Recent advances in immunoassays and biosensors for mycotoxins detection in feedstuffs and foods

Mycotoxins are secondary metabolites produced by fungus.Many mycotoxin species are highly toxic and are frequently found in cereals and feedstuffs.So,powerful detection methods are vital and effective ways to prevent feed contamination.Traditional detection methods can no longer meet the needs of massive,real-time,simple,and fast mycotoxin monitoring.Rapid detection methods based on advanced material and sensor technology are the future trend.In this review,we highlight recent progress of mycotoxin rapid detection strategies in feedstuffs and foods,especially for simultaneous multiplex mycotoxin determination.Immunoassays,biosensors,and the prominent roles of nanomaterials are introduced.The principles of different types of recognition and signal transduction are explained,and the merits and pitfalls of these methods are compared.Furthermore,limitations and challenges of existing rapid sensing strategies and perspectives of future research are discussed.

Establishment of a Multiplex Detection Method for Common Bacteria in Blood Based on Human Mannan-Binding Lectin Protein-Conjugated Magnetic Bead Enrichment Combined with Recombinase-Aided PCR Technology

Objective Recombinase-aided polymerase chain reaction(RAP)is a sensitive,single-tube,two-stage nucleic acid amplification method.This study aimed to develop an assay that can be used for the early diagnosis of three types of bacteremia caused by Staphylococcus aureus(SA),Pseudomonas aeruginosa(PA),and Acinetobacter baumannii(AB)in the bloodstream based on recombinant human mannanbinding lectin protein(M1 protein)-conjugated magnetic bead(M1 bead)enrichment of pathogens combined with RAP.Methods Recombinant plasmids were used to evaluate the assay sensitivity.Common blood influenza bacteria were used for the specific detection.Simulated and clinical plasma samples were enriched with M1 beads and then subjected to multiple recombinase-aided PCR(M-RAP)and quantitative PCR(qPCR)assays.Kappa analysis was used to evaluate the consistency between the two assays.Results The M-RAP method had sensitivity rates of 1,10,and 1 copies/μL for the detection of SA,PA,and AB plasmids,respectively,without cross-reaction to other bacterial species.The M-RAP assay obtained results for<10 CFU/mL pathogens in the blood within 4 h,with higher sensitivity than qPCR.M-RAP and qPCR for SA,PA,and AB yielded Kappa values of 0.839,0.815,and 0.856,respectively(P<0.05).Conclusion An M-RAP assay for SA,PA,and AB in blood samples utilizing M1 bead enrichment has been developed and can be potentially used for the early detection of bacteremia.

Fluorescent aptasensor for detection of live foodborne pathogens based on multicolor perovskite-quantum-dot-encoded DNA probes and dual-stirring-bar-assisted signal amplification

In this study,a fluorescent(FL)aptasensor was developed for on-site detection of live Salmonella typhimurium(S.T.)and Vibrio parahaemolyticus(V.P.).Complementary DNA(cDNA)of aptamer(Apt)-functionalized multicolor polyhedral oligomeric silsesquioxane-perovskite quantum dots(cDNA-POSSPQDs)were used as encoded probes and combined with dual-stirring-bar-assisted signal amplification for pathogen quantification.In this system,bar 1 was labeled with the S.T.and V.P.Apts,and then bar 2 was functionalized with cDNA-POSS-PQDs.When S.T.and V.P.were introduced,pathogen-Apt complexes would form and be released into the supernatant from bar 1.Under agitation,the two complexes reached bar 2 and subsequently reacted with cDNA-POSS-PQDs,which were immobilized on MXene.Then,the encoded probes would be detached from bar 2 to generate FL signals in the supernatant.Notably,the pathogens can resume their free state and initiate next cycle.They swim between the two bars,and the FL signals can be gradually enhanced to maximum after several cycles.The FL signals from released encoded probes can be used to detect the analytes.In particular,live pathogens can be distinguished from dead ones by using an assay.The detection limits and linear range for S.T.and V.P.were 30 and 10 CFU/mL and 10^(2) -10^(6) CFU/mL,respectively.Therefore,this assay has broad application potential for simultaneous on-site detection of various live pathogenic bacteria in water.

Detection performance and inversion processing of logging-while-drilling extra-deep azimuthal resistivity measurements

We present systematic investigations on the physics,detection performance and inversion of logging-while-drilling extradeep azimuthal resistivity measurements(EDARM).First,the definitions of EDRAM measurements are discussed,followed by the derivation of the attenuation and phase-shift geometrical factors to illustrate the relative contributions of formation units to the observed signals.Then,a new definition of detection depth,which considers the uncertainty of inversion results caused by the data noise,is proposed to quantify the detection capability of ED ARM.Finally,the B ayesian theory associated with Markov chain Monte Carlo sampling is introduced for fast processing of EDARM data.Numerical results show that ED ARM is capable of detecting the azimuth and distance of remote bed boundaries,and the detection capability increases with increasing spacing and resistivity contrast.The EDARM tool can accommodate a large range of formation resistivity and is able to provide the resistivity anisotropy at arbitrary relative dipping angles.In addition,multiple bed boundaries and reservoir images near the borehole are readily obtained by using the Bayesian inversion.

