Mesoporous silica coated core-shell nanoparticles substrate for size-selective SERS detection of chloramphenicol

Stacked long and short-term memory (SLSTM) - assisted terahertz spectroscopy combined with permutation importance for rapid red wine varietal identification

Mislabeling of low-value red wines as high-value ones is common, which seriously undermines consumer rights and interests. However, traditional sensory and chemical analysis methods have limitations, which highlights the need for novel detection techniques. To address above issues, terahertz time-domain spectroscopy (THz-TDS) combined with deep learning (DL) was employed to distinguish different red wine varieties quickly and non-destructively, contributing to correctly identifying red wine labels. Compared with the other models, the stacked long and short-term memory (SLSTM) model based on the first derivative (1-st der) spectra performed the best (Precision: 85.72 %, Recall: 85.61 %, F1-score: 85.59 %, Accuracy: 85.61 %). In addition, feature selection (FS) was used to explore the feasibility of improving model accuracy and reducing prediction time by eliminating redundant frequencies. Compared to full frequency, the 1-st der-SLSTM model based on permutation importance (PI) performed slightly lower (Precision: 84.42 %, Recall: 84.10 %, F1-score: 84.14 %, Accuracy: 84.18 %), but the prediction time was reduced by 2 s. Therefore, different models can be selected based on different detection needs by weighing accuracy and prediction time. In conclusion, the current research demonstrates that the SLSTM-assisted THz-TDS technology provides a novel approach for fast, accurate and non-destructive for fast, accurate and non-destructive discrimination of red wine labels, facilitating the maintenance of market discipline.

Synergistic pH-responsive MUC-1 aptamer-conjugated Ag/MSN Janus nanoparticles for targeted chemotherapy, photothermal therapy, and gene therapy in breast cancer

Drug resistance in cancer treatment, primarily attributed to the overexpression of the multidrug resistance (MDR) gene, significantly hampers the effectiveness of chemotherapy. This mechanism, driven by the increased production of P-glycoprotein (P-gp) efflux pumps, highlights the urgent need for innovative strategies to combat drug resistance in cancer patients. This study explores the application of antisense technology to suppress MDR gene expression, while addressing the challenges of instability and limited cellular uptake associated with antisense oligonucleotides. We synthesized Janus silver-mesoporous silica nanoparticles (Ag/MSN JNPs) using a sol-gel method, characterized by transmission electron microscopy (TEM) and dynamic light scattering (DLS), revealing uniformly sized, dumbbell-shaped nanoparticles with an average size of 285 ± 5.12 nm. Doxorubicin (DOX) was loaded into the porous structure of the mesoporous silica, and JNPs were functionalized with chitosan (CS) to incorporate P-gp antisense and a MUC-1 aptamer, serving as a pH-responsive gatekeeper. Our findings indicate that the Ap-As-DOX-JNPs achieved a remarkable 89 ± 0.59 % cell death in drug-resistant MCF-7/ADR cells after 48 h, alongside an 80 % reduction in P-gp expression. The combination of DOX, antisense technology, and photothermal therapy utilizing these JNPs demonstrates a promising strategy to effectively overcome drug resistance. Notably, normal MCF-7 cells exhibited reduced viability from 39.11 ± 1.12 % to 30.05 ± 1.07 % when treated with DOX-JNPs under near-infrared (NIR) irradiation. These results underscore the potential of utilizing MUC-1 aptamer-conjugated Janus nanoparticles in conjunction with chitosan as a gatekeeper to enhance the efficacy of chemotherapy, photothermal therapy, and gene therapy in overcoming multidrug resistance in cancer treatment.

