Detection Device Research Articles

Point-of-care testing based on colorimetric loop-mediated isothermal amplification coupled with a nondestructive device for rapid detection of Kudoa septempunctata in live olive flounder

Kudoa septempunctata, a myxosporean parasite newly identified in 2010, was first detected in the trunk muscle of an aquacultured olive flounder imported from Korea to Japan. Since 2003, foodborne disease outbreaks in Japan have been increasing, often linked to the ingestion of raw olive flounder. These illnesses, characterized by diarrhea and emesis, typically occur within 2–20 h after consuming raw olive flounder. Recent studies on the etiological agents responsible for these illnesses and animal experiments have implicated K. septempunctata as a potential causative agent of these novel foodborne disease outbreaks. Consequently, a rapid, sensitive, and convenient method for detecting K. septempunctata is required. This study presents a colorimetric loop-mediated isothermal amplification (LAMP) assay developed using a molecular beacon (MB) and horseradish peroxidase-mimicking DNAzyme for the rapid and sensitive detection of K. septempunctata in the muscle of olive flounder. Three pairs of primers targeting the 28S rDNA gene and an MB were designed and synthesized. The colorimetric LAMP assay was optimized by determining key factors such as MB concentration, incubation temperature, and time. Its specificity was investigated, and the method was validated using contaminated muscle samples of olive flounder (101–106 spores/g). The cutoff value of the colorimetric LAMP assay, optimized at 57.5 °C, was 1 × 101 spores/g, confirming its specificity to K. septempunctata. The developed assay can be completed within 1 h. Overall, this study demonstrates that the developed K. septempunctata-specific LAMP assay shows promise as a point-of-care molecular diagnostic technology, as it does not require expensive instruments such as a thermocycler or detector.

An enzyme-fused phycobiliprotein synthesis system developed for visual whole-cell biosensors for the detection of cadmium during wastewater treatment

Transcription factor-based whole-cell biosensors are simple and inexpensive tools for monitoring heavy metals during environmental processes. However, most biosensors are depend on instrumentation or have low sensitivity. Here, all the enzymes in the phycobiliprotein synthesis system were fused with the phycocyanin apoprotein to create a system to synthesize enzyme-fused phycobiliproteins with comparable fluorescence. We replaced the biliprotein synthesis system T7 promoter with cadmium-sensing genetic elements to create two visual cadmium biosensors (Epcad-cbsA and Epcad-cbsS). Cd2+ was detected at nanomolar concentrations by measuring the fluorescence intensity and evaluating the degree of color change of the cell pellets. Moreover, good linear correlations were observed with Cd2+ concentrations up to 250 nM. Compared with cellular fluorescence, our cadmium biosensor is more sensitive when cell color is used as the output signal, with detection limits of 7.6 nM for Epcad-cbsA and 3.2 nM for Epcad-cbsS. This visual platform was validated by assessing bioavailable cadmium during wastewater treatment. By immobilizing large amounts of phycobilin with the proteins in cells, our designed biosensors do not require pigment extraction or specialized light sources or detection devices. This work demonstrates that a biliprotein synthesis system can be a novel platform for the development of simple, low-cost, and highly sensitive visual biosensors for real-world applications.

Facile fabrication of foldable electrospun nanofiber electrodes for electrodes for electronic biosensing

This study presents a rapid, sensitive and selective sensor based on electrospun nanofibers on laser-patterned electrodes, in which the laser micromachining process can directly fabricate the graphene electrode device for the electronical detection of glucose molecule. The layer of graphene film was formed on the glass substrate by a screen printing technique, and then the graphene electrodes can be fabricated by the ultraviolet (UV) nanosecond laser process with the wavelength of 355 nm. Based on the controlled the laser fluence and pulses, the electrode gap of 60 μm within the device can be fabricated. The polyvinyl alcohol (PVA) and glucose oxidase (GOD) composite nanofiber with weight percentage of 8% can be used by the electrospun process with used Glutaraldehyde(GA) steam for cross linking process. After that, it is blended with the conductivity of poly(3,4-ethylenedioxythiophene): poly (styrene sulfonate) (PEDOT:PSS), and the foldable nanofiber structures was made by electrospun process on the graphene electrode device. Finally, the electrical detection of graphene electrode device with the nanofibers at different concentrations of glucose can be measured, resulting in the linear variation is detecting the glucose concentration ranging form 0.01 to 3.12 mM. This work indicated that the low concentration and highly sensitive can be used for electronic biosensors