Unified control and detection framework and its applications: a review, some new results, and future perspectives

Initiated three decades ago,integrated design of controllers and fault detectors has continuously attracted research attention.The recent development of the unified control and detection framework with an observer-based residual generator in its core gives a more general form of the previous works.Its applications to residual centred modelling of uncertain control systems,fault detection in feedback control systems with uncertainties,fault-tolerant control(FTC)as well as control performance degradation monitoring,detection and recovery are introduced.In conclusion,some future perspectives are proposed.

Multiple Targets Recognition for Highly-Compressed Color Images in a Joint Transform Correlator

In this paper, we are proposing a compression-based multiple color target detection for practical near real-time optical pattern recognition applications. By reducing the size of the color images to its utmost compression, the speed and the storage of the system are greatly increased. We have used the powerful Fringe-adjusted joint transform correlation technique to successfully detect compression-based multiple targets in colored images. The colored image is decomposed into three fundamental color components images (Red, Green, Blue) and they are separately processed by three-channel correlators. The outputs of the three channels are then combined into a single correlation output. To eliminate the false alarms and zero-order terms due to multiple desired and undesired targets in a scene, we have used the reference shifted phase-encoded and the reference phase-encoded techniques. The performance of the proposed compression-based technique is assessed through many computer simulation tests for images polluted by strong additive Gaussian and Salt & Pepper noises as well as reference occluded images. The robustness of the scheme is demonstrated for severely compressed images (up to 94% ratio), strong noise densities (up to 0.5), and large reference occlusion images (up to 75%).

mtDNA-triggered pH response signal-amplified fluorescent probe for multiple cell discrimination

Developing fluorescence probes with multiple responses has vital significance but remains challenging.Herein,for the first time,we present a mitochondrial DNA(mtDNA)-triggered pH response signalamplified fluorescent probe(QCY-DBT)for multiple cell detection.The probe exhibited a large stokes shift(229 nm),excellent DNA selectivity over RNA,and ultrasensitivity of detection limit(DL;74.0 ng/mL).Thus,QCY-DBT was successfully applied to analyze multiple human peripheral blood cells and visualize mtDNA in healthy and apoptotic cells.In the tumor acidic environment(pH 6.0–7.0),the absorbance of QCY-DBT at 436 nm increased,and the fluorescence signal(665 nm)was amplified by mtDNA,which enabled the direct observation of tumor cells.Our study provides help in designing smart probes with multiple responses for efficient abnormal cell detection.

A NEW DATA ASSOCIATION ALGORITHM USING PROBABILITY HYPOTHESIS DENSITY FILTER

Probability Hypothesis Density (PHD) filtering approach has shown its advantages in tracking time varying number of targets even when there are noise,clutter and misdetection. For linear Gaussian Mixture (GM) system,PHD filter has a closed form recursion (GMPHD). But PHD filter cannot estimate the trajectories of multi-target because it only provides identity-free estimate of target states. Existing data association methods still remain a big challenge mostly because they are com-putationally expensive. In this paper,we proposed a new data association algorithm using GMPHD filter,which significantly alleviated the heavy computing load and performed multi-target trajectory tracking effectively in the meantime.

Iterative inverse beamforming algorithm and its application in multiple targets detection of passive sonar

With the increasing of detection ability of passive sonar,the weak signal detection problem in multiple interferences becomes more and more important.In the time/bearing record(TBR) display of sonar detection,when there exist traces of multiple interferences,the identification of weak signal is difficult or impossible.The adaptive noise cancellation technique provides the theoretical basis for suppressing strong interferences.But the solution for finding the steady-state optimum filter matrix is quite difficult due to the real time calculation of inverse matrix of input data correlation matrix.The iterative inverse beamforming(IBF) algorithm for solving the optimum filter vector,which is expressed by inverse matrix of the ocean environment data,is derived in this paper,by which,the optimum filter can be eventually expressed as a sum of series simple matrices of constructed from sensor data.Based on the algorithm proposed in this paper,some examples of at sea experiment are provided.The strong interferences are cancelled and the weak signal is emerged,even it didn't appear in the conventional beamforming(CBF) processing.

