Simultaneous Detection Research Articles

Urease-Driven Janus Nanomotors for Dynamic Enrichment and Multiplexed Detection of Bladder Cancer MicroRNAs in Urine.

Bladder cancer diagnosis typically involves approaches such as cystoscopy, biopsy, urine cytology, and medical imaging. However, these invasive procedures carry a risk of complications, and direct in vitro detection on clinical samples often results in low sensitivity. Therefore, this study proposed urease-driven magnetic nanomotors for the simultaneous detection of bladder cancer biomarkers miRNA-21 and miRNA-182 in urine samples, aiming for noninvasive diagnosis. The nanomotor was constructed from gold nanorods, mesoporous organo-silica, Fe3O4, and hairpin DNA (hDNA), functioning as a recognition probe for the target miRNAs. In the urea solution, urease catalyzed urea into ammonia and carbon dioxide, propelling the nanomotor for about 60 min, which enhanced the capacity of the probes to capture the target miRNAs. Subsequently, magnetic enrichment enabled highly sensitive dual-miRNA analysis, allowing quantification of miRNA-21 and miRNA-182 with detection limits of 29 and 362 fM, respectively. The nanoprobes also effectively detected miRNAs in spiked urine samples. This simultaneous detection of multiple miRNAs increased the reliability of cancer diagnosis, presenting a novel noninvasive strategy for bladder cancer detection through precise in vitro analysis of actual urine samples.

Facile Synthesis of Polyethylene Glycol Passivated N-doping CQDs as Fluorescent Probe for Multi-Target Simultaneous Detection in Heavy-Metals Solution.

In order to quickly and conveniently detect multiple heavy metal ions in aqueous phase simultaneously, a polyethylene glycol passivated N-doping carbon quantum (p-N-CQDs) was synthesized by a hydrothermal method with citric acid (carbon source), urea (nitrogen source) and polyethylene glycol (passivator). The as-prepared p-N-CQDs could be evenly dispersed in deionized water, and the average diameter was 1.83nm, resulting in 18.72% of fluorescence quantum yield. As a sensor, the fluorescence of p-N-CQDs would be significantly quenched with Fe3+ or Cu2+ under the different maximum emission wavelength of 452nm and 448nm, respectively. Therefore, a method for simultaneously detecting multiple heavy metal ions was proposed by discriminative fitting of the fluorescence emission peaks after metal ion quenching. Upon the experiments, two linear calibration curves between resolving fluorescence intensities of p-N-CQDs and concentration of the metal ions were obtained within a range of 10 to 1000 µM of Cu2+ and 40 to 800 µM of Fe3+. And a limit of detection (LOD) of 0.032 µM was attained after resolving the curves based on the emission wavelength of 448nm for Cu2+ and 452nm for Fe3+ by a peak splitting software. In addition, the stability, selectivity and anti-interference of the proposal senor was confirmed.

PCR-based detection of Botryosphaeria canker pathogens in fig trees.

Canker and dieback, caused by members of the Botryosphaeriaceae family, pose significant threats to plant productivity, food security, and natural ecosystems, particularly in economically important woody crops including fig trees. Detecting and identifying these pathogens is challenging due to their latent infections and the presence of multiple pathogens within the same host. In our study, we developed a PCR assay using three carefully selected primer pairs based on sequence differences in two protein-coding genes, β-tubulin and RNA polymerase II. The species-specific primers TUB-Bd1 (specific for Botryosphaeria dothidea), TUB-Np1 (specific for Neofusicoccum parvum), and RPB-Nd2 (specific for Neoscytalidium dimidiatum) effectively amplified target gene sequences in pure cultures and infected tissue samples using PCR and nested PCR conditions. The efficiency test results demonstrated that TUB-Bd1, TUB-Np1, and RPB-Nd2 primer pairs could detect specific DNA fragments at very low concentrations in nested PCR. Furthermore, we collected 180 symptomatic and asymptomatic fig samples from different regions of Fars Province, Iran. Applying the species-specific primer pair RPB-Nd2 in direct PCR led to the detection of N. dimidiatum in 25.5% of symptomatic woody samples and 13% of asymptomatic one-year-old branch samples of fig trees. This represents a significant improvement compared to the mere 6.67% detected using traditional culturing methods on PDA. Interestingly, neither B. dothidea nor N. parvum were detected in the 180 samples using nested PCR. Moreover, multiplex PCR enabled simultaneous DNA detection of the target Botryosphaeriaceae pathogens. Our findings emphasize the importance of molecular techniques for early detection of evident and latent infections caused by these three pathogens in fig trees.

