Exploring the Chemical Constituents and Nutritive Potential of Bee Drone (Apilarnil): Emphasis on Antioxidant Properties.

A lesser-known bee product called drone brood homogenate (DBH, apilarnil) has recently attracted scientific interest for its chemical and biological properties. It contains pharmacologically active compounds that may have neuroprotective, antioxidant, fertility-enhancing, and antiviral effects. Unlike other bee products, the chemical composition of bee drone larva is poorly studied. This study analyzed the chemical compostion of apilarnil using several methods. These included liquid chromatography-mass spectrometry (LC-MS/MS) and a combination of gas chromatography/mass spectrometry with solid phase micro-extraction (SPME/GC-MS). Additionally, antioxidant activity of the apilarnil was assessed using 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. A chemical assessment of apilarnil showed that it has 6.3±0.00, 74.67±0.10 %, 3.65±0.32 %, 8.80±1.01 %, 13.16±0.94 %, and 8.79±0.49 % of pH, moisture, total lipids, proteins, flavonoids, and carbohydrates, respectively. LC-MS/MS analysis and molecular networking (GNPS) of apilarnil exhibited 44 compounds, including fatty acids, flavonoids, glycerophospholipids, alcohols, sugars, amino acids, and steroids. GC-MS detected 30 volatile compounds in apilarnil, mainly esters (24 %), ketones (23.84 %), ethers (15.05 %), alcohols (11.41 %), fatty acids (10.06), aldehydes (6.73 %), amines (5.46), and alkene (5.53 %). The antioxidant activity of apilarnil was measured using DPPH with an IC50 of 179.93±2.46 µg/ml.

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.

Fungal Communities Are More Sensitive to the Simulated Environmental Changes than Bacterial Communities in a Subtropical Forest: the Single and Interactive Effects of Nitrogen Addition and Precipitation Seasonality Change.

Increased nitrogen deposition (N factor) and changes in precipitation patterns (W factor) can greatly impact soil microbial communities in tropical/subtropical forests. Although knowledge about the effects of a single factor on soil microbial communities is growing rapidly, little is understood about the interactive effects of these two environmental change factors. In this study, we investigated the responses of soil bacterial and fungal communities to the short-term simulated environmental changes (nitrogen addition, precipitation seasonality change, and their combination) in a subtropical forest in South China. The interaction between N and W factors was detected significant for affecting some soil physicochemical properties (such as pH, soil water, and NO3- contents). Fungi were more susceptible to treatment than bacteria in a variety of community traits (alpha, beta diversity, and network topological features). The N and W factors act antagonistically to affect fungal alpha diversity, and the interaction effect was detected significant for the dry season. The topological features of the meta-community (containing both bacteria and fungi) network overrode the alpha and beta diversity of bacterial or fungal communities in explaining the variation of soil enzyme activities. The associations between Ascomycota fungi and Gammaproteobacteria or Alphaproteobacteria might be important in mediating the inter-kingdom interactions. In summary, our results suggested that fungal communities were more sensitive to N and W factors (and their interaction) than bacterial communities, and the treatments' effects were more prominent in the dry season, which may have great consequences in soil processes and ecosystem functions in subtropical forests.

Review of Marine Cyanobacteria and the Aspects Related to Their Roles: Chemical, Biological Properties, Nitrogen Fixation and Climate Change.