Thermodynamics-guided two-way interlocking DNA cascade system for universal multiplexed mutation detection

Detection of point mutations in driver genes is of great significance for the early diagnosis,treatment,and prognostic evaluation of cancer.However,current detection methods do not offer versatility,specificity,and rapid performance simultaneously.Thus,multiple mutation detection processes are necessary,which results in long processing times and high costs.In this study,we developed a thermodynamics-guided two-way interlocking DNA cascade system for universal multiplexed mutation detection(TTI-CS).This strategy is based on the DNA probe,which changes the thermodynamic balance of the DNA cascade by the designed bubble structure,thereby achieving a good distinction between mutant and wild-type DNA.The designed method greatly shortens the detection time through two-way intrusion.In addition,this method only changes two inexpensive trigger and bridge sequences,which replace the specific and expensive nucleic acid probes used in analyses based on traditional DNA probe methods,thereby enabling multiple detections.We performed the detection of synthetic single-stranded DNA for the five mutation points and successfully detected in endometrial cancer specimens.The detection limit of this method is0.1%,which better meets the needs of clinical low-abundance multiple mutation detection.Overall,TTI-CS is currently one of the best methods for detecting multiple mutation detections.

A multi-frame track-before-detect algorithm based on root label clustering for multiple targets

In this paper,a novel multi-frame track-before-detect algorithm is proposed,which is based on root label clustering to reduce the high computational complexity arising by observation area expansion and clutter/noise density increase.A criterion of track extrapolation is used to construct state transition set,root label is marked by state transition set to obtain the distribution information of multiple targets in measurement space,then measurement plots of multi-frame are divided into several clusters,and finally multi-frame track-before-detect algorithm is implemented in each cluster.The computational complexity can be reduced by employing the proposed algorithm.Simulation results show that the proposed algorithm can accurately detect multiple targets in close proximity and reduce the number of false tracks.

Tb^(3+)-xylenol orange complex-based colorimetric and luminometric dual-readout sensing platform for dipicolinic acid and metal ions

A dual-readout sensing platform based on two signal transduction channels can integrate the unique advantages of each sensing pattern,compensate for the deficiency in the adaptive capacity,and enable a more convincing performance in analytical applications.Here,we introduce a responsive molecule dye,xylenol orange(XO),to combine with lanthanide terbium ions(Tb^(3+)).The resultant Tb^(3+)-XO complex exhibited tunable optical properties and was used as a novel colorimetric and luminometric dual-readout sensing platform for assaying the anthrax biomarker,dipicolinic acid(DPA).In the presence of Tb^(3+),the XO solution underwent a color change from yellow to magenta;however,upon adding DPA,the color changed back to yellow immediately,accompanied by the characteristic luminescence emission of Tb^(3+).Considering the strong affinity between DPA/XO and metal ions,the proposed sensing platform was further employed for the determination and differentiation of certain metal ions using linear discriminant analysis.This convenient dual-readout sensing platform offers several notable features and significantly promotes the application and development of lanthanide-based materials.

A hierarchical clustering of features approach for vehicle tracking in traffic environments

Purpose-Developing algorithms for automated detection and tracking of multiple objects is one challenge in the field of object tracking.Especially in a traffic video monitoring system,vehicle detection is an essential and challenging task.In the previous studies,many vehicle detection methods have been presented.These proposed approaches mostly used either motion information or characteristic information to detect vehicles.Although these methods are effective in detecting vehicles,their detection accuracy still needs to be improved.Moreover,the headlights and windshields,which are used as the vehicle features for detection in these methods,are easily obscured in some traffic conditions.The paper aims to discuss these issues.Design/methodology/approach-First,each frame will be captured from a video sequence and then the background subtraction is performed by using the Mixture-of-Gaussians background model.Next,the Shi-Tomasi corner detection method is employed to extract the feature points from objects of interest in each foreground scene and the hierarchical clustering approach is then applied to cluster and form them into feature blocks.These feature blocks will be used to track the moving objects frame by frame.Findings-Using the proposed method,it is possible to detect the vehicles in both day-time and night-time scenarios with a 95 percent accuracy rate and can cope with irrelevant movement(waving trees),which has to be deemed as background.In addition,the proposed method is able to deal with different vehicle shapes such as cars,vans,and motorcycles.Originality/value-This paper presents a hierarchical clustering of features approach for multiple vehicles tracking in traffic environments to improve the capability of detection and tracking in case that the vehicle features are obscured in some traffic conditions.

Rapid identification of diarrheagenic Escherichia coli based on barcoded magnetic bead hybridization

Diarrhea,as a global public health problem,causes a large number of infections and deaths every year.Although Escherichia coli(E.coli)is one of the normal flo ra microorganisms in the human intestinal tract,it has five pathogenic bacteria types that can cause human diarrhea,known as diarrheagenic E.coli.When people are infected,rapid and accurate diagnosis,along with timely treatment,are especially important.Here,we introduce a new method to identify and analyze a large number of pathogenic strains in E.coli by multiplex PCR and barcoded magnetic bead hybridization.Results show that the detection sensitivities of enterohemorrhagic E.coli,enterotoxigenic E.coli,enteropathogenic E.coli,enteroinvasive E.coli and enteroaggregative E.coli were 1.3×10^3 CFU/mL,2×10^4 CFU/mL,4×10^4 CFU/mL,7.2×10^4 CFU/mL and 1.7 CFU/mL respectively.This method has strong specificity and high sensitivity and detects multiple target sequences in one experiment.Compared with other methods,BMB array has great application potential.