Novel Electrochemical Sensor Based on Cu-MOF/MWCNT-COOH for the Simultaneous Detection of Ascorbic Acid and Dopamine.

By utilizing carboxylated multiwalled carbon nanotubes (MWCNT-COOH) to strengthen the interaction between the electrode and the analytes and improve the conductivity of the composite material and in conjunction with the superior catalytic properties of copper-based metal-organic framework (MOFs), a novel electrochemical sensor was fabricated from a Cu-MOF/MWCNT-COOH composite, specifically designed for the simultaneous and distinct detection of ascorbic acid (AA) and dopamine (DA). Electrochemical analyses were conducted on the innovative Cu-MOF/MWCNT-COOH electrode through both CV and DPV, revealing unique electrochemical behaviors for AA and DA. The sensor not only showed exceptional electrocatalytic properties but also distinguished itself by its broad dynamic response ranges, covering concentrations from 3 to 1800 μM for AA and from 2 to 180 μM for DA, with detection limits (S/N = 3) of 3.00 μM for AA and 0.32 μM for DA. Furthermore, this electrochemical detection platform exhibited robust reproducibility and selectivity. Examinations of serum samples yielded the recovery rates of AA and DA which were 101.9% and 102.1%, respectively, confirming the sensor's capability to perform reliably under varied biological conditions. The findings confirm the sensor's potential of the proposed method for the simultaneous, sensitive, and reliable detection of AA and DA. In conclusion, the electrochemical sensor has a promising potential for practical applications.

Pt-Doped Reduced Graphene Oxide-Porphyrin-CNT Composite-Based Electrochemical Sensor for Simultaneous Detection of Dopamine, Serotonin and Norepinephrine

Abstract A novel electrochemical sensor for simultaneous and selective detection of dopamine (DA), serotonin (5-HT), and Norepinephrine (NE) was developed using a platinum-doped reduced graphene oxide-porphyrin-carbon nanotube (Pt-doped rGO-P-CNT) composite. This composite leverages the synergistic effects of its individual components: the aromatic π-π interactions and electrostatic attraction provided by porphyrin-functionalized graphene, the enhanced electron transfer capability from platinum doping, and the high surface area and conductivity of carbon nanotubes. The composite was synthesized in a multi-step process, starting with the oxidation of graphite to produce graphene oxide (GO), followed by reduction of GO and functionalization with porphyrin. Platinum nanoparticles were incorporated using a chemical reduction method, and carbon nanotubes were introduced to further improve conductivity and surface area. Electrochemical characterization demonstrated excellent separation of oxidation peak potentials for DA, 5-HT, and NE, allowing for precise multiplexed detection. The Pt-doped rGO-P-CNT composite showed high electrocatalytic activity and selectivity, with minimal interference from ascorbic acid. The sensor achieved a detection limit as low as 0.012 µM for DA & 5-HT and 0.015 µM for NE. Real-sample analyses in human urine and serum demonstrated the sensor’s practicality, achieving satisfactory recoveries and reproducibility. This Pt-doped rGO-P-CNT composite addresses key limitations in electrochemical biosensing.

Nanoliter Plasma Sample for Disease Diagnosis by Using a Visualization Platform of Counting Extracellular Vesicle Particles.

Extracellular vesicles (EVs) are an excellent candidate for noninvasive diagnostic and prognostic assessments for liquid biopsy applications owing to reflecting the dynamic changes of pathological and physiological states in the body and exceptional stability in vivo. Herein, we developed a single-extracellular vesicle fluorescence visualization and counting platform containing three parts of the nanoliter-liquid operating platform for aspirating the sample, antibody-functionalized coverslip for capturing targeted EVs, and the single-molecule fluorescence labeling and imaging system for the visualization and counting of EVs. Compared to previously reported studies, our developed platform not only minimized operational complexity but also successfully detected single EVs using a minimal volume of 25 nL of plasma. Moreover, the results of fluorescence spot counts demonstrated that the developed platform exhibits a wide dynamic range and an excellent linear correlation between fluorescence intensity and particle numbers for the detection of CD9+ EVs from standard samples. Remarkably, our developed single EVs capture and analysis platform was successfully applied not only in the quantitative analysis of EpCAM+ EVs to CD9+ EVs for the diagnosis of breast cancer (BC) but also in the quantitative analysis of CD14+ EVs to CD9+ EVs for the diagnosis of type 2 diabetes (T2DM). Collectively, our work provides new ideas for the diagnosis of breast cancer and type 2 diabetes while developing a versatile method for distinguishing other diseases by simultaneous detection of multibiomarkers of Exos subtypes in trace samples due to the substitutability of antibodies.