A fluorescent Aptasensor based on magnetic-separation strategy with gold nanoclusters for Deoxynivalenol (DON) detection

A highly sensitive method based on MBs-cDNA@Apt-AuNCs519 was developed for deoxynivalenol (DON) detection in wheat. The MBs-cDNA@Apt-AuNCs519 was established using green emission gold nanoclusters (AuNCs519) with aggregation-induced emission properties as signal probes and combining amino-modified DON-aptamer (Apt), biotin-modified DNA strand (the partially complementary to Apt (cDNA)), and streptavidin-modified magnetic beads (MBs). The Apt-AuNCs519 were well connected with MBs-cDNA without DON but dissociated from MBs-cDNA@Apt-AuNCs519 with the addition of DON, leading to a noticeable reduction in the fluorescent intensity of the aptasensor. Moreover, this fluorescence aptasensor showed two linear relationships in the concentration range of 0.1-50 ng/mL and 50-5000 ng/mL with a limit of detection of 3.73 pg/mL with good stability, reproducibility and specificity. The results were consistent with high-performance liquid chromatography and enzyme-linked immunosorbent assay methods, further indicating the potential of this method for accurate trace detection of DON in wheat.

Recent Progress in Nanomaterial-Based Surface-Enhanced Raman Spectroscopy for Food Safety Detection

Food safety has recently become a widespread concern among consumers. Surface-enhanced Raman scattering (SERS) is a rapidly developing novel spectroscopic analysis technique with high sensitivity, an ability to provide molecular fingerprint spectra, and resistance to photobleaching, offering broad application prospects in rapid trace detection. With the interdisciplinary development of nanomaterials and biotechnology, the detection performance of SERS biosensors has improved significantly. This review describes the advantages of nanomaterial-based SERS detection technology and SERS's latest applications in the detection of biological and chemical contaminants, the identification of foodborne pathogens, the authentication and quality control of food, and the safety assessment of food packaging materials. Finally, the challenges and prospects of constructing and applying nanomaterial-based SERS sensing platforms in the field of food safety detection are discussed with the aim of early detection and ultimate control of foodborne diseases.

Well-ordered Au@Ag NBPs/SiO2 nanoarray for sensitive detection of chloramphenicol via DNAzyme-assisted SERS sensing

Misuse of chloramphenicol (CAP) can lead to severe food safety issues. Therefore, the accurate and sensitive detection of CAP residues is important for public health. Herein, a convenient and reliable interfacial self-assembly technique was used to form a uniform Au@Ag nanobipyramids (NBPs) film on an ordered SiO2 nanosphere array (SiO2 NS), which served as a Raman-enhanced substrate. In conjunction with a deoxyribonucleic acid enzyme-induced signal amplification strategy, we developed a novel surface-enhanced Raman scattering (SERS) biosensor for the selective and sensitive detection of CAP. The biosensor exhibited a detection limit of 6.42 × 10-13 mol·L-1 and a detection range of 1.0 × 10-12-1.0 × 10-6 mol·L-1. The biosensor could detect CAP in spiked milk samples with a high accuracy, and its recovery rates ranged from 97.88% to 107.86%. The as-developed biosensor with the advantages of high sensitivity and high selectivity offers a new strategy for the rapid, reliable and sensitive detection of CAP, rendering it applicable to food safety control.

A tailored dual core-shell magnetic SERS substrate with precise shell-thickness control for trace organophosphorus pesticides residues detection

For addressing the challenges of strong affinity SERS substrate to organophosphorus pesticides (OPs), herein, a rapid water-assisted layer-by-layer heteronuclear growth method was investigated to grow uniform UiO-66 shell with controllable thickness outside the magnetic core and provide abundant defect sites for OPs adsorption. By further assembling the tailored Au@Ag, a highly sensitive SERS substrate Fe3O4-COOH@UiO-66/Au@Ag (FCUAA) was synthesized with a SERS enhancement factor of 2.11 × 107. The substrate's suitability for the actual vegetable samples (cowpeas and peppers) was confirmed under both destructive and non-destructive detection conditions, showing a strong SERS response to fenthion and triazophos, with limits of detection of 1.21 × 10-5 and 2.96 × 10-3 mg/kg in the vegetables under destructive conditions, and 0.13 and 1.39 ng/cm2 for non-destructive detection, respectively. The FCUAA substrate had high SERS performance, effective adsorption capability for OPs, and demonstrated good applicability, thus exhibiting great potential for rapid detection of trace OPs residues in the food industry.

