Quantum dots as advanced nanomaterials for food quality and safety applications: A comprehensive review and future perspectives.

The importance of food quality and safety lies in ensuring the best product quality to meet consumer demands and public health. Advanced technologies play a crucial role in minimizing the risk of foodborne illnesses, contamination, drug residue, and other potential hazards in food. Significant materials and technological advancements have been made throughout the food supply chain. Among them, quantum dots (QDs), as a class of advanced nanomaterials with unique physicochemical properties, are progressively demonstrating their value in the field of food quality and safety. This review aims to explore cutting-edge research on the different applications of QDs in food quality and safety, including encapsulation of bioactive compounds, detection of food analytes, food preservation and packaging, and intelligent food freshness indicators. Moreover, the modification strategies and potential toxicities of diverse QDs are outlined, which can affect performance and hinder applications in the food industry. The findings suggested that QDs are mainly used in analyte detection and active/intelligent food packaging. Various food analytes can be detected using QD-based sensors, including heavy metal ions, pesticides, antibiotics, microorganisms, additives, and functional components. Moreover, QD incorporation aided in improving the antibacterial and antioxidant activities of film/coatings, resulting in extended shelf life for packaged food. Finally, the perspectives and critical challenges for the productivity, toxicity, and practical application of QDs are also summarized. By consolidating these essential aspects into this review, the way for developing high-performance QD-based nanomaterials is presented for researchers and food technologists to better capitalize upon this technology in food applications.

Magnetic nanoparticle-based immunosensors and aptasensors for mycotoxin detection in foodstuffs: An update.

Mycotoxin contamination of food crops is a global challenge due to their unpredictable occurrence and severe adverse health effects on humans. Therefore, it is of great importance to develop effective tools to prevent the accumulation of mycotoxins through the food chain. The use of magnetic nanoparticle (MNP)-assisted biosensors for detecting mycotoxin in complex foodstuffs has garnered great interest due to the significantly enhanced sensitivity and accuracy. Within such a context, this review includes the fundamentals and recent advances (2020-2023) in the area of mycotoxin monitoring in food matrices using MNP-based aptasensors and immunosensors. In this review, we start by providing a comprehensive introduction to the design of immunosensors (natural antibody or nanobody, random or site-oriented immobilization) and aptasensors (techniques for aptamer selection, characterization, and truncation). Meanwhile, special attention is paid to the multifunctionalities of MNPs (recoverable adsorbent, versatile carrier, and signal indicator) in preparing mycotoxin-specific biosensors. Further, the contribution of MNPs to the multiplexing determination of various mycotoxins is summarized. Finally, challenges and future perspectives for the practical applications of MNP-assisted biosensors are also discussed. The progress and updates of MNP-based biosensors shown in this review are expected to offer readers valuable insights about the design of MNP-based tools for the effective detection of mycotoxins in practical applications.

Ratiometric Detection of Ochratoxin A Using a Regenerable COF-Au-MB-Apt Signal Probe on a Thermal-Regulated Sensor Module.

Ochratoxin A (OTA) frequently contaminates grains and consequently threatens human health. Herein, we develop a regenerable signal probe and apply it to a Au-based screen-printed electrode module (SPE) for OTA determination. The signal probe, containing a structural covalent organic framework, gold nanoparticles (AuNPs), indicative methylene blue (MB), and a highly selective aptamer, is synthesized with hydrothermal and self-assembly methods. The SPE is permanently functionalized with Prussian blue (PB), AuNPs, and semicomplementary ssDNA. The signal probe, absorbed onto this SPE via hybridization, is competitively expelled by OTA, providing a ratiometric readout of ΔIMB/IPB. Probe regeneration, to erase expired COF-Au-MB-Apt after each analysis, is established with the synergy of OTA-conducted Apt-ssDNA dissociation and on-chip thermal regulation. This advantage powerfully guarantees reduplicative analyses by avoiding irreversible Apt-OTA combination and accumulation on the sensing interface. Regenerations are performed in repetitive cycles (N = 7) with 98.5% reproduction efficiency, and IMB and IPB fluctuations are calculated as 1.45 and 1.12%. This method shows log-linear OTA response in a wide range from 0.2 pg/mL to 0.6 µg/mL, and the limit of detection is 0.12 pg/mL. During natural OTA determinations, recommended readouts match well with HPLC with less than 4.82% relative error.

