Improve Detection Sensitivity Research Articles

Use of magnetic nanoparticles for the removal of organic and inorganic pollution in wastewater treatment-a review

Abstract Magnetic nanoparticles (MNPs) have gained significant attention for their exceptional magnetic properties and nano-level impact, making them highly effective tools for detecting environmental pollutants. This paper provides a comprehensive overview of recent advancements in utilizing MNPs for identifying organic and inorganic contaminants in wastewater. Key aspects discussed include the intrinsic properties of MNPs, strategies for their modification, and production techniques. Emphasis is placed on their potential applications in water pollution detection, highlighting their ability to enhance contaminant concentration and separation efficiency compared to conventional methods. The findings suggest that MNP-based approaches not only improve detection sensitivity but also promote eco-friendly practices, contributing to sustainable environmental management.

DNA Tetrahedron Reformative Lateral Flow Assay for Improved Detection Sensitivity and Anti-Interference.

The lateral flow assay is a strip-based analytical method for the portable and convenient detection of analytes of interest. It has the advantages of visual observation, autonomous sample flow, fast coloration time, minimal tedious operation procedures, and reliance on specialized instruments. However, the rough surface of the nitrocellulose membrane renders it difficult for the immobilized nucleic acids to remain in an ordered arrangement, and the immobilized nucleic acids are also liable to be digested in a complex matrix, inducing limited sensitivity and anti-interference. In this work, we demonstrate that the decoration of DNA nanostructures on lateral flow strips can improve assay sensitivity and anti-interference in comparison with commonly studied single-stranded DNA-disposed strips. DNA nanostructures enable probes to be more orderly and arranged on the strip and provide protection. Using adenosine 5'-triphosphate (ATP) as an analyte, a DNA tetrahedron reformative lateral flow strip has increased sensitivity and improved reliability in detection. The DNA nanostructure-decorated lateral flow strip is further successfully applied for ATP detection in real samples, such as bacterium testing and tableware cleanliness checking, by detection of the ATP content therein.

Enhanced Near-Infrared Fluorescence Emission near a Graphene-Metal Hybrid Structure.

Plasmon resonance plays an important role in improving the detection of biomolecules, and it is one of the focuses of research to use metal plasmon resonance to achieve fluorescence enhancement and to improve detection sensitivity. However, the problems of nondynamic tuning and fluorescence quenching of metal plasmon resonance need to be solved. Graphene surface plasmon resonance can be dynamically controlled, and the graphene adsorption of fluorescent molecules can avoid fluorescence quenching and greatly improve the fluorescence emission intensity. The graphene-metal hybrid structure designed in this work can solve the above two problems well, and the plasmon resonance can improve the fluorescence emission efficiency of molecules on the surface of graphene and improve the sensitivity of biological detection. At the same time, graphene nanoribbons in our hybrid structure do not require patterning, which greatly lowers the threshold for graphene application in biosensing.

Rapid on-site colorimetric detection of Arsenic(V) by NH2-MIL-88(Fe) nanozymes-based Ultraviolet-visible spectroscopic and smartphone-assisted sensing platforms

BackgroundBecause arsenate (As(V)) is a highly toxic pollutant, timely on-site monitoring of its concentration is crucial for mitigating potential environmental and health hazards. Traditional on-site detection methods for As(V) often face limitations of long response time and low sensitivity. Nanozymes are nanomaterials that exhibit enzyme-like catalytic activity. Nanozyme-based colorimetric detection can amplify signals and improve detection sensitivity by catalytically converting a minimal substrate quantity into a substantial amount. However, current nanozymes-based As(V) detection methods still suffer from prolonged response time and the lack of convenient detection tools. ResultsWe develop a rapid and sensitive strategy for on-site colorimetric As(V) detection using a metal-organic framework (MOF) nanozyme, NH2-MIL-88(Fe). NH2-MIL-88(Fe) featured abundant Fe unsaturated metal centers (UMCs) and ordered porous structure, exhibiting excellent peroxidase-like activity, rapid As(V) adsorption, and high water dispersity. Fe UMCs efficiently catalyzed the oxidization of colorless tetramethylbenzidine (TMB) to blue oxTMB in the presence of H2O2. As(V) selectively inhibited this activity, reducing Ultraviolet-visible (UV-vis) absorption at 650 nm and fading the solution color. Mechanistically, As(V) interacted with Fe UMCs through As-O-Fe bonds, impeding Fe3+ reduction and Fe2+ catalytic ability, reducing •OH production. Under optimized conditions, As(V) was detected within 15 minutes, with detection limits of 2.78 μg•L-1 via UV-vis and 13.56 μg•L-1 via smartphone-assisted platform, covering a linear range of 5.00 - 600.00 μg•L-1. Additionally, NH2-MIL-88(Fe) was incorporated into an agarose hydrogel to create a portable composite for smartphone-based colorimetric analysis As(V). Significance and noveltyThis study addresses the existing issues of nanozyme-based As(V) sensors, elucidates the molecular mechanism by which As(V) affects NH2-MIL-88(Fe) nanozymes activity, and confirms the precision and accuracy of the established method in spiked river samples. Our rapid, sensitive, and facile approach offers a practical and efficient solution for on-site As(V) detection, facilitating swift intelligent risk identification and effective pollution prevention and remediation.