Developing a magnetic SERS nanosensor utilizing aminated Fe-Based MOF for ultrasensitive trace detection of organophosphorus pesticides in apple juice

The unreasonable use of organophosphorus pesticides leads to excessive pesticide residues in food, seriously threatening public health, and the potential of surface-enhanced Raman spectroscopy (SERS) technology, incorporating a metal-organic framework, is substantial for the rapid detection of trace pesticide residues. Here, a novel Fe3O4@NH2-MIL-101(Fe)@Ag (FNMA) SERS nanosensor was developed. Results indicated that the FNMA had a high enhancement factor of 1.53 × 108, a low limit of detection (LOD) of 4.55 × 10-12 M, and a relative standard deviation of 7.73 % for 4-nitrothiophenol, demonstrating its good SERS sensitivity and uniformity, and also possessed good storage stability for one month. In quantifying fenthion and methyl parathion in standard solutions and apple juice in the range of 0.05/0.02-20 mg/L, it showed LODs of 3.02 × 10-3 mg/L and 1.43 × 10-3 mg/L, and 0.0407 and 0.0075 mg/L, respectively, demonstrating potentials in ultrasensitive trace detection of pesticides in food.

Terahertz spectra reconstructed using convolutional denoising autoencoder for identification of rice grains infested with Sitophilus oryzae at different growth stages

Rice grains are often infected by Sitophilus oryzae due to improper storage, resulting in quality and quantity losses. The efficacy of terahertz time-domain spectroscopy (THz-TDS) technology in detecting Sitophilus oryzae at different stages of infestation in stored rice was employed in the current research. Terahertz (THz) spectra for rice grains infested by Sitophilus oryzae at different growth stages were acquired. Then, the convolutional denoising autoencoder (CDAE) was used to reconstruct THz spectra to reduce the noise-to-signal ratio. Finally, a random forest classification (RFC) model was developed to identify the infestation levels. Results showed that the RFC model based on the reconstructed second-order derivative spectrum with an accuracy of 84.78%, a specificity of 86.75%, a sensitivity of 86.36% and an F1-score of 85.87% performed better than the original first-order derivative THz spectrum with an accuracy of 89.13%, a specificity of 91.38%, a sensitivity of 88.18% and an F1-score of 89.16%. In addition, the convolutional layers inside the CDAE were visualized using feature maps to explain the improvement in results, illustrating that the CDAE can eliminate noise in the spectral data. Overall, THz spectra reconstructed with the CDAE provided a novel method for effective THz detection of infected grains.

Nanomaterials Based on 2,7,12,17-Tetra-tert-butyl-5,10,15,20-tetraaza-21H,23H-porphine Exhibiting Bifunctional Sensitivity for Monitoring Chloramphenicol and Co2

Monitoring antibiotic retention in human body fluids after treatment and controlling heavy metal content in water are important requirements for a healthy society. Therefore, the approach proposed in this study is based on developing new optical sensors using porphyrin or its bifunctional hybrid materials made with AuNPs to accomplish the accurate detection of chloramphenicol and cobalt. To produce the new optical chloramphenicol sensors, 2,7,12,17-tetra-tert-butyl-5,10,15,20-tetraaza-21H,23H-porphine (TBAP) was used, both alone in an acid medium and as a hybrid material with AuNPs in a water-DMSO acidified environment. The same hybrid material in the unchanged water-DMSO medium was the sensing material used for Co2+ monitoring. The best results of the hybrid materials were explained by the synergistic effects between the TBAP azaporphyrin and AuNPs. Chloramphenicol was accurately detected in the range of concentrations between 3.58 × 10-6 M and 3.37 × 10-5 M, and the same hybrid material quantified Co2+ in the concentration range of 8.92 × 10-5 M-1.77 × 10-4 M. In addition, we proved that AuNPs can be used for the detection of azaporphyrin (from 2.66 × 10-5 M to 3.29 × 10-4 M), making them a useful tool to monitor porphyrin retention after cancer imaging procedures or in porphyria disease. In conclusion, we harnessed the multifunctionality of this azaporphyrin and of its newly obtained AuNP plasmonic hybrids to detect chloramphenicol and Co2+ quickly, simply, and with high precision.

