Rapid Detection System Research Articles

Rapid detection of apple latent spherical virus infecting Angelica sinensis by gold immunochromatography reverse transcription loop-mediated isothermal amplification assay

Apple latent spherical virus (ALSV; genus: Cheravirus, family: Secoviridae) is capable of infecting Angelica sinensis under natural conditions and causing symptoms of greenish discoloration and mottling, affecting plant growth and causing a reduction in root quality and yield. Virus detection of ALSV is an urgent need for the continued development of angelica industry. Consequently, it is necessary to develop simple, sensitive, and reliable ALSV detection methods. We describe the preparation of polyclonal antibodies with high titer and high specificity using recombinant ALSV coat protein (CP) as the antigen. Using these antibodies, we established and optimized a rapid detection system using colloidal gold immunochromatography assay (GICA) to detect ALSV. A real-time reverse transcription loop-mediated isothermal amplification (RT-LAMP) system with a minimum detection line of 2.72 × 103copys/μl was also developed to detect ALSV. This assay was further enhanced using a combination GICA-RT-LAMP assay. This GICA assay successfully detected ALSV in infected plants without cross reactivity recorded from three other plant viruses. The sensitivity of GICA was the same as that of GICA-RT-PCR, whereas the sensitivity of GICA-RT-LAMP was at least 10-fold higher than that of GICA and GICA-RT-PCR. These methods can detect and identify ALSV under field conditions and accurately measure virus concentration in the laboratory.

An aM-level sensitive cascade CRISPR-Dx system (ASCas) for rapid detection of RNA without pre-amplification

The CRISPR/Cas system is known as one of the directions of the next generation of mainstream molecular diagnostic technology. However, most current CRISPR/Cas molecular diagnostics still rely on the pre-amplification of nucleic acid due to the limited sensitivity of CRISPR/Cas alone, which has no significant advantage over commercial Taqman-PCR and TwistAmp® Exo kits. Herein, we report an aM-level sensitive cascade CRISPR-Dx system (ASCas) that eliminates nucleic acid pre-amplification, thus avoiding aerosol contamination and greatly reducing the testing environment and personnel skill requirements for molecular diagnostics. Most importantly, the Cas13a nucleases with high sensitivity and trans-cleavage efficiency can rapidly cleaved RNA bubbles on the hybridized cascade probe at low concentration target RNA detection, which results in the destruction of the cascade probe and releases a large amount of trigger DNA for further signal amplification of secondary Cas12a reactions. Therefore, the ASCas system achieves amplification-free, ultra-sensitivity (1 aM), and ultra-fast (20 min) RNA detection. In addition, the ASCas system replaces the complicated screening process of primers and probes with the programmed Cas13a-crRNA design so that a suitable detection system can be constructed more quickly and straightforwardly for the mutation-prone SARS-CoV-2 virus.

Sensitive Detection of BVDV Using Gold Nanoparticle-Modified Few-Layer Black Phosphorus with Affinity Peptide-Based Electrochemical Sensor

The lethality of the bovine viral diarrhea virus (BVDV) in cattle involves inapparent infection and various, typically subclinical, syndromes. Cattle of all ages are vulnerable to infection with the virus. It also causes considerable economic losses, primarily due to reduced reproductive performance. In the absence of treatment that can completely cure infected animals, detection of BVDV relies on highly sensitive and selective diagnosis methods. In this study, an electrochemical detection system was developed as a useful and sensitive system for the detection of BVDV to suggest the direction of diagnostic technology through the development of conductive nanoparticle synthesis. As a countermeasure, a more sensitive and rapid BVDV detection system was developed using the synthesis of electroconductive nanomaterials black phosphorus (BP) and gold nanoparticle (AuNP). To increase the conductivity effect, AuNP was synthesized on the BP surface, and the stability of BP was improved by using dopamine self-polymerization. Moreover, its characterizations, electrical conductivity, selectivity, and sensitivity toward BVDV also have been investigated. The BP@AuNP-peptide-based BVDV electrochemical sensor exhibited a low detection limit of 0.59 copies mL-1 with high selectivity and long-term stability (retaining 95% of its initial performance over 30 days).

