Visual Detection Method Research Articles

Rapid Visual Detection of High Nitrogen-Use Efficiency Gene OsGRF4 in Rice (Oryza sativa L.) Using Loop-Mediated Isothermal Amplification Method.

The GROWTH-REGULATING FACTOR4 (OsGRF4) allele is an important target for the development of new high nitrogen-use efficiency (NUE) rice lines that would require less fertilizers. Detection of OsGRF4 through PCR (polymerase chain reaction)-based assay is cumbersome and needs advanced laboratory skills and facilities. Hence, a method for conveniently and rapidly detecting OsGRF4 on-field is a key requirement for further research and applications. In this study, we employed cleaved amplified polymorphic sequences (CAPs) and loop-mediated isothermal amplification (LAMP) techniques to develop a convenient visual detection method for high NUE gene OsGRF4NM73 (OsGRF4 from the rice line NM73). The TC→AA mutation at 1187-1188 bp loci was selected as the target sequence for the OsGRF4NM73 allele. We further employed this method of identification in 10 rice varieties that carried the OsGRF4 gene and results revealed that one variety (NM73) carries the target OsGRF4NM73 allele, while other varieties did not possess the osgrf4 genotype. The optimal LAMP reaction using hydroxynaphthol blue (HNB), a chromogenic indicator, was carried out at 65 °C for 60 min, and the presence of OsGRF4NM73 allele was confirmed by color changes from violet to sky blue. The results of this study showed that the LAMP method can be conveniently and accurately used to detect the OsGRF4NM73 gene in rice.

Functionalized bismuth quantum dots induced fluorescence resonance energy transfer with target-driven loop-mediated isothermal amplification for visual African swine fever detection

Sensitive, simple and visual detection methods have become the focus of research because they can realize real-time detection without rely on the various detection instruments, so it is of great significance to apply them to the detection of African swine fever virus (ASFV). In this work, functionalized bismuth quantum dots (Bi QDs) were prepared by hydrothermal method and used in loop-mediated isothermal amplification (LAMP) reaction to replace the fluorescent dyes. Due to the overlap of the spectra of Bi QDs and titanium carbide (Ti3C2) nanosheet, the fluorescence resonance energy transfer (FRET) phenomenon could occurred between the Bi QDs and Ti3C2 nanosheet, and Ti3C2 nanosheets were used as energy acceptor and Bi QDs were used as fluorescence donors, which resulted in the quench of Bi QDs fluorescence signal. When the target ASFV was present, the LAMP reaction was activated due to the specific binding between the primer and the target result the separation of the Bi QDs from the surface of the Ti3C2 nanosheets, which leading to fluorescence recovery. Thus a target-driven fluorescence recovery sensing system for ASFV detection was developed. The detection results of the sensing system showed that the visual blue fluorescence recovered gradually in the range of 5.0 × 10−12-1.0 × 10−6 g/L with the detection limit of 1.5 × 10−12 g/L (2.4 copies/μL) and satisfactory detection results were obtained in the infected ASFV samples. The proposed fluorescent visual sensing detection strategy opens up a new way for sensitive, simple and visual nucleic acid detection.

Construction of Metal Organic Framework-Derived Fe-N-C Oxidase Nanozyme for Rapid and Sensitive Detection of Alkaline Phosphatase.

Alkaline phosphatase (ALP) is a phosphomonoester hydrolase and serves as a biomarker in various diseases. However, current detection methods for ALP rely on bulky instruments, extended time, and complex operations, which are particularly challenging in resource-limited regions. Herein, we synthesized a MOF-derived Fe-N-C nanozyme to create biosensors for the coulometric and visual detection of ALP. Specifically, we found the Fe-N-C nanozyme can efficiently oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to generate blue-colored tetramethyl benzidine (TMBox) without the need for H2O2. To construct the biosensor, we incorporated the ALP enzymatic catalytic reaction to inhibit the oxidation of TMB by Fe-N-C oxidase nanozyme. This biosensor showed rapid and highly sensitive detection of ALP in both buffer and clinical samples. The limit of detection (LOD) of our approach could be achieved at 3.38 U L-1, and the linear range was from 5 to 60 U L-1. Moreover, we also developed a visual detection for ALP by using a smartphone-based assay and facilitated practical and accessible point-and-care testing (POCT) in resource-limited areas. The visual detection method also achieved a similar LOD of 2.12 U L-1 and a linear range of 5-60 U L-1. Our approach presents potential applications for other biomarker detections by using ALP-based ELISA methods.