Deep Learning Enabled SERS Identification of Gaseous Molecules on Flexible Plasmonic MOF Nanowire Films

Through the capture of a target molecule at the metal surface with a highly confined electromagnetic field induced by surface plasmon, surface enhanced Raman spectroscopy (SERS) emerges as a spectral analysis technology with high sensitivity. However, accurate SERS identification of a gaseous molecule with low density and high velocity is still a challenge due to its difficulty in capture. In this work, a flexible paper-based plasmonic metal-organic framework (MOF) film consisting of Ag nanowires@ZIF-8 (AgNWs@ZIF-8) is fabricated for SERS detection of gaseous molecules. Benefiting from its micronanopores generated by the nanowire network and ZIF-8 shell, the effective capture of the gaseous molecule is achieved, and its SERS spectrum is obtained in this paper-based flexible plasmonic MOF nanowire film. With optimal structure parameters, spectra of gaseous 4-aminothiophenol, 4-mercaptophenol, and dithiohydroquinone demonstrate that this film has good SERS performance, which could maintain obvious Raman signals within 30 days during reproducible detection. To realize SERS identification of gaseous molecules, deep learning is performed based on the SERS spectra of the mixed gaseous analyte obtained in this flexible porous film. The results point out that an artificial neural network algorithm could identify gaseous aldehydes (gaseous biomarker of colorectal cancer) in simulated exhaled breath with high accuracy at 93.7%. The integration of the flexible paper-based film sensors with deep learning offers a promising new approach for noninvasive colorectal cancer screening. Our work explores SERS applications in gaseous analyte detection and has broad potential in clinical medicine, food safety, environmental monitoring, etc.

Paper-based colorimetric sensor using Photoshop and a smartphone app for the quantitative detection of carbofuran

We developed a smartphone-assisted microchemistry analyzer for the quantitative detection of carbofuran using a paper-based colorimetric sensor, Photoshop software, and a smartphone app. The changes in color of the carbofuran enzymatic reaction in the paper-based sensor were captured and analyzed using a smartphone-controlled analyzer with an LED light source and a smartphone camera. The high accuracy of this method was demonstrated for the determination of carbofuran with a linear response in the range 0.05-1.0 ppm and limits of detection (LOD) of 0.02 and 0.018 ppm using Photoshop and smartphone app colorimetric analysis, respectively. These two methods not only show the high sensitivity and highly quantitative relationships between the concentrations of commercial carbofuran and characteristic color values of the blue channel in smartphone images but were also applied to infusions of tea. Moreover, the smartphone app is able to GPS tag the location of the test and transmit the results to a website that displays quantitative results from carbofuran samples on a map.

Multifaceted Assessment of Porous Silica Nanocomposites: Unraveling Physical, Structural, and Biological Transformations Induced by Microwave Field Modification

In response to the persistent challenge of heavy and noble metal environmental contamination, our research explores a new idea to capture silver through porous spherical silica nanostructures. The aim was realized using microwave radiation at varying power (P = 150 or 800 W) and exposure times (t = 60 or 150 s). It led to the development of a silica surface with enhanced metal-capture capacity. The microwave-assisted silica surface modification influences the notable changes within the carrier but also enforces the crystallization process of silver nanoparticles with different morphology, structure, and chemical composition. Microwave treatment can also stimulate the formation of core-shell bioactive Ag/Ag2CO3 heterojunctions. Due to the silver nanoparticles' sphericity and silver carbonate's presence, the modified nanocomposites exhibited heightened toxicity against common microorganisms, such as E. coli and S. epidermidis. Toxicological assessments, including minimum inhibitory concentration (MIC) and half-maximal inhibitory concentration (IC50) determinations, underscored the efficacy of the nanocomposites. This research represents a significant stride in addressing pollution challenges. It shows the potential of microwave-modified silicas in the fight against environmental contamination. Microwave engineering underscores a sophisticated approach to pollution remediation and emphasizes the pivotal role of nanotechnology in shaping sustainable solutions for environmental stewardship.