Split crRNA Precisely Assisted Cas12a Expansion Strategy for Simultaneous, Discriminative, and Low-Threshold Determination of Two miRNAs Associated with Multiple Sclerosis.

Multiple sclerosis (MS) can proceed into secondary progressive MS accompanied by persistent neurological deterioration; therefore, accurate diagnosis of MS is of vital significance. Irregularities of microRNAs (miRNAs) expression have been observed in MS, so miRNAs have been evaluated as novel biomarkers and therapeutic targets. Herein, a new strategy named split crRNA precisely assisted Cas12a expansion (SPACE) was developed for simultaneous, discriminative, and low-threshold determination of two MS-related miRNAs: miRNA-155 and miRNA-326. On the one hand, owing to the property that split crRNA could activate Cas12a, miRNAs were designed as the spacers of crRNA to combine with scaffold. These integrated crRNAs then recognized the activators, activating Cas12a and enabling RNA target identification. On the other hand, the SPACE strategy dexterously integrated the activator with reporter probe, and utilized Cas12a's cis-cleavage to achieve simultaneous detection and differential signal output for miRNA-155 and miRNA-326. Moreover, trans-cleavage with ultra-high efficiency was assembled in the SPACE strategy to achieve sensitive quantification of total miRNAs in blood samples at low thresholds. Overall, the diversified and integrated design of the SPACE strategy enabled simultaneous, discriminative, and low-threshold detection of dual MS-related miRNAs in one pot and one step, providing a reliable and accurate Cas12a detection tool for clinical low-threshold diagnosis.

Moar: A Swimmer Motion Swimming Style Identification Model using Deep Learning

Athletes in various sports, such as swimming, are increasingly using motion capture to identify and optimize their movement techniques. However, traditional motion capture systems tend to be expensive and limited. Computer vision-based methods have emerged as alternatives to identify four swimming styles: freestyle, backstroke, breaststroke, and butterfly. However, previous models did not identify flaws in swimmer movement. A significant challenge is the lack of labeled swimming video datasets that indicate these flaws. To overcome this challenge, this study collected and labeled a dataset of swimmer flaws and integrated them with the publicly available dataset SwimXYZ. Then, YOLO models were trained on the generated data. The YOLOv8s model demonstrated an impressive mean average precision (mAP@0.50) of 98% in the detection of swimming style and 95% in the simultaneous detection of swimming style and the identification of incorrect movements. This model can be used in real-time applications to help swimmers evaluate and improve the accuracy of their techniques.

Simultaneous detection and quantification of ciprofloxacin, doxycycline, and levofloxacin in municipal lake water via deep learning analysis of complex Raman spectra

Simultaneous detection and quantification of ciprofloxacin, doxycycline, and levofloxacin in municipal lake water via deep learning analysis of complex Raman spectra

Simultaneous Range and Velocity Detection With Asymmetric Dual-Chirped Photonic Radar

Simultaneous Range and Velocity Detection With Asymmetric Dual-Chirped Photonic Radar

Feature-engineering-enhanced multiple simultaneous fault detection in residential air conditioners

Feature-engineering-enhanced multiple simultaneous fault detection in residential air conditioners

Development of a duplex real-time recombinase aided amplification assay for the simultaneous and rapid detection of PCV3 and PCV4

BackgroundPorcine circoviruses 3 (PCV3) and 4 (PCV4) are emerging pathogens with global implications for swine industry, disturbing the diagnosis of PCVs associated diseases due to a range of similar clinical symptoms and increasingly coinfections. A rapid and accurate method for detection of PCV3 and PCV4 is critical for controlling the transmission of associated disease.MethodsWe developed a duplex real-time recombinase aided amplification (RAA) assay for detection of both PCV3 and PCV4 simultaneously. The assay was completed within 20 min at 39℃ with the designed optimal primers and probes.ResultsThe established assay was more convenient and simpler operation compared with conventional molecular biological assays. The assay achieved a detection limit of 73.67 copies/reaction for each circovirus (at 95% probability by probit regression analysis) and showed high specificity and no cross-reactivity with other important porcine viruses (including PCV2). The intra- and inter-group coefficients of variation (CV) were ranged from 2.08 to 4.97%, indicating high stability and reliability. Comparative analysis with PCV3 and PCV4 qPCR on 60 clinical samples and artificially spiked samples indicated high congruence (the kappa value was 0.966 and 1, respectively, with p < 0.001), with only minor discrepancies, validating effectiveness of the duplex RAA assay in detecting co-infections and its suitability for preliminary clinical diagnosis of PCV3 and PCV4.ConclusionsThis study provides a robust basis for multiplex detection of veterinary pathogens using RAA technique, enhancing the field’s capacity to control PCV3 and PCV4, and supporting reliable aid for epidemiological understanding of emerging circoviruses.