Intramicellar sensor assays: Improving sensing sensitivity of sensor array for thiol biomarkers.

Array-based analysis allows for precise disease diagnosis by simultaneously detecting multiple biomarkers. However, most array sensing platforms rely on non-covalent interactions between sensors and analytes, which limits their sensitivity. This study enhances the sensitivity of array analysis for thiol biomarkers by incorporating polyion complex micelles into the sensor array design. Polyion complex micelles are formed through the self-assembly of carbon dots (CDs) and anionic diblock copolymers. The sensing detection process can occur inside the core of the micelle, the confined space and ionic environment within the core reduce the interaction distance between CDs, metal ions, and analytes, thereby significantly improving detection sensitivity while minimizing metal ions consumption. The developed array system can accurately identify multiple thiols across a broad concentration range (0.5-1000μM) with 100% accuracy. Additionally, support vector machine (SVM) analysis reveals a detection limit of approximately 0.1μM for individual thiol systems. Compared to non-micellar approaches, this micelle-based array reduces the detection limit for thiol biomarkers by 20-fold and decreases Ag+ usage by 40-fold. The system is suitable for both qualitative and quantitative analysis of thiol biomarkers, offering a powerful tool for the accurate diagnosis of thiol-related diseases.

Detection of heavy metals in soil using Au@SiO2 nanoparticles and surface microstructure combined with laser-induced breakdown spectroscopy.

The detection of heavy metals in soil is of great scientific significance for food security and human health. However, traditional detection methods are complicated, time-consuming, and labor-intensive. Herein, we developed a novel method using Au@SiO2 nanoparticles (NPs) and surface microstructure combined with laser-induced breakdown spectroscopy (Au@SiO2 NPs-SMS-LIBS) for the rapid detection of lead (Pb), chromium (Cr), and copper (Cu) in soil samples. The surface microstructures and Au@SiO2 NPs were prepared to improve detection sensitivity and stability. The limits of detection (LODs) for Pb, Cr, and Cu were 0.36 mg/kg, 0.32 mg/kg, and 0.28 mg/kg, respectively, with relative standard deviations (RSDs) of 5.47-6.72 %. The mechanisms of spectral performance enhancement of LIBS detection were thoroughly investigated. Furthermore, the stacking combination model was developed to improve quantitative accuracy, with the correlation of the prediction set (Rp2) for Pb, Cr, and Cu being 0.9285, 0.8625, and 0.9160, respectively. This work offers a very promising solution to improve the sensitivity, stability, and accuracy of heavy metal detection. The developed method holds great application potential for large-scale soil assessments and real-time heavy metal pollution monitoring.

Enhanced Glucose Sensing via Nanoparticles-Modified Extended Gates: A Novel Approach to Electric Double Layer Modulation and Signal Amplification in Field Effect Transistors for Improved Detection Sensitivity

Enhanced Glucose Sensing via Nanoparticles-Modified Extended Gates: A Novel Approach to Electric Double Layer Modulation and Signal Amplification in Field Effect Transistors for Improved Detection Sensitivity

Deep Learning for Real-Time P-Wave Detection: A Case Study in Indonesia's Earthquake Early Warning System