A durian-shaped multilayer core-shell SERS substrate for flow magnetic detection of pesticide residues on foods

A new type of durian-shaped Fe3O4@Au@Ag@Au (DFAAA) multilayer core-shell composite was prepared as an efficient surface-enhanced Raman scattering (SERS) substrate. The optimization process and SERS enhancement mechanism of the substrate were further explained with finite-difference time-domain simulation. The dense and uniform spiny array on the DFAAA surface had abundant "hot spots", greatly improving sensitivity, uniformity and reproducibility, with a Raman enhancement factor of 3.01 × 107 and storage-life of 30 d. A "flow magnetic detection method" was proposed to realize rapid and flexible detection of pesticide residues on the surface of different foods including fish and apple. The limit of detection of malachite green and thiram on the fish and apple surfaces were 0.13 and 0.18 ng/cm2, respectively. With its high SERS performance and good magnetic, the DFAAA possessed great application prospects as a facile SERS substrate for rapid and non-destructive detection of trace pesticide residues on foods.

Fluorescent polythymidine-templated copper nanoclusters aptasensor for sensitive detection of tropomyosin in processed shrimp products

Tropomyosin (TM) is the main allergen in shellfish. Developing a novel, simple and accurate method to track and detect TM in food products is necessary. In this work, a label-free fluorescent aptasensor based on polythymidine (poly(T))-templated copper nanoclusters (CuNCs) was designed for sensitive detection of TM in processed shrimp products. Magnetic beads (MBs), aptamer and cDNA were used to construct an MBs-aptamer@cDNA complex as a detection probe, and with the presence of TM, the poly(T)-templated CuNCs attached at the end of the cDNA as the fluorescent signal was released from the complex to turn on the fluorescence. Under optimal conditions, the poly(T)-templated CuNCs aptasensor achieved a linear range from 0.1 to 50 μg/mL (R2 = 0.9980), a low limit of detection of 0.0489 μg/mL and an excellent recovery percentage of 105.29%-108.91% in the complex food matrix, providing a new approach for food safety assurance.

Developments in food neonicotinoids detection: novel recognition strategies, advanced chemical sensing techniques, and recent applications

Neonicotinoid insecticides (NEOs) are a new class of neurotoxic pesticides primarily used for pest control on fruits and vegetables, cereals, and other crops after organophosphorus pesticides (OPPs), carbamate pesticides (CBPs), and pyrethroid pesticides. However, chronic abuse and illegal use have led to the contamination of food and water sources as well as damage to ecological and environmental systems. Long-term exposure to NEOs may pose potential risks to animals (especially bees) and even human health. Consequently, it is necessary to develop effective, robust, and rapid methods for NEOs detection. Specific recognition-based chemical sensing has been regarded as one of the most promising detection tools for NEOs due to their excellent selectivity, sensitivity, and robust interference resistance. In this review, we introduce the novel recognition strategies-enabled chemical sensing in food neonicotinoids detection in the past years (2017-2023). The properties and advantages of molecular imprinting recognition (MIR), host-guest recognition (HGR), electron-catalyzed recognition (ECR), immune recognition (IR), aptamer recognition (AR), and enzyme inhibition recognition (EIR) in the development of NEOs sensing platforms are discussed in detail. Recent applications of chemical sensing platforms in various food products, including fruits and vegetables, cereals, teas, honey, aquatic products, and others are highlighted. In addition, the future trends of applying chemical sensing with specific recognition strategies for NEOs analysis are discussed.