Electrochemical Biosensor Based on Dual-Ligand Functionalized Lanthanide-Encapsulated Polyoxometalate Conductive Polymer Film for Detecting Broad-Spectrum Tumor Marker MicroRNA-155.

In this work, a dual-ligand functionalized lanthanide-encapsulated selenotungstate [H2N(CH3)2]16Na2H10[Ho6(H2O)10(HPACA)4W10O28(Ac)2][SeW9O33]6 · 60H2O (1, HPACA = 2-pyrazinecarboxylic acid, HAc = acetic acid) was successfully acquired by simultaneously incorporating rigid HPACA and flexible Ac- ligands to one reaction system. Interestingly, the polyanion [Ho6(H2O)10(HPACA)4W10O28(Ac)2][SeW9O33]628- of 1 is composed of six trivacant Keggin-type [B-α-SeW9O33]8- units interconnected through an organic-inorganic hybrid dual-ligand bimetallic [Ho6(H2O)10(HPACA)4W10O28(Ac)2]20+ cluster. Moreover, the 1@PNMPy film (PNMPy = poly(N-methylpyrrole)) was successfully prepared through an electrochemical polymerization strategy. The doping of 1 significantly narrows the bandgap in the 1@PNMPy film, which enables the 1@PNMPy film to exhibit remarkable conductivity and rapid electron transfer capability. Then, the 1@PNMPy film-modified glassy carbon electrode was used to construct a 1@PNMPy-based electrochemical biosensor (ECBS), which achieves sensitive electrochemical detection (a low limit of detection of 0.108 fM and a wide concentration detection range of 10-8-10-15 M) for broad-spectrum tumor marker microRNA-155. Also, the 1@PNMPy-based ECBS has a good specific recognition performance for microRNA-155 in a variety of interfering media. The research not only contributes to a deeper understanding of the synthetic chemistry of multicomponent polyoxometalate (POM)-based materials but also can further expand innovative applications of multicomponent POM-based materials in electrochemical detection and electrochemical devices.

Carbon Dot-Based Optical Point-of-Care Device for Detection of Neonatal Jaundice

Carbon Dot-Based Optical Point-of-Care Device for Detection of Neonatal Jaundice

A sensing system and solving method for dynamic detection of relative pose of hydraulic support group

The precise detection of the pose of hydraulic support groups is crucial for the construction of intelligent coal mines. Addressing current challenges in comprehensive position sensing of support groups, such as one-sided descriptions, missing information, and limited detection capabilities, this paper, based on the concept of digital twin, proposes a sensing system and solving method for dynamic detection of the relative pose of hydraulic support group. Initially, a relative pose detection model, based on the six-point localization principle, is proposed by combining existing sensor information. Then, a sensing system is designed, incorporating a photoelectric detection device for monitoring key position parameters and virtual sensors for determining pose information. Consequently, a method for dynamically deriving relative positions, driven by the fusion of real-virtual iterative solving, real-virtual error feedback, and iterative condition optimization, is established. Finally, a relative pose dynamic detection system for a hydraulic support prototype is constructed in a laboratory environment. Experimental results demonstrate that the sensor system and the relative position detection method designed in this paper achieve a relative position accuracy of over 95.32 % for the hydraulic support, with a dynamic reconstruction time of less than 0.2 s. This verifies the rationality of the sensor system and the feasibility and accuracy of the dynamic deduction method. To sum up, this work provides a theoretical foundation and technical support for the autonomous perception of hydraulic support group, autonomous frame adjustment between frames, and overall straightness adjustment. It also lays the groundwork for further research and the advancement of information-physical systems in the fully-mechanized mining face.

