Pathogenic Escherichia coli (E. coli) is a widespread and clinically significant foodborne pathogen. Due to its high mutation rates and phenotypic diversity, rapid identification of its subtypes remains challenging and prone to false positives when detecting single strains. In this study, we developed a plasmonic sensor array with high-dimensional signal readouts (ζ-potential, dynamic light-scattering (DLS), surface-enhanced Raman scattering (SERS), and ultraviolet-visible (UV-vis) absorption spectra) for the selective discrimination of pathogenic E. coli, integrated with bacterial culture methods. The plasmonic sensor units demonstrated strong encoding capabilities, facilitating the differentiation of subtle variations among various E. coli strains and showing excellent anti-interference performance. The array realized different pathogenic E. coli strains, bacterial mixture identification, and even quantitative detection. Remarkably, the working concentration for the sensor array was notably low, at 104 CFU/mL. Finally, by incorporating bacterial isolation culture, the designed sensor array obtained 100% accuracy in detecting E. coli in real food samples. These findings highlight the sensor array's potential for applications in food safety monitoring and clinical diagnostics, offering a sensitive, rapid, and reliable tool for pathogen detection in complex samples.

Aflatoxin B1 (AFB1) is a secondary metabolite produced by Aspergillus flavus and Aspergillus parasiticus. This toxin is highly carcinogenic and toxic, posing a serious threat to human and animal health. AFB1 primarily enters the human body through contaminated food, particularly peanuts, corn, nuts, and wheat. These foods are easily contaminated with AFB1 during planting, harvesting, storage, and processing. Therefore, the establishment of an accurate and sensitive method for the detection of AFB1 is essential to safeguard food safety and human health.

This study applied catalytic hairpin assembly (CHA), hybridization chain reaction (HCR), hollow octahedron PtNPs/Pd-Cu2O bifunctional nanozyme, and AuPtNPs/Ni-Co NCs to develop a colorimetric-electrochemical dual-mode aptasensor for AFB1 detection. Here, Pd-Cu2O corner-etched octahedra with cavities and oxygen vacancy defects were first designed, followed by the synthesis of PtNPs/Pd-Cu2O through the loading of PtNPs to enhance the peroxidase-like activity of Pd-Cu2O. PtNPs/Pd-Cu2O effectively catalyzed the generation of blue oxidation products from 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of hydrogen peroxide (H2O2). It also enhances the redox reaction of methylene blue (MB) at the electrode and improves the electrochemical signal. AuPtNPs/Ni-Co NCs possess a large specific surface area and excellent conductivity, enhanced the redox signal of MB. Additionally, the aptasensor combined the enzyme-free amplification strategies of CHA and HCR to improve sensitivity. The aptasensor reached limit of detection (LOD) 0.76 pg/mL in electrochemical mode and 0.49 pg/mL in colorimetric mode.

The designed colorimetric-electrochemical dual-mode aptasensor exhibits high selectivity, specificity, stability, and reliability. The dual-mode aptasensor had been successfully applied to the spiked analysis of edible oils, peanuts, and cornmeal, demonstrating excellent recovery rates. Therefore, the dual-mode aptasensor had a wide application prospect in the field of quality supervision and food safety.

Pb2+ has numerous sources in cosmetics, industrial pollution and other environments. Therefore, sensitive and accurate detection of Pb2+ content is extremely important in food safety. In this work, bifunctional nanomaterials Ti3C2@PtPd NPs with fluorescence quenching effect and peroxidase activity were prepared by in situ growth of platinum‑palladium nanoparticles (PtPd NPs) on the surface of 2D material Ti3C2. Combining the DNA enzyme recognition element with magnetic separation technology, we constructed a fluorescence/colorimetric dual-channel for the sensitive detection of Pb2+. Under the optimal conditions, the detection ranges of this fluorescence/colorimetric bimodal sensing strategy were 0.1-1000 nmol/L and 0.5-1000 nmol/L, respectively. The LOD of the fluorescence method was 23 pmol/L, and that of the colorimetric method was 74 pmol/L, and the results of the detection were visible to the naked eye. This dual-mode sensing method provides a new platform for accurate, reliable and visualized detection of Pb2+.