TPB-DMTP@S-CDs/MnO2 Fluorescence Composite on a Dual-Emission-Capture Sensor Module for Fingerprint Recognition of Organophosphorus Pesticides.

Residues of organophosphorus pesticides (OPs) raise considerable concern, while identifying OPs from unknown sources is still a challenge to onsite fluorescence techniques. Herein, a dual-emission-capture sensor module, based on a TPB-DMTP@S-CDs/MnO2 fluorescence composite, is developed for OP fingerprint recognition. TPB-DMTP@S-CDs/MnO2, synthesized by a hydrothermal method and self-assembly, is spectrographically validated as a dual-wavelength fluorescence source. OP-sensitive catalysis (acetylcholinesterase on acetylthiocholine chloride) is designed to regulate fluorescence by decomposing quenchable MnO2. A flexibly fabricated sensor module supports the optimal dual-wavelength fluorescence excitations and captures and converts fluorescence emissions into equivalent photocurrents for feasible access. The most prominent finding is that dual-fluorescence emissions alternatively respond to levels, species, and multi-pH pretreatments of OPs due to varied MnO2 sizes and distributions. Therefore, OP fingerprint recognition is conducted by refining the multidimensional information from fluorescence-triggered photocurrents and preset hydrolyzation using principal component analysis and the rule of maximum covariance. The recommended method provides a wide dynamic range (1 × 10-6 ∼ 12 µg mL-1), a good limit of detection (7.9 × 10-7 µg mL-1), 15-day stability, and good selectivity to guarantee fingerprint recognition. For laboratory and natural samples, this method credibly identifies a single kind of OPs from multiple species at trace levels (10-5 µg mL-1) and performs well in two-component and multicomponent analyses.

Flexible-fabricated sensor module with programmable magnetic actuators coupled to L-cysteine functionalized Ag@Fe3O4 complexes for Cu2+ detection in fish tissues.

Heavy metal contamination for seafood, particularly fish, is arising great concerns, and consequentially it is necessary to develop a simple and direct detection method. In this work, Ag@Fe3O4 is successfully prepared by simple solvothermal method, and we present a flexible-fabricated sensor module with assembled programmable magnetic actuators. The resulting sensor integrates a three-electrode system with two programmable magnetic actuators at the bottom of the device, which regulates the amount of current by adjusting the brake to control the adsorption force and vibration. The L-Cysteine functionalized Ag@Fe3O4 is coated on the surface of the electrode, then the Cu2+ is dropped into the reaction tank. Its performance is studied by cyclic voltammetry and electrochemical impedance spectroscopy, and the key experimental conditions such as deposition potential, deposition time, and electrolyte pH are gradually optimized. Under optimal conditions, Cu2+ can be detected over a wide linear range (0.01 ~ 4 µM) and at a low LOD (0.34 nM). The results show that the proposed method has a good application prospect in the detection of Cu2+. This method is successfully applied to Cu2+ analysis in fish samples with an acceptable recovery of 93 ~ 102%.

Mycotoxins detection: view in the lens of molecularly imprinted polymer and nanoparticles.

Molecularly imprinted polymers (MIPs) are tailor-made functional composites which selectively recognize and bind the target molecule of interest. MIP composites are products of the massively cross-linked polymer matrices, generated via polymerization, with bio-inspired recognition cavities that are morphologically similar in size, shape and spatial patterns to the target conformation. These features have enabled researchers to expand the field of molecular recognition, more specifically for target with peculiar requirements. Nevertheless, MIPs alone are characterized with weak sensitivity. Besides, nanoparticles (NPs) are remarkably sensitive but also suffer from poor selectivity. Intriguingly, the combination of the two results in a highly sensitive and selective MIP composite. For instance, the conjugation of different functional NPs with MIPs can generate new flexible target capture tools, either a dynamic sensor or a novel drug delivery system. In this regard, although the technology is considered an established and feasible approach, it is still perceived as a burgeoning technology for various fields, which makes it unceasingly worthy reviewing. Therefore, in this review, we attempt to give an update on various custom-made biosensors based on MIPs in combination with various NPs for the detection of mycotoxins, the toxic secondary metabolites of fungi. We first summarize the classification, prevalence, and toxicological characteristics of common mycotoxins. Next, we provide an overview of MIP composites and their characterization, and then segment the role of NPs with respect to common types of MIP-based sensors. At last, conclusions and outlook are discussed.