Microbial sensor system for rapid kanamycin detection in conducting solutions

Use of large numbers of antibacterial drugs leads to increased pollution of the environment, especially water resources. Therefore, it is important to devise methods for the rapid detection and determination of antibiotics in aqueous solutions. We describe a microbial sensor system that is based on a resonator with a lateral electric field and is intended for the rapid detection and determination of kanamycin in aqueous solutions. Kanamycin was selectively determined in a solution with a conductivity of 1300 μS/cm. The lower detection limit was 0.5 μg/mL, and the analysis time was less than 5 min. The change in the electric impedance modulus of the sensor after kanamycin action on the bacteria served as an analytical signal. This sensor system is promising, because it can be used repeatedly and does not require immobilization of the analysis components on the sensor surface.

An efficient edge/cloud medical system for rapid detection of level of consciousness in emergency medicine based on explainable machine learning models

Emergency medicine (EM) is one of the attractive research fields in which researchers investigate their efforts to diagnose and treat unforeseen illnesses or injuries. There are many tests and observations are involved in EM. Detection of the level of consciousness is one of these observations, which can be detected using several methods. Among these methods, the automatic estimation of the Glasgow coma scale (GCS) is studied in this paper. The GCS is a medical score used to describe a patient’s level of consciousness. This type of scoring system requires medical examination that may not be available with the shortage of the medical expert. Therefore, the automatic medical calculation for a patient’s level of consciousness is highly needed. Artificial intelligence has been deployed in several applications and appears to have a high performance regarding providing automatic solutions. The main objective of this work is to introduce the edge/cloud system to improve the efficiency of the consciousness measurement through efficient local data processing. Moreover, an efficient machine learning (ML) model to predict the level of consciousness of a certain patient based on the patient’s demographic, vital signs, and laboratory tests is proposed, as well as maintaining the explainability issue using Shapley additive explanations (SHAP) that provides natural language explanation in a form that helps the medical expert to understand the final prediction. The developed ML model is validated using vital signs and laboratory tests extracted from the MIMIC III dataset, and it achieves superior performance (mean absolute error (MAE) = 0.269, mean square error (MSE) = 0.625, R2 score = 0.964). The resulting model is accurate, medically intuitive, and trustworthy.

Establishment and preliminary evaluation of a fluorescent recombinase-aided amplification/CRISPR-Cas12a system for rapid detection of Plasmodium falciparum

To establish a fluorescent assay for rapid detection of Plasmodium falciparum based on recombinaseaided amplification (RAA) and CRISPR-Cas12a system,and to preliminarily evaluate the diagnostic efficiency of this system. The 18S ribosomal RNA (rRNA) gene of P. falciparum was selected as the target sequence, and three pairs of RAA primers and CRISPR-derived RNA (crRNA) were designed and synthesized. The optimal combination of RAA primers and crRNA was screened and the reaction conditions of the system were optimized to create a fluorescent RAA/CRISPR-Cas12a system. The plasmid containing 18S rRNA gene of the P. falciparum strain 3D7 was generated, and diluted into concentrations of 1 000, 100, 10, 1 copy/μL for the fluorescent RAA/CRISPR-Cas12a assay, and its sensitivity was evaluated. The genomic DNA from P. vivax, P. malariae, P. ovum, hepatitis B virus, human immunodeficiency virus and Treponema pallidum was employed as templates for the fluorescent RAA/CRISPR-Cas12a assay, and its specificity was evaluated. Fifty malaria clinical samples were subjected to the fluorescent RAA/CRISPR-Cas12a assay and nested PCR assay, and the consistency between two assays was compared. In addition, P. falciparum strain 3D7 was cultured in vitro. Then, the culture was diluted into blood samples with parasite densities of 1 000, 500, 200, 50, 10 parasites/μL with healthy volunteers' O-positive red blood cells for the RAA/CRISPR-Cas12a assay, and the detection efficiency was tested. The Pf-F3/Pf-R3/crRNA2 combination, 2.5 μL as the addition amount of B buffer, 40 min as the RAA reaction time, 37 °C as the reaction temperature of the CRISPR-Cas12a system were employed to establish the fluorescent RAA/CRISPR-Cas12a system. Such a system was effective to detect the plasmid containing 18S rRNA gene of the P. falciparum strain 3D7 at a concentration of 1 copy/μL, and presented fluorescent signals for detection of P. falciparum, but failed to detect P. ovum, P. malariae, P. vivax, T. pallidum, hepatitis B virus or human immunodeficiency virus. The fluorescent RAA/CRISPR-Cas12a system and nested PCR assay showed completely consistent results for detection of 50 malaria clinical samples (kappa = 1.0, P < 0.001). Following 6-day in vitro culture of the P. falciparum strain 3D7, 10 mL cultures were generated and the fluorescent RAA/CRISPR-Cas12a system showed the minimal detection limit of 50 parasites/μL. The fluorescent RAA/CRISPR-Cas12a system is rapid, sensitive and specific for detection of P. falciparum, which shows promising value for rapid detection and risk monitoring of P. falciparum.