Detecting seismic events in real-time for prompt alerts and responses is a challenging task that requires accurately capturing P-wave arrivals. This task becomes even more challenging in regions like Indonesia, where widely spaced seismic stations exist. The wide station spacing makes associating the seismic signals with specific even more difficult. This paper proposes a novel deep learning-based model with three convolutional layers, enriched with dual attention mechanisms—Squeeze, Excitation, and Transformer Encoder (CNN-SE-T) —to refine feature extraction and improve detection sensitivity. We have integrated several post-processing techniques to further bolster the model's robustness against noise. We conducted comprehensive evaluations of our method using three diverse datasets: local earthquake data from East Java, the publicly available Seismic Waveform Data (STEAD), and a continuous waveform dataset spanning 12 hours from multiple Indonesian seismic stations. The performance of the CNN-SE-T P-wave detection model yielded exceptionally high F1 scores of 99.10% for East Java, 92.64% for STEAD, and 80% for the 12-hour continuous waveforms across Indonesia's network, demonstrating the model's effectiveness and potential for real-world application in earthquake early warning systems.

High-sensitive Fabry-Perot cavity-enhanced optical resonator for photoacoustic sensing

Highly sensitive broadband acoustic detectors are needed to expand the capabilities of geological exploration, photoacoustic imaging, and industrial inspection techniques. However, while pursuing miniaturization, it is difficult to combine high sensitivity and wide acoustic detection frequency range. Meanwhile, the consistency and mechanical stability of the manufacturing process become important challenges for optical sensors in practical applications. To address this issue, we present a new silicon-based cavity-enhanced Fabry-Pérot interferometer photoacoustic sensor and fully characterize its acoustic performance. Micro-resonant cavity-enhanced photoacoustic sensor with broadband acoustic responses up to 50 Hz-10 k Hz has been fabricated. The detection sensitivity is also impressive, reaching -120.23 dB re rad/µPa @ 1 k Hz, with a noise equivalent pressure (NEP) of 88.7 µPa/√Hz @ 1 k Hz. This approach will help design photoacoustic sensors to improve detection sensitivity and bandwidth with limited fabrication accuracy and size.

Modular and Fast Assembly of Self-Immobilizing Fluorogenic Probes for β-Galactosidase Detection.

β-Galactosidase (β-gal) has emerged as a pivotal biomarker in primary ovarian cancer. Despite the existence of numerous fluorescent probes for β-gal activity detection, quinone methide-based immobilizing probes were shown to avoid rapid diffusion of the activated fluorophore and improve the resolution. However, the synthesis of these fluorophores, particularly near-infrared fluorophores, still exhibits lower efficiency. In this study, we introduce modular and rapidly assembled self-immobilizing fluorogenic probes, capitalizing on the proximity labeling properties of quinone methide (QM). Compared to conventional fluorescent probes, these new probes not only exhibit a fluorogenic response but also achieve permanent retention, demonstrating improved detection sensitivity, particularly after cell fixation and in vivo animal model studies. This straightforward synthesis approach holds promise for broader applications in detecting other analytes.

Advances in aggregation-induced emission luminogens for biomedicine: From luminescence mechanisms to diagnostic applications

Advancements in early detection have demonstrated the significance of biomarkers as indicators of health and disease. Traditional detection methods often face limitations, such as low sensitivity and time consumption. Fluorescence-based techniques are considered promising approaches because of their noninvasiveness and rapid response. However, these conventional methods have some drawbacks, such as low quantum yield, photobleaching, and aggregation-caused quenching. Recently, aggregation-induced emission (AIE) has emerged as a potential alternative, characterized by luminous emission upon aggregation, thus improving detection sensitivity and stability. This review explores the recent advancements in AIE luminogens (AIEgens) in biomedical engineering, with a particular focus on their application in biomarker detection. Here, we discuss the different types of AIE mechanisms and their advantages in disease diagnosis and imaging. In addition, we summarize the development of various AIEgen-based probes for the detection of diverse biomarkers. Finally, we address the remaining challenges and future directions for AIE materials in modern biomedical engineering, emphasizing the potential of AIEgens in biomarker detection and disease diagnosis strategies.

Blood biomarkers in Down syndrome: Facilitating Alzheimer's disease detection and monitoring.

