Size photometry and fluorescence imaging of immobilized immersed extracellular vesicles.

Immunofluorescence analysis of individual extracellular vesicles (EVs) in common fluorescence microscopes is gaining popularity due to its accessibility and high fluorescence sensitivity; however, EV number and size are only measurable using fluorescent stains requiring extensive sample manipulations. Here we introduce highly sensitive label-free EV size photometry (SP) based on interferometric scattering (iSCAT) imaging of immersed EVs immobilized on a glass coverslip. We implement SP on a common inverted epifluorescence microscope with LED illumination and a simple 50:50 beamsplitter, permitting seamless integration of SP with fluorescence imaging (SPFI). We present a high-throughput SPFI workflow recording >10,000 EVs in 7 min over ten 88 × 88 µm2 fields of view, pre- and post-incubation imaging to suppress background, along with automated image alignment, aberration correction, spot detection and EV sizing. We achieve an EV sizing range from 37 to ∼220 nm in diameter with a dual 440 and 740 nm SP illumination scheme, and suggest that this range can be extended by more advanced image analysis or additional hardware customization. We benchmark SP to flow cytometry using calibrated silica nanoparticles and demonstrate superior, label-free sensitivity. We showcase SPFI's potential for EV analysis by experimentally distinguishing surface and volumetric EV dyes, observing the deformation of EVs adsorbed to a surface, and by uncovering distinct subpopulations in <100 nm-in-diameter EVs with fluorescently tagged membrane proteins.

Compact Laser-Induced Fluorescence Detector with Adjustable Laser Focal Spot for Multiple Purposes.

In many research fields, the demand for miniaturized laser-induced fluorescence (LIF) detection systems has been increasing. This work has developed a compact LIF detector, employing a laser diode as the excitation source and a photodiode as the photodetector with an adjustable laser focal spot, to meet the diverse requirements of various observation targets, such as capillaries, PCR tubes, and microfluidic chips. It features the functionalities of background fluorescence correction, the adaptive adjustment of the dynamic range, and constant power control for the laser. The influence of the excitation power on the detection limit was studied through experiments, and the configuration results for LED/LD as light sources and 487/450 nm wavelengths were compared and optimized. A fully integrated, compact, modular epifluorescence LIF detector was subsequently constructed, measuring 40 × 22 × 38 mm3 in total size, with a cost of USD 320, and achieving a detection limit of 0.4 nM for fluorescein sodium. Finally, the detector was integrated into a nucleic acid detection system with a microfluidic chip on the Chinese Space Station (CSS) and was also tested with PCR tubes and capillaries, proving its broad practicality and adaptability to various analytical systems.

From Proteomics to the Analysis of Single Protein Molecules.

Limit of detection (LoD) is a term that is used to characterize the sensitivity of an analytical method. The existing limitation of the sensitivity of analysis using modern mass spectrometry methods has been experimentally shown to be a limiting factor in the application of proteomic technologies in medicine. This article proposes a concept of a new technology that will set a new vector of development in the development of systems for solving problems of medical diagnostics and deals with theoretical and practical aspects of creating a new technology for the detection of single biomacromolecules (in particular, proteins) in biological samples. Such technology should be based on the principle of signal registration similar to that used in a Geiger counter (also known as a Geiger-Müller counter or G-M counter), a device that automatically counts the number of ionizing particles that hit it. This counter is free from probabilistic components; it registers a signal if there is at least one target molecule in the analysis chamber. Predictive medical diagnostics require technology based on methods where sensitivity allows for the detection of single marker molecules in a biological sample volume of 1-10 µL, the smallest volume of biomaterial used in laboratory diagnostics. Creation of a detector with a sensitivity of 10-18 M would allow for the detection of one molecule in 1 µL of the sample, which fundamentally makes this approach analogous to a G-M counter for solutions. To date, bioanalytical methods are limited to a sensitivity of 10-12 M (which is approximately 1 million molecules per 1 µL), which is insufficient to capture the early stages of pathological processes.

Analytical and Diagnostic Performance of a Dual-Target Blood Detection Test for Hepatocellular Carcinoma.