Detection of E.coli 23S rRNA by electrocatalytic “off-on” DNA beacon assay with femtomolar sensitivity

Prevention of food spoilage, environmental bio-contamination, and pathogenic infections requires rapid and sensitive bacterial detection systems. Among microbial communities, the bacterial strain of Escherichia coli is most widespread, with pathogenic and non-pathogenic strains being biomarkers of bacterial contamination. Here, we have developed a fM-sensitive, simple, and robust electrocatalytically-amplified assay facilitating specific detection of E.coli 23S ribosomal rRNA, in the total RNA sample, after its site-specific cleavage by RNase H enzyme. Gold screen-printed electrodes (SPE) were electrochemically pre-treated to be productively modified with a methylene-blue (MB) – labelled hairpin DNA probes, which hybridization with the E. coli-specific DNA placed MB in the top region of the DNA duplex. The formed duplex acted as an electrical wire, mediating electron transfer from the gold electrode to the DNA-intercalated MB, and further to ferricyanide in solution, enabling its electrocatalytic reduction otherwise impeded on the hairpin-modified SPEs. The assay facilitated 20 min 1 fM detection of both synthetic E. coli DNA and 23S rRNA isolated from E.coli (equivalent to 15 CFU mL−1), and can be extended to fM analysis of nucleic acids isolated from any other bacteria.

Highly sensitive and quantitative fluorescent strip immunosensor based on an independent control system for rapid detection of tetrodotoxin in shellfish

Tetrodotoxin (TTX) in shellfish poses a serious public health threat, and there is thus an urgent need to develop an accurate approach for detecting TTX. In this study, a new method of rapid detection using an immune strip sensor achieved on-site detection of TTX in shellfish. Time-resolved fluorescent microspheres were used as fluorescent labels that were conjugated with anti-TTX antibody as a detection probe. Meanwhile, a streptavidin-biotin system was introduced as an independent control system to make the fluorescence intensity of the control line more stable. The developed immune strip sensor could achieve rapid detection of TTX within 20 min; the detection limit was as low as 0.05 ng/mL with the linear range of 0.5–40 ng/mL, and the acceptable recovery was 97–102%. The reliability of this method for real sample detection was verified by the comparison to the results of ultra-performance liquid chromatography/tandem mass spectrometry. The proposed method provides an effective approach for instant screening and detection of TTX in shellfish samples.

Rapid electrochemical biosensor composed of DNA probe/iridium nanoparticle bilayer for Aphanizomenon flos-aquae detection in fresh water

Toxic cyanobacteria pose a serious threat to aquatic ecosystems and require adequate detection and control systems. Aphanizomenon flos-aquae is a harmful cyanobacterium that produces the toxicant saxitoxin. Therefore, it is necessary to detect the presence of A. flos-aquae in lakes and rivers. We proposed a rapid electrochemical biosensor composed of DNA primer/iridium nanoparticles (IrNP) bilyer for the detection of A. flos-aquae in freshwater. The extracted A. flos-aquae gene (rbcL-rbcX) is used as a target, and it was fixed to the electrode using a 5'-thiolated DNA primer (capture probe). Then, Avidin@IrNPs complex for amplification of electrical signals was bound to the target through a 3'-biotinylated DNA primer (detection probe). To rapidly detect the target, an alternating current electrothermal flow technique was introduced in the detection step, which could reduce the detection time to within 20 min. To confirm the biosensor fabrication, atomic force microscopy was used to investigate the surface morphology. To evaluate the biosensor performance, cyclic voltammetry and electrochemical impedance spectroscopy were used. The target gene was detected at a concentration of 9.99 pg/mL in tap water, and the detection range was 0.1 ng/mL to 103 ng/mL with high selectivity. Based on the combined system, we employed A. flos-aquae in tap water. This rapid cyanobacteria detection system is a powerful tool for CyanoHABs in the field.