Competitive electrochemical sensing for cancer cell evaluation based on thionine-interlinked signal probes.

The development of effective methods for tracking cancer cells is of significant importance in the early diagnosis and treatment of tumor diseases. Compared with the developed techniques, the electrochemical assay has shown considerable potential for monitoring glycan expression on the cell surface using nondestructive means. However, the application expansion of the electrochemical strategy is strongly impeded owing to its dependence on electroactive species. In this study, a competitive electrochemical strategy was reported for monitoring cancer cells based on mannose (a typical glycan) as a clinical biomarker. Herein, functionalized carbon nanotubes were used to load the thiomannosyl dimer, and thionine-interlinking signal probes were designed for competitive recognition. After effective competition between cancer cells and the anchored mannose, a decreased current was obtained as the cell concentration increased. Under optimal conditions, the proposed biosensor exhibited attractive performance for cancer cell analysis with a detection limit as low as 20 cells per mL for QGY-7701 and 35 cells per mL for QGY-7703, facilitating great promise for the sensitive detection of cancer cells and thus showing potential applications in cancer diagnosis.

Tectonic Implication of the 2022 MS 6.9 Earthquake in Menyuan, Qinghai, China: Analysis of Precise Earthquake Locations and InSAR.

Precise earthquake locations and InSAR (Interferometric Synthetic Aperture Radar) deformation observation are the major methods to understand the earthquake occurrence and disaster-causing process. This paper proposes a processing framework for analyzing strong earthquake mechanisms from one-dimensional velocity inversion to precise earthquake locations combined with InSAR deformation observation, and discusses earthquake-generating fault and dynamic mechanisms of tectonic deformation. We analyzed the Menyuan Ms 6.9 earthquake in 2022 and discuss the historical seismic activities and corresponding stress adjustment processes in the research region. To analyze and study the seismogenic structure and mechanism of the earthquake, we investigated the spatial and temporal distribution characteristics of the Menyuan earthquake sequence and analyzed the InSAR coseismic deformation field. We obtained the precise locations of the main shock and aftershocks and the coseismic InSAR deformation field of the main shock. It was confirmed that the Ms 6.9 earthquake was a shallow sinistral strike-slip earthquake, which led to the sequential activation of the Tuolaishan and Lenglongling faults. The main seismogenic fault of the mainshock was the northwestern end of the Lenglongling fault, and the earthquake rupture was segmented. It can be inferred that the earthquake was a stress-adjusted event triggered in the Qilian-Haiyuan tectonic belt caused by the northeasterly push of the Qinghai-Tibet Plateau. The risk of moderate to high earthquakes in the region remains high in the future, requiring enhanced seismic observations.

A Renewable Biosensor Based on LNA-Aptamer Hybridization for the Detection of Salmonella enteritidis in Penaeus vannamei.

Salmonella enteritidis (SE) is an important factor causing foodborne disease, and electrochemical sensors have drawn much attention for SE prevention and detection due to their many advantages. A renewable electrochemical sensor using specially designed locked nucleic acids (LNA) as linkers for the detection of SE was proposed to improve the reusability and reproducibility of biosensors. One end of the LNA was designed as an anchor to attach to modified electrodes through the sulfhydryl group; the other end was used to match with a short segment of SE aptamers, which will allow for the convenient renewal of occupied aptamers by raising the temperature. Results revealed that the manufactured biosensor had good stability, reproducibility, and selectivity in addition to a linear range of 6 × 101-6 × 105 CFU/mL and a limit of detection (LOD) of 20.704 CFU/mL. The recovery rate of SE for the real sample varied from 98.84% to 134.82% without exceeding 16.27% in the relative standard deviation (RSD). The proposed biosensor appears to be a promising tool for foodborne pathogen detection.