BACKGROUND: Surveillance approaches with high sensitivity and specificity for hepatocellular carcinoma (HCC) are still urgently needed. Previous studies have shown that methylation of GNB4 and Riplet can effectively diagnose HCC. AIMS: This study plan to analyze the performance of a blood test for detecting HCC using GNB4 and Riplet methylation. METHODS AND RESULTS: This study mainly investigated the analytical performance of the dual-target HCC blood test (DT-HBT), including cut-off value, limit of detection (LOD), precision, analytical specificity, and coincidence rate. In addition, the detection performance for HCC was validated in 1030 clinical plasma samples (214 HCC and 816 non-HCC). Plasma samples from 25 HCC patients after hepatectomy were collected to assess the feasibility of the kit for postoperative recurrence monitoring. All analytical performance of the DT-HBT met prespecified requirements. The LOD for GNB4, Riplet, and ß-actin was 1% methylation/100 copies/µL with cut-offs of 43, 43, and 35, respectively. The DT-HBT showed excellent precision, within 5% CV. It had a specificity of 91.5% for detecting other cancers, and 100% for breast, lung, and bladder cancer. No cross-reactions were observed with 9 potential interfering substances. The DT-HBT achieved a 100% coincidence rate in detecting reference and clinical samples. The clinical performance study found that the kit showed a sensitivity of 81.7% for stage I HCC, and an overall sensitivity and specificity of 87.4% and 92.3%, respectively. The detection sensitivity for postoperative recurrent patients was 95.8%, with a specificity of 100%. CONCLUSION: The analytical performance of the DT-HBT met prespecified criteria. It provided HCC patients with a reliable and high-performing new blood test for the HCC diagnosis and surveillance. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT05685524.

A Novel Ferrocene-Linked Thionine as a Dual Redox Mediator for the Electrochemical Detection of Dopamine and Hydrogen Peroxide.

We introduce a novel dual redox mediator synthesized by covalently linking ferrocene dicarboxylic acid (FcDA) and thionine (TH) onto a pre-treated glassy carbon electrode. This unique structure significantly enhances the electro-oxidation of dopamine (DA) and the reduction of hydrogen peroxide (H2O2), offering a sensitive detection method for both analytes. The electrode exhibits exceptional sensitivity, selectivity, and stability, demonstrating potential for practical applications in biosensing. It facilitates rapid electron transfer between the analyte and the electrode surface, detecting H2O2 concentrations ranging from 1.5 to 60 µM with a limit of detection (LoD) of 0.49 µM and DA concentrations from 0.3 to 230 µM with an LoD of 0.07 µM. The electrode's performance was validated through real-sample analyses, yielding satisfactory results.

Emerging Low Detection Limit of Optically Activated Gas Sensors Based on 2D and Hybrid Nanostructures.

Gas sensing is essential for detecting and measuring gas concentrations across various environments, with applications in environmental monitoring, industrial safety, and healthcare. The integration of two-dimensional (2D) materials, organic materials, and metal oxides has significantly advanced gas sensor technology, enhancing its sensitivity, selectivity, and response times at room temperature. This review examines the progress in optically activated gas sensors, with emphasis on 2D materials, metal oxides, and organic materials, due to limited studies on their use in optically activated gas sensors, in contrast to other traditional gas-sensing technologies. We detail the unique properties of these materials and their impact on improving the figures of merit (FoMs) of gas sensors. Transition metal dichalcogenides (TMDCs), with their high surface-to-volume ratio and tunable band gap, show exceptional performance in gas detection, especially when activated by UV light. Graphene-based sensors also demonstrate high sensitivity and low detection limits, making them suitable for various applications. Although organic materials and hybrid structures, such as metal-organic frameworks (MoFs) and conducting polymers, face challenges related to stability and sensitivity at room temperature, they hold potential for future advancements. Optically activated gas sensors incorporating metal oxides benefit from photoactive nanomaterials and UV irradiation, further enhancing their performance. This review highlights the potential of the advanced materials in developing the next generation of gas sensors, addressing current research gaps and paving the way for future innovations.

Construction of Cu2Y2O5/g-C3N4 Novel Composite for the Sensitive and Selective Trace-Level Electrochemical Detection of Sulfamethazine in Food and Water Samples.