Microbial biosensors for diagnostics, surveillance and epidemiology: Today's achievements and tomorrow's prospects.

Microbial biosensors hold great promise for engineering high-performance, field-deployable and affordable detection devices for medical and environmental applications. This review explores recent advances in the field, highlighting new sensing strategies and modalities for whole-cell biosensors as well as the remarkable expansion of microbial cell-free systems. We also discuss improvements in robustness that have enhanced the ability of biosensors to withstand the challenging conditions found in biological samples. However, limitations remain in expanding the detection repertoire, particularly for proteins. We anticipate that the AI-powered revolution in protein design will streamline the engineering of custom-made sensing modules and unlock the full potential of microbial biosensors.

Monitoring of insulator pollution discharge in overhead distribution network based on acoustic emission technology

Abstract During the continuous operation of the distribution network, dirt often accumulates on the surface of insulators. Once encountering a humid climate environment, it may cause accidental discharge, leading to the occurrence of flashover pollution accidents. In order to effectively monitor this issue, this study adopted a monitoring method based on acoustic emission technology. This article introduces the discharge process and acoustic emission phenomenon of insulators in overhead distribution networks under pollution conditions. By using emission signal detection devices, acoustic signals generated during insulator discharge are captured. And the wavelet denoising algorithm was used to process its signal, based on which the discharge characteristics of insulator pollution in the overhead distribution network were extracted. The emission amount of insulator pollution in the overhead distribution network was determined according to the set threshold, achieving monitoring of pollution emissions. The results indicate that the proposed method can accurately monitor the discharge of insulators in overhead distribution networks, provide scientific basis for timely maintenance measures, and improve the operational safety and reliability of distribution networks.

Surprisingly fast self-healing coatings with anti-fog and antimicrobial activities via host-guest interaction

Dual functional coatings with anti-fog and antimicrobial performances greatly enhance the safety and reliability of medical detection devices, but are prone to mechanical damage, resulting in reduced performance and a shorter service lifespan. Herein, a semi-interpenetrating polymer network (SIPN) coating, featuring hydrophobic-hydrophilic balanced copolymers as bulk chains and host–guest inclusion compounds (HGICs) as cross-linkers, is reported, which demonstrates particularly effective anti-fog and antibacterial performances, along with a surprisingly fast self-healing capability under various scenarios. This HGIC-based coating displayed remarkable anti-fog capability over a wide temperature range from −20 ℃ to 85 ℃ and exhibited reliable antibacterial activities (≥98 %) against both gram-positive and gram-negative bacteria. Also, this coating showed extremely high self-healing ability (≥92 % recovery rate) within just 20 s, significantly outperforming traditional self-healing systems. These findings support the development of functional coatings that can highly maintain rapid self-healing performance while also providing anti-fog and antibacterial properties in medical detection devices.

Characteristics and fire-inducing risk analyses of arc faults in low-voltage electrical systems

Arc fault is a prevalent phenomenon in low-voltage residential power systems and the main cause of electrical fires. This paper explores the fire risks associated with arc faults and employs standards from arc fault detection devices (AFDD) to create an arc fault experimental system complemented by an integrated multi-sensor system for ignition related data collection. The objective is to synthetically examine the dynamic characteristics and ignition mechanisms of arc faults. This paper investigates the generation mechanisms, waveforms, and energy characteristics of arc faults, including waveform distinctions across different load types and patterns of energy variation during arcing. Data from the multi-sensor system become the cornerstone of the correlation analysis between the current, energy, and ignition phenomena, facilitating the construction of an ignition probability model based on maximum likelihood estimation. The reliability of the model is verified across various datasets with a 95 % confidence interval, offering a quantitative fire-inducing risk assessment of arc faults. Furthermore, the paper assesses the AFDD standards’ break time limits and evaluates the performance of seven AFDD prototypes based on the proposed model, demonstrating the effectiveness of this technology in mitigating the risks of fires induced by arc faults. This study systematically analyzes the behaviors and ignition mechanisms of arc faults, thereby providing scientific evidence and data that support the enhancement of arc fault detection technologies and the development of fire prevention strategies.