Determination of Dicofol in Tea Using Surface-Enhanced Raman Spectroscopy Coupled Chemometrics.

Dicofol is a highly toxic residual pesticide in tea, which seriously endangers human health. A method for detecting dicofol in tea by combining stoichiometry with surface-enhanced Raman spectroscopy (SERS) technology was proposed in this study. AuNPs were prepared, and silver shells were grown on the surface of AuNPs to obtain core-shell Au@AgNPs. Then, the core-shell Au@AgNPs were attached to the surface of a PDMS membrane by physical deposition to obtain a Au@AgNPs/PDMS substrate. The limit of detection (LOD) of this substrate for 4-ATP is as low as 0.28 × 10-11 mol/L, and the LOD of dicofol in tea is 0.32 ng/kg, showing high sensitivity. By comparing the modeling effects of preprocessing and variable selection algorithms, it is concluded that the modeling effect of Savitzky-Golay combined with competitive adaptive reweighted sampling-partial least squares regression is the best (Rp = 0.9964, RPD = 10.6145). SERS technology combined with stoichiometry is expected to rapidly detect dicofol in tea without labels.

Non-destructive discrimination of homochromatic foreign materials in cut tobacco based on VIS-NIR hyperspectral imaging.

BACKGROUND: The presence of foreign materials (FM) not only reduces the commercial value of tobacco and the quality of cigarette products, but also affects the aroma and flavor of cigarettes. Existing tobacco deblending equipment has received little study with respect to homochromatic FM. In the present study, visible-near infrared (VIS-NIR) hyperspectral imaging technique combined with chemometrics were used to identify and visualize the homochromatic FM on the surface of thining tobacco. A comparison with conventional vision method was made to analyze the feasibility of the method. The importance of detecting FM in cut tobacco was further demonstrated by first studying the volatile organic compounds produced in cigarette mixed FM smoke and their effects on human health before conducting hyperspectral experiments. RESULTS: The results indicated that solid-phase microextraction and gas chromatography mass spectrometry could detect volatile organic compounds in mainstream cigarette smoke that were not cigarette components and affected consumer health. Then, spectral features of the samples were extracted from hyperspectral images for building identification models to distinguish FM from cut tobacco. The visual RGB values of cut tobacco and FM were also used for the analysis of the recognition models. The results showed that the accuracy, precision and recall reached 100.00% using the back propagation artificial neural network classification model based on the principal component analysis raw wavelengths. The visualization results based on the optimal model produced clearer localization than conventional computer vision method. CONCLUSION: The present study revealed that the VIS-NIR hyperspectral imaging technology had advantage in the detection and localization of FM on the surface of thinning tobacco, which provided a foundation for improving the quality and safety of cut tobacco production. © 2023 Society of Chemical Industry.

Fast Burst-Sparsity Learning-Based Baseline Correction (FBSL-BC) Algorithm for Signals of Analytical Instruments.

Baseline correction is a critical step for eliminating the interference of baseline drift in spectroscopic analysis. The recently proposed sparse Bayesian learning (SBL)-based method can significantly improve the baseline correction performance. However, it has at least two disadvantages: (i) it works poorly for large-scale datasets and (ii) it completely ignores the burst-sparsity structure of the sparse representation of the pure spectrum. In this paper, we present a new fast burst-sparsity learning method for baseline correction to overcome these shortcomings. The first novelty of the proposed method is to jointly adopt a down-sampling strategy and construct a multiple measurements block-sparse recovery problem with the down-sampling sequences. The down-sampling strategy can significantly reduce the dimension of the spectrum; while jointly exploiting the block sparsity among the down-sampling sequences avoids losing the information contained in the original spectrum. The second novelty of the proposed method is introducing the pattern-coupled prior into the SBL framework to characterize the inherent burst-sparsity in the sparse representation of spectrum. As illustrated in the paper, burst-sparsity commonly occurs in peak zones with more denser nonzero coefficients. Properly utilizing such burst-sparsity can further enhance the baseline correction performance. Results on both simulated and real datasets (such as FT-IR, Raman spectrum, and chromatography) verify the substantial improvement, in terms of estimation accuracy and computational complexity.