The most frequently used sulfonamide is sulfamethazine (SMZ) because it is often found in foods made from livestock, which is hazardous for individuals. Here, we have developed an easy, quick, selective, and sensitive analytical technique to efficiently detect SMZ. Recently, transition metal oxides have attracted many researchers for their excellent performance as a promising sensor for SMZ analysis because of their superior redox activity, electrocatalytic activity, electroactive sites, and electron transfer properties. Further, Cu-based oxides have a resilient electrical conductivity; however, to boost it to an extreme extent, a composite including two-dimensional (2D) graphitic carbon nitride (g-C3N4) nanosheets needs to be constructed and ready as a composite (denoted as g-C3N4/Cu2Y2O5). Moreover, several techniques, including X-ray diffraction analysis, scanning electron microscopy analysis, energy-dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy, and Raman spectroscopy were employed to analyze the composites. The electrochemical measurements have revealed that the constructed g-C3N4/Cu2Y2O5 composites exhibit great electrochemical activity. Nevertheless, the sensor achieved outstanding repeatability and reproducibility alongside a low limit of detection (LOD) of 0.23 µM, a long linear range of 2 to 276 µM, and an electrode sensitivity of 8.86 µA µM-1 cm-2. Finally, the proposed GCE/g-C3N4/Cu2Y2O5 electrode proved highly effective for detection of SMZ in food samples, with acceptable recoveries. The GCE/g-C3N4/Cu2Y2O5 electrode has been successfully applied to SMZ detection in food and water samples.

Fe-Mediated Tweaking of Band Bending and Activation Energy in α-MoO3 Nano Lamella for Enhanced NO2 Gas Detection Under Low Operating Temperature.

Concern over increasing pollution and ways to mitigate it is in high demand due to the swift advancement of technology and the creation of advanced utilities. Nitrogen oxide (NO2) is a well-known evolved toxin that poses a threat to human health, the environment, and biodiversity. Therefore, several works are carried to sense the NO2 gas at its trace concentration. However, the majority of NO2 sensors that have been reported have inadequate Limit of Detection (LOD), high operating temperature, and low sensitivity. Orthorhombic molybdenum oxide (α-MoO3) recently emerged as hotspot in the gas sensing research and noted for its high sensitivity, and distinct sensing capabilities owing to its unique layered structure. In this study, Fe-doped α-MoO3 nanosheets for NO2 sensing is prepared, and at a low operating temperature of 110 °C, an excellent sensitivity of 1282% for 10 ppm of NO2 is achieved. Long-term stability, good repeatability, and an ultra-low detection limit of 79 ppt are also demonstrated by the manufactured sensors. In addition, the obtained low activation energy of -2.9 KJ mol-1 and the high band bending for FM6 supports the highly responsive NO2 detection at low operating temperatures.

An Internally Attached Aptameric Graphene Nanosensor for Sensitive Vasopressin Measurement in Critical Patient Monitoring.

This paper presents an aptameric graphene nanosensor for rapid and sensitive measurement of arginine vasopressin (AVP) toward continuous monitoring of critical care patients. The nanosensor is a field-effect transistor (FET) with monolayer graphene as the conducting channel and is functionalized with a new custom-designed aptamer for specific AVP recognition. Binding between the aptamer and AVP induces a change in the carrier density in the graphene and resulting in measurable changes in FET characteristics for determination of the AVP concentration. The aptamer, based on the natural enantiomer D-deoxyribose, possess optimized kinetic binding properties and is attached at an internal position to the graphene for enhanced sensitivity to low concentrations of AVP. Experimental results show that this aptameric graphene nanosensor is highly sensitive (with a limit of detection of 0.3 pM and a resolution of 0.1 pM) to AVP, and rapidly responsive (within 90 s) to both increasing and decreasing AVP concentration changes. The device is also reversable (within 4%), repeatable (within 4%) and reproducible (within 5%) in AVP measurements.

Comparison of EV characterization by commercial high-sensitivity flow cytometers and a custom single-molecule flow cytometer.

