Quantitative Detection System Research Articles

A silicon-based functional self-assembled aptasensor for the detection of aflatoxin B1 by SERS sensing.

One of the most harmful contaminants found in corn and its products is aflatoxin B1 (AFB1) and thus developing reliable detection methods is of great significance to consumers and the food industry. In this research, AuMBA@Ag nanoparticles (NPs) and AgNPs deposited on a silicon wafer (Si@AgNPs) were functionalized with an aptamer and its complementary strand, respectively, and self-assembled into a SERS aptasensor, which generated strong SERS signals. AFB1 bound to the aptamer prior to the complementary chain, causing AuMBA@Ag NPs to detach from Si@AgNPs. The complex dissociated, leading to a decrease in signal intensity from the solid-phase substrate. Under optimal conditions, the linear detection range was 0.05-20.0 ng mL-1, and the detection limit was 0.039 ng mL-1. Notably, the aptasensor demonstrated a recovery rate between 92.77% and 110.13% when utilized for the detection of AFB1 in corn flour and oil, indicating its good potential for detecting AFB1 in real sample matrices. In conclusion, a quantitative and reliable specific SERS detection system for AFB1 was developed in this study with significant applicability to food safety.

Rapid quantitative detection system constructed via photonic PCR based on the photothermal effect of NH2-MWCNTs/TiO2

In this work, the photothermal effect of aminomodified MWCNTs/TiO2/SiO2/PDMS nanocomposites was utilized as a photothermal substrate to replace the metal heating block of traditional qPCR combining of the advantages of high photothermal effect of composite materials and low sample volume of static microfluidic PCR. Meanwhile, Multiple PCR rapid thermal cycles under 808 nm laser irradiation was accomplished through a non-contact energy conversion method and the use of chamber-immobilized PCR chips as specific reaction vessels. Notably, the chip chamber architecture requires merely about 8 μL of reagents compared to traditional PCR tubes. While reducing the amount of PCR reagents used, the higher specific surface area results in a larger contact surface (SSA) between the heat source and the solution. Thereafter, the CCD image sensor is then used as a fluorescence detector to monitor the amplification of the target DNA during the PCR reaction, thus enabling simultaneous fluorescence detection. In addition, the threshold cycle (Ct) value of qPCR and standard PCR curves for SARS-CoV-2 virus have been analysed in depth. Importantly, this study has important implications for the development of low-cost materials, miniaturized and portable Point-of-Care Testing (POCT) chips/systems.

Total atmospheric carbon detection by LIBS with multivariate physicochemical model based on transition and collision mechanism

The importance of total atmospheric carbon (TAC) has been increasingly recognized in light of the growing significance of global climate change. The concept of TAC has expanded beyond its previous focus solely on CO2 to encompass additional novel components. Here, a promising detection-analysis system for TAC quantitative detection is self-developed using LIBS and a multivariate physicochemical model based on transition and collision mechanism (MP-TC model). Spectral signals under different compositions were analyzed based on static detection. Then, a MP-TC model was developed by incorporating particle collisions and transition mechanisms. Subsequently, three dynamic monitoring were conducted analyzing the dynamic spectra obtained when CO2, CO, and CH4 were the different primary components of TAC. Interestingly, an anomalous CN transition was observed in Fuel combustion and the inhibited low vibrational transitions in symmetric molecules can be explored in CH4 gradient concentration. Additionally, each dynamic process was fitted using the MP-TC model, confirming its reliability in TAC detection and its better alignment with the observed trends.