CRISPR/Cas12a and G-quadruplex DNAzyme-driven multimodal biosensor for visual detection of Aflatoxin B1

Aflatoxin B1 (AFB1) contamination severely threatens human and animal health, it is thus critical to construct a strategy for its rapid, accurate, and visual detection. Herein, a multimodal biosensor was proposed based on CRISPR/Cas12a cleaved G-quadruplex (G4) for AFB1 detection. Briefly, specific binding of AFB1 to the aptamer occupied the binding site of the complementary DNA (cDNA), and cDNA then activated Cas12a to cleave G4 into fragments. Meanwhile, the intact G4-DNAzyme could catalyze 3, 3', 5, 5'-tetramethylbenzidine (TMB) to form colourimetric/SERS/fluorescent signal-enhanced TMBox, and the yellow solution produced by TMBox under acidic conditions could be integrated with a smartphone application for visual detection. The colourimetric/SERS/fluorescent biosensor yielded detection limits of 0.85, 0.79, and 1.65 pg·mL-1, respectively, and was applied for detecting AFB1 in peanut, maize, and badam samples. The method is suitable for visual detection in naturally contaminated peanut samples and has prospective applications in the food industry.

Micromolding-Assisted Production of SERS-Active Microcylinders for Size- and Charge-Selective Molecular Detection

Surface-enhanced Raman scattering (SERS) is an effective technique for amplifying the Raman signal of molecules by using metal nanostructures. However, these metal surfaces are susceptible to contamination by undesirable adhesives in complex mixtures, typically necessitating a time-consuming and costly sample pretreatment. In order to circumvent this, metal nanoparticles have been uniformly embedded within microgels by using microfluidics. In this work, we introduce a simple, scalable micromolding method for creating SERS-active cylindrical microgels designed to eliminate the need for pretreatment. These microcylinders are created through the simultaneous photoreduction and photo-cross-linking of precursor solutions. These solutions are optimized for consistent, high-intensity Raman signals as well as molecular size and charge selectivity. A sequential micromolding method is employed to design dual-compartment microcylinders, offering additional functionalities such as optical encoding, magnetoresponsiveness, and dual-charge selectivity. These SERS-active microcylinders provide robust Raman signals of small molecules, even in the presence of adhesive proteins, without compromising sensitivity. To demonstrate this capability, we directly detect pyocyanin in saliva and tartrazine in whole milk without any need for sample pretreatment.

High-efficiency SERS platform based on 3D porous PPDA@Au NPs as a substrate for the detection of pesticides on vegetables

Nowadays, the presence of highly toxic and persistent residues of pesticides in water and food around the world is becoming a serious problem, and so their rapid and sensitive detection is critical to human health. In this work, a 3D composite nanoparticle of porous PDA (polydopamine) microspheres and Au NPs (PPDA@Au NPs) was proposed as a SERS substrate to detect pesticides. Porous PDA as a substrate was first synthesized with F127 (Pluronic F127), dopamine hydrochloride, and 1,3,5-TMB (1,3,5-trimethylbenzene) under weakly alkaline conditions by a one-step method. Then, HAuCl4 was in situ reduced in the pores of PPDA spheres and grew sequentially for effecting the reducibility of PPDA. As a result, uniform 3D PPDA@Au NPs with "hot spots" were successfully synthesized as SERS substrates, which could effectively avoid the agglomeration of gold nanoparticles to greatly improve the sensitivity and uniformity of the SERS platform. At the same time, methyl parathion, 4-chlorophenol, and 2,4-D as representatives of pesticides were detected with the proposed PPDA@Au NP-based SERS platform, with detection limits lower than 7.26, 7.52, and 11 ng mL-1, separately. The current work presents a simple preparation method to prepare sensitive and uniform SERS platform PPDA@Au NPs, which have potential for applications in actual pesticide and drug testing.