Multi-Electrode Extended Gate Field Effect Transistors Based on Laser-Induced Graphene for the Detection of Vitamin C and SARS-CoV-2.

Despite the clinical data showing the importance of ascorbic acid (AA or vitamin C) in managing viral respiratory infections, biosensors for their simultaneous detection are lacking. To address this need, we developed a portable and wireless device for simultaneous detection of AA and SARS-CoV-2 virus by integrating commercial transistors with printed laser-induced graphene (LIG) as the extended gate. We studied the effect of laser printing pass number and showed that with two laser printing passes (2-pass LIG), the sensor sensitivity and limit of detection (LOD) for AA improved by a factor of 1.6 and 12.8, respectively. Using complementary characterization methods, we attribute the improved response to a balanced interplay of crystallinity, defect density, surface area, surface roughness, pore density and diameter, and mechanical integrity/stability. These factors enhance analyte transport, reduce noise/variability, and ensure consistent sensor performance, making 2-pass LIG the most effective material in this work. Our sensors exhibit promising performance for detecting AA with a selective response in the presence of common salivary interfering molecules, with sensitivity and LOD of 73.67 mV/dec and 54.04 nM in 1× phosphate buffered saline and 81.05 mV/dec and 78.34 nM in artificial saliva, respectively. We also showed that functionalization of the 2-pass LIG gate with S-protein antibody enables the detection of SARS-CoV-2 protein antigens with an ultralow LOD of 52 zg/mL─an improvement of more than 10-fold compared to 1-pass LIG─and 4 particles/mL for virion mimics with a selective response against influenza virus and multiple human coronavirus strains. With low signal drift/hysteresis and wireless capabilities, the developed device holds great potential for improving at-home monitoring and clinical decision-making.

Gastric neoplasm detection of computer-aided detection-assisted esophagogastroduodenoscopy changes with implement scenarios: a real-world study.

The implementation of computer-aided detection (CAD) devices in esophagogastroduodenoscopy (EGD) could autonomously identify gastric precancerous lesions and neoplasms and reduce the miss rate of gastric neoplasms in prospective trials. However, there is still insufficient evidence of their use in real-life clinical practice. A real-world, two-center study was conducted at Wenzhou Central Hospital (WCH) and Renmin Hospital of Wuhan University (RHWU). High biopsy rate and low biopsy rate strategies were adopted, and CAD devices were applied in 2019 and 2021 at WCH and RHWU, respectively. We compared differences in gastric precancerous and neoplasm detection of EGD before and after the use of CAD devices in the first half of the year. A total of 33 885 patients were included and 32 886 patients were ultimately analyzed. In WCH of which biopsy rate >95%, with the implementation of CAD, more the number of early gastric cancer divided by all gastric neoplasm (EGC/GN) (0.35% vs 0.59%, P=0.028, OR [95% CI]=1.65 [1.0-2.60]) was found, while gastric neoplasm detection rate (1.39% vs 1.36%, P=0.897, OR [95% CI]=0.98 [0.76-1.26]) remained stable. In RHWU of which biopsy rate <20%, the gastric neoplasm detection rate (1.78% vs 3.23%, P<0.001, OR [95% CI]=1.84 [1.33-2.54]) nearly doubled after the implementation of CAD, while there was no significant change in the EGC/GN. The application of CAD devices devoted to distinct increases in gastric neoplasm detection according to different biopsy strategies, which implied that CAD devices demonstrated assistance on gastric neoplasm detection while varied effectiveness according to different implementation scenarios.