The development of straightforward and cost-efficient methods for bacterial identification is very important. In this study, we utilized xylenol orange, metal ions, and diverse bacterial carbon sources to construct a sensor array, achieving precise bacterial identification. Initially, we examined the absorbance variations of xylenol orange with five metal ions (Mn2+, Co2+, Ni2+, Cu2+, and Zn2+) at pH levels ranging from 4 to 7, observing significant changes at 570 nm or 580 nm. Given that bacteria can generate varying amounts of acid in different carbon sources, we employed a blend of xylenol orange and the five metal ions as pH-sensitive probes to characterize bacterial metabolism in three carbon sources, resulting in the development of a five-sensor array that effectively differentiated seven bacteria. Additionally, by utilizing xylenol orange with Co2+, we successfully identified six different bacterial mixtures and five types of probiotic drink products. These findings highlight the potential of our methods for broader practical application in bacterial identification in practical use.

The accurate discrimination of bacterial infection is imperative for precise clinical diagnosis and treatment. Here, this work presents a simplified sensor array utilizing "All-in-One" Pdots for efficient discrimination of diverse bacterial samples. The "All-in-One" Pdots sensor (AOPS) were synthesized using three components that exhibit fluorescence resonance energy transfer (FRET) effect, facilitating the efficient integration of multiple discrimination channels to generate specific fluorescence response patterns through a single detection under single-wavelength excitation. Additionally, machine learning techniques were employed to visually represent the fluorescence response patterns of AOPS upon exposure to bacterial metabolites derived from diverse bacterial species. The as-prepared sensor platform demonstrated excellent performance in analyzing eight common bacteria, drug-resistant strains, mixed bacterial samples, bacterial biofilms and real samples, presenting significant potential in the identification of complex samples for bacterial analysis.

The integration of smartphones with conventional analytical approaches plays a crucial role in enhancing on-site detection platforms for point-of-care testing. Here, we developed a simple, rapid, and efficient three-channel colorimetric sensor array, leveraging the peroxidase (POD)-like activity of polydopamine-decorated FeNi foam (PDFeNi foam), to identify antioxidants using both microplate readers and smartphones for signal readouts. The exceptional catalytic capacity of PDFeNi foam enabled the quick catalytic oxidation of three typical peroxidase substrates (TMB, OPD and 4-AT) within 3 min. Consequently, we constructed a colorimetric sensor array with cross-reactive responses, which was successfully applied to differentiate five antioxidants (i.e., glycine (GLY), glutathione (GSH), citric acid (CA), ascorbic acid (AA), and tannic acid (TAN)) within the concentration range of 0.1-10 μM, quantitatively analyze individual antioxidants (with AA and CA as model analytes), and assess binary mixtures of AA and GSH. The practical application was further validated by discriminating antioxidants in serum samples with a smartphone for signal readout. In addition, since pesticides could be absorbed on the surface of PDFeNi foam through π-π stacking and hydrogen bonding, the active sites were differentially masked, leading to featured modulation on POD-like activity of PDFeNi foam, thereby forming the basis for pesticides discrimination on the sensor array. The nanozyme-based sensor array provides a simple, rapid, visual and high-throughput strategy for precise identification of various analytes with a versatile platform, highlighting its potential application in point-care-of diagnostic, food safety and environmental surveillance.