Preparation of Fe3O4@UiO-66(Zr)@Ag NPs core-shell-satellite structured SERS substrate for trace detection of organophosphorus pesticides residues

Surface-enhanced Raman spectroscopy (SERS) technology has been revived and developed with the introduction of metal-organic frameworks (MOFs), while more valuable properties of MOFs for SERS substrates remain largely unexplored. This work constructed a new SERS substrate Fe₃O₄@UiO-66(Zr)@Ag nanoparticles (FUAs) with excellent SERS detection sensitivity, uniformity, reproducibility and stability, exhibiting a high Raman enhancement factor (5.62 × 10⁶), low limit of detection (LOD, 2.11 × 10^-11 M) and RSD (12.41 %) for 4-NBT, and maintaining 81 % SERS activity within 60 days. The FUAs took full advantage of the strong affinity of UiO-66(Zr) for organophosphorus pesticides (OPs) to realize trace OPs detection. The LODs of phoxim, triazophos and methyl parathion in apple juice were 0.041, 0.021 and 0.0031 mg/L, respectively, with good linearities ranging from 0.02 or 0.1-50 mg/L, meeting the requirements of the food control standards, indicating that the potentials and prospects of the FUAs SERS substrate for trace detecting OPs in foods.

Plasmonic Nanopillars-A Brief Investigation of Fabrication Techniques and Biological Applications

Nanopillars (NPs) are submicron-sized pillars composed of dielectrics, semiconductors, or metals. They have been employed to develop advanced optical components such as solar cells, light-emitting diodes, and biophotonic devices. To integrate localized surface plasmon resonance (LSPR) with NPs, plasmonic NPs consisting of dielectric nanoscale pillars with metal capping have been developed and used for plasmonic optical sensing and imaging applications. In this study, we studied plasmonic NPs in terms of their fabrication techniques and applications in biophotonics. We briefly described three methods for fabricating NPs, namely etching, nanoimprinting, and growing NPs on a substrate. Furthermore, we explored the role of metal capping in plasmonic enhancement. Then, we presented the biophotonic applications of high-sensitivity LSPR sensors, enhanced Raman spectroscopy, and high-resolution plasmonic optical imaging. After exploring plasmonic NPs, we determined that they had sufficient potential for advanced biophotonic instruments and biomedical applications.

Distinguishing pericarpium citri reticulatae of different origins using terahertz time-domain spectroscopy combined with convolutional neural networks

The geographical indication of pericarpium citri reticulatae (PCR) is very important in grading the quality and price of PCRs. Therefore, terahertz time-domain spectroscopy (THz-TDS) technology combined with convolutional neural networks (CNN) was proposed to distinguish PCRs of different origins without damage in this study. The one-dimensional CNN (1D-CNN) model with an accuracy of 82.99% based on spectral data processed with SNV was established. The two-dimensional image features were transformed from unprocessed spectral data using the gramian angular field (GAF), the Markov transition field (MTF) and the recurrence plot (RP), which were used to build a two-dimensional CNN (2D-CNN) model with an accuracy of 78.33%. Further, the CNN models with different fusion methods were developed for fusing spectra data and image data. In addition, the adding spectra and images based on the CNN (Add-CNN) model with an accuracy of 86.17% performed better. Eventually, the Add-CNN model based on ten frequencies extracted using permutation importance (PI) achieved the identification of PCRs from different origins. Overall, the current study would provide a new method for identifying PCRs of different origins, which was expected to be used for the traceability of PCRs products.

Microwave Irradiation vs. Structural, Physicochemical, and Biological Features of Porous Environmentally Active Silver–Silica Nanocomposites

Heavy metals and other organic pollutants burden the environment, and their removal or neutralization is still inadequate. The great potential for development in this area includes porous, spherical silica nanostructures with a well-developed active surface and open porosity. In this context, we modified the surface of silica spheres using a microwave field (variable power and exposure time) to increase the metal uptake potential and build stable bioactive Ag2O/Ag2CO3 heterojunctions. The results showed that the power of the microwave field (P = 150 or 700 W) had a more negligible effect on carrier modification than time (t = 60 or 150 s). The surface-activated and silver-loaded silica carrier features like morphology, structure, and chemical composition correlate with microbial and antioxidant enzyme activity. We demonstrated that the increased sphericity of silver nanoparticles enormously increased toxicity against E. coli, B. cereus, and S. epidermidis. Furthermore, such structures negatively affected the antioxidant defense system of E. coli, B. cereus, and S. epidermidis through the induction of oxidative stress, leading to cell death. The most robust effects were found for nanocomposites in which the carrier was treated for an extended period in a microwave field.