Research on Rate Adaptation of Underwater Optical Communication with Joint Control of Photoelectric Domain

As the communication distance changes, the received signal strength of an underwater optical communication system will change, and the range of its variation may not only exceed the dynamic range of the photoelectric detection device but also cause the reliability of communication to change due to the change in the received signal-to-noise ratio. In order to maintain better communication over a longer distance, this paper proposes a rate-adaptive method for underwater optical communication with joint control in the photoelectric domain. In the optical domain, the incident light’s power is adaptively adjusted by controlling the transmittance of the liquid crystal light valve to reduce saturation distortion. In the electrical domain, the constellation distribution is optimized according to the desired probability mass function, and the modulation order is adjusted in real time by estimating the received signal-to-noise ratio of the link. The simulation results show that under the forward error correction (FEC) threshold, the proposed method increases the dynamic range of the photomultiplier tube (PMT) by about 10 dB and expands the dynamic range of the system’s communication distance.

Development of a novel ternary MOF nanozyme-based smartphone-integrated colorimetric and microfluidic paper-based analytical device for trace glyphosate detection

Given the significant and potential fatal implications of glyphosate (GLY) residues on human health and the integrity of ecosystems, their presence has garnered substantial global concern and scrutiny. Herein, we introduced a pioneering colorimetric sensing platform, the first of its kind, based on ternary metal-organic frameworks (ZnCo-ZIFs@MIL-101(Fe)). This innovative platform enabled ultra-sensitive, affordable, portable and rapid on-site detection of GLY. This platform achieved a wider linear range for GLY of 0.02–40 μg/mL with an exhibiting remarkable detection limit of 1 ng/mL, which was attributed to the electronic hybridization of the Fe3+, Co2+, and Zn2+ metal centers of ZnCo-ZIFs@MIL-101(Fe), significantly enhancing the composite's catalytic performance. The assay was successfully employed to detect GLY in food and herb samples. Moreover, to meet the demand of in-field detection for GLY, a smartphone detection method based on ZnCo-ZIFs@MIL-101(Fe) with visual, intelligent, and portable features was fabricated. This detection concentration range of GLY was 0–1 μg/mL, and the limit of smartphone detection was 23 ng/mL. Furthermore, this sensor seamlessly integrated with smartphones and paper-based microfluidic chips (μPADs), which constructed a portable test strips-smartphone sensing platform for facilitating real-time and on-site visual quantitative detection of GLY. The detection concentration range was 0–1 μg/mL, and the limit was calculated as low as 75 ng/mL. The assay was highly adaptable in practical applications. In summary, our study paved a novel pathway for the design and utilization of multi-metal MOF nanozymes in on-site pesticide monitoring.

A novel machine-learning aided platform for rapid detection of urine ESBLs and carbapenemases: URECA-LAMP.

Pathogenic gram-negative bacteria frequently carry genes encoding extended-spectrum beta-lactamases (ESBL) and/or carbapenemases. Of great concern are carbapenem resistant Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. Despite the need for rapid AMR diagnostics globally, current molecular detection methods often require expensive equipment and trained personnel. Here, we present a novel machine-learning-aided platform for the rapid detection of ESBLs and carbapenemases using Loop-mediated isothermal Amplification (LAMP). The platform consists of (i) an affordable device for sample lysis, LAMP amplification, and visual fluorometric detection; (ii) a LAMP screening panel to detect the most common ESBL and carbapenemase genes; and (iii) a smartphone application for automated interpretation of results. Validation studies on clinical isolates and urine samples demonstrated percent positive and negative agreements above 95% for all targets. Accuracy, precision, and recall values of the machine learning model deployed in the smartphone application were all above 92%. Providing a simplified workflow, minimal operation training, and results in less than an hour, this study demonstrated the platform's feasibility for near-patient testing in resource-limited settings.IMPORTANCEExtended-spectrum beta-lactamases (ESBL) and carbapenemases confer resistance to third-generation cephalosporins and carbapenems in pathogenic Gram-negative bacteria such as Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. Conventional antimicrobial susceptibility testing is based on phenotypic methods, and results can take several days to be obtained. Current genotypic detection methods can be rapid but require expensive equipment and trained personnel. In this study, we present a novel machine learning-aided platform for the rapid detection of ESBLs and carbapenemases using Loop-mediated isothermal Amplification (LAMP). The validation of the platform demonstrated percent positive and negative agreements above 95% for all targets. The newly developed platform provided a simplified workflow, minimal technical training, and results in less than an hour. This study demonstrated the platform's feasibility for rapid testing of ESBL and carbapenemases in bacteria and urine specimens.