Water-Based SRR Sensor With Machine Learning Algorithms for Simultaneous Temperature and Pressure Detection

Water-Based SRR Sensor With Machine Learning Algorithms for Simultaneous Temperature and Pressure Detection

Simultaneous and instrument-free detection of quinine and crystal violet based on a dual-emissive Eu3+-functionalized metal-organic framework

Simultaneous and instrument-free detection of quinine and crystal violet based on a dual-emissive Eu3+-functionalized metal-organic framework

A blind navigation guide model for obstacle avoidance using distance vision estimation based YOLO-V8n

Obstacle is an object positioned along a path of propagation with the potential to cause a collision and hence, an accident. Over the years, several papers have applied advanced computer vision techniques, particularly transfer learning algorithms, to solve this problem, but despite their success, in specific vision applications such as blind guide navigation systems, the model finds it difficult to distinguish between objects and obstacles recognized in the same video frame, hence attracting research attention. In this paper, the aim was to develop a blind navigation guide model for obstacle avoidance using distance vision estimation-based YOLO-V8n. To achieve this, an improved data model was developed using the MS COCO dataset and primary data collected from several indoor environments. Then, the YOLO-V8n architecture was improved by adding a Weighted Feature Enhancement (WFE) model to the backbone for improved feature extraction, and Bi-directional Feature Pyramid Network (Bi-FPN) was applied to the neck to improve multi-scale feature representation. In addition, a Distance Vision Estimation (DVE) algorithm was developed and applied to the Bi-FPN before connecting it to the head of the YOLO-V8n to facilitate simultaneous object detection and distance measurement in real-time video. Furthermore, the issue of bounding box overlap in the model was addressed by applying a Wise Intersection over Unit (WIoU) loss function. Collectively, these formulated the new transfer learning algorithm called YOLO-V8n+WFE+Bi-FPN+DVE+WIoU used in this work for high-level obstacle detection and distance estimation. The model was trained considering different experimental architectures of the YOLO-V8 and loss functions, respectively, and then evaluated with precision, recall, mean absolute precision, and average precision, respectively, before validation through comparative analysis. Upon selection of the best model, it was further validated through comparison with other state-of-the art algorithms before deployment for obstacle avoidance in an indoor environment, having satisfied the condition of reliability. Real world testing of the model was performed at four different indoor sites, and the results showed that while the model was able to correctly classify objects, it could also measure their distance accurately, thereby making it suitable for deployment as a blind vision guide navigation system.

Electrochemical nanoprobe for highly sensitive and simultaneous detection of ascorbic acid, dopamine, and uric acid

Electrochemical nanoprobe for highly sensitive and simultaneous detection of ascorbic acid, dopamine, and uric acid

Entropy driven-based catalytic biosensors for bioanalysis: From construction to application-A review.

The rapid advancement of precision medicine and the continuous emergence of novel pathogens have presented new challenges for biosensors, necessitating higher requirements. Target amplification technology serves as the core component in biosensor construction. Enzyme-based amplification methods are often sensitive and selective but involve relatively complex operational steps, whereas enzyme-free amplification methods offer simplicity but frequently fail to meet both sensitivity and selectivity simultaneously. Existing research has confirmed that entropy-driven catalyst (EDC) biosensors not only fulfills the demands for sensitivity and selectivity concurrently but also offers ease of operation and flexibility in construction. In this review, we summarize the key advantages of EDC, explore how to construct DNA nanomachines based on these advantages to achieve intracellular detection and simultaneous detection of multiple targets, as well as point-of-care testing (POCT) to address practical issues in clinical diagnosis and treatment. We also anticipate potential challenges, propose corresponding solutions, and outline future development directions for EDC-based biosensors in practical clinical applications. We firmly believe that EDC sensors will emerge as a crucial branch within the realm of biosensor development.

A miniaturized RPA-CRISPR/Cas12a-based nucleic acid diagnostic platform for rapid and simple self-testing of SARS-CoV-2.