Microfluidic-LAMP chip for the point-of-care detection of gene-deleted and wild-type African swine fever viruses and other four swine pathogens.

Different pathogens causing mixed infection are now threatening the pig industry in the context of the African Swine Fever (ASF) circulating especially in China, and it is crucial to achieving the early diagnosis of these pathogens for disease control and prevention. Here we report the development of a rapid, portable, sensitive, high-throughput, and accurate microfluidic-LAMP chip detection system for simultaneous detection and differentiation of gene-deleted type and wild-type African swine fever virus (ASFV), pseudorabie virus (PRV), porcine parvovirus (PPV), porcine circovirus type 2 (PCV2), and porcine reproductive and respiratory syndrome (PRRSV). The newly developed system was shown to be sensitive with detection limits of 101 copies/μl for ASFV-MGF505-2R/P72, PPV, and PCV2, 102 copies/μl for ASFV-CD2v, PRV, and PRRSV. The system was highly specific (100%) and stable (C.V.s < 5%) in its ability to detect different pathogens. A total 213 clinical samples and 15 ASFV nucleic acid samples were collected to assess the performance of the detection system, showing highly effective diagnosis. Altogether, the developed microfluidic-LAMP chip system provides a rapid, sensitive, high-throughput and portable diagnostic tool for the accurate detection of multiple swine pathogens.

Highly Pathogenic Avian Influenza H5N8 Outbreak in Backyard Chickens in Serbia

In winter 2016/2017, the highly pathogenic avian influenza virus H5N8 was detected in backyard poultry in Serbia for the first time. The second HPAI outbreak case in backyard poultry was reported in 2022, caused by subtype H5N1. This is the first study that documents the laboratory identification and pathology associated with highly pathogenic avian influenza in poultry in Serbia during the first and second introduction waves. In both cases, the diagnosis was based on real-time reverse transcriptase PCR. The most common observed lesions included subepicardial hemorrhages, congestion and hemorrhages in the lungs, and petechial hemorrhages in coelomic and epicardial adipose tissue. Histologically, the observed lesions were mostly nonpurulent encephalitis accompanied by encephalomalacia, multifocal necrosis in the spleen, pancreas, and kidneys, pulmonary congestion, and myocardial and pulmonary hemorrhages. In H5N8-infected chickens, immunohistochemical examination revealed strong positive IHC staining in the brain and lungs. Following these outbreaks, strict control measures were implemented on farms and backyard holdings to prevent the occurrence and spread of the disease. Extensive surveillance of birds for avian influenza virus did not detect any additional cases in poultry. These outbreaks highlight the importance of a rapid detection and response system in order to quickly suppress outbreaks.

Custom-Developed Reflection-Transmission Integrated Vision System for Rapid Detection of Huanglongbing Based on the Features of Blotchy Mottled Texture and Starch Accumulation in Leaves.

Huanglongbing (HLB) is a highly contagious and devastating citrus disease that causes huge economic losses to the citrus industry. Because it cannot be cured, timely detection of the HLB infection status of plants and removal of diseased trees are effective ways to reduce losses. However, complex HLB symptoms, such as single HLB-symptomatic or zinc deficiency + HLB-positive, cannot be identified by a single reflection imaging method at present. In this study, a vision system with an integrated reflection-transmission image acquisition module, human-computer interaction module, and power supply module was developed for rapid HLB detection in the field. In reflection imaging mode, 660 nm polarized light was used as the illumination source to enhance the contrast of the HLB symptoms in the images based on the differences in the absorption of narrow-band light by the components within the leaves. In transmission imaging mode, polarization images were obtained in four directions, and the polarization angle images were calculated using the Stokes vector to detect the optical activity of starch. A step-by-step classification model with four steps was used for the identification of six classes of samples (healthy, HLB-symptomatic, zinc deficiency, zinc deficiency + HLB-positive, magnesium deficiency, and boron deficiency). The results showed that the model had an accuracy of 96.92% for the full category of samples and 98.08% for the identification of multiple types of HLB (HLB-symptomatic and zinc deficiency + HLB-positive). In addition, the classification model had good recognition of zinc deficiency and zinc deficiency + HLB-positive samples, at 92.86%.