Photoinduced Zn-Air Battery-Assisted Self-Powered Sensor Utilizing Cobalt and Sulfur Co-Doped Carbon Nitride for Portable Detection Device.

Most self-powered electrochemical sensors (SPESs) are limited by low open circuit voltage and power density, leading to a narrow detection range and low sensitivity. Herein, a photoinduced Zn-air battery-assisted SPES (ZAB-SPES) is proposed based on cobalt and sulfur co-doped carbon nitride with the cyano group (Co, S-CN). The cyano functionalization remarkably enhances visible light utilization, and the cyano moiety acts as an electron-withdrawing group to promote electron enrichment. Co and S co-doping can create a p-n homojunction within carbon nitride, enabling the efficient migration and separation of carriers, thereby significantly improving the performance of the oxygen reduction reaction. The synergistic effects endow Co, S-CN photocathode with an open circuit voltage of 1.85V and the maximum power density of 43.5µW cm-2 in the photoinduced ZAB. Employing heavy metal copper ions as the target model, the photoinduced ZAB-SPES exhibited dual-mode and sensitive detection. Furthermore, a portable detection device based on the photoinduced ZAB-SPES is designed and exhibits high linearity in the range of 5 ~ 600nM with a detection limit of 1.7nM. This work offers a portable detection method based on the photoinduced ZAB-SPES in the aquatic environment.

Clinical Utility of Deep Learning Assistance for Detecting Various Abnormal Findings in Color Retinal Fundus Images: A Reader Study.

To evaluate the clinical usefulness of a deep learning-based detection device for multiple abnormal findings on retinal fundus photographs for readers with varying expertise. Fourteen ophthalmologists (six residents, eight specialists) assessed 399 fundus images with respect to 12 major ophthalmologic findings, with or without the assistance of a deep learning algorithm, in two separate reading sessions. Sensitivity, specificity, and reading time per image were compared. With algorithmic assistance, readers significantly improved in sensitivity for all 12 findings (P < 0.05) but tended to be less specific (P < 0.05) for hemorrhage, drusen, membrane, and vascular abnormality, more profoundly so in residents. Sensitivity without algorithmic assistance was significantly lower in residents (23.1%∼75.8%) compared to specialists (55.1%∼97.1%) in nine findings, but it improved to similar levels with algorithmic assistance (67.8%∼99.4% in residents, 83.2%∼99.5% in specialists) with only hemorrhage remaining statistically significantly lower. Variances in sensitivity were significantly reduced for all findings. Reading time per image decreased in images with fewer than three findings per image, more profoundly in residents. When simulated based on images acquired from a health screening center, average reading time was estimated to be reduced by 25.9% (from 16.4 seconds to 12.1 seconds per image) for residents, and by 2.0% (from 9.6 seconds to 9.4 seconds) for specialists. Deep learning-based computer-assisted detection devices increase sensitivity, reduce inter-reader variance in sensitivity, and reduce reading time in less complicated images. This study evaluated the influence that algorithmic assistance in detecting abnormal findings on retinal fundus photographs has on clinicians, possibly predicting its influence on clinical application.