Chemodynamic therapy (CDT) has emerged as a promising approach for treating infected diabetic wounds, while reliable imaging technology for simultaneous monitoring of ROS and therapeutic processes is still a formidable challenge. Herein, smart covalent organic framework (COF) nanoreactors (COF NRs) are constructed by hyaluronic acid (HA) packaged glucose oxidase (GOx) covalently linked Fe-COF for diabetic wound healing. Upon the breakdown of the HA protective layer, GOx consumes glucose to produce gluconic acid and hydrogen peroxide (H2O2), resulting in decreased local pH and H2O2 supplementation. Density functional theory (DFT) calculations show that Fe-COF has high catalytic activity towards H2O2, leading to in situ generation of hydroxyl radicals (·OH) for sterilization, and the localized downregulation of glucose effectively improved the microenvironment of diabetic wounds. Meanwhile, based on the near-infrared photothermal imaging of oxidized 3,3',5,5'-tetramethylbenzidine (oxTMB), the authors showed that TMB can be applied for the point-of-care testing of ·OH and glucose, and assessing the sterilization progress in vivo. More significantly, the facile photothermal signaling strategy can be extended to monitor various ROS-mediated therapeutic systems, enabling accurate prediction of treatment outcomes.

In this work, we present an array-based chemical nose sensor that utilizes a set of ensemble-modified aptamer (EMAmer) probes to sense subtle physicochemical changes on the cell surface for cancer cell identification. The EMAmer probes are engineered by domain-selective incorporation of different types and/or copies of positively charged functional groups into DNA scaffolds, and their differential interactions with cancer cells can be transduced through competitive adsorption of fluorophore-labeled EMAmer probes loaded on MoS2 nanosheets. We demonstrate that this MoS2-EMAmer-based sensor array enables rapid and effective discrimination among six types of cancer cells and their mixtures with a concentration of 104 cells within 60 min, achieving a 94.4% accuracy in identifying blinded unknown cell samples. The established MoS2-EMAmer sensing platform is anticipated to show significant promise in the advancement of cancer diagnostics.

Rapid detection of histamine remains a challenge due to the complexity of food matrices. Based on the high peroxidase-like activity of sea urchin-shaped Pt@Au NPs (SU-Pt@Au NPs), a novel dual-mode nanoplatform is developed for the sensitive detection of histamine utilizing an indirect competitive enzyme-linked immunosorbent assay. According to the colorimetric-based UV-vis nanoplatform, histamine is sensitively detected with a liner range from 0.5 to 100 ng/mL and a limit of detection (LOD) as low as 0.3 ng/mL. Then, a smartphone-loaded color picker APP can intelligently detect histamine in point-of-care testing (POCT) based on the R/B ratio of the color channels, with a detection range of 0.5 to 1000 ng/mL and a LOD as low as 0.15 ng/mL, significantly expanding the detection range. Such an easy-to-use and sensitive detection system is employed to quantify histamine in Pacific saury, crab, and pork samples, indicating outstanding application potential in protein-rich meat food safety.

Post-operative pathogenic infections in liver transplantation seriously threaten human health. It is essential to develop novel methods for the highly sensitive and rapid detection of Staphylococcus aureus (S. aureus). Interestingly, the combination of the property of bacteria to secrete hydrogen peroxidase, bacterial metabolism-triggered-chemiluminescence (CL)-based bioassays can be as a candidate point-of-care testing (POCT) for the detection of S. aureus against the CL substrate Luminol and hydrogen peroxide without excitation light sources. Here, a CL-based strategy with stable and visualized CL intensity was fabricated according to a hybrid biomimetic enzyme of copper-Hemin metal-organic framework, which enhances the biological enzyme activity while improving the stability and sensitivity of the assay. By further integrating S. aureus-specific capture and one-step separation of the antibody-modified Fe3O4 NPs (Fe3O4 NPs@Ab), the portable device integrated smartphone enables CL-based POCT for specific detection of S. aureus in the range of 101-106 CFU/mL with a limit of detection as low as 1 CFU/mL. Specifically, S. aureus can be eliminated after detection with high antibacterial efficiency due to the excellent photothermal properties of Fe3O4 NPs@Ab. The developed multifunctional platform has the advantages of simplicity of operation and low cost, indicating great potential in clinical applications.