Blood-based biomarkers continue to be explored for disease detection, monitoring of progression, and therapeutic outcomes as the diagnostic determination of Alzheimer's Disease in Down Syndrome (DS-AD) remains challenging in clinical settings. This perspective highlights the current status of this effort. Overall, amyloid (A), tau (T), and neurodegeneration (AT[N]) blood-based biomarkers have been shown to increase with disease pathology for individuals with DS. Phosphorylated tau biomarkers (p-tau217, p-tau181) have been consistently shown to track disease progression for DS-AD and are likely good candidates for use in clinical settings. Biomarkers of inflammation (glial fibrillary acidic protein) also show promise; however, additional work is needed. Findings from stability work of blood-based biomarkers conducted among non-DS also supportthe potential longitudinal utility of biomarkers such as neurofilament light chain and p-tau181 in DS. Gaps in our knowledge are highlighted, and a potential role for sex differences in biomarker outcomes is noted, along with recommendations for determining the appropriate context of use when translating biomarkers into clinical applications. HIGHLIGHTS: An overview of blood-based biomarkers for Alzheimer's disease (AD) was provided for consideration of their utility among individuals with Down syndrome when looking toward potential clinical applications. Longitudinal stability of many blood biomarkers and improvement in detection sensitivity make blood such as plasma a viable source for exploring AD pathology. Variability in reviewed findings regarding the application of blood biomarkers highlights the importance of understanding and defining the appropriate context of use, particularly when translating them into clinical practice.

Synthesis and application of electrospun polyvinylidene fluoride/polyvinylidene glycol nanofibrous membrane for enhanced biomarker detection in immunochromatography assay

Immunochromatography assay (ICA) stands as a pioneering point-of-care testing (POCT) method, leveraging the simplicity, portability, and versatility of dry-strip testing method, chromatographic and antigen-antibody immunological reaction. Despite its numerous advantages, the shortcomings like low sensitivity, limited matrix, restricted matrix compatibility, and uncontrollable chromatographic rates, have hindered the ICA application. To overcome the aforementioned challenges, we proposed constructing a novel ICA strip based on homemade hydrophilic, flexible membranes to replace the commercially available nitrocellulose (NC). The key to the innovation lies in the spinning solution of a blend of poly (vinylidene fluoride) (PVDF) and polyethylene glycol (PEG), which is made into a nanofibrous membrane named EPVDF/PEG membrane by electrostatic spinning technique. This membrane, due to its high specific surface area and high porosity, can be loaded with more detection reagents than normal substrates, increasing the reaction time and achieving improved detection sensitivity. This membrane also has adjustable chromatographic rate, high protein loading capacity, good biocompatibility and excellent colouring ability. As a result, the established EPVDF/PEG-based ICA strips demonstrate an ultralow detection limit, as low as 0.5 mIU∙mL−1 when human chorionic gonadotropin (HCG) serves as the biomarker model, which is a 50-fold increase in detection sensitivity compared to commercial strips. Furthermore, EPVDF/PEG-based ICA strips can be produced on a large scale for the availability of efficient and mature electrospinning technologies. In summary, this work offers a transformative advancement in ICA development, potentially opening new horizons for sensitive biomarker detection.

CTR-FAPI PET enables precision management of medullary thyroid carcinoma.

Medullary thyroid carcinoma (MTC) can only be cured through the excision of all metastatic lesions, but 29-60% patients failed to localize the disease in the current clinical practice. Previously, we developed a fibroblast activation protein inhibitor (FAPI)-based covalent targeted radioligand (CTR) for improved detection sensitivity and accuracy. In this first-in-class clinical trial, we head-to-head compared [68Ga]Ga-CTR-FAPI PET-CT and [18F]FDG PET-CT in 50 MTC patients. The primary endpoint was the patient-based detection rate, with [68Ga]Ga-CTR-FAPI exhibiting higher detection than [18F]FDG (98% vs. 66%, p=0.0002). This improved detection was attributed to increased tumor uptake (SUVmax 11.71±9.16 vs. 2.55±1.73, p<0.0001). Diagnostic accuracy, validated on lesions with gold-standard pathology, was greater for [68Ga]Ga-CTR-FAPI compared to [18F]FDG (96.7% vs. 43.3%, p<0.0001). Notably, 32% patients altered management following [68Ga]Ga-CTR-FAPI PET-CT, and 66.7% patients changed their surgical plan. Overall, [68Ga]Ga-CTR-FAPI PET-CT provided superior detection and diagnostic accuracy compared to [18F]FDG PET-CT, enabling precision management of MTC patients.