Chemistry and the Potential Antiviral, Anticancer, and Anti-Inflammatory Activities of Cardiotonic Steroids Derived from Toads.

Cardiotonic steroids (CTS) were first documented by ancient Egyptians more than 3000 years ago. Cardiotonic steroids are a group of steroid hormones that circulate in the blood of amphibians and toads and can also be extracted from natural products such as plants, herbs, and marines. It is well known that cardiotonic steroids reveal effects against congestive heart failure and atrial fibrillation; therefore, the term "cardiotonic" has been coined. Cardiotonic steroids are divided into two distinct groups: cardenolides (plant-derived) and bufadienolides (mainly of animal origin). Cardenolides have an unsaturated five-membered lactone ring attached to the steroid nucleus at position 17; bufadienolides have a doubly unsaturated six-membered lactone ring. Cancer is a leading cause of mortality in humans all over the world. In 2040, the global cancer load is expected to be 28.4 million cases, which would be a 47% increase from 2020. Moreover, viruses and inflammations also have a very nebative impact on human health and lead to mortality. In the current review, we focus on the chemistry, antiviral and anti-cancer activities of cardiotonic steroids from the naturally derived (toads) venom to combat these chronic devastating health problems. The databases of different research engines (Google Scholar, PubMed, Science Direct, and Sci-Finder) were screened using different combinations of the following terms: "cardiotonic steroids", "anti-inflammatory", "antiviral", "anticancer", "toad venom", "bufadienolides", and "poison chemical composition". Various cardiotonic steroids were isolated from diverse toad species and exhibited superior anti-inflammatory, anticancer, and antiviral activities in in vivo and in vitro models such as marinobufagenin, gammabufotalin, resibufogenin, and bufalin. These steroids are especially difficult to identify. However, several compounds and their bioactivities were identified by using different molecular and biotechnological techniques. Biotechnology is a new tool to fully or partially generate upscaled quantities of natural products, which are otherwise only available at trace amounts in organisms.

Targeting NF-κB signaling pathway in cancer by dietary polyphenols.

Being a transcription factor, NF-κB regulates gene expressions involving cell survival and proliferation, drug resistance, metastasis, and angiogenesis. The activation of NF-κB plays a central role in the development of inflammation and cancer. Thus, the down-regulation of NF-κB may be an exciting target in prevention and treatment of cancer. NF-κB could act as a tumor activator or tumor suppressant decided by the site of action (organ). Polyphenols are widely distributed in plant species, consumption of which have been documented to negatively regulate the NF-κB signaling pathway. They depress the phosphorylation of kinases, inhibit NF-κB translocate into the nucleus as well as interfere interactions between NF-κB and DNA. Through inhibition of NF-κB, polyphenols downregulate inflammatory cascade, induce apoptosis and decrease cell proliferation and metastasis. This review highlights the anticancer effects of polyphenols on the basis of NF-κB signaling pathway regulation.

Fluorometric and electrochemical dual-mode nanoprobe for tetracycline by using a nanocomposite prepared from carbon nitride quantum dots and silver nanoparticles.

A fluorometric and electrochemical dual-mode method is described for sensitive and specific detection of tetracycline (Tc). A novel nanoprobe was designed that is making use of a Tc-specific aptamer (apta), carbon nitride quantum dots (CNQDs) and silver nanoparticles (AgNPs). The aptamer was linked to the CNQDs which then were used as templates to synthesize the apta-CNQD@AgNP nanocomposites. The blue fluorescence of the nanocomposites (with excitation/emission maxima at 365/440 nm) is quenched. The addition of Tc leads to fluorescence recovery and a decrease in the electroconductivity of a gold electrode modified with apta-CNQD@AgNPs. The fluorometric method has a linear response in the 0.1 µM - 10 mM Tc concentration range and a 15 nM detection limit. The amperometric method (best performed at a working voltage of 0.21 V vs. Ag/AgCl) has a linear response in the 1 nM to 0.1 mM Tc concentration range and a 0.26 nM detection limit. Recoveries of Tc from spiked milk samples were comparable to data obtained by HPLC. Graphical abstractA fluorometric and electrochemical dual-mode nanoprobe (apta-CNQD@AgNPs) was prepared from aptamer (apta), carbon nitride quantum dots (CNQDs) and silver nanoparticles (AgNPs). The nanoprobe can be used for determination of tetracycline (Tc) based on fluorescence recovery of apta-CNQD@AgNPs and a decrease in the electroconductivity of a gold electrode modified with apta-CNQD@AgNPs.

Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics.

It is crucial for the efficacy of the apple storage to apply methods like electronic nose systems for detection and prediction of spoilage or infection by Penicillium expansum. Based on the acquisition of electronic nose signals, selected sensitive feature sensors of spoilage apple and all sensors were analyzed and compared by the recognition effect. Principal component analysis (PCA), principle component analysis-discriminant analysis (PCA-DA), linear discriminant analysis (LDA), partial least squares discriminate analysis (PLS-DA) and K-nearest neighbor (KNN) were used to establish the classification model of apple with different degrees of corruption. PCA-DA has the best prediction, the accuracy of training set and prediction set was 100% and 97.22%, respectively. synergy interval (SI), genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) are three selection methods used to accurately and quickly extract appropriate feature variables, while constructing a PLS model to predict plaque area. Among them, the PLS model with unique variables was optimized by CARS method, and the best prediction result of the area of the rotten apple was obtained. The best results are as follows: Rc = 0.953, root mean square error of calibration (RMSEC) = 1.28, Rp = 0.972, root mean square error of prediction (RMSEP) = 1.01. The results demonstrated that the electronic nose has a potential application in the classification of rotten apples and the quantitative detection of spoilage area.

A ratiometric fluorescence sensor for ultra-sensitive detection of trypsin inhibitor in soybean flour using gold nanocluster@carbon nitride quantum dots.

Gold nanocluster@carbon nitride quantum dot nanocomposites protected by bovine serum albumin (BSA-AuNC@CNQDs) were designed as a ratiometric fluorescence nanosensor for ultra-sensitive detection of trypsin inhibitor (TI). CNQDs were prepared via thermal treatment of carbon nitride powder. BSA-CNQDs acted as templates to synthesize BSA-AuNC@CNQDs with dual-emission peaks at 450 and 650 nm. Trypsin can catalyze the hydrolysis of BSA and decompose BSA-AuNC@CNQDs resulting in fluorescence quenching. The fluorescence quenching at 650 nm was prevented by the addition of TI to inhibit the activity of trypsin. The nanosensor-trypsin system showed a satisfactory ability toward TI detection. The ratiometric responses (the ratio of intensity at 650 to 450 nm, I650/I450) had an excellent linearity (R2 = 0.981) with logarithmic values of TI concentrations in the broad range of 1-10,000 ng/mL. The limit of detection (LOD, 0.089 ng/mL) indicates ultra-sensitive detection of TI can be achieved. Additionally, TI in soybean flour was detected by the proposed ratiometric method with satisfactory recoveries (98.15-105.52%) and less than 6% of coefficient of variation. This study reveals that BSA-AuNC@CNQDs have potential applications in detection of TI in real samples.

Colorimetric determination of As(III) based on 3-mercaptopropionic acid assisted active site and interlayer channel dual-masking of Fe-Co-layered double hydroxides with oxidase-like activity.