High-sensitivity flow cytometers have been developed for multi-parameter characterization of single extracellular vesicles (EVs), but performance varies among instruments and calibration methods. Here we compare the characterization of identical (split) EV samples derived from human colorectal cancer (DiFi) cells by three high-sensitivity flow cytometers, two commercial instruments, CytoFLEX/CellStream, and a custom single-molecule flow cytometer (SMFC). DiFi EVs were stained with the membrane dye di-8-ANEPPS and with PE-conjugated anti-EGFR or anti-tetraspanin (CD9/CD63/CD81) antibodies for estimation of EV size and surface protein copy numbers. The limits of detection (LODs) for immunofluorescence and vesicle size based on calibration using cross-calibrated, hard-dyed beads were ∼10 PE/∼80 nm EV diameter for CytoFLEX and ∼10 PEs/∼67 nm for CellStream. For the SMFC, the LOD for immunofluorescence was 1 PE and ≤ 35 nm for size. The population of EVs detected by each system (di-8-ANEPPS+/PE+ particles) differed widely depending on the LOD of the system; for example, CellStream/CytoFLEX detected only 5.7% and 1.5% of the tetraspanin-labelled EVs detected by SMFC, respectively, and median EV diameter and antibody copy numbers were much larger for CellStream/CytoFLEX than for SMFC as measured and validated using super-resolution/single-molecule TIRF microscopy. To obtain a dataset representing a common EV population analysed by all three platforms, we filtered out SMFC and CellStream measurements for EVs below the CytoFLEX LODs as determined by bead calibration (10 PE/80 nm). The inter-platform agreement using this filtered dataset was significantly better than for the unfiltered dataset, but even better concordance between results was obtained by applying higher cutoffs (21 PE/120 nm) determined by threshold analysis using the SMFC data. The results demonstrate the impact of specifying LODs to define the EV population analysed on inter-instrument reproducibility in EV flow cytometry studies, and the utility of threshold analysis of SMFC data for providing semi-quantitative LOD values for other flow cytometers.

Detection and quantification of Brucella abortus DNA in water buffaloes (bubalus bubalis) using droplet digital polymerase chain reaction.

Brucellosis represents a major public health concern worldwide. Human transmission is mainly due to the consumption of unpasteurized milk and dairy products of infected animals. The gold standard for the diagnosis of Brucella spp in ruminants is the bacterial isolation, but it is time-consuming. Polymerase Chain Reaction (PCR) is a quicker and more sensitive technique than bacterial culture. Droplet digital PCR (ddPCR) is a novel molecular assay showing high sensitivity in samples with low amount of DNA and lower susceptibility to amplification inhibitors. Present study aimed to develop a ddPCR protocol for the detection of Brucella abortus in buffalo tissue samples. The protocol was validated using proficiency test samples for Brucella spp by real time qPCR. Furthermore, 599 tissue samples were examined. Among reference materials, qPCR and ddPCR demonstrated same performance and were able to detect up to 225 CFU/mL. Among field samples, ddPCR showed higher sensitivity (100%), specificity and accuracy of 93.4% and 94.15%, respectively. ddPCR could be considered a promising technique to detect B. abortus in veterinary specimens, frequently characterized by low amount of bacteria, high diversity in matrices and species and poor storage conditions.

The LOD paradox: When lower isn't always better in biosensor research and development.

Biosensor research has long focused on achieving the lowest possible Limits of Detection (LOD), driving significant advances in sensitivity and opening up new possibilities in analysis. However, this intense focus on low LODs may not always meet the practical needs or suit the actual uses of these devices. While technological improvements are impressive, they can sometimes overlook important factors such as detection range, ease of use, and market readiness, which are vital for biosensors to be effective in real-world applications. This review advocates for a balanced approach to biosensor development, emphasizing the need to align technological advancements with practical utility. We delve into various applications, including the detection of cancer biomarkers, pathology-related biomarkers, and illicit drugs, illustrating the critical role of LOD within these contexts. By considering clinical needs and broader design aspects like cost-effectiveness, sustainability, and regulatory compliance, we argue that integrating technical progress with practicality will enhance the impact of biosensors. Such an approach ensures that biosensors are not only technically sound but also widely useable and beneficial in real-world applications. Addressing the diverse analytical parameters alongside user expectations and market demands will likely maximize the real-world impact of biosensors.