Application of Path Planning and Tracking Control Technology in Mower Robots

Path planning and tracking is the most basic technology for mowing robots, among which the performance of algorithms has a great impact on their intelligence and efficiency. Based on the research of relevant references on mower robots, it mainly focuses on complete coverage path planning, path tracking control, and obstacle avoidance path planning. In complete coverage path planning, three methods were introduced, including simple complete coverage planning, optimal complete coverage planning, and hybrid complete coverage planning. In the path tracking control section, the control methods are divided into three types based on whether the control method depends on the robot model and the type of model, namely model free control method, kinematic model-based control method, and dynamic model-based control method. In obstacle avoidance path planning, we introduce the environment detection device and obstacle avoidance planning algorithm. Then the relevant research papers are analyzed in classification, comparing the research and validation methods adopted by the researchers in the form of charts. Finally, we pointed out the limitations of path planning technology in the application of mower robots. Meanwhile, future development trends are predicted.

A dual-mode strategy for early detection of sugarcane pokkah boeng disease pathogen: A portable sensing device based on Cross-N DNA framework and MoS2@GDY

Sucrose, a common sugar primarily derived from sugarcane, is a crucial national strategic resource. However, its yield is significantly affected by various serious diseases, with pokkah boeng disease being one of the most damaging. Therefore, developing a sensitive method for the accurate detection of the pokkah boeng disease pathogen is crucial for ensuring the safety of sugar. This work presents a portable dual-modal detection device, assisted by a smartphone, which is based on MoS2@GDY, Mn3O4@Au nanomenzyme, cross-N DNA framework and Exo III exonuclease-assisted CHA signal amplification technology. The cross-N DNA framework provides many binding sites and is not restricted by AuNPs scattering positions, enhancing the signal output strength of the sensor. Additionally, the detection system incorporates a high-power-density capacitor to further amplify the electrochemical detection signal, increasing sensitivity by 9.1 times. Moreover, the use of electrochemical and colorimetric dual-mode detection effectively avoids mutual interference, reducing the likelihood of false positives from a single signal. Under optimized conditions, the proposed method has a linear range of 0.0001–10,000 pM, and with a detection limit of 6.1 aM (S/N=3). This high-sensitivity, high-reliability portable sensing method shows significant potential for the early detection and real-time on-site monitoring of the pokkah boeng disease pathogen.

A novel double-door-opening sensor for visual determination of cardiac troponin I based on DNA hydrogel and bimetallic nanozyme

Cardiac troponin I (cTnI), as a cardiac biomarker, holds significant importance in the diagnosis of acute myocardial infarction. However, the current detection methods mostly require specialized personnel and large analytical instruments, making it difficult to achieve convenient and on-site testing. This situation leads to delayed disease diagnosis and treatment, that increases patient suffering, and reduces the cure rate. This strategy presents the development of a portable visual DNA hydrogel colorimetric sensing platform based on a smartphone. Utilizing dual-mode detection with ultraviolet signals and solution colorimetry, the platform achieves ultra-sensitive and real-time detection of cTnI. Furthermore, optimization of detection conditions, such as the amount of polyacrylamide, reaction time, aptamer concentration, encapsulation of the nanozyme, incubation time, and reaction temperature, were performed based on this platform. The proposed ultraviolet and visual detection platforms exhibited good linear relationships with the signal within the ranges of 0.003 ng mL−1 to 10.00 ng mL−1 and 0.01 ng mL−1 to 7.00 ng mL−1, with detection limits of 2.57 pg mL−1 and 0.013 pg mL−1, respectively. Additionally, utilizing 3D printing technology, a portable detection device was designed and employed for the detection of cTnI concentrations in human serum samples. Whatever in the initial and spiked samples, the results showed high sensitivities. The sensitivity and convenience of the sensor in detecting cTnI make it promising for home testing of patients, with broad market prospects.