Marine cyanobacteria are an ancient group of photosynthetic microbes dating back to 3.5 million years ago. They are prolific producers of bioactive secondary metabolites. Over millions of years, natural selection has optimized their metabolites to possess activities impacting various biological targets. This paper discusses the historical and existential records of cyanobacteria, and their role in understanding the evolution of marine cyanobacteria through the ages. Recent advancements have focused on isolating and screening bioactive compounds and their respective medicinal properties, and we also discuss chemical property space and clinical trials, where compounds with potential pharmacological effects, such as cytotoxicity, anticancer, and antiparasitic properties, are highlighted. The data have shown that about 43% of the compounds investigated have cytotoxic effects, and around 8% have anti-trypanosome activity. We discussed the role of different marine cyanobacteria groups in fixing nitrogen percentages on Earth and their outcomes in fish productivity by entering food webs and enhancing productivity in different agricultural and ecological fields. The role of marine cyanobacteria in the carbon cycle and their outcomes in improving the efficiency of photosynthetic CO2 fixation in the chloroplasts of crop plants, thus enhancing the crop plant's yield, was highlighted. Ultimately, climate changes have a significant impact on marine cyanobacteria where the temperature rises, and CO2 improves the cyanobacterial nitrogen fixation.

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.

Localized bulging of an inflated rubber tube with fixed ends.

When a rubber tube with free ends is inflated under volume control, the pressure will first reach a maximum and then decrease monotonically to approach a constant asymptote. The pressure maximum corresponds to the initiation of a localized bulge and is predicted by a bifurcation condition, whereas the asymptote is the Maxwell pressure corresponding to a 'two-phase' propagation state. By contrast, when the tube is first pre-stretched and then has its ends fixed during subsequent inflation, the pressure as a function of the bulge amplitude has both a maximum and a minimum, and the behaviour on the right ascending branch has previously not been fully understood. We show that for all values of the pre-stretch and tube length, the ascending branches all converge to a single curve that is dependent only on the ratio of the tube thickness to the outer radius. This curve represents the Maxwell state to be approached in each case (if Euler buckling or axisymmetric wrinkling does not occur first), but this state is pressure-dependent, in contrast to the free-ends case. We also demonstrate experimentally that localized bulging cannot occur when the pre-stretch is sufficiently large and investigate what strain-energy functions can predict this observed phenomenon. This article is part of the theme issue 'The Ogden model of rubber mechanics: Fifty years of impact on nonlinear elasticity'.

Stress Detection of Conical Frustum Windows in Submersibles Based on Polarization Imaging.

Stress detection of the conical frustum window is a very important issue to ensure the safety of deep manned submersibles. In this paper, we propose a method based on polarization imaging to evaluate the stress accumulation and recovery in the conical frustum window. An experimental setup of Mueller matrix polarimetry is built, and the samples are made by referring to the typical conical frustum windows in submersibles. By pressurizing different pressures on the samples, we can find the changes of their Mueller matrix images and further derived polarization parameters. The results show that the polarization parameters can characterize the stress transfer process and the elastic-plastic transformation process of the window under different pressurization pressures. We also use a two-layered wave plate model to simulate the stress distribution in the window, which reveals different performances of the former and latter layers of the window under pressurization. Finally, we use a finite element model to simulate and understand some of the above experimental results. This proposed method is expected to provide new possibilities for monitoring the window stress and further ensure the safety of deep manned submersibles.

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.

Statistical Mueller matrix driven discrimination of suspended particles.

An effective method to calculate the statistical Mueller matrix (SMM) of suspended particles based on polarized light scattering is presented that takes advantage of the Stokes vectors measurement of individual particles. The calculation method of the SMM is derived based on statistics. Experimental results of Microcystis samples confirm that the SMM can characterize cells of different states. Then, pairwise contrast experiments indicate the great prospect of the SMM applied on the discrimination of suspended particles. It helps to find the optimal incident polarization state to discriminate suspended particles, and it has optimal discrimination ability. The parameter derived from the SMM can simultaneously discriminate particles including microalgae, microplastics, and sand-like particles.

Controllable Flowing of a Dielectric Fluid Droplet under the Action of Corona Discharge.

Polymer microfluidic technology is widely used in chemistry, biology, medicine, nanoparticles synthesis, and other fields. In this article, we introduce a novel method for the controllable flowing of dielectric fluid droplets. Under the action of corona discharge, the dielectric fluid droplet can be controllably driven to one or more conductive plate electrodes that are connected to the negative electrode on the substrate. Phenomena of polymerization, migration, and separation and merger are experimentally verified in detail, and the spreading speeds and steady-state time are discussed. The experimental results show that the proposed method is accurate and controllable.