Quantile regression for longitudinal data with values below the limit of detection and time-dependent covariates-application to modeling carbon nanotube and nanofiber exposures.

BACKGROUND: In studies of occupational health, longitudinal environmental exposure, and biomonitoring data are often subject to right skewing and left censoring, in which measurements fall below the limit of detection (LOD). To address right-skewed data, it is common practice to log-transform the data and model the geometric mean, assuming a log-normal distribution. However, if the transformed data do not follow a known distribution, modeling the mean of exposure may result in bias and reduce efficiency. In addition, when examining longitudinal data, it is possible that certain covariates may vary over time. OBJECTIVE: To develop predictive quantile regression models to resolve the issues of left censoring and time-dependent covariates and to quantitatively evaluate if previous and current covariates can predict current and/or future exposure levels. METHODS: To address these gaps, we suggested incorporating different substitution approaches into quantile regression and utilizing a method for selecting a working type of time dependency for covariates. RESULTS: In a simulation study, we demonstrated that, under different types of time-dependent covariates, the approach of multiple random value imputation outperformed the other approaches. We also applied our methods to a carbon nanotube and nanofiber exposure study. The dependent variables are the left-censored mass of elemental carbon at both the respirable and inhalable aerosol size fractions. In this study, we identified some potential time-dependent covariates with respect to worker-level determinants and job tasks. CONCLUSION: Time dependency for covariates is rarely accounted for when analyzing longitudinal environmental exposure and biomonitoring data with values less than the LOD through predictive modeling. Mistreating the time-dependency as time-independency will lead to an efficiency loss of regression parameter estimation. Therefore, we addressed time-varying covariates in longitudinal exposure and biomonitoring data with left-censored measurements and illustrated an entire conditional distribution through different quantiles.

Nested PCR effective to detect low viral loads of SARS-CoV-2 in animal samples.

SARS-CoV-2 emerged from an animal source and was then transmitted to humans, causing the COVID-19 pandemic. Since a wide range of animals are susceptible to SARS-CoV-2 infection, the zoonotic potential of SARS-CoV-2 increases with every new animal infected. The molecular gold standard assay for SARS-CoV-2 detection is real-time RT-PCR, where the Ct obtained is proportional to the amount of nucleic acid and can be a semi-quantitative measure of the viral load. However, since the use of real-time RT-PCR assays in animal samples is low due to the high costs, the use of validated nested PCR assays will help to monitor large-scale animal samplings, by reducing the costs of detection. In the present study, 140 samples from dogs and cats (15 SARS-CoV-2-positive samples with Ct values from 27 to 33, and 125 negative samples), previously analyzed by real-time RT-PCR, were analyzed by nested PCR. To increase the number of positive samples to determine the sensitivity of the assay, 40 human samples obtained during COVID-19 diagnosis in 2020 were included. The specificity of the primers was analyzed against samples positive to canine coronavirus (CCV) and feline infectious peritonitis virus (FIPV). To calculate the limit of detection (LoD) of the nested PCR, the viral load was estimated extrapolating the Ct value obtained by real-time RT-PCR. The Ct values obtained were considered as semi-quantitative and were able to distinguish between high, moderate and low viral loads. The Kappa value or "agreement" between assays and reliability of the nested PCR were also determined. Eleven of the animal samples analyzed by nested PCR targeting the N gene were detected as positive, while 129 were detected as negative to the virus, with Ct values ranging between17 and 31.5. All the samples from humans analyzed by nested PCR were positive. These results indicate that the assay has a sensitivity of near 95 % and a specificity of 100 %. No unspecific reactions analyzed by nested PCR were observed with the samples positive to CCV and FIPV. The samples detected as positive to SARS-CoV-2 by nested PCR were those that presented a Ct between17 and 31.5. The LoD of the nested PCR was estimated close to 50 copies/µL of viral load, corresponding with a Ct of 31.5. The Kappa value between assays was excellent (k = 0.829). The results obtained demonstrate that nested PCR is useful to detect SARS-CoV-2 low viral loads at a lower cost than with real-time RT-PCR.