Fast and Sensitive Detection of SARS-CoV-2 Nucleic Acid Using a Rapid Detection System Free of RNA Extraction.

To establish and evaluate the analytical and clinical performance of the Flash20 SARS-CoV-2 nucleic acid rapid detection system free of RNA extraction. The limit of detection (LoD) was determined using a negative nasopharyngeal swab matrix spiked with different concentrations of SARS-CoV-2 virus; a total of 734,337 reference sequences of viral genomes from GenBank were used for the in-silico analysis to assess the inclusivity of the assay. The specificity of the system was evaluated by testing 27 medically relevant organisms. A total of 115 clinical specimens were collected and tested on the Flash20 SARS-CoV-2 detection system and with an FDA-approved comparator test to assess the clinical performance of the system. The LoD of the Flash20 SARS-CoV-2 detection system is 250 copies/mL with a positive rate ≥90% (n = 20); alignments results showed that over 99% identity of the primer and probe of the Flash20 SARS-CoV-2 nucleic acid rapid detection system to the available SARS-CoV-2 sequences; the omicron samples tested 100% positive. None of the 27 organisms showed cross-reactivity with the Flash20 SARS-CoV-2 nucleic acid rapid detection system. Among all the 215 clinical samples, the Flash20 SARS-CoV-2 nucleic acid rapid detection system exhibits a high sensitivity of 99.24% (131/132) and 100% (83/83) specificity. The nucleic acid rapid detection system provides sensitive and accurate detection of SARS-CoV-2 free of RNA extraction. The high sensitivity and short time to results of approximately 35 minutes may impact earlier infection control and disease management.

Accuracy of an antigen-detecting SARS-CoV-2 assay with self- and provider-collected specimens interpreted visually and with BD Veritor™ Plus analyzer

BackgroundSARS-CoV-2 rapid antigen tests (RATs) are in high demand for reducing the spread of SARS-CoV-2. Reduced involvement from health care professionals (HCPs) for collection and interpretation could significantly foster the wide-spread implementation of RATs, but data evaluating RATs, when used by lay people, is limited. ObjectiveTo valuate agreement between BD Veritor test results for self- and HCP-collected specimens, and visually- and analyzer-interpreted results. MethodsIndividuals with onset of COVID-19 symptoms within five days of enrollment had three nasal swabs collected; one self-collected and the other two HCP-collected. One HCP-collected swab was stored for future testing while the order of the other two (self and HCP) was randomized before testing. with the BD Veritor System for Rapid Detection of SARS-CoV-2. Results were first assessed visually, followed by interpretation with the analyzer. ResultsWhen self-collection was compared to HCP collection for SARS-CoV-2 detection, interpretation by analyzer resulted in positive percent agreement (PPA) of 94.7% (95% CI 82.7, 98.5) and negative percent agreement (NPA) of 99.0% (95% CI 97.5, 99.6). When visual interpretation was compared to analyzer-read results, collection by HCPs had a PPA of 97.4% (95% CI 86.5, 99.5) and NPA of 99.8% (95% CI 98.6, 100.0) while self-collection resulted in PPA of 94.9% (95% CI 83.1, 98.6) and NPA of 99.8% (95% CI 98.6, 100). ConclusionsSimilar PPA and NPA were observed for self- and HCP-collected specimens as well as visually- and analyzer-interpreted tests. The equivalence in performance supports the use of expanded collection and testing methods.