Supramolecular Catalyst for Improving the Sensitivity of Biomolecule Detection

AbstractSupermolecule refers to two or more molecules that are bonded together by secondary bonds between molecules to form a multimolecular system at the level of more than molecules. At this point, the molecules form an orderly aggregation, showing its unique structure and function. Supramolecular catalysts can form structures with specific functions through non‐covalent interactions (e. g., hydrogen bonding, π‐π stacking, etc.) to mimic the catalytic mechanism of natural enzymes and achieve susceptible and specific detection of biomolecules. The application of supramolecules is mainly focused on the self‐assembly of components for the construction of sensing platform. Therefore, supramolecular catalysts have a huge potential in biomolecule detection. This article focuses on the application of cyclodextrins(CD), cucurbit[n]uril(CB), porphyrins(PP) and Calix[n]arenes(CA) in the field of catalysis and in improving detection sensitivity. Research progress of supramolecular catalysts in polymerization amplification is summarized in this paper.

Spatially resolved metabolomics: From metabolite mapping to function visualising.

Mass spectrometry imaging (MSI)-based spatially resolved metabolomics addresses the limitations inherent in traditional liquid chromatography-tandem mass spectrometry (LC-MS)-based metabolomics, particularly the loss of spatial context within heterogeneous tissues. MSI not only enhances our understanding of disease aetiology but also aids in the identification of biomarkers and the assessment of drug toxicity and therapeutic efficacy by converting invisible metabolites and biological networks into visually rendered image data. In this comprehensive review, we illuminate the key advancements in MSI-driven spatially resolved metabolomics over the past few years. We first outline recent innovations in preprocessing methodologies and MSI instrumentation that improve the sensitivity and comprehensiveness of metabolite detection. We then delve into the progress made in functional visualization techniques, which enhance the precision of metabolite identification and annotation. Ultimately, we discuss the significant potential applications of spatially resolved metabolomics technology in translational medicine and drug development, offering new perspectives for future research and clinical translation. HIGHLIGHTS: MSI-driven spatial metabolomics preserves metabolite spatial information, enhancing disease analysis and biomarker discovery. Advances in MSI technology improve detection sensitivity and accuracy, expanding bioanalytical applications. Enhanced visualization techniques refine metabolite identification and spatial distribution analysis. Integration of MSI with AI promises to advance precision medicine and accelerate drug development.

Bifunctional MoO3-x/CuS Heterojunction Nanozyme-Driven "Turn-On" SERS Signal for the Sensitive Detection of Cerebral Infarction Biomarker S100B.

The use of nanozymes has become a promising auxiliary approach to "turn on" surface-enhanced Raman scattering (SERS) signals for the label-free detection of disease markers. Nevertheless, there are still major challenges to develop bifunctional nanomaterials with both excellent enzyme-like activity and high SERS performance. To this end, a novel Z-scheme MoO3-x/CuS heterojunction was first constructed as a powerful "two-in-one" substrate, which can not only catalyze leucomalachite green (LMG) to SERS-active malachite green (MG) but also serve as an efficient substrate to amplify the SERS signal of catalysate. Due to the strong interfacial coupling effect between the MoO3-x and CuS nanomaterial, which promoted the separation and transport of carriers in the heterojunction, the MoO3-x/CuS heterojunction showed higher peroxidase-like activity compared to individual components and the previously reported heterojunction nanozymes. Inspired by these results, a sandwich-type SERS immunoassay for the detection of the cerebral infarction biomarker S100 calcium-binding protein (S100B) was proposed based on the output signal of MG at 1620 cm-1. Furthermore, introducing the antifouling material chitosan on the surface of the MoO3-x/CuS heterojunction can effectively resist nonspecific protein adsorption and significantly improve the detection accuracy of the immunoassay. Therefore, the SERS immunoassay based on the MoO3-x/CuS heterojunction realized highly sensitive and selective detection of S100B in the concentration range of 0.001 to 100 ng/mL, with a low limit of detection of 0.47 pg/mL. The developed method has been successfully used for the accurate detection of S100B in clinical serum. The results showed that the level of S100B in the serum of cerebral infarction patients can be distinguished from those of healthy individuals and intracranial tumor patient controls. In addition, the acquired values of S100B in the serum of cerebral infarction patients based this strategy were well consistent with the results of electrochemiluminescence (ECL) detection with a relative error of less than ±7.3. It is expected that this work may open up a paradigm for improving detection sensitivity and accuracy for the early diagnosis and treatment monitoring of cerebral infarction in the clinic.

Open-loop narrowband magnetic particle imaging based on mixed-frequency harmonic magnetization response.