Cyanobacteria-From the Oceans to the Potential Biotechnological and Biomedical Applications.

Cyanobacteria are photosynthetic prokaryotic organisms which represent a significant source of novel, bioactive, secondary metabolites, and they are also considered an abundant source of bioactive compounds/drugs, such as dolastatin, cryptophycin 1, curacin toyocamycin, phytoalexin, cyanovirin-N and phycocyanin. Some of these compounds have displayed promising results in successful Phase I, II, III and IV clinical trials. Additionally, the cyanobacterial compounds applied to medical research have demonstrated an exciting future with great potential to be developed into new medicines. Most of these compounds have exhibited strong pharmacological activities, including neurotoxicity, cytotoxicity and antiviral activity against HCMV, HSV-1, HHV-6 and HIV-1, so these metabolites could be promising candidates for COVID-19 treatment. Therefore, the effective large-scale production of natural marine products through synthesis is important for resolving the existing issues associated with chemical isolation, including small yields, and may be necessary to better investigate their biological activities. Herein, we highlight the total synthesized and stereochemical determinations of the cyanobacterial bioactive compounds. Furthermore, this review primarily focuses on the biotechnological applications of cyanobacteria, including applications as cosmetics, food supplements, and the nanobiotechnological applications of cyanobacterial bioactive compounds in potential medicinal applications for various human diseases are discussed.

Optimized Classification of Suspended Particles in Seawater by Dense Sampling of Polarized Light Pulses.

Suspended particles affect the state and vitality of the marine ecosystem. In situ probing and accurately classifying the suspended particles in seawater have an important impact on ecological research and environmental monitoring. Individual measurement of the optical polarization parameters scattered by the suspended particles has been proven to be a powerful tool to classify the particulate compositions in seawater. In previous works, the temporal polarized light pulses are sampled and averaged to evaluate the polarization parameters. In this paper, a method based on dense sampling of polarized light pulses is proposed and the experimental setup is built. The experimental results show that the dense sampling method optimizes the classification and increases the average accuracy by at least 16% than the average method. We demonstrate the feasibility of dense sampling method by classifying the multiple types of particles in mixed suspensions and show its excellent generalization ability by multi-classification of the particles. Additional analysis indicates that the dense sampling method basically takes advantage of the high-quality polarization parameters to optimize the classification performance. The above results suggest that the proposed dense sampling method has the potential to probe the suspended particles in seawater in red-tide early warning, as well as sediment and microplastics monitoring.

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.

Evaluation of matcha tea quality index using portable NIR spectroscopy coupled with chemometric algorithms.

BACKGROUND: The study reports a portable near infrared (NIR) spectroscopy system coupled with chemometric algorithms for prediction of tea polyphenols and amino acids in order to index matcha tea quality. RESULTS: Spectral data were preprocessed by standard normal variate (SNV), mean center (MC) and first-order derivative (1st D) tests. The data were then subjected to full spectral partial least squares (PLS) and four variable selection algorithms, such as random frog partial least square (RF-PLS), synergy interval partial least square (Si-PLS), genetic algorithm-partial least square (GA-PLS) and competitive adaptive reweighted sampling partial least square (CARS-PLS). RF-PLS was established and identified as the optimum model based on the values of the correlation coefficients of prediction (RP ), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD), which were 0.8625, 0.82% and 2.13, and 0.9662, 0.14% and 3.83, respectively, for tea polyphenols and amino acids. The content range of tea polyphenols and amino acids in matcha tea samples was 8.51-14.58% and 2.10-3.75%, respectively. The quality of matcha tea was successfully classified with an accuracy rate of 83.33% as qualified, unqualified and excellent grade. CONCLUSION: The proposed method can be used as a rapid, accurate and non-destructive platform to classify various matcha tea samples based on the ratio of tea polyphenols to amino acids. © 2019 Society of Chemical Industry.