Automated sample-to-answer system for rapid and accurate diagnosis of emerging infectious diseases

Automated sample-to-answer systems that promptly diagnose emerging infectious diseases, such as zoonotic diseases, are crucial to preventing the spread of infectious diseases and future global pandemics. However, automated, rapid, and sensitive diagnostic testing without professionals and sample capacity and type limitations remains unmet needs. Here, we developed an automated sample-to-answer diagnostic system for rapid and accurate detection of emerging infectious diseases from clinical specimens. This integrated system consists of a microfluidic platform for sample preparation and a bio-optical sensor for nucleic acid (NA) amplification/detection. The microfluidic platform concentrates pathogens and NAs in a large sample volume using adipic acid dihydrazide and a low-cost disposable chip. The bio-optical sensor allows label-free, isothermal one-step NA amplification/detection using a ball-lensed optical fiber-based silicon micro-ring resonator sensor. The system is integrated with software to automate testing and perform analysis rapidly and simply; it can distinguish infection status within 80 min. The detection limit of the system (0.96 × 101 PFU) is 10 times more sensitive than conventional methods (0.96 × 102 PFU). Furthermore, we validated the clinical utility of this automated system in various clinical specimens from emerging infectious diseases, including 20 plasma samples for Q fever and 13 (11 nasopharyngeal swabs and 2 saliva) samples for COVID-19. The system showed 100% sensitivity and specificity for detecting 33 samples of emerging infectious diseases, such as Q fever, other febrile diseases, COVID-19, human coronavirus OC43, influenza A, and respiratory syncytial virus A. Therefore, we envision that this automated sample-to-answer diagnostic system will show high potential for diagnosing emerging infectious diseases in various clinical applications.

Establishment and Application of a Multiplex PCR Assay for Detection of Sclerotium rolfsii, Lasiodiplodia theobromae, and Fusarium oxysporum in Peanut.

Southern blight, stem rot, and root rot are serious soil-borne fungal diseases of peanut, which are caused by Sclerotium rolfsii, Lasiodiplodia theobromae, and Fusarium oxysporum, respectively. These diseases are difficult to be diagnosed in early stage of infection, causing the optimal treatment period was often missed. Therefore, establishing a rapid detection system is of great significance for early prevention of peanut soil-borne fungal diseases. Here, we have invented a multiplex PCR detection system to detect fungal pathogens of peanut southern blight, stem rot, and root rot at the same time. The quarantine fungal pathogen primer pairs were amplified to the specific number of base pairs in each of the following fungal pathogens: 1005-bp (F. oxysporum), 238-bp (L. theobromae), and 638-bp (S. rolfsii). The detection limit for the single and multiplex PCR primer sets was 1ng of template DNA under in vitro conditions. Amplification of fungi of non-target species yielded no non-specific products. The validation showed that the multiplex PCR could effectively detect single and mixed infections in field samples. Overview, this study proved that this mPCR assay was a rapid, reliable, and simple tool for the simultaneous detection of three important peanut soil-borne diseases, which facilitated prompt treatment and prevention of peanut root diseases.

Clustered Regularly Interspaced Short Palindromic Repeats-Associated Proteins13a combined with magnetic beads, chemiluminescence and reverse transcription-recombinase aided amplification for detection of avian influenza a (H7N9) virus.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and Clustered Regularly Interspaced Short Palindromic Repeats-Associated Proteins (CRISPR-Cas) have promising prospects in the field of nucleic acid molecular diagnostics. However, Clustered Regularly Interspaced Short Palindromic Repeats-based fluorescence detection technology is mainly hindered by proteins with conjugated double bonds and autofluorescence, resulting in high fluorescence background, low sensitivity and incompatible reaction systems, which are not conducive to automatic clinical testing. Chemiluminescence (CL) detection technology has been applied mainly owing to its greatly high sensitivity, as well as low background and rapid response. Therefore, we developed a rapid, ultrasensitive and economical detection system based on Clustered Regularly Interspaced Short Palindromic Repeats-Clustered Regularly Interspaced Short Palindromic Repeats-Associated Proteins 13a combined with magnetic beads (MBs) and chemiluminescence (CL) (Cas13a-MB-CL) to detect Influenza A (H7N9), an acute respiratory tract infectious disease. The carboxyl functionalized magnetic beads (MBs-COOH) were covalently coupled with aminated RNA probe while the other end of the RNA probe was modified with biotin. Alkaline phosphatase labeled streptavidin (SA-ALP) binds with biotin to form magnetic beads composites. In presence of target RNA, the collateral cleavage activity of Cas13a was activated to degrade the RNA probes on MBs and released Alkaline phosphatase from the composites. The composites were then magnetically separated followed by addition of ALP substrate Disodium 2-chloro-5-{4-methoxyspiro [1,2-dioxetane-3,2'-(5'-chloro) tricyclo (3.3.1.13,7) decan]-4-yl}-1-phenyl phosphate (CDP-star), to generate the chemiluminescence signal. The activity of Associated Proteins 13a and presence of target RNA was quantified by measuring the chemiluminescence intensity. The proposed method accomplished the detection of H7N9 within 30min at 25°C. When combined with Reverse Transcription- Recombinase Aides Amplification (RT-RAA), the low detection limit limit of detection was as low as 19.7fM (3S/N). Our proposed MB-Associated Proteins 13a-chemiluminescence was further evaluated to test H7N9 clinical samples, showing superior sensitivity and specificity.