Rapid quantitative and qualitative analysis of talcum powder in wheat flour by microwave detection combined with multivariate analysis

Rapid and accurate monitoring of talcum powder in wheat flour is of great practical importance for maintaining market order, public health and food safety. In this study, the potential of a home-made microwave detection system for rapid quantitative and qualitative detection of talcum powder adulteration in wheat flour at 2.5–11.5 GHz was investigated. Useful microwave spectral information is selected using three feature selection strategies, the bootstrapping soft shrinkage (BOSS), the multiple feature spaces ensemble with least absolute shrinkage and selection operator (MEF-LASSO), and the competitive adaptive reweighted sampling (CARS). The eXtreme Gradient Boosting (XGBoost) classification and regression models are constructed and evaluated, and three nature-inspired optimization algorithms (NIOA) are used for parameter optimization: the Osprey Optimization Algorithm (OOA), the Crested Porcupine Optimizer (CPO), and the Sparrow Search Algorithm (SSA). The experimental results show that both feature selection strategies and NIOA algorithms can effectively improve the model performance. The SSA-XGBoost classification model has the highest prediction accuracy, and its prediction accuracy and F1-score can reach 100 % and 1, respectively. The MEF-LASSO-SSA-XGBoost regression model has strong robustness. The root mean square error (RMSE) was 1.76 %, the prediction coefficient of determination (R2) was 0.98, and the ratio of performance to deviation (RPD) was 8.66. The results of this study showed that the combination of microwave technology and machine learning model with multivariate analysis method can realize the rapid and accurate determination of qualitative and quantitative talcum powder in wheat flour.

Design of a handheld and portable fluorescence imaging system for quantitative detection of pregnancy-specific biomarkers in cattle.

Reproductive management significantly impacts dairy farm productivity, necessitating accurate timely pregnancy detection in cattle. This paper presents a novel handheld and portable fluorescence imaging system designed for quantitative assessment of pregnancy-specific biomarkers, addressing the limitations of current detection methods. The objective was to develop a cost-effective, at-farm solution for detecting pregnancy-specific protein B (PSPB) in bovine plasma samples. The system integrates an imaging module and a custom software application, enabling image capture, data processing, and PSPB concentration determination. Calibration utilizing known PSPB concentrations achieved a 0.6ng/mL limit of detection. Validation encompassed a comparison with a standard ELISA method using 100 bovine plasma samples; minimal bias and good agreement were observed within the linear range of the calibration curve for both methods. The system offers portability, user-friendliness, and potential for multiplex detection, promising real-time, at-farm reproductive management. This study demonstrates the successful development and validation of a portable fluorescence imaging system, offering an efficient and accurate approach to detecting pregnancy-specific biomarkers in cattle. Its implications extend to improving dairy farm productivity by enabling timely and reliable reproductive management practices.

Rapid quantitative detection system for measles virus-neutralizing antibodies using HiBiT-tagged virus-like particles.

Immunological testing to detect neutralizing antibodies (NAbs) is important in measles (MV) infection control. Currently, the plaque reduction neutralization testis the only credible method for measuring actual virus NAbs; however, its feasibility is hampered by drawbacks, such as long turnaround times, low throughput, and the need for laboratory biosafety equipment. To solve these problems, we developed a simple and rapid MV-NAb detection system using lentivirus-based virus-like particlesincorporated with the NanoLuc fragment peptide HiBiT comprising the MV fusion protein and hemagglutinin on their exterior surface. Overall, this simple, safe, and rapid method could be used to detect MV NAbs.

The Quantitative Detection System and Method for Natural Ice Covering of Composite Insulators by Quasi-Distributed Fiber Bragg Gratings

The Quantitative Detection System and Method for Natural Ice Covering of Composite Insulators by Quasi-Distributed Fiber Bragg Gratings

Inhibition of Citrus Huanglongbing Disease by Paenibacillus polymyx KN-03 and Analysis with Transcriptome and Microflora

