Fructose oxidase-like activity of CuO nanoparticles supported by phosphate for a tandem catalysis-based fructose sensor

A fluorescent NBD "turn-on" probe for the rapid and on-site analysis of fructose in food

High fructose intake is an important cause of metabolic disease. Due to the increasing prevalence of metabolic diseases worldwide, the development of an accurate and efficient tool for monitoring fructose in food is urgently needed to control the intake of fructose. Herein, a new fluorescent probe NBD-PQ-B with 7-nitrobenz-2-oxa-1, 3-diazole (NBD) as the fluorophore, piperazine (PQ) as the bridging group and phenylboronic acid (B) as the recognition receptor, was synthesized to detect fructose. The fluorescence of NBD-PQ-B increased linearly at 550 nm at an excitation wavelength of 497 nm with increasing fructose concentration from 0.1 to 20 mM. The limit of detection (LOD) of fructose was 40 μM. The pKa values of NBD-PQ-B and its fructose complexes were 4.1 and 10.0, respectively. In addition, NBD-PQ-B bound to fructose in a few seconds. The present technique was applied to determine the fructose content in beverages, honey, and watermelon with satisfactory results. Finally, the system could not only be applied in an aqueous solution with a spectrophotometer, but also be fabricated as a NBD-PQ-B/polyvinyl oxide (PEO) film by electrospinning for on-site food analysis simply with the assistance of a smartphone.

Deep convolutional neural network-based 3D fluorescence sensor array for sugar identification in serum based on the oxidase-mimicking property of CuO nanoparticles

Developing sensor arrays capturing comprehensive fluorescence (FL) spectra from a single probe is crucial for understanding sugar structures with very high similarity in biofluids. Therefore, the analysis of highly similar sugar' structures in biofluids based on the entire FL of a single nanozyme probe needs more concern, which makes the development of novel alternative approaches highly wanted for biomedical and other applications. Herein, a well-designed deep learning model with intrinsic information of 3D FL of CuO nanoparticles (NPs)' oxidase-like activity was developed to classify and predict the concentration of a group of sugars with very similar chemical structures in different media. The findings presented that the overall accuracy of the developed model in classifying the nine selected sugars was (99-100 %), which prompted us to transfer the developed model to predict the concentration of the selected sugars at a concentration range of (1-100 μM). The transferred model also gave excellent results (R2 = 97-100 %). Therefore, the model was extended to other more complex applications, namely the identification of mixtures of sugars in serum and the detection of polysaccharides in different media such as serum and lake water. Notably, LOD for fructose was determined at 4.23 nM, marking a 120-fold decrease compared to previous studies. Our developed model was also compared with other deep learning-based models, and the results have demonstrated remarkable progress. Moreover, the identification of other possible coexisting interference substances in lake water samples was considered. This work marks a significant advancement, opening avenues for the widespread application of sensor arrays integrating nanozymes and deep learning techniques in biomedical and other diverse fields.

Synergistic action of cavity and catalytic sites in etched Pd-Cu2O octahedra to augment the peroxidase-like activity of Cu2O nanoparticles for the colorimetric detection of isoniazid and ascorbic acid

Despite the widespread use of nanozyme-based colorimetric assays in biosensing, challenges such as limited catalytic efficiency, inadequate sensitivity to analytes, and insufficient understanding of the structure-activity relationship still persist. Overcoming these hurdles by enhancing the inherent enzyme-like performance of nanozymes using the unique attributes of nanomaterials is still a significant obstacle. Here, we designed and constructed Pd-Cu2O nanocages (Pd-Cu2O NCs) by selectively etching the vertices of the copper octahedra to enhance the peroxidase-like (POD-like) activity of Cu2O nanoparticles. The improved catalytic activity of Pd-Cu2O NCs was attributed to their high specific surface area and abundant catalytic sites. Mechanistic studies revealed that reactive oxygen species (ROS) intermediates (•OH) were generated through the decomposition of H2O2, resulting in POD-like activity of the Pd-Cu2O NCs. The designed Pd-Cu2O NCs can oxidize 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of H2O2, producing a blue oxidation product (oxTMB). The oxidation reaction was inhibited and led to a significant bleaching of the blue color in the presence of reducing substances isoniazid (INH) and ascorbic acid (AA). Based on these principles, we developed a colorimetric sensing platform for the detection of INH and AA, exhibiting good sensitivity and stability. This work provided a straightforward approach to the structural engineering of nanomaterials and the enhancement of enzyme-mimicking properties.

A dual-mode sensing system based on carbon quantum dots and Fe nanozymes for the detection of α-glucosidase and its inhibitors

In this research, a sensitive fluorometric and colorimetric dual-mode sensing platform based on nitrogen-doped carbon quantum dots (NCDs) and magnetic Fe nanoparticles with peroxidase-like activity (Fe nanozymes, Fe NZs) was established, and was further applied for the detection of α-glucosidase (α-glu) and its inhibitors. The ⋅OH that produced by H2O2 catalyzed by Fe NZs can oxidize the colorless diammonium 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate) (ABTS) to green oxABTS, and a noticeable absorption peak at 417 nm appeared. Simultaneously, oxABTS can quench the fluorescence of NCDs at 402 nm via fluorescence resonance energy transfer (FRET). 2-O-α-D-glucopyranosyl-L-ascorbic acid (AAG) can be decomposed by α-glu to glucose and ascorbic acid (AA), AA can prevent the oxidation of ABTS, resulting in the absorption at 417 nm decreased. Moreover, the quenching effect of oxABTS on NCDs is weakened, and the fluorescence at 402 nm is restored. Therefore, based on the change of absorption at 417 nm and fluorescence at 402 nm, the fluorometric and colorimetric dual-mode sensing method can be used for the determination of acarbose and voglibose that are the inhibitors of α-glu.

Nanomaterial-based biosensors for the detection of foodborne bacteria: a review

Ensuring food safety is a critical concern for the development and well-being of humanity, as foodborne illnesses caused by foodborne bacteria have increasingly become a major public health concern worldwide. Traditional food safety monitoring systems are expensive and time-consuming, relying heavily on specialized equipment and operations. Therefore, there is an urgent need to develop low-cost, user-friendly and highly sensitive biosensors for detecting foodborne bacteria. In recent years, the combination of nanomaterials with optical biosensors has provided a prospective future platform for the detection of foodborne bacteria. By harnessing the unique properties of nanomaterials, such as their high surface area-to-volume ratio and exceptional sensitivity, in tandem with the precision of optical biosensing techniques, a new prospect has opened up for the rapid and accurate identification of potential bacterial contaminants in food. This review focuses on recent advances and new trends of nanomaterial-based biosensors for the detection of foodborne pathogens, which mainly include noble metal nanoparticles (NMPs), metal organic frameworks (MOFs), graphene nanomaterials, quantum dot (QD) nanomaterials, upconversion fluorescent nanomaterials (UCNPs) and carbon dots (CDs). Additionally, we summarized the research progress of color indicators, nanozymes, natural enzyme vectors and fluorescent dye biosensors, focusing on the advantages and disadvantages of nanomaterial-based biosensors and their development prospects. This review provides an outlook on future technological directions and potential applications to help identify the most promising areas of development in this field.