A colorimetric method is described for the determination of As(III). It is based on the use of 3-mercaptopropionic acid (3-MPA) assisted active site and interlayer channel dual-masking of oxidase-like Fe-Co-layered double hydroxides (Fe-Co-LDH). The Fe-Co-LDH acts as an oxidase-mimicking nanozyme with high activity. It catalyzes the oxidation of colorless 3,3'5,5'-tetramethylbenzidine (TMB) to form a blue product (oxTMB) with an absorption maximum at 652 nm. It is found that As(III) firmly anchors onto the Fe* sites of the 3-MPA-modified Fe-Co-LDH via forming a stable Fe─As(III)─3-MPA─As(III)─Fe structure. This results in masking the active sites and interlayer channels of the Fe-Co-LDH nanozyme. As a result, the presence of As(III) as well as 3-MPA specifically inhibit the LDH-catalyzed chromogenic reaction. Based on the above principle, a colorimetric assay was designed for the determination of As(III). It provided linear response in the 0.10~8.33 µM As(III) concentration range and a detection limit as low as 35 nM. The assay was applied to the quantitation of As(III), even in the presence of potential interferents including As(V), Hg(II) and Pb(II), in environmental and drinking water samples. Graphical abstractSchematic illustration of the As(III) sensing mechanism based on 3-mercaptopropionic acid (3-MPA) assisted active site and interlayer channel dual-masking of Fe-Co-layered double hydroxides (Fe-Co-LDH) with oxidase-like activity. 3-MPA with sulfhydryl and carboxyl groups can assist As(III) to firmly anchor onto the Fe* sites inside the interlayer channels of the Fe-Co-LDH via forming a Fe─As(III)─3-MPA─As(III)─Fe structure, thus selectively resulting in a significant suppression of the chromogenic reaction.

Simulation of Starch Gel Printing and Deformation Process Using COMSOL.

The food industry holds immense promise for 3D printing technology. Current research focuses mainly on optimizing food material composition, molding characteristics, and printing parameters. However, there is a notable lack of comprehensive studies on the shape changes of food products, especially in modeling and simulating deformations. This study addresses this gap by conducting a detailed simulation of the starch gel printing and deformation process using COMSOL Multiphysics 6.2 software. Additive manufacturing (AM) technology is widely acclaimed for its user-friendly operation and cost-effectiveness. The 3D printing process may lead to changes in part dimensions and mechanical properties, attributable to the accumulation of residual stresses. Studies require a significant amount of time and effort to discover the optimal composition of the printed material and the most effective deformed 3D structure. There is a risk of failure, which can lead to wasted resources and research delays. To tackle this issue, this study thoroughly analyzes the physical properties of the gel material through COMSOL Multiphysics 6.2 software, It simulates the heat distribution during the 3D printing process, providing important insights into how materials melt and solidify. Three-part models with varying aspect ratios were meticulously designed to explore shape changes during both the printing process and exposure to an 80 °C environment, employing NMR and rheological characterization. Using the generalized Maxwell model for material simulation in COMSOL Multiphysics, the study predicted stress and deformation of the parts by analyzing solid heat transfer and solid mechanics physical fields. Simulation results showed that among three models utilizing a gel-PET plastic membrane bilayer structure, Model No. 1, with the largest aspect ratio, exhibited the most favorable deformation under an 80 °C baking environment. It displayed uniform bending in the transverse direction without significant excess warpage in the edge direction. In contrast, Models No. 2 and No. 3 showed varying degrees of excess warpage at the edges, with Model No. 3 exhibiting a more pronounced warpage. These findings closely aligned with the actual printing outcomes.

Raman spectroscopy-based microfluidic platforms: A promising tool for detection of foodborne pathogens in food products.

Rapid and sensitive detection of foodborne pathogens in food products is paramount for ensuring food safety and public health. In the ongoing effort to tackle this issue, detection methods are continually researched and upgraded to achieve rapidity, sensitivity, portability, and cost-effectiveness. This review addresses the critical need for improved technique by focusing on Raman spectroscopy-based microfluidic platforms, which have shown potential in revolutionizing the field of foodborne pathogen analysis offering point-of-care diagnosis and multiplex detection. The key problem lies in the persistent threat of compromised food quality and public health due to inadequate pathogen detection. The review elucidates the various trapping strategies employed in a microfluidic platform, including optical trapping, electrical trapping, mechanical trapping, and acoustic trapping for the capture of microbial cells. Subsequently, the review delves into the key aspects of the application of microbial detection in food products, highlighting recent advances and challenges in the field. The integrated technique allows point-of-care application assessment, which is an attractive quality for in-line and real-time detection of foodborne pathogens. However, the application of the technique in food products is limited and requires further research to combat the complexity of the food matrix, reduced costs of production, and ensure real-time use for diverse pathogens. Ultimately, this review aims to propel advancements in microbial detection, thus promoting enhanced food safety through state-of-the-art technologies.