Soil drench treatment using Paenibacillus polymyxa strain KN-03 was applied to citrus plants infected with Candidatus Liberibacter asiaticus (CLas). The infection status was assessed using PCR and a real-time quantitative PCR detection system (qPCR). The application of KN-03 resulted in a notable reduction in CLas levels in citrus plants. Specifically, by the 257th day post treatment commencement, following 24 KN-03 applications, the negative rates of CLas in the vein, root tip, and shoot tip were 50%, 0%, and 50%, respectively. After 24 cycles, KN-03 application significantly enhanced plant growth and stimulated reactive oxygen production in citrus leaves compared to control plants. Transcriptome analysis identified specific upregulated pathways. Furthermore, flora analysis revealed an increased abundance of microorganisms possessing potential utilization value, including Burkholderia-Caballeronia-Paraburkholderia, uncultured_bacterium_o_Acidobacteriales, uncultured_bacterium_f_Gemmatimonadaceae, and Rhodanobacter, in the root zone. Moreover, the BugBase analysis indicated that KN-03 treatment increased the abundance of beneficial rhizosphere bacteria associated with biofilm formation, element mobilization, and stress tolerance. These findings support the utility of Paenibacillus polymyxa KN-03 as an effective plant-growth-promoting bacterium for CLas management, with additional benefits for plant growth and soil health, specifically offering detoxification resources for shoot tip grafting.

The Identification of the Banana Endogenous Reference Gene MaSPS1 and the Construction of Qualitative and Quantitative PCR Detection Methods.

Endogenous reference genes play a crucial role in the qualitative and quantitative PCR detection of genetically modified crops. Currently, there are no systematic studies on the banana endogenous reference gene. In this study, the MaSPS1 gene was identified as a candidate gene through bioinformatics analysis. The conservation of this gene in different genotypes of banana was tested using PCR, and its specificity in various crops and fruits was also examined. Southern blot analysis showed that there is only one copy of MaSPS1 in banana. The limit of detection (LOD) test showed that the LOD of the conventional PCR method is approximately 20 copies. The real-time fluorescence quantitative PCR (qPCR) method also exhibited high specificity, with a LOD of approximately 10 copies. The standard curve of the qPCR method met the quantitative requirements, with a limit of quantification (LOQ) of 1.14 × 10-2 ng-about 20 copies. Also, the qPCR method demonstrated good repeatability and stability. Hence, the above results indicate that the detection method established in this study has strong specificity, a low detection limit, and good stability. It provides a reliable qualitative and quantitative detection system for banana.

A novel RCA-based DNA sensor system for specific and quantitative detection of Klebsiella pneumonia

The timely detection of Klebsiella pneumoniae (K. pneumoniae) infection is of great importance for patient management and the prevention of nosocomial infections. In this study, we present the development of a novel detection assay that enables sensitive and specific identification of K. pneumoniae-encoded topoisomerase IV (K. pneumoniae Topo IV) using a DNA sensor system in combination with Rolling Circle Amplification (RCA) technology. The DNA sensor system was designed by immobilizing DNA hairpin substrates on RCA primers modified slide surface. This modular reacting mode enhances the adaptability and flexibility of the sensor, thereby improving its universality as a sensing platform. When K. pneumoniae is present, the active Topo IV triggers the cleavage-ligation of DNA hairpin substrates, followed by RCA and labeling with fluorescent probes. This results in the visualization of K. pneumoniae at the single-molecule level by the DNA sensor, compared to situations when there are no K. pneumoniae present. The reliability and sensitivity of the DNA sensor were verified using purified enzymes and bacterial extracts, which establishes the foundation for quantitative detection of clinical samples. Notably, the sensor's detection limit for K. pneumoniae extracts was found to be 70 colony-forming units (CFU)/µL, a range considered clinically relevant for infections. Moreover, the DNA sensor system exhibited high sensitivity and accuracy in detecting K. pneumoniae from clinical samples, suggesting its potential application in clinical settings for detecting pathogenic microbes beyond K. pneumoniae.