Nano-Photonic Crystal D-Shaped Fiber Devices for Label-Free Biosensing at the Attomolar Limit of Detection.

Maintaining both high sensitivity and large figure of merit (FoM) is crucial in regard to the performance of optical devices, particularly when they are intended for use as biosensors with extremely low limit of detection (LoD). Here, a stack of nano-assembled layers in the form of 1D photonic crystal, deposited on D-shaped single-mode fibers, is created to meet these criteria, resulting in the generation of Bloch surface wave resonances. The increase in the contrast between high and low refractive index (RI) nano-layers, along with the reduction of losses, enables not only to achieve high sensitivity, but also a narrowed resonance bandwidth, leading to a significant enhancement in the FoM. Preliminary testing for bulk RI sensitivity is carried out, and the effect of an additional nano-layer that mimics a biological layer where binding interactions occur is also considered. Finally, the biosensing capability is assessed by detecting immunoglobulin G in serum at very low concentrations, and a record LoD of 70 aM is achieved. An optical fiber biosensor that is capable of attaining extraordinarily low LoD in the attomolar range is not only a remarkable technical outcome, but can also be envisaged as a powerful tool for early diagnosis of diseases.

Rapid Drug Susceptibility Testing to Preserve Antibiotics.

Antibiotic resistance is a global challenge likely to cost trillions of dollars in excess costs in the health system and more importantly, millions of lives every year. A major driver of resistance is the absence of susceptibility testing at the time a healthcare worker needs to prescribe an antimicrobial. The effect is that many prescriptions are unintentionally wasted and expose mutable organisms to antibiotics increasing the risk of resistance emerging. Often simplistic solutions are applied to this growing issue, such as a naïve drive to increase the speed of drug susceptibility testing. This puts a spotlight on a technological solution and there is a multiplicity of such candidate DST tests in development. Yet, if we do not define the necessary information and the speed at which it needs to be available in the clinical decision-making progress as well as the necessary integration into clinical pathways, then little progress will be made. In this chapter, we place the technological challenge in a clinical and systems context. Further, we will review the landscape of some promising technologies that are emerging and attempt to place them in the clinic where they will have to succeed.

Advances in the determination of trace amounts of iron cations through electrochemical methods: A comprehensive review of principles and their limits of detection.

Quantification of trace amounts of iron is of great importance in various fields. In the industrial sector, it is crucial to monitor the release of iron out of corrosion, pickling treatment, and steel manufacturing to address potential environmental and economic challenges. In biological systems, despite its indispensability, it is essential to maintain iron concentration below a specific threshold. Electrochemical (EC) methods provide significant analytical capabilities due to their simplicity, ease of use, and cost-effectiveness. This review focuses on the fundamental principles of EC methods for iron detection, including potentiometry, amperometry, coulometry, voltammetry, and electrochemical impedance spectroscopy (EIS). It further explains the process of obtaining calibration curves, and subsequently, determining the concentration of unknown ions. Additionally, technical notes are presented on selecting the initial signal value, reducing the duration of tests, excluding non-faradaic signals, and extending the linear region with the lowest detection limit. These notes are supported by key findings from relevant case studies.

Analysis of three characterization assays reveals ddPCR of LIN28A as the most sensitive for the detection of residual pluripotent stem cells in cellular therapy products.

BACKGROUND AIMS: With the continuous development and advancement of human pluripotent stem cell (PSC)-derived cell therapies, an ever-increasing number of clinical indications can benefit from their application. Due to the capacity for PSCs to form teratomas, safety testing is required to ensure the absence of residual PSCs in a cell product. To mitigate these limitations, in vitro analytical methods can be utilized as quality control after the production of a PSC-derived cell product. Sensitivity of these analytic methods is critical in accurately quantifying residual PSC in the final cell product. In this study, we compared the sensitivity of three in vitro assays: qPCR, ddPCR and RT-LAMP. METHODS: The spike-in samples were produced from three independent experiments, each spiked with different PSC lines (PSC1, NH50191, and WA09 referred to as H9) into a background of primary fibroblasts (Hs68). These samples were then subjected to qPCR, ddPCR and RT-LAMP to determine their detection limit in measuring a commonly used PSC marker, LIN28A. RESULTS: The results indicated that the three analytic methods all exhibited consistent results across different cell-line spiked samples, with ddPCR demonstrating the highest sensitivity of the three methods. The LIN28A ddPCR assay could confidently detect 10 residual PSCs in a million fibroblasts. DISCUSSION: In our hand, ddPCR LIN28A assay demonstrated the highest sensitivity for detection of residual PSCs compared to the other two assays. Correlating such in vitro safety results with corresponding in vivo studies demonstrating the tumorigenicity profile of PSC-derived cell therapy could accelerate the safe clinical translation of cell therapy.

