sesame DNA in sesame seed, sesame oil, olive oil, and sunflower oil. In brief, the developed approach constitutes a simple and affordable alternative to perform a highly sensitive detection of DNA in food without complex methodologies or the requirement of expensive instrumentation.

High-Performance Fluorescent Microspheres Based on Fluorescence Resonance Energy Transfer Mode for Lateral Flow Immunoassays

The label with a large Stokes shift and strong fluorescence properties could improve the sensitivity of the lateral flow immunoassay (LFIA). Herein, two aggregation-induced emission (AIE) luminogens with spectral overlap were encapsulated in polymers by using the microemulsion method as a label, and the construction of a fluorescence resonance energy transfer mode was further verified via theoretical calculation and spectral analysis. Satisfactorily, the doped AIE polymer microspheres (DAIEPMs) exhibited a large Stokes shift of 285 nm and a 10.8-fold fluorescence enhancement compared to those of the AIEPMs loaded with acceptors. Benefiting from the excellent optical performance, DAIEPMs were applied to the LFIA for sensitive detection of chlorothalonil, which is an organochlorine pesticide. The limit of detection of the proposed DAIEPMs-LFIA was 1.2 pg/mL, which was 4.8-fold and 11.6-fold lower than those of quantum dot bead LFIA and gold nanoparticle LFIA, respectively. This work provides a new strategy to improve the optical properties of fluorescent materials and construct a sensitive and reliable detection platform.

Fluorescence immunoassay based on magnetic separation and ZnCdSe/ZnS quantum dots as a signal marker for intelligent detection of sesame allergen in foods

To detect sesame allergens, a novel fluorescent immunoassay incorporating a magnetic separation step has been developed via two measurement devices: a fluorescence spectrophotometer and a smartphone equipped with a color reader. Sesame allergen monoclonal antibody (Ab) was covalently bonded with quantum dots (QDs) to act as a signal probe. The capture probes were synthesized as sesame allergen (SA) modified carboxyl-functional magnetic polystyrene microspheres (MPMs). Analytical variables such as the amount of modified SA, the reaction volume of the QDs-Ab, the ionic strength, the pH, and the incubation time of the reaction were optimized. The analytical range and the limit of detection (LOD) of the spectrophotometer-based assay were 80-640 μg/L and 12.75 μg/L, respectively. The analytical range and the LOD with smartphone read-out were 80-640 μg/L and 10.15 μg/L, respectively. Furthermore, the developed assay using the fluorescence spectrophotometer and the smartphone read-out was successfully applied to field testing of SA in solution extracts of biscuits, bread, almond beverage, and energy bars with acceptable results. The recovery rates were in the range 89-108%. It was concluded that the new assay may be used for rapid sesame allergen testing in the laboratory and in the field.

Immunocolorimetric assay based on amplified gold nanoparticles and magnetic separation beads for detection of sesame allergens in food

We have developed a magnetic separation-based immunocolorimetric assay to detect sesame allergens. Sesame monoclonal antibody (Ab) was modified onto gold nanoparticles (AuNPs) to create signal probes (AuNPs-Ab), and sesame allergens (SA) were attached to carboxyl-functionalized magnetic polystyrene microspheres (MPMs) to act as capture probes (MPMs-SA). Based on the competition format, the capture probes competed with the sesame allergens in the sample to bind the corresponding signal probes. When sesame allergens were present, two immune complexes (AuNPs-Ab@MPMs-SA and AuNPs-Ab@SA) were formed. The immune complex AuNPs-Ab@SA was used to quantify the sesame allergens in the sample. This immunoassay had a detection linear range from 50 to 800 μg L^-1 with a limit of detection (LOD) of 45.53 μg L^-1. Based on the optimized conditions, the recovery of sesame allergens in bread, biscuit, almond beverage, and energy bar samples was between 82.50% and 116.67%. The LODs for the bread, biscuit, almond beverage, and energy bar samples were 0.36, 0.36, 0.27, and 0.55 mg kg^-1, respectively.