Portable automatic detection system with infrared imaging for measuring steel wires corrosion damage

Accurate, cost-efficient and lightweight quantitative detection of steel wire corrosion in cable is an unsolvable issue that puzzles researchers and bridge owners. This paper proposed a portable automatic detection system for quantitative corrosion detection of replaced steel wires. The developed system consists of three parts (an automatic detection device, high-precision infrared imager, and corrosion evaluation algorithm). The proposed method is derived on the basis of Joule's law and the formula for calculating heat release. Then, the corroded specimens with different corrosion degrees and corresponding mass loss ratio were obtained by pre-corroded test to simulate industrial air corrosion and pickling test. The prior knowledge acquisition test utilizing presented automatic detection equipment was conducted to acquire the surface temperature of steel wires with various corrosion ratios by infrared camera after electric heating. Subsequently, the optimal quantitative corrosion prediction model after electric excitation is selected after infrared image processing, outlier filtering, theoretical method comparison, and model modification. Finally, the damaged steel wires from an in-service cable-stayed bridge are chosen to validate the proposed model's generalization ability and predictive accuracy. Furthermore, based on the discovery of characteristics on surface temperature of corroded steel wires after heating, the automatic detection device can be upgraded to realize the quantitative detection of in-situ corrosion of bridge cable.

Quantitative hydrogen and methane gas sensing via implementing AI based spectral analysis of plasma discharge

In this report we explore the feasibility of a quantitative gas detection system concept based on alternations in spectral emissions of a radio frequency power generated plasma in presence of a target gas. We then proceed with training a deep learning residual network computer vison model with the spectral data obtained from the plasma to be able to perform regressive calculation of the target gas content in the plasma. We explore this concept with hydrogen and methane gas present in the plasma at know quantities to evaluate the applicability of the concept as hydrogen or methane detection system. We will demonstrate that the system is well capable of quantitatively detecting either of the gases efficiently while it is challenging to estimate hydrogen content in presence of methane.

Hg2+-triggered cascade strand displacement assisted CRISPR-Cas12a for Hg2+ quantitative detection using a portable glucose meter

CRISPR-Cas12a is a powerful and programmable tool that has revolutionized the field of biosensing. However, the construction of a CRISPR-Cas12a-mediated portable system for on-site and quantitative detection of mercury ion (Hg2+) has yet to be explored. By integrating a target-triggered cascade toehold-mediated strand displacement reaction (TSDR) and CRISPR-Cas12a, we herein construct a portable on-site biosensor for the quantitative, sensitive, and selective detection of Hg2+ with a glucose meter. The Hg2+ initiates two cascade TSDRs through the T-Hg2+-T interaction to produce multiple double-stranded DNAs that can activate Cas12a′s trans-cleavage activity. The Cas12a cleaves the sucrase-modified DNA on the electrode, resulting in the liberation of sucrase into the solution. The freed sucrase can catalyze sucrose to generate glucose, which can be quantitatively monitored by a glucometer. The developed portable biosensor provides a dynamic range of 5 orders of magnitude with a detection limit of 40 fM. This biosensor also displays excellent selectivity and stability for detecting Hg2+. Moreover, environmental water samples are utilized to further verify the robustness and effectiveness of the developed biosensor, highlighting its potential application in environmental monitoring and food safety analysis.

Rapid Detection of Norovirus GII by Fluorescent Reverse Transcription Loop-Mediated Isothermal Amplification (RT-LAMP) and Nanomagnetic Bead Separation

Noroviruses (NoVs) is the main cause of gastroenteritis in humans worldwide, mainly affecting school-age children and adults. NoVs are transmitted through feces and vomitus, including human contact, food, and water. Presently, NoVs are detected using molecular biological methods. Loop-mediated isothermal amplification (LAMP), specifically, requires little detection equipment, a short detection time, and low technical skills. Here, we established our own NoV reverse transcription (RT) polymerase chain reaction (PCR) quantitative detection system and a NoV GII RT-LAMP detection system. We collected 40 clinical samples, extracted RNAs, and used RT-PCR and RT-LAMP to detect NoV GII. The qualitative results of RT-LAMP were consistent with those of RT-PCR. However, a significant difference was observed between RT-LAMP and RT-PCR quantitative detection results. The NoV GII RT-LAMP detection system showed good sensitivity, up to 101, as well as good specificity. Furthermore, GI and GII did not interfere with each other. No false-positive responses were obtained for other gastrointestinal RNA viruses, such as Coxsackie virus A16 or enterovirus 71. Our results showed that the RT-LAMP detection system for NoV GII is suitable for the quantitative determination of NoV.