Machine-learning assisted multicolor platform for multiplex detection of antibiotics in environmental water samples

Antibiotic (AB) resistance is one of daunting challenges of our time, attributed to overuse of ABs and usage of AB-contaminated food resources. Due to their detrimental impact on human health, development of visual detection methods for multiplex sensing of ABs is a top priority. In present study, a colorimetric sensor array consisting of two types of gold nanoparticles (AuNPs) were designed for identification and determination of ABs. Design principle of the probe was based on aggregation of AuNPs in the presence of ABs at different buffer conditions. The utilization of machine learning algorithms in this design enables classification and quantification of ABs in various samples. The response profile of the array was analyzed using linear discriminant analysis algorithm for classification of ABs. This colorimetric sensor array is capable of accurate distinguishing between individual ABs and their combinations. Partial least squares regression was also applied for quantitation purposes. The obtained analytical figures of merit demonstrated the potential applicability of the developed sensor array in multiplex detection of ABs. The response profiles of the array were linearly correlated to the concentrations of ABs in a wide range of concentration with limit of detections of 0.05, 0.03, 0.04, 0.01, 0.06, 0.05 and 0.04 μg.mL–1 for azithromycin, amoxicillin, ciprofloxacin, clindamycin, cefixime, doxycycline and metronidazole respectively. The practical applicability of this method was further investigated by analysis of mixture samples of ABs and determination of ABs in river and underground water with successful verification.

A review of deep learning methods for cross-subject rapid serial visual presentation detection in World Robot Contest 2022

The rapid serial visual presentation (RSVP) paradigm has garnered considerable attention in brain–computer interface (BCI) systems. Studies have focused on using cross-subject electroencephalogram data to train cross-subject RSVP detection models. In this study, we performed a comparative analysis of the top 5 deep learning algorithms used by various teams in the event-related potential competition of the BCI Controlled Robot Contest in World Robot Contest 2022. We evaluated these algorithms on the final data set and compared their performance in cross-subject RSVP detection. The results revealed that deep learning models can achieve excellent results with appropriate training methods when applied to cross-subject detection tasks. We discussed the limitations of existing deep learning algorithms in cross-subject RSVP detection and highlighted potential research directions.

Pose visual detection method for cellphone dropping process incorporating prior information

Pose visual detection method for cellphone dropping process incorporating prior information

Visual and rapid detection of escolar (Lepidocybium flavobrunneum) using loop mediated isothermal amplification in conjunction with a specific molecular beacon probe

Species adulteration has become a main reason for the unexpected exposure to escolar, which is often related with the gastrointestinal disease called keriorrhea. Sensitive and accurate identification of escolar is required to protect consumers from commercial and health frauds. The present study established a visual and rapid method for escolar detection using LAMP (loop-mediated isothermal amplification) in conjunction with a MB (molecular beacon) probe. The visual MB-LAMP assay demonstrated high specificity and superb sensitivity (1 pg DNA) for escolar and low to 0.1 % (w/w) simulated adulteration could be detected within 25 min. Additionally, method validation on commercial products highlighted the umbrella term of white tuna for escolar on Chinese market. All these results indicated that the MB-LAMP method is a useful tool for rapid, sensitive and convenient detection of escolar and can also be used as a point-of-care molecular diagnostic technique since it does not require the expensive equipment.