Diagnostic performance of mpox virus (MPXV) real-time PCR assays: multicenter assessment and extended sensitivity analysis.

PURPOSE: To comprehensively investigate the diagnostic performance of routinely used assays in MPXV testing, the National Center of Clinical Laboratories in China conducted a nationwide external quality assessment (EQA) scheme and an evaluated nine assays used by ≥ 5 laboratories in the EQA. METHODS: MPXV virus-like particles with 2700, 900 and 300 copies/mL were distributed to 195 EQA laboratories. For extended analysis, triple-diluted samples from 9000 to 4.12 copies/mL were repeated 20 times using the assays employed by ≥ 5 laboratories. The diagnostic performance was assessed by analyzing EQA data and calculating the limits of detection (LODs). RESULTS: The performance was competent in 87.69% (171/195) of the participants and 87.94% (175/199) of the datasets. The positive percentage agreements (PPAs) were greater than 99% for samples at 2700 and 900 copies/mL, and 95.60% (761/796) for samples at 300 copies/mL. The calculated LODs for the two clades ranged from 228.44 to 924.31 copies/mL and were greater than the LODs specified by the respective kits. EasyDiagnosis had the lowest calculated LODs and showed superior performance in EQA, whereas BioGerm and Sansure, with higher calculated LODs, did not perform well in EQA. CONCLUSION: This study provides valuable information from the EQA data and evaluation of the diagnostic performance of MPXV detection assays. It also provided insights into reagent optimization and enabled prompt public health interventions for the outbreak.

Gold Nanoparticle-Based Plasmonic Detection of Escherichia coli, Salmonella enterica, Campylobacter jejuni, and Listeria monocytogenes from Bovine Fecal Samples.

Current diagnostic methods for detecting foodborne pathogens are time-consuming, require sophisticated equipment, and have a low specificity and sensitivity. Magnetic nanoparticles (MNPs) and plasmonic/colorimetric biosensors like gold nanoparticles (GNPs) are cost-effective, high-throughput, precise, and rapid. This study aimed to validate the use of MNPs and GNPs for the early detection of Escherichia coli O157:H7, Salmonella enterica spp., Campylobacter jejuni, and Listeria monocytogenes in bovine fecal samples. The capture efficiency (CE) of the MNPs was determined by using Salmonella Typhimurium (ATCC_13311) adjusted at an original concentration of 1.5 × 108 CFU/mL. One (1) mL of this bacterial suspension was spiked into bovine fecal suspension (1 g of fecal sample in 9 mL PBS) and serially diluted ten-fold. DNA was extracted from Salmonella Typhimurium to determine the analytical specificity and sensitivity/LOD of the GNPs. The results showed that the CE of the MNPs ranged from 99% to 100% and could capture as little as 1 CFU/mL. The LOD of the GNPs biosensor was 2.9 µg/µL. The GNPs biosensor was also tested on DNA from 38 naturally obtained bovine fecal samples. Out of the 38 fecal samples tested, 81.6% (31/38) were positive for Salmonella enterica spp., 65.8% (25/38) for C. jejuni, 55.3% (21/38) for L. monocytogenes, and 50% (19/38) for E. coli O157:H7. We have demonstrated that MNP and GNP biosensors can detect pathogens or their DNA at low concentrations. Ensuring food safety throughout the supply chain is paramount, given that these pathogens may be present in cattle feces and contaminate beef during slaughter.