Discrimination of Pericarpium Citri Reticulatae in different years using Terahertz Time-Domain spectroscopy combined with convolutional neural network

Pericarpium Citri Reticulatae (PCR) in longer storage years possess higher medicinal values, but their differentiation is difficult due to similar morphological characteristics. Therefore, this study investigated the feasibility of using terahertz time-domain spectroscopy (THz-TDS) combined with a convolutional neural network (CNN) to identify PCR samples stored from 1 to 20 years. The absorption coefficient and refractive index spectra in the range of 0.2-1.5 THz were acquired. Partial least squares discriminant analysis, random forest, least squares support vector machines, and CNN were used to establish discriminant models, showing better performance of the CNN model than the others. In addition, the output data points of the CNN intermediate layer were visualized, illustrating gradual changes in these points from overlapping to clear separation. Overall, THz-TDS combined with CNN models could realize rapid identification of different year PCRs, thus providing an efficient alternative method for PCR quality inspection.

A SERS-Fluorescence dual-signal aptasensor for sensitive and robust determination of AFB1 in nut samples based on Apt-Cy5 and MNP@Ag-PEI

Food aflatoxin B1 (AFB1) contamination greatly threatens human health and its sensitive determination is imperative. In this study, a surface-enhanced Raman scattering (SERS) and fluorescence dual-signal aptasensor was constructed for sensitive AFB1 detection in peanuts, walnuts, and almonds samples. Fluorescent dye cy5 was used as fluorophore and Raman reporter, while polyethyleneimine modified Ag coating magnetic nanoparticles (MNP@Ag-PEI) were utilized to absorb the cy5 modified aptamer (apt-cy5). Results indicated that linear ranges of 0.001-1000 ng/mL and 0.2-20,000 ng/mL with detection limits of 0.45 pg/mL and 0.135 ng/mL for the SERS and fluorescence methods were obtained, respectively, and AFB1 detection in the nut samples using the aptasensor achieved satisfactory recoveries of 95.2%-108.6% for SERS and 94.7%-109.7% for fluorescence. Compared with other mono signal detection, the established aptasensor facilely fused the merits of the two signals and improved the detection accuracy and flexibility.

Analysis and detection using novel terahertz spectroscopy technique in dietary carbohydrate-related research: Principles and application advances

As one of the main functional substances, carbohydrates account for a large proportion of the human diet. Conventional analysis and detection methods of dietary carbohydrates and related products are destructive, time-consuming, and labor-intensive. In order to improve the efficiency of measurement and ensure food nutrition and consumer health, rapid and nondestructive quality evaluation techniques are needed. In recent years, terahertz (THz) spectroscopy, as a novel detection technology with dual characteristics of microwave and infrared, has shown great potential in dietary carbohydrate analysis. The current review aims to provide an up-to-date overview of research advances in using the THz spectroscopy technique in analysis and detection applications related to dietary carbohydrates. In the review, the principles of the THz spectroscopy technique are introduced. Advances in THz spectroscopy for quantitative and qualitative analysis and detection in dietary carbohydrate-related research studies from 2013 to 2022 are discussed, which include analysis of carbohydrate concentrations in liquid and powdery foods, detection of foreign body and chemical residues in carbohydrate food products, authentication of natural carbohydrate produce, monitoring of the fermentation process in carbohydrate food production and examination of crystallinity in carbohydrate polymers. In addition, applications in dietary carbohydrate-related detection research using other spectroscopic techniques are also briefed for comparison, and future development trends of THz spectroscopy in this field are finally highlighted.