A point-of-care microfluidic biosensing system for rapid and ultrasensitive nucleic acid detection from clinical samples.

Rapid and ultrasensitive point-of-care RNA detection plays a critical role in the diagnosis and management of various infectious diseases. The gold-standard detection method of reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is ultrasensitive and accurate yet limited by the lengthy turnaround time (1-2 days). On the other hand, an antigen test offers rapid at-home detection (typically ~15 min) but suffers from low sensitivity and high false-negative rates. An ideal point-of-care diagnostic device would combine the merits of PCR-level sensitivity and rapid sample-to-result workflow comparable to antigen testing. However, the existing detection platforms typically possess superior sensitivity or rapid sample-to-result time, but not both. This paper reports a point-of-care microfluidic device that offers ultrasensitive yet rapid detection of viral RNA from clinical samples. The device consists of a microfluidic chip for precisely manipulating small volumes of samples, a miniaturized heater for viral lysis and ribonuclease inactivation, a Cas13a-electrochemical sensor for target preamplification-free and ultrasensitive RNA detection, and a smartphone-compatible potentiostat for data acquisition. As demonstrations, the devices achieve the detection of heat-inactivated SARS-CoV-2 samples with a limit of detection down to 10 aM within 25 minutes, which is comparable to the sensitivity of RT-PCR and rapidness of an antigen test. The platform also successfully distinguishes all nine positive unprocessed clinical SARS-CoV-2 nasopharyngeal swab samples from four negative samples within 25 minutes of sample-to-result time. Together, this device provides a point-of-care solution that can be deployed in diverse settings beyond laboratory environments for rapid and accurate detection of RNA from clinical samples. The device can potentially be expandable to detect other viral targets, such as human immunodeficiency virus self-testing and Zika virus, where rapid and ultrasensitive point-of-care detection is required.

Multiple real-time fluorescence detection system for rapid on-site nucleic acid detection

Multiple real-time fluorescence detection system for rapid on-site nucleic acid detection

CountShoots: Automatic Detection and Counting of Slash Pine New Shoots Using UAV Imagery.

The density of new shoots on pine trees is an important indicator of their growth and photosynthetic capacity. However, traditional methods to monitor new shoot density rely on manual and destructive measurements, which are labor-intensive and have led to fewer studies on new shoot density. Therefore, in this study, we present user-friendly software called CountShoots, which extracts new shoot density in an easy and convenient way using unmanned aerial vehicles based on the YOLOX and Slash Pine Shoot Counting Network (SPSC-net) models. This software mainly consists of 2 steps. Firstly, we deployed a modified YOLOX model to identify the tree species and location from complex RGB background images, which yielded a high recognition accuracy of 99.15% and 95.47%. These results showed that our model produced higher detection accuracy compared to YOLOv5, Efficientnet, and Faster-RCNN models. Secondly, we constructed an SPSC-net. This methodology is based on the CCTrans network, which outperformed DM-Count, CSR-net, and MCNN models, with the lowest mean squared error and mean absolute error results among other models (i.e., 2.18 and 1.47, respectively). To our best knowledge, our work is the first research contribution to identify tree crowns and count new shoots automatically in slash pine. Our research outcome provides a highly efficient and rapid user-interactive pine tree new shoot detection and counting system for tree breeding and genetic use purposes.