Biosensors have been widely used for bacteria determination with great success. However, the "lock-and-key" methodology used by biosensors to identify bacteria has a significant limitation: it can only detect one species of bacteria. In recent years, optical (fluorescent and colorimetric) sensor arrays are gradually gaining attention from researchers as a new type of biosensor. They can acquire multiple features of a target simultaneously, form a feature pattern, and determine the bacteria species with the help of pattern recognition/machine learning algorithms. Previous reviews in this area have focused on the interaction between the sensor array and bacteria or the materials used to make the sensors. This review, on the other hand, will provide researchers with a better understanding of the field by discussing fluorescent and colorimetric sensor arrays based on the mechanism of optical signal generation. These sensor arrays will be compared based on the identified species. Finally, we will discuss the limitations of these sensor arrays and explore possible solutions.

Although photothermal therapy (PTT) employing nanozymes has shown excellent antibacterial potential, excessive heating generally harms host cells and hinders recovery. Herein, we report an innovative technique for acquiring the programmed temperature by managing the catalytic activity of nanozymes. The photothermal system of CeO2 + F- + TMB can obtain precise photothermal temperature by adjusting the concentration of fluoride ions under near-infrared irradiation. At the optimized photothermal temperature, the photothermal system affords fine photothermal antibacterial treatment with high-efficiency antibacterial effects against Staphylococcus aureus and Escherichia coli in vitro. In vivo wound healing experiments confirm that the system can effectively promote fibroblast proliferation, angiogenesis and collagen deposition with remarkable wound healing efficiency. This strategy offers a novel design concept for creating a new generation of PTT and opens the way for the creation of alternative antibiotics.

Pathogenic bacteria can pose a great threat to food safety and human health. It is therefore imperative to develop a rapid, portable, and sensitive determination and discrimination method for pathogenic bacteria. Over the past few years, various nanomaterials (NMs) have been employed as desirable nanoprobes because they possess extraordinary properties that can be used for optical signal enabled detection and identification of bacteria. By means of modification, NMs can, depending on different mechanisms, sense targets directly or indirectly, which then provides an essential support for the detection and differentiation of pathogenic bacteria. In this review, recent application of NMs-based optical biosensors for food safety bacterial detection and discrimination is performed, mainly in but not limited to noble metal NMs, fluorescent NMs, and point-of-care testing (POCT). This review also focuses on future trends in bacterial detection and discrimination, and machine learning in performing intelligent rapid detection and multiple accurate identification of bacteria.

Rapid and accurate identification of foodborne pathogens improves public health. Currently employed methods are time-consuming, sensitive to environmental factors, and complex. This study develops a colorimetric sensor for detecting multiple bacteria with one probe using double-enzyme-induced colorimetry. Based on alkaline phosphatase (ALP) in bacteria decomposes L-ascorbic acid 2-magnesium phosphate salt hydrate into ascorbic acid (AA). Manganese dioxide flowers (MnO₂ NFs) can oxidize TMB to etch gold nanorods (Au NRs), which can be inhibited by AA reduction to produce rich colors. Bacteria with varying ALP levels can be identified based on color changes and plasmon resonance wavelength signals produced from Au NRs. Furthermore, the conversion of RGB signals to digital signals and the use of linear discriminant analysis (LDA) allowed 99.57% accuracy in identifying multiple bacteria. It can simultaneously identify five foodborne pathogens across diverse environments (shrimp, meat, milk, etc.). This method may be useful for the rapid and simple identification of foodborne illnesses.