The role of regulator FucP in Edwardsiella tarda pathogenesis and the inflammatory cytokine response in tilapia.

The animal intestine provides a competitive environment for the microbiota. Successful colonization by pathogens requires sensing chemical signals to regulate the expression of virulence genes. Some bacteria rely on a two-component chemical signal transduction system, named FusKR, to regulate virulence genes expression by intestinal fucose. Here we construct the fucP gene deletion strain prove FucP regulation of the T3SS in E. tarda. The result showed that the mutant strain had down-regulated significantly the gene expression of FusKR and T3SS compared to the wild-type strain (P < 0.05). This mutant strain significantly increased LD50 in zebrafish compared to the wild-type strain (P < 0.05), and significantly decreased penetration and motility in mucin than the wild-type strain (P < 0.05). Meanwhile, tilapia infected with mutant strain show significantly reduced E. tarda adherence and colonization than those infected with the wild-type strain (P < 0.05). Fish infected with EIB202 and ΔfucP showed significantly higher (P < 0.05) gene expression of IL-1ß, TNF-α, IFN-γ, TGF-ß and HSP-70 in head kidney than fish treated with PBS in the whole observed period; however CPP-3 did not show significant differences (P > 0.05) in all groups. Fish infected with EIB202 showed significantly higher (P < 0.05) gene expression of TGF-ß in head kidney than fish treated with ΔfucP in the whole observed period; however other cytokines did not show significant differences (P > 0.05) in the whole observed period. In addition, Fish infected with EIB202 showed significantly higher (P < 0.05) gene expression of IL-1ß, TNF-α and TGF-ß in spleen than fish treated with ΔfucP in the whole observed period, however IFN-γ, CPP-3, and HSP-70 did not show significant differences (P > 0.05) in the whole observed period. Although the gene expression of cytokines was induced similarly by both strains, all results indicate that the fucP gene deletion down-regulates the key gene expression of FucKR and T3SS, reduces the pathogenicity of E. tarda in fish, particularly decreases inducing the gene expression of TGF-ß in the head kidney and IL-1ß, TNF-α and TGF-ß in the spleen.

Different concentrations of Edwardsiella tarda ghost vaccine induces immune responses in vivo and protects Sparus macrocephalus against a homologous challenge.

Bacterial ghosts (BGs) can be generated by the controlled expression of the PhiX174 lysis gene E in gram-negative bacteria. They are intriguing vaccine candidates since ghosts retain functional antigenic cellular determinants often lost during traditional inactivation procedures. Here we prepared Edwardsiella tarda ghost (ETG) and tested different concentrations in vaccination trials. The results showed that serum IgM antibody titers were significantly higher in three different concentration immunization groups than control group (P < 0.05), However, there was no significant (P > 0.05) difference between the immunized groups. The phagocytic percentage (PP) was significantly higher (P < 0.05) in ETG immunized groups than in the control group from 3 days post-treatment. The PP continued to rise with time until day 21, when the values of three ETG immunized groups were 45.7%,51.2% and 50.7%, respectively. In addition, phagocytic index (PI) was significantly higher (P < 0.05) in ETG immunized groups than in the control group after 7 days post-treatment. However, there was no significant (P > 0.05) difference of PP or PI between immunized groups. In addition, non-specific immune immunity, such as acid phosphatase, alkaline phosphatase, superoxide dismutase and lysozyme activities displayed a similar pattern in all immunized groups, all immunized fish showed significantly higher activities than control group fish (P < 0.05). Most importantly three ETG immunized groups were all significantly more protected against the E. tarda challenge (19/25, 76% survival), (21/25, 84% survival) and (20/25, 80% survival) respectively, compared to (9/25, 36% survival) survival in the control group, but there was no significant (P > 0.05) difference of survival rate (SR) or relative percent survival (RPS) between immunized groups. All these results suggest that an ETG could stimulate cellular and humoral immunity, and could be used as a vaccine candidate in S.m. In summary, ETG can protect fish from Edwardsiellosis, and there is no significant difference in SR and RPS when three different concentrations of ETG are used, so it can easily be developed as a vaccine for mechanical and artificial operations.