Fluorescent and smartphone imaging detection of tetracycline residues based on luminescent europium ion-functionalized the regular octahedral UiO-66-NH2

Antibiotic residues cause extensive damage to food security, thus arousing serious concerns. Hence, rapid and sensitive detection of antibiotic residues is crucial to food safety. This study aimed to propose a portable, visual, intelligent and rapid method for tetracycline detection. We developed a ratiometric fluorescent sensor based on the Eu3+-functionalized regular octahedral UiO-66-NH2 material. The developed sensor could quantify tetracycline in the concentration range of 0.5–200 μM with a detection limit as low as 0.2 μM under the optimum conditions. Furthermore, the analytical results obtained using the designed sensor in the actual samples were basically consistent with those obtained using high-performance liquid chromatography. Based on these achievements, a smartphone application-integrated fluorescent testing paper was designed for facile, intelligent, and visual detection of tetracycline. The integrated portable sensor not only saved cost and time for testing but also provided a forward-looking approach to fast, sensitive detection of antibiotic residues.

A rapid visual detection method for Potato virus Y based on loop mediated isothermal amplification (LAMP)

A rapid visual detection method for Potato virus Y based on loop mediated isothermal amplification (LAMP)

Matched or moved? Asymmetry in high- and low-level visual processing of motion events

AbstractConsensus on the extent to which cross-linguistic differences affect event cognition is currently absent. This is partly because cognitive influences of language have rarely been examined within speakers of different languages in tasks that manipulate the level of visual processing. This study presents a novel combination of a high-level approach upregulating the involvement of language, namely self-paced sentence-video verification, and a low-level visual detection method without language use, namely breaking continuous flash suppression (b-CFS) (Yang et al., 2014). The results point to cross-linguistic effects on event cognition by revealing variations in visual processing patterns of manner and path by English versus Mandarin Chinese speakers. Language specificity was found on both levels of processing. An asymmetry in response speed across tasks highlights an important difference between facilitation of detecting contrasts when recruitment of verbal labels is automatic, versus facilitation of verifying correspondences when labels are overt.

Sulfonium-cation-containing aggregation-induced emission block copolymers: self-assembly, multicolor emission, and detection for DNA polyplexes

Amphiphilic aggregation-induced emission (AIE) polymers have emerged as highly attractive materials that exhibit the synergistic effect of functional polymeric self-assemblies with AIE luminogens. In this study, we design and synthesize block copolymers containing sulfonium cations and a hydrophobic tetraphenylethene (TPE) unit. These copolymers exhibit distinct self-assembly behaviors with AIE, polyplex formation with DNA, and tunable color emissions. Amphiphilic block copolymer PMTEAMe+Cl--b-PATPE, consisting of 4-(1,2,2-triphenylvinyl)phenyl acrylate (ATPE) and cationized 2-(methylthio)ethyl acrylate (MTEAMe+Cl-), was synthesized via reversible addition–fragmentation chain transfer polymerization, followed by cationization. Self-assembled structures containing TPE-aggregated cores and cationic PMTEAMe+Cl- shells and their emission behaviors were investigated. By introducing charged fluorescent dyes (Rose Bengal and Rhodamine B) into aqueous solutions of amphiphilic PMTEAMe+Cl--b-PATPE, we observed a shift in the emission color from blue to orange/red, which was attributed to the electrostatic interactions and fluorescence resonance energy transfer between the dyes and the copolymers. The emission color and intensity were also governed by polyplex formation between the negatively charged DNA and the positively charged sulfonium segments in the shell, depending on the charged states of the dyes. This system provides a method for efficient visual detection of DNA polyplex formation using multicolor fluorescent coding.

Rapid Visual LAMP Method for Detection of Genetically Modified Organisms.

We developed a novel loop-mediated isothermal amplification (LAMP) method using DNA captured on polyacrylamide microparticles (PAMMPs) as templates (PAMMPs@DNA-LAMP) for rapid qualitative detection of genetically modified organisms (GMOs). Here, DNA was extracted by a fast and cost-effective method using PAMMPs. Four LAMP primers were designed for the PAMMPs@DNA-LAMP method to detect the cauliflower mosaic virus 35S (CaMV35S) promotor in GMOs. We thus developed this method for rapid extraction of DNA (5-10 min) and fast amplification of DNA within ∼30 min at a constant temperature of 63 °C. Moreover, the DNA captured by PAMMPs (PAMMPs@DNA) could be effectively detected by both conventional and quantitative PCR (qPCR) and LAMP. The PAMMPs@DNA-LAMP method was validated with high specificity, sensitivity, and performance for practical sample analysis. This assay detected 0.01% target sequences, which had a high specificity like qPCR and better than the conventional PCR (cPCR). Furthermore, PAMMPs@DNA-LAMP was successfully used to extract and detect DNA from food samples of the major crops (soybean, maize, rice, etc.). In summary, a novel PAMMPs@DNA-LAMP assay has been developed, which has higher sensitivity and spends less time than the cPCR detection using the conventional DNA extracted process. This method offers a novel approach for rapid detection of GMOs in the field.