Artificial intelligence‐assisted point‐of‐care testing system for ultrafast and quantitative detection of drug‐resistant bacteria

AbstractAs one of the major causes of antimicrobial resistance, β‐lactamase develops rapidly among bacteria. Detection of β‐lactamase in an efficient and low‐cost point‐of‐care testing (POCT) way is urgently needed. However, due to the volatile environmental factors, the quantitative measurement of current POCT is often inaccurate. Herein, we demonstrate an artificial intelligence (AI)‐assisted mobile health system that consists of a paper‐based β‐lactamase fluorogenic probe analytical device and a smartphone‐based AI cloud. An ultrafast broad‐spectrum fluorogenic probe (B1) that could respond to β‐lactamase within 20 s was first synthesized, and the detection limit was determined to be 0.13 nmol/L. Meanwhile, a three‐dimensional microfluidic paper‐based analytical device was fabricated for integration of B1. Also, a smartphone‐based AI cloud was developed to correct errors automatically and output results intelligently. This smart system could calibrate the temperature and pH in the β‐lactamase level detection in complex samples and mice infected with various bacteria, which shows the problem‐solving ability in interdisciplinary research, and demonstrates potential clinical benefits.

Effects of predator odor on anti-predation behavior and hypothalamic c-fos mRNA expression of Chinese mole shrew

Chinese mole shrew (Anourosorex squamipes, Soricidae) is a small mammal, with a large population in the low mountain basin area of Sichuan, China, and it is one of the main pests in farmland. We exposed A. squamipes to cat（a natural predator） and rabbit（a non-natural predator） odors, and compared their behaviors and hypothalamus c-fos mRNA expression. This paper explored the behavioral changes in predator odor stress of A. squamipes, which reveals the shrews’ stress response mechanism to natural predators. In this study, 36 Chinese mole shrew individuals were exposed to different odors for a short time (10 min) under laboratory conditions. Distilled water was used as the control group (CG), rabbit urine odor as the non-predator group (NG), and cat urine odor as the predator group (PG). SuperMaze animal behavior video analysis system was used to observe and record anti-predation behavior data. The real-time fluorescence quantitative nucleic acid amplification detection system (QPCR) was used to determine the expression of hypothalamic c-fos genes. The results showed that 1) both male and female shrews were significantly stimulated by cat odor, and their time of concealment, sniffing, wariness, and escape behavior showed significant increases, showing that the shrews responded strongly to the odors of a natural predator and showed clear anti-predation behavior. 2) different odor stimuli resulted in different expression of c-fos mRNA in the shrews’ hypothalamus, and there was no significant difference between the rabbit odor treatment group and that of the control group. The expression of c-fos mRNA in the cat odor was significantly higher than other two groups, indicating that the stress response of A. squamipes to natural predator is closely related to the expression of c-fos mRNA. The result shows that A. squamipes can recognize the scent of predators and regulate their own behavior by promoting the expression of c-fos mRNA in the hypothalamus, thereby increasing the investment into anti-predation defense strategies.

A highly quantitative detection system for cell entry of human norovirus-like particles based on the complementation of NanoLuc luciferase

Human norovirus (HuNoV) is the common cause of acute gastroenteritis worldwide. Norovirus-like particles (VLPs) have been applied to analyze virus–host cell interactions. This study established a highly quantitative detection system for HuNoV VLP entry into live cells based on the NanoLuc luciferase complementation. First, we generated a HiBiT-tagged VLP and examined VLP-HiBiT entry into Vero cells expressing LgBiT. The entry was saturable and competed by a non-labeled VLP, indicating the VLP-specific entry into the host cells. Upon comparison of the VLP-HiBiT entry among some cell lines, Caco-2 cells were found to be the most susceptible. The VLP-HiBiT entry was unaffected by treatment at an acidic pH value above 3.0 and was significantly reduced by heat treatment at 75°C for more than 2 min. These results reflected those of previous studies, indicating the stability of VLPs and binding to histo-blood group antigens at various pH ranges and temperatures and cellular tropism.