[Near-infrared spectra combining with CARS and SPA algorithms to screen the variables and samples for quantitatively determining the soluble solids content in strawberry].

In using spectroscopy to quantitatively or qualitatively analyze the quality of fruit, how to obtain a simple and effective correction model is very critical for the application and maintenance of the developed model. Strawberry as the research object, this research mainly focused on selecting the key variables and characteristic samples for quantitatively determining the soluble solids content. Competitive adaptive reweighted sampling (CARS) algorithm was firstly proposed to select the spectra variables. Then, Samples of correction set were selected by successive projections algorithm (SPA), and 98 characteristic samples were obtained. Next, based on the selected variables and characteristic samples, the second variable selection was performed by using SPA method. 25 key variables were obtained. In order to verify the performance of the proposed CARS algorithm, variable selection algorithms including Monte Carlo-uninformative variable elimination (MC-UVE) and SPA were used as the comparison algorithms. Results showed that CARS algorithm could eliminate uninformative variables and remove the collinearity information at the same time. Similarly, in order to assess the performance of the proposed SPA algorithm for selecting the characteristic samples, SPA algorithm was compared with classical Kennard-Stone algorithm Results showed that SPA algorithm could be used for selection of the characteristic samples in the calibration set. Finally, PLS and MLR model for quantitatively predicting the SSC (soluble solids content) in the strawberry were proposed based on the variables/samples subset (25/98), respectively. Results show that models built by using the 0.59% and 65.33% information of original variables and samples could obtain better performance than using the ones obtained by using all information of the original variables and samples. MLR model was the best with R(pre)2 = 0.9097, RMSEP=0.3484 and RPD = 3.3278.

[Application of characteristic NIR variables selection in portable detection of soluble solids content of apple by near infrared spectroscopy].

In order to detect the soluble solids content(SSC)of apple conveniently and rapidly, a ring fiber probe and a portable spectrometer were applied to obtain the spectroscopy of apple. Different wavelength variable selection methods, including unin- formative variable elimination (UVE), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA) were pro- posed to select effective wavelength variables of the NIR spectroscopy of the SSC in apple based on PLS. The back interval LS- SVM (BiLS-SVM) and GA were used to select effective wavelength variables based on LS-SVM. Selected wavelength variables and full wavelength range were set as input variables of PLS model and LS-SVM model, respectively. The results indicated that PLS model built using GA-CARS on 50 characteristic variables selected from full-spectrum which had 1512 wavelengths achieved the optimal performance. The correlation coefficient (Rp) and root mean square error of prediction (RMSEP) for prediction sets were 0.962, 0.403°Brix respectively for SSC. The proposed method of GA-CARS could effectively simplify the portable detection model of SSC in apple based on near infrared spectroscopy and enhance the predictive precision. The study can provide a reference for the development of portable apple soluble solids content spectrometer.

Resistance model of an active capsule endoscope in a peristaltic intestine.

In the past studies, the resistance of magnetically controlled capsules running through the small intestine has been modeled assuming that the small intestine was a circular tube with a constant diameter. Peristalsis is an important character of the human gastrointestinal system, and it would result in some changes in the diameter of the intestine, meaning that the existing resistance models would no longer be applicable. In this paper, based on the assumption that intestinal peristalsis is actually a sinusoidal wave, a resistance model of the capsule running in the peristaltic intestine is established, and then it is validated experimentally. The model provides a realistic foundation for the optimization and control of the magnetically controlled endoscopy.

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.