Magnetic particle imaging (MPI), a radiation-free, dynamic, and targeted imaging technique, has gained significant traction in both research and clinical settings worldwide. Signal-to-noise ratio (SNR) is a crucial factor influencing MPI image quality and detection sensitivity, and it is affected by ambient noise, system thermal noise, and the magnetization response of superparamagnetic nanoparticles. Therefore to address the high amplitude system and inherent thermal noise present in conventional MPI systems is essential to improve detection sensitivity and imaging resolution. This study introduces a novel open-loop, narrow-band MPI signal acquisition system based on mixed-frequency harmonic magnetization response. Allowing superparamagnetic nanoparticles to be excited by low frequency, high amplitude magnetic fields and high frequency, low amplitude magnetic fields, the excitation coil generates a mixed excitation magnetic field at a mixed frequency of 8.664 kHz (f H + 2f L ), and the tracer of superparamagnetic nanoparticles can generate a locatable superparamagnetic magnetization signal with rich harmonic components in the mixed excitation magnetic field and positioning magnetic field. The third harmonic signal is detected by a Gradiometer coil with high signal-to-noise ratio, and the voltage cloud image is formed. The experimental results show that the external noise caused by the excitation coil can be effectively reduced from 12 to about 1.5 μV in the imaging area of 30 mm × 30 mm, which improves the stability of the detection signal of the Gradiometer coil, realizes the detection of high SNR, and makes the detection sensitivity reach 10 μg Fe. By mixing excitation, the total intensity of the excitation field is reduced, resulting in a slight improvement of the resolution under the same gradient field, and the spatial resolution of the image reconstruction is increased from 2 mm under the single frequency excitation (20.7 kHz) in the previous experiment to 1.5 mm under the mixed excitation (8.664 kHz). These experimental results highlight the effectiveness of the proposed open-loop narrowband MPI technique in improving signal detection sensitivity, achieving high signal-to-noise ratio detection and improving the quality of reconstructed images by changing the excitation magnetic field frequency of the excitation coil, providing novel design ideas and technical pathways for future MPI systems.

Development and optimization of immunomagnetic bead separation-convective PCR (IMBS-CPCR) for on-site detection of four common Vibrio species in aquaculture

Foodborne infectious diseases, particularly those caused by pathogenic Vibrio species in aquaculture, are a significant concern in the field of seafood safety. They not only hinder the economic development of the industry but also pose a major threat to public health. Traditional detection methods are often too slow, insensitive, or impractical for portable use, highlighting the urgent need for a sensitive, on-site detection method for Vibrio that prioritizes convenience and speed. This study developed a visual IMBS-CPCR method for the detection of four common pathogenic Vibrio species: Vibrio alginolyticus, Vibrio anguillarum, Vibrio fluvialis, and Vibrio harveyi. The method achieved high capture rates for target bacteria (82.6%–83.3%) and low capture rates for non-target bacteria (below 11%), demonstrating good sensitivity by detecting bacteria at concentrations as low as 10 CFU/mL. Optimal amplification conditions were determined for each species, with specificity tests confirming that only target bacteria produced amplification bands. Sensitivity tests revealed detection limits of 101 CFU/mL for V. alginolyticus, V. anguillarum, and V. fluvialis, and 102 CFU/mL for V. harveyi. The combined techniques improved detection sensitivity in simulated fish samples by 10–100 fold compared to direct CPCR or PCR methods.

Recent Advances in Monitoring Microbial Toxins in Food Samples by HPLC-Based Techniques: A Review

This study examines the significant impact of bacterial, algal, and fungal toxins on foodborne illnesses, and stresses the importance of advanced detection techniques, such as high-performance liquid chromatography (HPLC)-based methodologies. It emphasizes the urgent need for further advancements in these techniques to ensure food safety, as they offer significant benefits, including low detection limits and the ability to be combined with other techniques to detect a wide range of toxins. In this regard, HPLC has emerged as a versatile and sensitive analytical technique for this purpose. Various HPLC methods, often enhanced with detectors such as ultraviolet (UV), fluorescence (FD), and mass spectrometry (MS), have been developed to identify and quantify microbial toxins in a wide variety of food samples. Recent advancements include HPLC-FD methods that utilize the natural fluorescence of certain aflatoxins, improving detection sensitivity. HPLC-MS/MS and UHPLC-MS/MS techniques offer high selectivity and sensitivity, making them suitable for detecting a wide range of toxins in trace quantities. The adaptability of HPLC, combined with innovative detection technologies and sample preparation methods, holds significant potential for enhancing food safety monitoring and reducing the global burden of foodborne diseases.