Nucleic acid testing is the most effective detection method currently available for the diagnosis of respiratory infectious diseases. However, the conventional real-time fluorescent quantitative PCR technique, which is regarded as the gold standard method for nucleic acid detection, presents significant challenges for implementation in home self-testing and popularization in underdeveloped regions due to its rigorous experimental standards. It is therefore clear that an easy-to-use, miniaturized nucleic acid testing technology and products for nonprofessionals are of great necessity to define the pathogens and assist in controlling disease transmission. (87) RESULTS: In this study, we propose a strategy for self-testing of respiratory pathogen nucleic acid that is oriented towards the public and user-friendly. The proposed system integrates the processes of extraction-free nucleic acid release, RPA isothermal amplification, and CRISPR fluorescence detection into a compact configuration. A microfluidic testing chip actuated by air pouches and a battery/USB-powered reusable device has been developed to enable simultaneous detection of internal reference genes and viral targets in a fully enclosed condition. The system allows for sample-in, and result-out testing in less than 30min with a detection limit of 2 copies/μL. Additionally, a straightforward signal-light-based result display method has been developed to make it easy and intuitive for users to access the results. Furthermore, freeze-drying reagent is introduced to guarantee the storage and transportation of testing chips in ambient conditions. (135) SIGNIFICANCE: This work presents a miniaturized, portable, and highly sensitive nucleic acid detection system, where simple operating procedures have been designed for unskilled users. It is our belief that the testing system developed in this work is well suited for home-based self-testing and infection diagnosis in resource-limited areas, due to the above-mentioned advantages. (52).

The effect of inhaled nitric oxide treatment on biomarkers of oxidative/nitrosative damage to proteins and DNA/RNA.

Inhaled nitric oxide (iNO) is a selective pulmonary vasodilator that is used as a treatment for persistent pulmonary hypertension in neonates (PPHN) with hypoxic respiratory failure. The generation of reactive oxygen and nitrogen species might induce oxidative/nitrosative damage to multiple organs. There is an increasing scientific and clinical interest in the determination of specific biomarkers to measure the degree of oxidative/nitrosative stress in non-invasively collected biofluids. A method for the simultaneous detection of a panel of oxidative and nitrosative stress-related biomarkers for quantifying damage to proteins and DNA/RNA in 20μL of infant urine samples based on reversed-phase ultra-performance liquid chromatography coupled to tandem mass spectrometry operating in positive electrospray ionization mode (ESI+) was optimized and validated. Infant urine samples from two different studies were analyzed: (i) term and preterm infants from a nutrition study (Nutrishield, N=50) and (ii) infants with respiratory insufficiency, including infants with PPHN (N=16) that required iNO treatment and a control group without treatment (N=14). Eleven of 14 metabolites were detected in >50% of infant urine samples, with ranges between 0.008 and 1400μmol/g creatinine. When comparing across groups, differences in samples collected after iNO treatment in comparison to the rest of the groups were found for m-tyrosine (m-Tyr and m-Tyr/Phe) and ortho-tyrosine (o-Tyr and o-Tyr/Phe) (p-values <0.001, Wilcoxon rank-sum test). Positive linear relationships were found with NO exposure corrected by infant weight for m-Tyr, m-Tyr/Phe, o-Tyr, o-Tyr/Phe and 3-nitrotyrosine. Future studies will focus on the evaluation of the impact of iNO treatment on health and oxidative/nitrosative stress-related morbidities associated with prematurity.

Detection methods and control measures of Burkholderia gladioli and its toxins: A review.

Burkholderia gladioli is a widely distributed Gram-negative bacterium. Under suitable environmental conditions, it can produce harmful toxins bongkrekic acid (BKA) and toxoflavin (TF) in food carriers (such as fermented cereal products, spoiled fresh Tremella and Auricularia auricula, and fermented potatoes), posing a serious threat to the safety of food producers and consumers. Food poisoning caused by B. gladioli can manifest as comprehensive symptoms such as diarrhea, and in severe cases, symptoms such as convulsions and shock may occur. Therefore, it is necessary to conduct a comprehensive and in-depth exploration of the food safety issues it causes. First, this article summarizes the clinical cases and prevalence caused by B. gladioli. Second, the detection methods for BKA and the methods for simultaneous detection of BKA and TF were reviewed. Finally, the methods that can inhibit the proliferation of B. gladioli and effective measures to control its production of BKA in different food carriers were reviewed. This review will help to comprehensively understand the spread of B. gladioli and its toxins and preventive measures, aiming to reduce their harm to human health.