The in situ identification of superbugs with the simultaneous killing of it is key to preventing human health. Here, a one-stop identification and killing platform for near-infrared (NIR) triggering was designed and constructed using lignosulfonate (LS), cationic guar gum (CG) and Ag₂O NPs hydrogels (LS/CG/Ag₂O). The hydrogel network is used as a fixed matrix for Ag₂O NPs and a nano reactor, meanwhile 3,3', 5,5'-tetramethylbenzidine (TMB) as a single probe sensor array for bacterial identification. In contrast to conventional methods, hybrid hydrogels have catalytic qualities through which TMB be catalyzed to generate oxidized TMB (oxTMB). The drug resistance of the same strain can be distinguished based on the different inhibition abilities of drug-resistant superbacteria in TMB and hydrogel reactions. Then, the employing of oxTMB photothermal characteristics, it can be efficiently killed in real time while being driven by a near-infrared laser. The proposed one-stop hydrogel platform paves a way for the rapid identification and killing of drug-resistant superbacteria.

Antibiotic-resistant ESKAPE pathogens cause nosocomial infections that lead to huge morbidity and mortality worldwide. Rapid identification of antibiotic resistance is vital for the prevention and control of nosocomial infections. However, current techniques like genotype identification and antibiotic susceptibility testing are generally time-consuming and require large-scale equipment. Herein, we develop a rapid, facile, and sensitive technique to determine the antibiotic resistance phenotype among ESKAPE pathogens through plasmonic nanosensors and machine learning. Key to this technique is the plasmonic sensor array that contains gold nanoparticles functionalized with peptides differing in hydrophobicity and surface charge. The plasmonic nanosensors can interact with pathogens to generate bacterial fingerprints that alter the surface plasmon resonance (SPR) spectra of nanoparticles. In combination with machine learning, it enables the identification of antibiotic resistance among 12 ESKAPE pathogens in less than 20 min with an overall accuracy of 89.74%. This machine-learning-based approach allows for the identification of antibiotic-resistant pathogens from patients and holds great promise as a clinical tool for biomedical diagnosis.

Misuse and overuse of tetracycline antibiotics (TCs) brings serious issues to ecological environment, food safety and human health. It is urgent to develop unique platform for high efficient identification and removal of TCs. In the present investigation, an effective and simple fluorescence sensor array was constructed based on the interaction between metal ions (Eu³⁺ and Al³⁺) and antibiotics. Benefiting from the different affinities between the ions and TCs, the sensor array can identify TCs from other antibiotics, which also can further differentiating four kinds of TCs (OTC, CTC, TC and DOX) from each other via linear discriminant analysis (LDA) technique. Meanwhile, the sensor array performed well in quantitative analysis of single TC antibiotic and differentiation of TCs mixtures. More interestingly, Eu³⁺ and Al³⁺-doped sodium alginate/polyvinyl alcohol hydrogel beads (SA/Eu/PVA and SA/Al/PVA) were further constructed, which can not only identify the TCs but simultaneously remove the antibiotics with high efficiency. The investigation provided an instructive way for rapid detection and environment protection.

As living standards rise, the demand for high-quality chilled meat among consumers also grows. Researchers and enterprises have been interested in ensuring the quality of chilled meat in all links of the downstream industry. Nanozyme has shown the potential to address the aforementioned requirements. Reasons and approaches for the application of nanozymes in the freshness assessment or shelf life extension of chilled meat were discussed. The challenges for applying these nanozymes to ensure the quality of chilled meat were also summarized. Finally, this review examined the safety, regulatory status, and consumer attitudes toward nanozymes. This review revealed that the freshness assessment of chilled meat is closely related to mimicking the enzyme activities of nanozymes, whereas the shelf life changes of chilled meat are mostly dependent on the photothermal activities and pseudophotodynamic activities of nanozymes. In contrast, studies regarding the shelf life of chilled meat are more challenging to develop, as excessive heat or reactive oxygen species impair its quality. Notably, meat contains a complex matrix composition that may interact with the nanozyme, reducing its effectiveness. Nanopollution and mass manufacturing are additional obstacles that must be overcome. Therefore, it is vital to choose suitable approaches to ensure meat quality. Furthermore, the safety of nanozymes in meat applications still needs careful consideration owing to their widespread usage.