Visual Anomaly Detection via Partition Memory Bank Module and Error Estimation

Reconstruction method based on the memory module for visual anomaly detection attempts to narrow the reconstruction error for normal samples while enlarging it for anomalous samples. Unfortunately, the existing memory module is not fully applicable to the anomaly detection task, and the reconstruction error of the anomaly samples remains small. Towards this end, this work proposes a new unsupervised visual anomaly detection method to jointly learn effective normal features and eliminate unfavorable reconstruction errors. Specifically, a novel Partition Memory Bank (PMB) module is proposed to effectively learn and store detailed features with semantic integrity of normal samples. It develops a new partition mechanism and a unique query generation method to preserve the context information and then improves the learning ability of the memory module. The proposed PMB and the skip connection are alternatively explored to make the reconstruction of abnormal samples worse. To obtain more precise anomaly localization results and solve the problem of cumulative reconstruction error, a novel Histogram Error Estimation module is proposed to adaptively eliminate the unfavorable errors by the histogram of the difference image. It improves the anomaly localization performance without increasing the cost. To evaluate the effectiveness of the proposed method for anomaly detection and localization, extensive experiments are conducted on three widely-used anomaly detection datasets. The encouraging performance of the proposed method compared to the recent approaches based on the memory module demonstrates its superiority.

A novel Cu(II)-assisted peptide fluorescent probe for highly sensitive detection of glyphosate in real samples: real application in test strips and smartphone.

Glyphosate (Glyp) is an organophosphorus herbicide, and its abuse causes potential harm to the environment and human health. Thus, the development of simple and portable methods for rapid and visual detection of glyphosate is of great importance. Herein, we successfully developed a new fluorescent probe L with dansyl fluorophore as a fluorescent dye and tetrapeptide (Ala-Ser-Arg-His-NH2) as a recognition group. According to the design, L exhibited a specific fluorescence quenching response to Cu2+ and formed an L-Cu2+ ensemble with a molecular ratio of 2:1, demonstrating a limit of detection (LOD) as low as 12.04nM. Interestingly, the L-Cu2+ ensemble as a relay response probe exhibited a specific fluorescence "off-on" response to glyphosate without interference from other pesticides and anions based on the strong complexation of glyphosate and Cu2+. The LOD of the L-Cu2+ ensemble for glyphosate was calculated as 12.59nM. Additionally, the results of three recovery experiments with real samples showed that L has good practicability and accuracy in detecting glyphosate. Test strips were also fabricated to achieve facile detection of glyphosate to demonstrate the practical application potential of the L-Cu2+ ensemble. The L-Cu2+ ensemble was integrated with a smartphone for semi-quantification of glyphosate in a field environment under a 365nm UV lamp.

Rapid and visual field diagnosis of tomato brown rugose fruit virus using reverse transcription recombinase aided amplification (RT RAA) combined with lateral flow strips (LFS)

Tomato brown rugose fruit virus (ToBRFV) causes significant disease outbreaks in tomato and pepper production areas worldwide. A simple, fast, and visual detection method for ToBRFV is critical for controlling the viral disease. Here, a method was constructed to detect ToBRFV by combining reverse transcription recombinase assisted amplification (RT RAA) and lateral flow test strips (LFS). After selecting the primers and probe, the concentration of the modified reverse primer and magnesium acetate in the RT RAA-LFS assay were optimized. The RT RAA could amplify the target sequence in 16 min at a constant temperature of 39 °C, and the amplification products could be visualized by LFS within 5 min. Importantly, there was no cross-reaction with other viruses that can infect tomatoes, such as tobacco mosaic virus, tomato mild mottle virus, pepper mild mottle virus, tobacco mild green mosaic virus, broad bean wilt virus, pepper vein yellows virus, and chilli veinal mottle virus. Furthermore, the RT RAA-LFS assay was highly sensitive, with a detection limit of 2.1 × 101 copies/50-μL reaction. Using 138 field samples and 6 commercial seeds with suspected infection of ToBRFV, the RT RAA-LFS and RT-PCR methods gave identical results, indicating that the RT RAA-LFS method is as reliable as the standard RT-PCR method for detecting ToBRFV. Our RT RAA-LFS assay could be a valuable tool for the rapid and accurate detection of ToBRFV.