Localized photonic nanojet based sensing platform for highly efficient signal amplification and quantitative biosensing

Light-analyte interaction systems are key elements of novel near-field optics based sensing techniques used for highly-sensitive detection of various kinds of targets. However, it is still a great challenge to achieve quantitative analysis of the targets using these sensing techniques, since critical difficulties exist on how to efficiently and precisely introduce the analytes into the desired location of the near-field light focusing, and quantitatively measure the enhanced optical signal reliably. In this work, we present for the first time a localized photonic nanojet (L-PNJ) based sensing platform which provides a strategy to achieve quantitative biosensing via utilizing a unique light-analyte interaction system. We demonstrate that individual fluorescent microsphere of different sizes can be readily introduced to the light-analyte interaction system with loading efficiency more than 70%, and generates reproducible enhanced fluorescence signals with standard deviation less than 7.5%. We employ this sensing platform for fluorescent-bead-based biotin concentration analysis, achieving the improvement on the detection sensitivity and limit of detection, opening the door for highly sensitive and quantitative biosensing. This L-PNJ based sensing platform is promising for development of next-generation on-chip signal amplification and quantitative detection systems.

Development of an IoT-integrated multiplexed digital PCR system for quantitative detection of infectious diseases.

For rapid detection of the COVID-19 infection, the digital polymerase chain reaction (dPCR) with higher sensitivity and specificity has been presented as a promising method of point-of-care testing (POCT). Unlike the conventional real-time PCR (qPCR), the dPCR system allows absolute quantification of the target DNA without a calibration curve. Although a number of dPCR systems have previously been reported, most of these previous assays lack multiplexing capabilities. As different variants of COVID-19 have rapidly emerged, there is an urgent need for highly specific multiplexed detection systems. Additionally, the advances in the Internet of Things (IoT) technology have enabled the onsite detection of infectious diseases. Here, we present an IoT-integrated multiplexed dPCR (IM-dPCR) system involving sample compartmentalization, DNA amplification, fluorescence imaging, and quantitative analysis. This IM-dPCR system comprises three modules: a plasmonic heating-based thermal cycler, a multi-color fluorescence imaging set-up, and a firmware control module. Combined with a custom-developed smartphone application built on an IoT platform, the IM-dPCR system enabled automatic processing, data collection, and cloud storage. Using a self-priming microfluidic chip, 9 RNA groups (e.g., H1N1, H3N2, IFZ B, DENV2, DENV3, DENV4, OC43, 229E, and NL63) associated with three infectious diseases (e.g., influenza, dengue, and human coronaviruses) were analyzed with higher linearity (>98%) and sensitivity (1 copy per μL). The IM-dPCR system exhibited comparable analytical accuracy to commercial qPCR platforms. Therefore, this IM-dPCR system plays a crucial role in the onsite detection of infectious diseases.

Label-free fiber-optic spherical tip biosensor to enable picomolar-level detection of CD44 protein

Increased level of CD44 protein in serum is observed in several cancers and is associated with tumor burden and metastasis. Current clinically used detection methods of this protein are time-consuming and use labeled reagents for analysis. Therefore exploring new label-free and fast methods for its quantification including its detection in situ is of importance. This study reports the first optical fiber biosensor for CD44 protein detection, based on a spherical fiber optic tip device. The sensor is easily fabricated from an inexpensive material (single-mode fiber widely used in telecommunication) in a fast and robust manner through a CO2 laser splicer. The fabricated sensor responded to refractive index change with a sensitivity of 95.76 dB/RIU. The spherical tip was further functionalized with anti-CD44 antibodies to develop a biosensor and each step of functionalization was verified by an atomic force microscope. The biosensor detected a target of interest with an achieved limit of detection of 17 pM with only minor signal change to two control proteins. Most importantly, concentrations tested in this work are very broad and are within the clinically relevant concentration range. Moreover, the configuration of the proposed biosensor allows its potential incorporation into an in situ system for quantitative detection of this biomarker in a clinical setting.