Method for detecting surface defects of underwater buildings: Binocular vision based on sinusoidal grating fringe assistance

In underwater building-surface defect detection, high pressure, cold and other underwater factors will cause harm to frogmen, sonar and other detection techniques contain limited information and accuracy is difficult to meet the demand. In view of the above disadvantages, a sine stripe-assisted visual detection method of underwater building surface-defects is proposed. By generating a fixed sine stripe by program and projected it on the surface of the underwater building, and then control a binocular CCD to acquire six frames of sinusoidal stripes with different phases in one sampling period. Experiment results show that the error of our method does not exceed 0.5 mm and the reconstruction efficiency is not less than 5 m2/s in the 3D dimensional measurement of the defects on the surface of the submerged building body.

RAMFAE: a novel unsupervised visual anomaly detection method based on autoencoder

RAMFAE: a novel unsupervised visual anomaly detection method based on autoencoder

Multiple thermocycles followed by LAMP with only two primers for ultrasensitive colorimetric viral RNA testing and tracking at single-base resolution

Rapid, accurate and high throughput measurement of infectious viruses is an urgent need to prevent viral transmission. Loop-mediated isothermal amplification (LAMP) is an attractive isothermal amplification method for nucleic acid detection, especially for point-of-care (POC) testing, but it needs at least four primers and its sensitivity is also limited when integrating with visual detection methods. Herein, by designing only two primers to precisely recognize the four regions of the target, we developed a multiple thermocycles-based LAMP method (MTC-LAMP) for sensitive and specific testing and tracking of viral RNA. We also introduced a novel SYBR Green I (SG)-assisted stable colorimetric assay induced by the amplification products through the charge neutralization effect of positively charged SG toward gold nanoparticles (AuNPs). The ultralow nonspecific background of the double exponential amplification improved the detection sensitivity to near single-molecule level (1 aM, 3 copies in 5 μL solution), which was higher than RT-PCR and RT-LAMP. After adding AuNPs, a significant color difference between target and blank was immediately observed by naked eye. By introducing a peptide nucleic acid (PNA) clamp into our colorimetric MTC-LAMP assay, the specific distinguish of virus variants at single-base resolution was observed without the requirement of any equipment. This assay shows great potential for large-scale screening and tracking of the threatening viruses with ultrahigh sensitivity and pronounced colorimetric output, which is of great importance for pandemic control.

A doubt–confirmation-based visual detection method for foreign object debris aided by assembly models

Foreign object debris (FOD) impacts significantly on the quality control during product assembly because it usually causes product failure. The vision-based method as a nondestructive and efficient technology has become an important approach to FOD detection. However, it faces two important challenges: (1) inexhaustible types (almost any object can become FOD) and (2) unpredictable locations (FOD can appear almost anywhere on surface of a product). Therefore, this paper proposes an FOD visual detection method based on doubt–confirmation strategy and aided by assembly models. Firstly, a coarse-to-fine method is designed for feature extraction and registration to align the test image with the reference image. Then, to solve the unpredictable location problem, different types of suspected FOD are extracted from the test image by a combined method of supervision and nonsupervision. Finally, to solve the inexhaustible type problem, an image comparison method based on a Histogram of Line Direction Angle is proposed, and re-recognition rules of suspected FOD established to complete the final discrimination. Experiments are conducted on a product with complex shape, and the results demonstrate the effectiveness and efficiency of our approach.

The Seismic Vulnerability of Buildings in the Central Zone of Peru through the Application of the Rapid Visual Detection Method

The Seismic Vulnerability of Buildings in the Central Zone of Peru through the Application of the Rapid Visual Detection Method